WO2024177704A1

WO2024177704A1 - Smart spinal interbody trial

Info

Publication number: WO2024177704A1
Application number: PCT/US2023/081209
Authority: WO
Inventors: Brett FREEDMAN; Mohamad BYDON; Lawrence FREEDMAN
Original assignee: Neuro Innovations 20 LLC
Current assignee: Neuro Innovations 20 LLC
Priority date: 2023-02-21
Filing date: 2023-11-27
Publication date: 2024-08-29
Anticipated expiration: 2025-08-21

Abstract

An interbody implant trial system includes an interbody implant trial with an expandable body having a first portion and a second portion, each of the first and second portions having a vertebral body facing surface, and an expansion mechanism between the first and second portions. The system includes an insertion tool for engaging the expansion mechanism of the implant trial to adjust at least one of the height and lordosis between the first and second portions. The implant trial also includes one or more sensors for detecting a force impacting the vertebral body facing surface of the first or second portion. The detected force is transmitted from the implant trial to an external device and is used in combination with preoperative data for a patient to determine an optimal implant for use in the patient.

Description

SMART SPINAL INTERBODY TRIAL CROSS-REFERENCE TO RELATED APPLICATION [0001] This application claims priority to U.S. Provisional Application No.63/447,174, filed on February 21, 2023, the entirety of which is herein incorporated by reference. TECHNICAL FIELD [0002] This document relates to a medical device trial system configured to be used to determine a suitable spinal implant and implant position in a patient. BACKGROUND [0003] Human spines include a column of coupled vertebrae cushioned by cartilaginous spacers, referred to as intervertebral discs between opposing vertebral endplates. When an intervertebral disc fails, surgical intervention can be required, which may include implantation of an artificial disc or implant to restore the height of the spinal column and angle between adjacent vertebrae. A surgeon prepares the intervertebral space for an implant by removing damaged disc material, distracting the adjacent vertebrae and inserting an implant. [0004] Implants produced by a manufacturer can be available in a variety of heights and sizes. Before insertion of the implant and securing of the implant in position using screws or other fastening mechanisms, the surgeon may use an implant trial to gauge the size of the intervertebral space to select an implant from the available implants produced by the manufacturer. SUMMARY [0005] Some embodiments of a medical device trial system include an expandable spinal implant trial for insertion into the vertebral disc space to determine an optimal position of an implant in the vertebral disc space. The spinal implant trial includes a first vertebral body facing surface on a first expandable portion and a second vertebral body facing surface on a second expandable portion. The spinal implant trial includes on the first and/or second vertebral body facing surfaces one or more sensors on a vertebral body facing surface for detecting contact area, force, and/or torque when the spinal implant trial is expanded to contact vertebral bodies. The detected contact area, force, and/or torque is transmitted from the spinal implant trial to an external processor which displays detected contact area, force, and/or torque to a surgical team. The external processor also correlates the detected contact area, force, and/or torque and other intraoperative data with preoperative data to determine a recommended implant and implant height and lordosis for the vertebral disc space of the patient. [0006] In a first aspect, an interbody implant trial system includes an interbody implant trial and an insertion tool. The interbody implant trial includes an expandable body having a first portion and a second portion, the first portion and the second portion each including a vertebral body facing surface, and one or more sensors positioned to detect force on the vertebral body facing surface. The insertion tool is sized and shaped to allow coupling to the interbody implant trial, and the insertion tool engages the expandable body to adjust at least one of a height between the first portion and the second portion of the expandable body and a lordosis of the first portion relative to the second portion. [0007] In another aspect, a method of using the interbody implant includes coupling the insertion tool to the interbody implant trial, inserting the interbody implant trial into a patient’s vertebral disc space while the interbody implant trial is in a closed configuration using the insertion tool, expanding a height of the interbody implant trial using the insertion tool, and monitoring a contact area between a vertebral-facing surface of the first and second portions with vertebral bodies defining the vertebral disc space. The method also includes adjusting a lordosis of the first portion and the second portion within the vertebral disc space using the insertion tool, monitoring the contact area and a force between the vertebral-facing surface of the first and second portions with the vertebral bodies defining the vertebral disc space while adjusting the lordosis, and transmitting data representative of the contact area and the force from the interbody implant trial to an external device. [0008] In another aspect, a method for determining an interbody implant for implantation in a vertebral disc space of a patient includes obtaining preoperative data specific to the patient, obtaining intraoperative data specific to the patient, correlating the preoperative data and the intraoperative data using at least one processor, and determining an interbody implant for use in the patient based on the correlation of both the preoperative data and intraoperative data using an algorithm. [0009] In another aspect, an interbody implant trial includes an expandable body having a first portion and a second portion, the first portion and the second portion each having a vertebral body facing surface, and an expansion mechanism positioned between the first portion and the second portion, the expansion mechanism for adjusting a position of the first portion relative to the second portion, and at least one of the first portion and the second portion includes one or more sensors for detecting a force on the vertebral body facing surface. [0010] In another aspect, a method of using a interbody implant trial includes obtaining a interbody implant trial including an expandable body having a first portion and a second portion, the first portion and the second portion each having a vertebral body facing surface, an expansion mechanism positioned between the first portion and the second portion, and a plurality of sensors positioned on the vertebral body facing surfaces of the first and second portions, the plurality of sensors for detecting forces on the interbody implant trial at a plurality of locations on the vertebral body facing surfaces where the vertebral body facing surfaces are in contact with vertebral bodies in a patient’s vertebral disc space. The method also includes inserting the interbody implant trial into a vertebral space of a patient in a first configuration, wherein the vertebral body facing surfaces of the first portion and the second portion are substantially parallel in the first configuration, and expanding the interbody implant trial from the first configuration using an expansion mechanism to a second configuration in which the vertebral body facing surfaces of the first portion and the second portion are in contact with first and second vertebral surfaces defining the vertebral space. [0011] In another aspect, a system includes a spinal implant trial and a computer having a memory and one or more processors. The spinal implant trial includes an expandable body having a first portion and a second portion, the first portion and the second portion each having a vertebral body facing surface, and a plurality of sensors positioned on the vertebral body facing surfaces of the first and second portions, the plurality of sensors for detecting forces on the spinal implant trial at a plurality of locations on the vertebral body facing surfaces where the vertebral body facing surfaces are in contact with vertebral bodies in a patient’s vertebral disc space. The one or more processors of the computer for receiving data from the spinal implant trial and the memory for storing the data from the spinal implant trial. The one or more processors determine a force profile representing forces between vertebral implant facing surfaces of the spinal implant trial and vertebral bodies of the patient from the received data, and display the force profile on a display. [0012] In an aspect a spinal implant trial includes a plurality of sensors positioned on vertebral body facing surfaces for detecting forces on the spinal trial implant at a plurality of locations on the vertebral body facing surfaces where the vertebral body facing surfaces are in contact with vertebral bodies in a patient’s vertebral disc space. [0013] In an aspect an expandable spinal implant trial includes one or more sensors positioned on vertebral body facing surfaces. [0014] In an aspect, a method of providing surgical decision support includes receiving preoperative data at a processor, receiving surgical data including intraoperative data having one or more dimensions of an interbody implant trial currently inserted in a spine of a patient and at least one stress measurement detected at the interbody implant trial, determining a risk grade of subsidence related to the interbody implant trial in the spine of the patient, the risk grade based on the preoperative data and the intraoperative data, and outputting on a display an indication of the determined risk grade for subsidence related to the one or more dimensions of the interbody implant trial currently inserted in the spine of the patient. [0015] Some of all of the embodiments described herein can have one or more of the following advantages. First, the interbody implant trial system selects an appropriate implant to optimize patient outcomes from spinal surgery based on relevant data. The interbody implant trial uses sensors to measure forces on the vertebral body facing surfaces of the interbody implant trial where the interbody implant trial contacts the adjacent vertebral bodies, and reports the measured forces as well as locations of the forces as a contact area of the implant trial to the surgeon in real time. The interbody implant trial system uses this data to identify the area where there was greatest contact for a rigid surface of the trial/implant, leading to least stress. The interbody implant trial system combines this information about the fit of the interbody implant trial within the patient’s vertebral space with preoperative and intraoperative data to holistically determine an optimal available implant for use in the patient’s vertebral space. The determination is not only based on the size, shape, and angle of the patient’s vertebral space, but also on preoperative information such as bone strength, density, or health data. The determination of the implant to be used based on preoperative and intraoperative data increases the likelihood of a favorable patient outcome, in which the implant does not suffer from subsidence after implantation. [0016] Second, the interbody implant trial system provides an indication to the surgeon of an appropriate height and lordosis of the selected implant. The interbody implant trial is able to be expanded in height and lordosis, and force measurements can be sensed and reported to the surgeon during expansion. The interbody implant trial system presents the information in a display and can provide indications of acceptable and unacceptable forces and contact areas at various heights and lordosis angles of the implant, and can further correlate the optimal implant height and angle to an available implant for use. The interbody implant trial system can function as a stand-alone surgeon decision support tool that informs the surgeon of the best implant dimension to use in the disc space. The surgeon is able to confirm that a pre- selected implant will fit the patient’s vertebral disc space with appropriate contact and forces prior to implantation of the implant, which increases the likelihood of a successful implant and recovery for the patient. [0017] Third, by presenting the information to the surgeon and also selecting and presenting an optimal implant for the patient’s particular vertebral disc space and other health data, the interbody implant trial system reduces risk of subsidence. A primary mode of failure for interbody devices, namely subsidence through macro or micro failure of the endplates due to a mismatch between contact stress and bone strength. By incorporating information from the interbody implant trial sensors related to force, stress, and contact area, as well as preoperative data related to bone strength, health, and density, the interbody implant trial system can select an implant which is least likely to fail via subsidence. [0018] Fourth, the interbody implant trial system links the measured force data from the implant trial with additional preoperative and intraoperative data using an evidenced-based algorithm for predicting bone failure which incorporates information related to outcomes from other implant surgeries to identify the optimal implant for a favorable surgical outcome in a particular surgery. The algorithm can learn and improve by continuously incorporating into its training additional surgeries and surgical outcomes. The algorithm can also become surgeon specific by learning the preferences of a particular surgeon in various situations. [0019] The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims. DESCRIPTION OF DRAWINGS [0020] FIG.1 illustrates an exemplary implant trial for determining an implant for surgical implantation in a patient. [0021] FIGS.2A-C illustrate views of a vertebral-facing surface of an exemplary implant trial. [0022] FIG.3 illustrates a spinal implant trial system for determining an implant for surgical implantation in a patient. [0023] FIG.4 illustrates a flow chart of data to an exemplary algorithm of a spinal implant trial system. [0024] FIG.5 illustrates a flow chart for a method of determining an implant for surgical implantation in a patient. [0025] FIG.6 illustrates a flow chart for a method of using an interbody implant trial. [0026] FIG.7 illustrates a flow chart for a method of using an interbody implant trial system. [0027] FIG.8 illustrates an example process for determining metrics of a subject. [0028] FIG.9 illustrates a block diagram of computing devices that may be used to implement the systems and methods described in this document, as either client or as a server or a plurality of servers. DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS [0029] Referring to FIG.1, an example embodiment of an interbody implant trial system 100 includes an interbody implant trial 102 and an insertion tool 104. The interbody implant trial 102 includes a body 106 having a first portion 107 and a second portion 109. The first portion 107 has a first vertebral body facing surface 108 and the second portion 109 has a second vertebral body facing surface 110. The body 106 has a longitudinal axis 112. The first portion 107 and the second portion 109 are expandable from a first configuration (not shown) in which the first vertebral body facing surface 108 and the second vertebral body facing surface 110 are parallel to one another and to the longitudinal axis 112, and a second configuration (as shown in Fig.1) in which the first vertebral body facing surface 108 and the second vertebral body facing surface 110 form an angle 118 relative to the longitudinal axis 112. A distance 116 between the first vertebral body facing surface 108 and the second vertebral body facing surface 110 can also be adjusted. [0030] The interbody implant trial 102 includes one or more sensors that detect forces or pressures on the first vertebral body facing surface 108 and the second vertebral body facing surface 110. The sensors are not shown in FIG.1, but are illustrated in FIGS.2A-C. While each of the first vertebral body facing surface 108 and the second vertebral body facing surface 110 includes sensors, only the first vertebral body facing surface 108 is shown in FIGS.2A-C for simplicity. The second vertebral body facing surface 110 can have the same or a different orientation of sensors compared to the first vertebral body facing surface 108. [0031] FIG.2A shows the first vertebral body facing surface 108 with an aperture 148 through a center of the first vertebral body facing surface 108 and sensor arrays 145a-c positioned on the first vertebral body facing surface 108 surrounding the aperture 148. FIG. 2B shows the first vertebral body facing surface 108 with a sensor array 146 positioned at a center of the first vertebral body facing surface 108 and additional sensors 150a-b positioned near the proximal end of the first vertebral body facing surface 108. FIG.2C shows the first vertebral body facing surface 108 with sensors 150a-m positioned on the surface. As depicted in FIGS.2A-C, the sensors can be positioned over a majority of the surface of the first vertebral body facing surface 108, or can be placed in particular positions where interaction and contact with adjacent vertebral bodies is likely. [0032] In some implementations, the sensors are formed as arrays of sensors. In some implementations, the sensors are formed as piezoelectric components. In other implementations, the sensors can be one or more other sensors suitable for the operation such as one or more load cells (pneumatic load cells, hydraulic load cells, inductive load cells, capacitive load cells, magnetostrictive load cells, and/or strain gage load cells) and/or one or more force sensitive resistors (e.g. single-point or multi-point matrix). [0033] The forces sensed by the sensors can provide information about the locations where adjacent vertebral bodies contact the first vertebral body facing surface 108 and the second vertebral body facing surface 110. The forces can be used to form a contact area map of the first vertebral body facing surface 108 and the second vertebral body facing surface 110. In some implementations, one or more of the sensors on the first vertebral body facing surface 108 and the second vertebral body facing surface 110 measures another biomechanical impact of the implant on the bony endplates of the vertebral bodies, for example, an expansion force, expansion torque or other measurement. In some implementations, one or more sensors is positioned on a part of the interbody implant trial 102 other than the first vertebral body facing surface 108 and the second vertebral body facing surface 110, for example, between the first vertebral body facing surface 108 and the second vertebral body facing surface 110, or on a side of the body 106. In some implementations, one or more sensors is positioned on part of the interbody implant trial system 100 other than directly in or on the interbody implant trial 102, such as in the insertion tool 104. In some implementations, one or more sensors is positioned on the expansion mechanism of the interbody implant trial 102. Different types of sensors can be positioned on different parts of the interbody implant trial 102, for example, a torque sensor can be positioned on the expansion mechanism for sensing a torque to drive the implant expansion and/or a force sensor can be positioned on the vertebral body facing surfaces to sense the position and force of the interbody implant trial 102 with the vertebral bodies. A stress can be calculated based on the measured stress and contact area. A force and/or stress can be calculated as a function of torque. In some implementations, a pressure sensor is positioned between the first and second portions 107 and 109. The sensors can be used together or separately, and one or more of the torque, force, and pressure sensors can be positioned on the interbody implant trial 102 in various positions. [0034] The force exerted at the contact locations between the first vertebral body facing surface 108 and the second vertebral body facing surface 110 and adjacent vertebral bodies, or other biomechanical measures, can indicate the stress that an implant would exert on the vertebral bodies at the contact location and can be used to identify likelihood of subsidence and appropriate height and angles of the implant for a vertebral disc space. Stress can be calculated as the force over the contact area, and is the mechanical parameter closely associated with predicting bone failure leading to subsidence. The stress can be calculates as a general stress over the full contact area, stress over a particular contact area, stress on one of the first and second vertebral body facing surfaces, or any other suitable stress calculation. As will be discussed below, the calculated stress is used to determine a risk of subsidence for use in selection of an interbody implant for use in a patient. [0035] An implant trial that fits the vertebral disc space poorly may show point loading at various surfaces across the implant (e.g., small regions of contact between the first and second vertebral body facing surfaces and the vertebral bodies). This point loading greatly reduces the contact area between the first and second vertebral body facing surfaces and the vertebral bodies, which greatly increases the stress on the vertebral bodies. Because the vertebral spaces of different patients may have very different geometries and bony endplate shapes, placing a same implant into two different vertebral spaces of similar bone quality can have vastly different outcomes, either causing or not causing endplate failure. If there is excellent conformity between the surface of the implant and the adjacent vertebral bodies, there is greater contact area and therefore less point stress. If there is poor conformity, then there is less contact area and therefore greater point stress which could exceed the failure limit of the abutting bone, leading to fracture, subsidence and possible nonunion and/or other clinical failure. [0036] Referring again to FIG.1, the insertion tool 104 includes an elongate shaft 124 which can be coupled to the interbody implant trial 102 to adjust the height and angle of the interbody implant trial 102 in the vertebral disc space. The insertion tool 104 couples to an expansion mechanism (not shown) of the interbody implant trial 102, and can be manipulated to expand the interbody implant trial 102 from the first configuration to the second configuration. For example, the insertion tool 104 can adjust the configuration of the interbody implant trial 102 by a rotation 126 of the elongate shaft 124. In response to the rotation 126 of the elongate shaft 124, the height 116 can be adjusted in directions 122a and 122b, and/or the angle 118 can be adjusted in directions 120a and 120b. The first portion 107 and the second portion 109 can be coupled to one another by a hinge, a pivot, or any other suitable connection mechanism that allows adjustment of lordosis and height. In some implementations, the expansion mechanism is a wedge, a screw or threaded mechanism, a series of gears, a linkage, a hydraulic actuator, a pneumatic actuator, and/or another expander suitable for the application. The expansion mechanism can be electronic, mechanical, or both. In some implementations, the expansion mechanism includes one or more sensors. In some implementations, the expansion mechanism includes a torque sensor for measuring a torque required to drive the first portion and the second portions 107, 109 apart to increase the height 116 or angle 118 of the interbody implant trial 102. The measured torque can approximate the force being exerted by the first and second vertebral body facing surfaces 108 and 110 against the endplate bone of the vertebral surfaces. [0037] In some implementations, the elongate shaft 124 can be used to perform multiple adjustments to the interbody implant trial 102, for example, the distance 116 between the first vertebral body facing surface 108 and the second vertebral body facing surface 110 can be adjusted by rotation 126 of a portion of the elongate shaft 124, and a further adjustment to the angle 118 of the first vertebral body facing surface 108 and the second vertebral body facing surface 110 relative to the longitudinal axis 112 can be adjusted by rotation 126 of the portion of the elongate shaft 124 after pushing a button, engaging a gear, or any other mechanism. In some implementations, the rotation 126 of the elongate shaft 124 adjusts one of the distance 116 and the angle 118, and a rotation of a second tool inserted through the elongate shaft 124 adjusts another of the distance 116 and the angle 118. In some implementations, the adjustment of the interbody implant trial 102 is accomplished not by rotation 126 of the elongate shaft 124, but by another method such as manipulation of a handle located at a proximal end of the elongate shaft 124, or by robotic control at a user interface, the controls transmitted through the elongate shaft 124 to the expansion mechanism in the interbody implant trial. [0038] In some implementations, the angle 118 of the first vertebral body facing surface 108 and the second vertebral body facing surface 110 relative to the longitudinal axis 112 are adjusted simultaneously, and an angle 118 of the first vertebral body facing surface 108 relative to the longitudinal axis 112 is the same as an angle of the second vertebral body facing surface 110 relative to the longitudinal axis 112. In some implementations, the angle of the first vertebral body facing surface 108 and the second vertebral body facing surface 110 relative to the longitudinal axis 112 are separately adjustable by the insertion tool 104. In some implementations, the angle of the first vertebral body facing surface 108 and the angle of the second vertebral body facing surface 110 relative to the longitudinal axis 112 are different, but are adjusted simultaneously by the insertion tool 104. In some implementations, one or more additional dimensions of the interbody implant trial 102 is adjustable by the insertion tool 104, such as a depth, width, length, extension or flexion. [0039] The interbody implant trial 102 can be implant system specific, or can be used for all interbody approaches, including ALIF, OLIF, LLIF, and P/TLIF. [0040] FIG.3 illustrates an exemplary embodiment of the interbody implant trial system 100 coupled to an external device 140 which can include, for example, one or more computers, tablets, smart phones, and/or other computing devices. The interbody implant trial 102 is shown positioned between two vertebral bodies 130a and 130b. As described above, the insertion tool 104 is used to adjust one or more of the height and lordosis angle of the vertebral body facing surfaces of the interbody implant trial 102 within the vertebral disc space to bring the vertebral body facing surfaces 108 and 110 of the interbody implant trial 102 into contact with the surfaces of the two vertebral bodies 130a and 130b. The sensors (shown in FIGS.2A-C) on the vertebral body facing surfaces 108 and 110 of the interbody implant trial 102 detect the force and contact locations of the vertebral bodies 130a and 130b on the vertebral body facing surfaces of the interbody implant trial 102 as the interbody implant trial 102 is expanded (or as the height and lordosis is adjusted from an expanded state). [0041] The force and contact location data is transmitted from the interbody implant trial 102 to the external device 140 over communications pathway 142. In some implementations, communications pathway 142 is a wired connection. In some implementations, communications pathway 142 is a wireless connection, for example Wi-Fi, Bluetooth, or near field communication. In some implementations, the communications pathway 142 extends through an insertion tool (not shown) from the interbody implant trial 102 to the external device 140. The data is transmitted as a signal, which is received at the external device 140. In some implementations, current trial dimensions, such as a height and/or angle of the interbody implant trial 102 is communicated from the interbody implant trial 102 to the external device 140 in real-time (i.e., continuously updated during the procedure), so that the surgeon can monitor the dimensions of the interbody implant trial 102. In some implementations, the footprint of the interbody implant trial 102 (e.g., a length, width, shape, or indication of manufacturer device having a matching footprint) is also communicated from the trial to the external device 140. In some implementations, the external device 140 can display the implant size of the specific commercially available implant system matching current trial dimensions of the interbody implant trial 102. In some implementations, the external device 140 can display information related to the size or dimensional limits of commercially available implant systems relative to the current trial dimensions of the interbody implant trial. The comparison of the trial dimensions to available implant dimensions allows the surgeon to determine if additional height and/or lordosis can be achieved with the available implants having the footprint of the trial and can help to determine a suitable implant for implantation. [0042] A decision support tool on the external device 140 uses the data signal to identify a contact area between the interbody implant trial 102 and adjacent vertebral bodies 130a and 130b, as well as a measure of the force, pressure, or stress over the contact area. As described above, stress over all or part of the contact area is a predictor of subsidence and bone failure. In some implementations, the decision support tool determines a risk of subsidence and/or a suitable interbody implant based on the calculated stress on the interbody implant trial. In some implementations, the decision support tool determines a risk of subsidence and/or a suitable interbody implant based on the measured force at the interbody implant trial alone. In such implementations, sensors for sensing a contact area may be omitted, and the sensor for sensing a force can be located on the vertebral facing bodies of the interbody implant trial, or elsewhere on the interbody implant trial, such as between the first and second portions or on the expansion mechanism. [0043] The decision support tool displays the information on a display screen 144. As illustrated in FIG.3, the display screen 144 includes color maps showing the contact area and stresses on the first and second vertebral body facing surfaces. In some implementations, the external device 140 includes one or more user interfaces, such as a keyboard, mouse, audio input, voice recognition, joystick, or haptic feedback mechanism to allow for direct data entry (including clinical documentation and surgeon specific data to be integrated into the algorithm training data) during and after the operation. In some implementations, the external device 140 is a sterile device and/or includes a sterile cover for use in an operating theater. [0044] The decision support tool provides real-time output on the display screen 144, including information related to a calculated risk grade for subsidence related to a currently inserted interbody implant trial. The risk for subsidence is based on the dimensions of the current trial, including the footprint, height, and lordosis. The risk for subsidence is also based on preoperative bone health data and other intraoperative measures including force, contact area, and/or stress measures. In some implementations, the risk for subsidence is also based on a torque required to move expand the height and/or lordosis of the interbody implant trial, as measured by a torque sensor positioned on an expansion mechanism. [0045] In some implementations, the decision support tool receives postoperative outcomes, including information about the selected interbody implant for the surgery. The decision support tool correlates the selected interbody implant and postoperative outcomes with the risk for subsidence determined for the particular selected interbody implant and improves future risk calculations based on the correlation. In some implementations, the decision support tool improves suggestions for a particular surgeon based on the correlation with postoperative data. [0046] The decision support tool on the external device 140 accesses preoperative and intraoperative data through connections to the interbody implant trial 102 and to servers or other devices where data is stored or measured. In some implementations, the decision support tool on the external device 140 accesses an algorithm trained on data from a plurality of spinal surgeries using one or more versions of the interbody implant trial 102 to make a determination as to an suitable available implant for use in the patient’s vertebral disc space. [0047] FIG.4 illustrates an exemplary block diagram showing the flow of information to the external device 140, executing the algorithm 458. The algorithm 458 accepts as inputs preoperative patient data 452, preoperative surgical information 454, and intraoperative data 456. The preoperative patient data 452 includes scan images from MRI, CT scan or other scanning technologies; bone density and bone health data; and patient demographic data, as well as any other relevant preoperative data. The preoperative surgical information 454 includes the type of surgery including the approach, the surgical procedure steps, the desired surgical outcomes, and surgeon preferences related to the surgery or the selection of the implant. The intraoperative data 456 includes data from the interbody implant trial such as expansion force data, contact area, pressure or force data, and torque data. The intraoperative data 456 also includes data collected from other sources during the surgery, including details of the patient anesthesia; neural monitoring; vital signs or physiological signs such as heart rate, temperature, and respiration rate; and images collected by intraoperative imaging (e.g., CT, MRI, or others). In some implementations, the intraoperative data 456 also includes data related to the torques of screws placed in bone near the vertebral bodies to predict failure limits of implant expansion. [0048] The algorithm 458 accepts these data inputs and performs high-powered computational analysis to determine an optimal implant from a set of available implants (e.g., an implant available at the hospital or surgery center identified by manufacturer, implant name, and size). The determined implant provides algorithm-based surgeon decision support to inform the surgeon of which implant may be optimal (or if no specific determination is made as to being optimal, may be identified as recommended, preferred, or suitable), confirm the surgeon’s choice of implant, and/or provide information relevant to the likely outcome of selection of a particular implant. The algorithm 458 can also provide a recommendation as to the best (or if no specific determination is made as to being best, may be identified as recommended, preferred, or suitable) height and lordosis of the selected implant to fit the vertebral disc space of the patient. In some implementations, the algorithm determines the best (or recommended, preferred, or suitable) height and lordosis by correlating the disc height change to foraminal volume, intersegmental lordosis, and/or the contact area and stress. [0049] The determination can be based on the data from the interbody implant trial 102 and other intraoperative data 456, preoperative patient data 452, and preoperative surgical information 454. The determination can also take into account the surgical data and outcomes from the plurality of other spinal surgeries used in training the algorithm 458 (which can be a machine learning algorithm), to improve the likelihood of selection of a best fitting selection of the realistically available implants which will lead to a favorable surgical outcome. [0050] The algorithm 458 outputs the recommended implant and positioning based on trial implant data 460. The algorithm 458 and/or software integrated with the algorithm further provides a surgeon decision support tool with real-time integration of intraoperative information and preoperative information to facilitate expedience in the OR and to help the surgeon select the best implant to match the patient's bone quality while respecting the measured contact area between the implant and the patient’s bony anatomy. The algorithm 458 provides real-time feedback to the surgeon on whether the cortical epithelial cells can withstand stress that a specific shaped/sized implant will exert on the vertebral bodies (e.g., via a green/yellow/red indication for a particular implant shape). In some implementations, the algorithm 458 assigns a risk grade to a specific shaped/sized implant, the risk grade indicating a risk of subsidence of the implant. In some implementations, the risk grade is calculated as a tertile and assigned a color of red, yellow, or green for display on the screen to indicate high level of risk, moderate level of risk, and low risk, respectively. [0051] The output of the algorithm 458 can also include surgical procedure steps and checklists which may be directly from the preoperative surgical data 454, or may be altered by the algorithm to include tips or changes based on the machine learning training on the surgical data and outcomes from the plurality of other spinal surgeries. The alterations or tips can be clearly indicated in the presented procedure steps and checklists so that they can be identified by the surgical team and accepted or ignored based on the surgeon’s expertise and understanding of the current surgery. [0052] The surgical team or other members of the patients care team can input patient postoperative outcomes 462 into software, such as an electronic patient record. The postoperative outcomes 462 may be fed back into the algorithm 458 as part of additional machine learning training data 464 such that the algorithm 458 continues to “learn” from patient outcomes to better select a best fitting implant selection for a favorable patient outcome. The algorithm can also learn the particular preferences of a given surgeon based on the machine learning training data 464, so that the selection of the best fitting implant is specific to a particular surgeon. For example, the algorithm 458 can determine based on the machine learning training data 464 that a particular surgeon prefers to use implants from a specific manufacturer, and can tailor the recommendation as to the best-fitting implant based on the surgeon preferences. [0053] In some implementations, the preoperative surgical information 454 includes data input by the surgeon. For example, the surgeon can input data and self-determined or external guideline determined dimensions for each disc space to be achieved at end of surgery to produce an overall preferred spinal alignment. This inputted data related to the surgical plan is input by the surgeon (or surgical team or another on behalf of the surgeon) prior to surgery. The algorithm 458 uses the data input by the surgeon with the intraoperative data 456 to provide the surgeon with real-time feedback during the trialing of the interbody implant trials and during the implantation of the selected interbody implant to indicate whether the desired overall final spinal alignment is being achieved. [0054] The overall final spinal alignment is influenced by the size/shape of the implant at each level over the course of the surgery, and the real-time feedback to the surgeon provides guidance regarding whether to “push” the endplate stress (e.g., by selecting a particular implant dimension), or if the surgeon should consider performing more soft tissue interventions, such as soft tissue or osteophyte releases to allow for the vertebral disc space to become more flexible, reducing stress exerted by the implant onto the end plate and allowing for a great conformational change. The real-time information provided to the surgeon informs the surgeon and surgical team whether they are sticking to surgical plan to achieve the desired overall final spinal alignment, and can be used to inform the surgeon and surgical team when they intentionally decide to vary from the preoperative plan to reduce subsidence risk. [0055] Referring again to FIG.3, the external device 140 displays the output of the algorithm 458 on the display screen 144, and can also display other information on the display screen 144, including current angle and height of the interbody implant trial 102, numeric representations of maximum stress detected at the first and second vertebral body facing surfaces, and patient demographic and identification data. The external device 140 can display an indication of fit of the interbody implant trial 102 in a current configuration (for example, with an indication of poor/ok/good or with a color indicator such as red/yellow/green). [0056] In some implementations, the external device 140 displays a list of available implants with an indication of whether they would be a good fit based on the current data. For example, in some implementations only available implants which are a good fit are listed, implants which would be a good fit are listed in green, or each implant has an associated score displayed next to it showing the likelihood of fitting in the vertebral space with favorable outcome based on the current data. The external device 140 can display intraoperative data specific to the patient such as patient physiological signals like heart rate and respiration rate, anesthesia dose, identification of the vertebral disc space. Additionally, in some implementations, the external device 140 can display surgical steps in the current surgical procedure or surgical goals of the surgical procedure. In some implementations, the surgical steps for the procedure appear one at a time, in a pre-set step-by-step sequence. This allows the entire operative team to be aware of the current step, facilitating communication and expediency during the procedure. In some implementations, the external device 140 includes an audio component and provides the surgical steps audibly. In some implementations, the preoperative plan or surgical goals may be in the form of a checklist. The preoperative plan includes the screw sizes and predicted cage sizes, as well as predicted alignment/correction needs for the patient. For example, predicted areas of needed decompression can be included in the predicted needs of the patient. By presenting the preoperative plan or surgical goals as a checklist, the surgical team can ensure that prior to the end of the operation that all of the goals of surgery have been achieved. [0057] By measuring contact pressure and contact area of the interbody implant trial 102 in a patient’s vertebral space and linking the measurements to preoperative patient data such as bone health by a machine learning algorithm, a patient-specific selection of an optimal implant can be achieved. Additionally, the information related to the contact area and contact force or pressure can allow the surgeon to modify the space for a particular implant. [0058] In some implementations, the interbody trial system 100 is coupled to the interbody implant trial 102 by a threaded connection, one or more adjustable prongs, one or more arms which engage the implant, by one or more magnets, or any other suitable connection mechanism. In some implementations, the interbody implant trial system 100 is fully disposable. In some implementations, interbody implant trial 102 is disposable, while the insertion tool 104 can be reused. In some implementations the trial body 106 is formed from poly ethyl ether ketone (PEEK) or a metal. In some implementations, one-time use and/or disposable force or contact area sensors are affixed to the vertebral body facing surfaces 108, 110. In some implementations, the disposable interbody implant trial 102 also includes a disposable communication transmission mechanism to allow the sensors to communicate the readings to the external device 140. In other implementations, the sensor readings are communicated to the external device 140 by a wire connection from the interbody implant trial 102 through the insertion tool’s elongate shaft 124. In some implementations, the interbody implant trial 102 and the insertion tool 104 are disposable. In some implementations, the interbody implant trial 102 and the insertion tool 104 are reusable, and the interbody implant trial 102 and the insertion tool 104 are formed from materials that tolerate high heat allowing for a cleaning and sterilization process between uses. [0059] In some implementations, various interbody implant trials 102 are available with different orientations or configurations of sensors on the vertebral body facing surfaces. In some implementations, various interbody implant trials 102 are available, each corresponding to the shape and available configurations of a set of implants produced by a manufacturer. [0060] The algorithm 458 can be a data analytic predictive algorithm. Data analytic predictive algorithms can correlate the intraoperative measures of force (e.g., expansion torque, sensors, and/or force plates), contact area and stress to preoperative measures of bone health such as DXA (BMD, TBS), CT (HU and EP cortical thickness, sclerosis and morphometry), CT Bone Strength (FEA - like OND), MR (VBQ), XR (ILA, Regional and Global alignment measures as well as spondy grade/stability) and FRAX and surgical technique factors (i.e., number of levels, LL-PI mismatch, LL, LLL and SVA change, where In is (i.e., end level of central to the overall construct, type of cage (ant, lat, post (bullet, crescent, expandable), preoperative disc height and postoperative disc height, preoperative lordosis and postoperative lordosis (e.g., each disc, low lumbar and total) to predict EP failure and possibly final total correction at healing (i.e., by not over stuffing, and by knowing area of contact as well as lordosis of implant, the algorithm can predict the final lordosis). [0061] In some implementations, preoperative imaging data can be downloaded to the external device 140 that can use AI, machine learning, or manual methods to measure key parameters and build a surgical plan for the case (akin to UNiD). The external device 140 can have an internet site/cloud and/or phone app that allows the surgeon to create their own plan or view an auto-generated or third party generated surgical plan anywhere. That plan can then be loaded to the external device 140, so that in addition to measuring ideal interbody implant dimensions, the system is also able to calculate the amount of correction being delivered compared to the amount determined by the preoperative plan. [0062] FIG.5 illustrates an exemplary flow chart for a method 500 of determining an implant for surgical implantation in a patient. The method 500 begins at step 502 by obtaining preoperative data specific to a patient. At step 504 the method 500 continues by obtaining intraoperative data specific to the patient. At step 506, the method 500 continued by correlating the preoperative data and the intraoperative data, using at least one processor. At step 508, the method 500 continues by determining an interbody implant for use in the patient based on the correlation (obtained at step 506) of the preoperative data obtained at step 502 and the intraoperative data obtained at step 504. For example, in steps 506 and 508, as described above, the algorithm accepts intraoperative and preoperative data as inputs and correlates the data to select an optimal (or recommended, preferred, or suitable) interbody implant for use in a patient, taking into account measurements of the disc space (e.g., contact area and force) obtained by an interbody implant trial and preoperative indicators of bone health and strength and endplate ability to resist the stress of the implant. The algorithm uses the information to select an implant that most changes the shape of the space between the patient’s vertebra in a favorable fashion to increase foraminal height and/or inter-vertebral angle to lead to the best shape of the fused segment. The determined optimal (or recommended, preferred, or suitable) interbody implant is the implant with the best (or recommended, preferred, or suitable) final shape of an implantable interbody fusion device that allows for the greatest (or recommended, preferred, or suitable) degree of foraminal height gain and/or intervertebral angle change to achieve the predetermined best (or recommended, preferred, or suitable) relationship between the vertebral body above and below the device, in a sustainable fashion (i.e., a low or lowest chance of micro/macro failure and subsidence, which induces an uncontrolled change in the foraminal height and/or intervertebral angle). [0063] FIG.6 illustrates an exemplary flow chart for a method 600 of using an interbody implant trial. The method 600 begins at step 602 by obtaining an interbody implant trial (for example, interbody implant trial 102 shown in FIGS.1 and 3). As illustrated in FIGS.1 and 2A-C, the interbody implant trial includes a first portion and a second portion each with a vertebral body facing surface, an expansion mechanism positioned between the first portion and the second portion, and a plurality of sensors. [0064] At step 604, the interbody implant trial is inserted into a vertebral space of a patient in a first configuration, the vertebral body facing surfaces of the first portion and the second portion being substantially parallel in the first configuration. The interbody implant trial is inserted into the vertebral disc space of the patient in an under-sized configuration so that little or no force is required for insertion into the space. [0065] At step 606, the interbody implant trial is expanded, using the expansion mechanism, from the first configuration to a second configuration in which the vertebral body facing surfaces of the first portion and the second portion are in contact with the first and second vertebral surfaces defining the vertebral space. When the vertebral body facing surfaces are in contact with the first and second vertebral surfaces, the sensors on the vertebral body facing surfaces can detect the force exerted between the interbody implant trial and the vertebral surfaces. [0066] FIG.7 illustrates an exemplary flow chart for a method 700 of using an interbody implant trial system (for example interbody implant trial system 300 in FIG.3). The method 700 begins at step 702 by coupling an insertion tool (for example insertion tool 104 in FIGS. 1 and 3) to an interbody implant trial (for example interbody implant trial 102 in FIGS.1 and 3). As described above, the interbody implant trial includes first and second portions each with a vertebral body facing surface, and an expansion mechanism between the first and second portions. [0067] At step 704, the interbody implant trial is inserted into a patient’s vertebral disc space while the interbody implant trial is in a closed configuration (e.g., the first and second vertebral body facing surfaces are parallel, or substantially parallel, such that little or no force is required to insert the interbody implant trial). The interbody implant trial is inserted using the insertion tool. After insertion, at step 706 the height of the interbody implant trial is expanded using the insertion tool. The height is adjusted in a controlled fashion, and can be measured by a sensor or indicator located in or on the interbody implant trial or insertion tool and reported via a physical indicator or the display to the surgeon during expansion. In some implementations, a height of the interbody implant trial is communicated from the trial to an external device in real-time, so that the surgeon can monitor the dimensions of the interbody implant trial. In some implementations, the footprint of the interbody implant trial (e.g., a length, width, shape, or indication of manufacturer device having a matching footprint) is also communicated from the trial to the external device. At step 708, a contact area between a vertebral body facing surface of the first and second portions and vertebral bodies defining the vertebral disc space is monitored. Sensors on the vertebral body facing surface of the first and second portions detect the force and location of contact between the vertebral body facing surface of the first and second portions and the vertebral bodies, and the information is transmitted as a signal from the interbody implant trial to a computer or processing device. [0068] At step 710, the lordosis of the first portion and the second portion (e.g., an angle between the vertebral body facing surface of the first and second portions relative to a longitudinal axis of the interbody implant trial) is adjusted using the insertion tool while the interbody implant trial is within the vertebral disc space. The lordosis is changed in a controlled fashion, and is changed independently from the height of the interbody implant trial. The lordosis can be measured by a sensor or indicator located in or on the interbody implant trial or insertion tool and reported via a physical indicator or the display to the surgeon during expansion. As described above with regard to the height and footprint of the interbody device, in some implementations, a lordosis of the interbody implant trial is communicated from the trial to an external device in real-time, so that the surgeon can monitor the dimensions of the interbody implant trial. [0069] At step 712, the contact area and force between the vertebral facing surface of the first and second portions with the vertebral bodies defining the vertebral disc space is monitored while the lordosis of the interbody implant trial is adjusted. By monitoring the contact area and force between the vertebral facing surface of the first and second portions and the vertebral bodies as height and lordosis are changed, various configurations can be trialed and the impact of the various heights and lordosis combination can be understood by the surgeon to inform the selection of implant size. Stress can be calculated based on the force divided by the contact area, and the calculated stress can indicate a likelihood or risk of subsidence. An algorithm can use the information to select an optimal (or recommended, preferred, or suitable) interbody implant for the vertebral space, and after the height and lordosis of the interbody implant trial have been adjusted to explore the possible configurations, a decision support tool using the algorithm can report that the intended final conformation (i.e. height and lordosis angle) has been achieved or an algorithmically driven bone stress cut point has been reached. From the information provided by the decision support tool, the surgeon can determine which implant from a set of available implants is likely to have a favorable outcome for the patient. In some implementations, the decision support tool provides the determination of the optimal (or recommended, preferred, or suitable) implant, and in other implementations, the decision support tool provides information regarding the ideal (or recommended, preferred, or suitable) height and lordosis for a favorable outcome, from which the surgeon can determine a best implant. In some implementations, the algorithm selects an interbody implant for the vertebral space based on a calculated stress (and associated risk of subsidence). In some implementations, the algorithm selects an interbody implant for the vertebral space based on a measured force alone. In some implementations, the algorithm selects an interbody implant for the vertebral space based on another intraoperative measurement, such as an expansion torque or an expansion pressure. [0070] In some implementations, an interbody implant trial is capable of sizing each option for an implant that is available with a particular footprint (i.e., the width and depth of the trial). Interbody device systems can come in a variety of footprints, such as coming in three to four footprints. In some implementations, the interbody implant trial is capable of adjusting the width and depth parameters of the trial so that the interbody implant trial can be used for many or all implant sizes and footprints. [0071] FIG.8 shows an example process 800 for determining a best implant for implantation in the vertebral disc space of a subject. The process 800 can be performed, for example, by the sensors 150, a data source 802, the training computer hardware 830, and the operations computer hardware 832, though other components may be used to perform the process 800 or other similar processes. [0072] The sensors 150 sense force measurements 804 and send the force measurements to the training computer hardware 830. The training computer hardware 830 receives the force measurements of the implant trial recorded during the expansion of the trial. The force measurements of the data include pressure and location of the force on the trial. [0073] The data source 802 provides preoperative data 808 to the training computer hardware 830 and the training computer hardware 830 receives the preoperative data for the subject. For example, the data sources 802 may include a database stored in one or more servers connected to the training computer hardware 830 over a data network such as the internet. [0074] The training computer hardware 830 generates segmented training-data 812 using the force measurements and preoperative data. To generate the segmented data, the hardware 830 can apply one or more band-pass filters to at least some of the force measurements, e.g., to remove high and low values greater than and less than given thresholds. The force measurements can be correlated with heights and/or lordosis of the interbody implant trial. [0075] The hardware 830 can use tagging data that tags each force measurement with the height, lordosis, or other positioning of the interbody implant trial. The training computer hardware 830 uses the segmented training-data generates to generate force measurement features for the patient. For example, the features of force measurements may be categorized based on force thresholds which are pre-set, or determined based on preoperative data, for example bone health, bone strength, or other. In another example, the features of force measurements may be defined based on areas of the vertebral body facing surfaces of the implant trial where forces are detected, for example on the top vertebral body facing surface (i.e., the first portion of the implant), the bottom vertebral body facing surface (i.e., the second portion of the implant), toward the distal or proximal end of the implant, and/or on the sides of the vertebral body facing surface. The generation of force measurement features can aid in the determination of an optimal implant to fit the patient’s vertebral disc space and to accomplish the surgical goals of an implant surgery for a particular patient. [0076] The training computer hardware 830 selects 816 a subset of the force measurement features as selected features. For example, one or more analyses may be performed to identify the subset of the force measurement features as those features most predictive of the fit of an implant in a vertebral disc space and favorable surgical outcomes that do not result in subsidence of the vertebral bodies. To select the features, cross-validated mean absolute error (MAE) (e.g., finding and averaging the difference, without regard to the sign of the differences) with an extreme learning machine (ELM) regressor (e.g., using a feedforward neural network such as those with hidden nodes having parameters that are not tuned) may be performed. [0077] The training computer hardware 830 generates 818 one or more function-metric classifiers comprising training a model that defines at least one relationship between the force measurements and one or more other aspects, such as patient age or demographic, preoperative data such as bone strength or health measurements, surgical outcome, type of surgery, type of implant, or vertebral disc space. For example, the model may predict new results based on old training data. The training can include determining hyperparameters of the model or hyperparameters that control learning processes for a model using a Bayesian optimization algorithm. This optimization algorithm can be configured to target various targets or loss functions, such as a model’s performance in repeated k-fold cross-validation. The training can use, for example, a regression; a regression with a loss function based on a residual-label covariance analysis, or a deep label distribution algorithm. [0078] The training can include refining the model to reduce bias. For example, it may be the case that some implementations may use models that exhibit a mathematical bias (e.g., generation of an output set in which data incorrectly skews, clusters, or oscillates around one or more attractor point in the output space, or that applies an weighting to a parameter or set of parameters that is either greater or smaller than the weighting exhibited by the ground truth) related to age or another demographic criteria. In such a case, the training of the model can include refining or other editing in a way that reduces the bias along this parameter or multiple parameters. This refining can include first identifying a parameter for which the model exhibits bias, then applying one or more modifications to the model and/or model output to reduce or eliminate. For example, it may be determined that the model performs well for patients in a particular demographic, for example for patients of a given age (e.g., 65 years and younger) but less well for older users. In such a case, an output-conditioning function can be applied to all outputs or outputs for users of age 65 years or greater. One such adjustment includes a linear adjustment, however, other adjustments are possible including non-linear scaling. [0079] The training computer hardware 830 distributes 820 the function-metric classifiers to a plurality of user devices (e.g., operating computer hardware 832) that are receive the classifier 822. The operating computer hardware 832 also receives new force measurements 824 for the same or a different patient. The hardware 832 can receive, from one or more sensors of an interbody implant trial, new force measures recorded after the function-metric classifiers have already been generated. [0080] The operating computer hardware 832 provides 826, as output, a function-metric value determined based on the defined relationship between the force measurements and other characteristics such as patient age, surgical outcomes, surgical procedures, implant types, vertebral disc space, or any other characteristic. A report of the functional metric may be displayed on a computer screen, via a mobile application, or in a printed report. [0081] To create this metric for the clinician, the hardware 832 can submit the new force measurements to at least one of the function-metric classifiers as the input; and receive as output from the at least one function-metric classifier the function-metric value. In addition to a single metric, the classifier can also provide other types of output including but not limited to a confidence value, a variance value, a model interpretation, a human-readable instruction displayable to a user of an output device, and an automation-instruction that, when executed by an automated device causes the automated device to actuate. [0082] FIG 9 shows an example of a computing device 900 and an example of a mobile computing device that can be used to implement the techniques described herein. The computing device 900 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The mobile computing device is intended to represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart-phones, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed in this document. [0083] The computing device 900 includes a processor 902, a memory 904, a storage device 906, a high-speed interface 908 connecting to the memory 904 and multiple high-speed expansion ports 910, and a low-speed interface 912 connecting to a low-speed expansion port 914 and the storage device 906. Each of the processor 902, the memory 904, the storage device 906, the high-speed interface 908, the high-speed expansion ports 910, and the low- speed interface 912, are interconnected using various busses, and can be mounted on a common motherboard or in other manners as appropriate. The processor 902 can process instructions for execution within the computing device 900, including instructions stored in the memory 904 or on the storage device 906 to display graphical information for a GUI on an external input/output device, such as a display 916 coupled to the high-speed interface 908. In other implementations, multiple processors and/or multiple buses can be used, as appropriate, along with multiple memories and types of memory. Also, multiple computing devices can be connected, with each device providing portions of the necessary operations (e.g., as a server bank, a group of blade servers, or a multi-processor system). [0084] The memory 904 stores information within the computing device 900. In some implementations, the memory 904 is a volatile memory unit or units. In some implementations, the memory 904 is a non-volatile memory unit or units. The memory 904 can also be another form of computer-readable medium, such as a magnetic or optical disk. [0085] The storage device 906 is capable of providing mass storage for the computing device 900. In some implementations, the storage device 906 can be or contain a computer-readable medium, such as a floppy disk device, a hard disk device, an optical disk device, or a tape device, a flash memory or other similar solid state memory device, or an array of devices, including devices in a storage area network or other configurations. A computer program product can be tangibly embodied in an information carrier. The computer program product can also contain instructions that, when executed, perform one or more methods, such as those described above. The computer program product can also be tangibly embodied in a computer- or machine-readable medium, such as the memory 904, the storage device 906, or memory on the processor 902. [0086] The high-speed interface 908 manages bandwidth-intensive operations for the computing device 900, while the low-speed interface 912 manages lower bandwidth- intensive operations. Such allocation of functions is exemplary only. In some implementations, the high-speed interface 908 is coupled to the memory 904, the display 916 (e.g., through a graphics processor or accelerator), and to the high-speed expansion ports 910, which can accept various expansion cards (not shown). In the implementation, the low-speed interface 912 is coupled to the storage device 906 and the low-speed expansion port 914. The low-speed expansion port 914, which can include various communication ports (e.g., USB, Bluetooth, Ethernet, wireless Ethernet) can be coupled to one or more input/output devices, such as a keyboard, a pointing device, a scanner, or a networking device such as a switch or router, e.g., through a network adapter. [0087] The computing device 900 can be implemented in a number of different forms, as shown in the figure. For example, it can be implemented as a standard server 920, or multiple times in a group of such servers. In addition, it can be implemented in a personal computer such as a laptop computer 922. It can also be implemented as part of a rack server system 924. Alternatively, components from the computing device 900 can be combined with other components in a mobile device (not shown), such as a mobile computing device 950. Each of such devices can contain one or more of the computing device 900 and the mobile computing device 950, and an entire system can be made up of multiple computing devices communicating with each other. [0088] The mobile computing device 950 includes a processor 952, a memory 964, an input/output device such as a display 954, a communication interface 966, and a transceiver 968, among other components. The mobile computing device 950 can also be provided with a storage device, such as a micro-drive or other device, to provide additional storage. Each of the processor 952, the memory 964, the display 954, the communication interface 966, and the transceiver 968, are interconnected using various buses, and several of the components can be mounted on a common motherboard or in other manners as appropriate. [0089] The processor 952 can execute instructions within the mobile computing device 950, including instructions stored in the memory 964. The processor 952 can be implemented as a chipset of chips that include separate and multiple analog and digital processors. The processor 952 can provide, for example, for coordination of the other components of the mobile computing device 950, such as control of user interfaces, applications run by the mobile computing device 950, and wireless communication by the mobile computing device 950. [0090] The processor 952 can communicate with a user through a control interface 958 and a display interface 956 coupled to the display 954. The display 954 can be, for example, a TFT (Thin-Film-Transistor Liquid Crystal Display) display or an OLED (Organic Light Emitting Diode) display, or other appropriate display technology. The display interface 956 can comprise appropriate circuitry for driving the display 954 to present graphical and other information to a user. The control interface 958 can receive commands from a user and convert them for submission to the processor 952. In addition, an external interface 962 can provide communication with the processor 952, so as to enable near area communication of the mobile computing device 950 with other devices. The external interface 962 can provide, for example, for wired communication in some implementations, or for wireless communication in other implementations, and multiple interfaces can also be used. [0091] The memory 964 stores information within the mobile computing device 950. The memory 964 can be implemented as one or more of a computer-readable medium or media, a volatile memory unit or units, or a non-volatile memory unit or units. An expansion memory 974 can also be provided and connected to the mobile computing device 950 through an expansion interface 972, which can include, for example, a SIMM (Single In Line Memory Module) card interface. The expansion memory 974 can provide extra storage space for the mobile computing device 950, or can also store applications or other information for the mobile computing device 950. Specifically, the expansion memory 974 can include instructions to carry out or supplement the processes described above, and can include secure information also. Thus, for example, the expansion memory 974 can be provided as a security module for the mobile computing device 950, and can be programmed with instructions that permit secure use of the mobile computing device 950. In addition, secure applications can be provided via the SIMM cards, along with additional information, such as placing identifying information on the SIMM card in a non-hackable manner. [0092] The memory can include, for example, flash memory and/or NVRAM memory (non- volatile random access memory), as discussed below. In some implementations, a computer program product is tangibly embodied in an information carrier. The computer program product contains instructions that, when executed, perform one or more methods, such as those described above. The computer program product can be a computer- or machine- readable medium, such as the memory 964, the expansion memory 974, or memory on the processor 952. In some implementations, the computer program product can be received in a propagated signal, for example, over the transceiver 968 or the external interface 962. [0093] The mobile computing device 950 can communicate wirelessly through the communication interface 966, which can include digital signal processing circuitry where necessary. The communication interface 966 can provide for communications under various modes or protocols, such as GSM voice calls (Global System for Mobile communications), SMS (Short Message Service), EMS (Enhanced Messaging Service), or MMS messaging (Multimedia Messaging Service), CDMA (code division multiple access), TDMA (time division multiple access), PDC (Personal Digital Cellular), WCDMA (Wideband Code Division Multiple ACCess), CDMA2000, or GPRS (General Packet Radio Service), among others. Such communication can occur, for example, through the transceiver 968 using a radio-frequency. In addition, short-range communication can occur, such as using a Bluetooth, WiFi, or other such transceiver (not shown). In addition, a GPS (Global Positioning System) receiver module 970 can provide additional navigation- and location- related wireless data to the mobile computing device 950, which can be used as appropriate by applications running on the mobile computing device 950. [0094] The mobile computing device 950 can also communicate audibly using an audio codec 960, which can receive spoken information from a user and convert it to usable digital information. The audio codec 960 can likewise generate audible sound for a user, such as through a speaker, e.g., in a handset of the mobile computing device 950. Such sound can include sound from voice telephone calls, can include recorded sound (e.g., voice messages, music files, etc.) and can also include sound generated by applications operating on the mobile computing device 950. [0095] The mobile computing device 950 can be implemented in a number of different forms, as shown in the figure. For example, it can be implemented as a cellular telephone 980. It can also be implemented as part of a smart-phone 982, personal digital assistant, or other similar mobile device. [0096] Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device. [0097] These computer programs (also known as programs, software, software applications or code) include machine instructions for a programmable processor, and can be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the terms machine-readable medium and computer-readable medium refer to any computer program product, apparatus and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine- readable medium that receives machine instructions as a machine-readable signal. The term machine-readable signal refers to any signal used to provide machine instructions and/or data to a programmable processor. [0098] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a LCD (liquid crystal display) display screen for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input. [0099] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet. [0100] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. [0101] While this specification contains many specific implementation details, these should not be construed as limitations on the scope of the disclosed technology or of what may be claimed, but rather as descriptions of features that may be specific to particular embodiments of particular disclosed technologies. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment in part or in whole. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Moreover, although features may be described herein as acting in certain combinations and/or initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination. Similarly, while operations may be described in a particular order, this should not be understood as requiring that such operations be performed in the particular order or in sequential order, or that all operations be performed, to achieve desirable results. Particular embodiments of the subject matter have been described. Other embodiments are within the scope of the following claims. [0102] In various implementations, operations that are performed “in response to” or “as a consequence of” another operation (e.g., a determination or an identification) are not performed if the prior operation is unsuccessful (e.g., if the determination was not performed). Operations that are performed “automatically” are operations that are performed without user intervention (e.g., intervening user input). Features in this document that are described with conditional language may describe implementations that are optional. In some examples, “transmitting” from a first device to a second device includes the first device placing data into a network for receipt by the second device, but may not include the second device receiving the data. Conversely, “receiving” from a first device may include receiving the data from a network, but may not include the first device transmitting the data. [0103] “Determining” by a computing system can include the computing system requesting that another device perform the determination and supply the results to the computing system. Moreover, “displaying” or “presenting” by a computing system can include the computing system sending data for causing another device to display or present the referenced information. [0104] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (“LAN”), a wide area network (“WAN”), peer-to-peer networks (having ad-hoc or static members), grid computing infrastructures, and the Internet. [0105] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. [0106] Further to the descriptions above, a user may be provided with controls allowing the user to make an election as to both if and when systems, programs or features described herein may enable collection of user information (e.g., information about a user's social network, social actions or activities, profession, a user's preferences, or a user's current location), and if the user is sent content or communications from a server. In addition, certain data may be treated in one or more ways before it is stored or used, so that personally identifiable information is removed. For example, a user's identity may be treated so that no personally identifiable information can be determined for the user, or a user's geographic location may be generalized where location information is obtained (such as to a city, ZIP code, or state level), so that a particular location of a user cannot be determined. Thus, the user may have control over what information is collected about the user, how that information is used, and what information is provided to the user. [0107] By combining preoperative image-based assessment of bone health with intraoperative direct force and contact area measures, an optimal implant can be identified to achieve the planned changes in the relationship between a patient’s adjacent vertebrae to produce the best immediate and sustainable outcome. Conventional techniques for trialing an interbody implant use a trial with a fixed footprint, height and lordotic angle that matches each of the available implants in a particular system, and a surgeon proceeds from the smaller implant sizes up until the ideal height and lordosis angle is identified. Currently, the only governing input for selecting the proper size is how hard you have to mallet the fixed shape trial into the disc space, and the method is imprecise. As a result, there is a high rate of subsidence for interbody fusion devices which have poor contact area or exert large stresses on the surrounding vertebrae. In contrast, the use of an expandable interbody implant trial enables a surgeon to trial a variety of implant sizes and height/lordosis configurations quickly and without use of a mallet. The sensors on the interbody implant trial provide precise measurements and indications of the contact locations and stresses between the trail and the adjacent vertebrae. This information, along with preoperative information indicative of bone strength and health of the vertebrae, allows a decision support tool to determine an optimal implant from a selection of available implants for a favorable outcome for the patient. The decision support tool can use a machine learning algorithm trained on many spinal surgeries and postsurgical outcomes to become better at predicting the optimal implant and configuration, and can also learn the preferences of a particular surgeon to provide surgeon- specific recommendations informed by real-time measurements, intraoperative data, and preoperative data. [0108] A number of embodiments of the invention have been described. Nevertheless, it will be understood that various modifications may be made without departing from the scope of the invention. For example, size and shape of the interbody implant trials, and size, shape and orientation of sensors on the implants can be modified as appropriate for a given application. As another example, additional preoperative or intraoperative data can be used in the determination of an optimal implant for use in a patient. Similarly, one or more components described with respect to one example of an interbody implant trial or interbody implant trial system can be combined with other examples of interbody implant trial systems described herein. Accordingly, other embodiments are within the scope of the following claims.

Claims

WHAT IS CLAIMED IS: 1. An interbody implant trial system comprising: an interbody implant trial, comprising: an expandable body comprising a first portion and a second portion, the first portion and the second portion each comprising a vertebral body facing surface; and one or more sensors positioned to detect force on the vertebral body facing surface; and an insertion tool configured to be coupled to the interbody implant trial, the insertion tool configured to engage the expandable body to adjust at least one of a height between the first portion and the second portion of the expandable body and a lordosis of the first portion relative to the second portion.

2. The system of claim 1, wherein the insertion tool comprises a first proximal end and a first distal end, the first distal end configured to be coupled to the interbody implant trial.

3. The system of claim 1, wherein the insertion tool is releasably coupled to the interbody implant trial.

4. The system of claim 3, wherein the insertion tool is configured to be coupled to the interbody implant trial by a threaded end portion.

5. The system of claim 3, wherein the insertion tool is configured to be coupled to the interbody implant trial by first and second arms, the first and second arms configured to engage with first and second indentations of the interbody implant trial.

6. The system of claim 3, wherein the interbody implant trial is configured to be disposable following release from the insertion tool.

7. The system of claim 6, wherein the interbody implant trial is formed at least in part from a metal or poly ethyl ether ketone (PEEK).

8. The system of claim 3, wherein the interbody implant trial and the insertion tool are configured to be disposable.

9. The system of claim 1, wherein the insertion tool is configured to provide a means for transmitting a signal from the interbody implant trial to an external device.

10. The system of claim 9, wherein the signal is representative of the detected force.

11. The system of claim 9, wherein the signal transmitted from the interbody implant trial to the external device includes current trial dimensions of the interbody implant trial.

12. The system of claim 1, further comprising an expansion mechanism configured to change a height between the first portion and the second portion and a lordotic angle of the first portion relative to the second portion.

13. The system of claim 12, wherein the expansion mechanism comprises a screw configured to change one or both of the height and lordotic angle of the first portion and the second portion.

14. The system of claim 13, wherein the expansion mechanism comprises a torque sensor coupled to the screw, the torque sensor configured to detect a torque required to drive the screw and transmit the detected torque to an external device.

15. The system of claim 12, wherein the expansion mechanism is configured to change an implant length by adjusting a position of the first portion relative to the second portion.

16. The system of claim 12, wherein the first portion is coupled to the second portion at one end by a hinge.

17. The system of claim 12, wherein the one or more sensors are positioned on the expansion mechanism.

18. The system of claim 1, wherein the one or more sensors are positioned on the vertebral body facing surfaces.

19. The system of claim 1, wherein the one or more sensors are positioned between the first and second portions.

20. The system of claim 1, wherein the interbody implant trial further comprises: means for measuring contact area, stress, and expansion force.

21. The system of claim 1, wherein the interbody implant trial is configured to be used for at least one of ALIF, OLIF, LLIF, and P/TLIF interbody approaches.

22. A method of using the interbody implant trial system of claim 1, the method comprising: coupling the insertion tool to the interbody implant trial; inserting, using the insertion tool, the interbody implant trial into a patient’s vertebral disc space while the interbody implant trial is in a closed configuration; expanding, using the insertion tool, a height of the interbody implant trial; monitoring a contact area between a vertebral-facing surface of the first and second portions with vertebral bodies defining the vertebral disc space; adjusting, using the insertion tool, a lordosis of the first portion and the second portion within the vertebral disc space; monitoring the contact area and a force between the vertebral-facing surface of the first and second portions with the vertebral bodies defining the vertebral disc space while adjusting the lordosis; and transmitting data representative of the contact area and the force from the interbody implant trial to an external device.

23. A method for determining an interbody implant for implantation in a vertebral disc space of a patient, the method comprising: obtaining preoperative data specific to the patient; obtaining intraoperative data specific to the patient; correlating, using at least one processor, the preoperative data and the intraoperative data; and determining, using an algorithm, an interbody implant for use in the patient based on the correlation of both the preoperative data and intraoperative data.

24. The method of claim 23, wherein the preoperative data specific to the patient comprises at least one of CT scan images, MRI scan images, bone density data, neural monitoring, and bone health data.

25. The method of claim 23, wherein the intraoperative data specific to the patient comprises at least one of neural monitoring, anesthesia information, and data received from an interbody implant trial.

26. The method of claim 25, wherein the data received from the interbody implant trial comprises at least one of (i) a contact area between at least one surface of the interbody implant trial and at least one vertebral body of the patient, and (ii) a force measurement representative of a force between the at least one surface of the interbody implant trial and the at least one vertebral body of the patient, wherein the contact area and/or the force measurement is measured while the interbody implant trial is positioned within the vertebral disc space of the patient.

27. The method of claim 26, further comprising dividing the force measurement by the contact area to determine a stress measurement.

28. The method of claim 27, wherein the stress measurement is a measurement of stress over a particular contact area.

29. The method of claim 27, wherein the stress measurement is a measurement of stress over all contact areas.

30. The method of claim 27, wherein the determining an interbody implant comprises selecting the interbody implant based at least in part on the determined stress measurement.

31. The method of claim 26, wherein the determining an interbody implant comprises selecting the interbody implant based at least in part on the force measurement.

32. The method of claim 26, further comprising: comparing the received data comprising at least one of the contact area and the force measurement to a plurality of pre-set implant specifications, each of the plurality of pre-set implant specifications corresponding to an implant of a plurality of commercially available implants; and based on the comparison, selecting an optimal implant of the plurality of commercially available implants.

33. The method of claim 23, the method further comprising: displaying at least part of the preoperative data or the intraoperative data on a display during a surgery to implant the interbody implant into the patient.

34. The method of claim 33, wherein displaying at least part of the preoperative data or the intraoperative data comprises displaying a color map of a representation of the interbody implant, the color map representative of pressure on a trial implant during intraoperative insertion into a vertebral space of the patient.

35. The method of claim 24, wherein obtaining the preoperative data or the intraoperative data comprises obtaining data from an external device.

36. The method of claim 35, the method further comprising: accessing a repository of anonymized interbody implant trial preoperative data or intraoperative data for a plurality of patients; and determining a risk associated with use of the determined interbody implant based on the repository of anonymized interbody implant trial preoperative data or intraoperative data for the plurality of patients.

37. An interbody implant trial comprising: an expandable body comprising a first portion and a second portion, the first portion and the second portion each comprising a vertebral body facing surface; and an expansion mechanism positioned between the first portion and the second portion, the expansion mechanism configured to adjust a position of the first portion relative to the second portion; wherein at least one of the first portion and the second portion comprises one or more sensors for detecting a force on the vertebral body facing surface.

38. The interbody implant trial of claim 37, further comprising: means for communicating the detected force from the one or more sensors to an external device.

39. The interbody implant trial of claim 37, further comprising: a coupler configured to couple the implant to an insertion tool such that the insertion tool engages the expansion mechanism for expansion of the first portion with respect to the second portion.

40. The interbody implant trial of claim 37, wherein the expansion mechanism is configured to change one or more of implant height, lordosis, and implant length.

41. The interbody implant trial of claim 37, wherein the first portion is coupled to the second portion at one end by a hinge.

42. The interbody implant trial of claim 37, further comprising means for measuring contact area, stress, and expansion force.

43. The interbody implant trial of claim 37, wherein the implant is configured to be used for at least one of ALIF, OLIF, LLIF, and P/TLIF interbody approaches.

44. A method of using a interbody implant trial, the method comprising: obtaining a interbody implant trial comprising: an expandable body comprising a first portion and a second portion, the first portion and the second portion each comprising a vertebral body facing surface; an expansion mechanism positioned between the first portion and the second portion; and a plurality of sensors positioned on the vertebral body facing surfaces of the first and second portions, the plurality of sensors configured to detect forces on the interbody implant trial at a plurality of locations on the vertebral body facing surfaces where the vertebral body facing surfaces are in contact with vertebral bodies in a patient’s vertebral disc space; inserting the interbody implant trial into a vertebral space of a patient in a first configuration, wherein the vertebral body facing surfaces of the first portion and the second portion are substantially parallel in the first configuration; and expanding the interbody implant trial from the first configuration using an expansion mechanism to a second configuration in which the vertebral body facing surfaces of the first portion and the second portion are in contact with first and second vertebral surfaces defining the vertebral space.

45. The method of claim 44, wherein expanding the interbody implant trial comprises: one or both of (i) increasing a distance between the vertebral body facing surfaces of the first portion and the second portion while the vertebral body facing surfaces of the first portion and the second portion remain parallel and (ii) increasing a distance between the vertebral body facing surfaces of the first portion and the second portion at a first end of the first portion and the second portion.

46. The method of claim 44, wherein expanding the interbody implant trial comprises: first, increasing a distance between the vertebral body facing surfaces of the first portion and the second portion while the vertebral body facing surfaces of the first portion and the second portion remain parallel; and second, adjusting an angle between the vertebral body facing surfaces of the first portion and the second portion by increasing a distance between the vertebral body facing surfaces of the first portion and the second portion at a first end of the first portion and the second portion.

47. The method of claim 44, wherein the plurality of sensors comprises an array of sensors.

48. The method of claim 47, wherein the array of sensors comprises an array of piezoelectric components.

49. The method of claim 44, further comprising: transmitting the detected forces to an external device.

50. The method of claim 44, the interbody implant trial further comprising: a first aperture formed through the vertebral body facing surface of the first portion; and a second aperture formed through the vertebral body facing surface of the second aperture; wherein the plurality of sensors are arranged about a perimeter of the first and second apertures of the first portion and the second portion.

51. The method of claim 44, further comprising: testing a bone density adjacent to the interbody implant trial using a tool.

52. The method of claim 51, wherein the tool comprises an insertional torque detection device for use with a screw.

53. The method of claim 44, further comprising: returning the interbody implant trial to the first configuration; and removing the interbody implant trial from the vertebral space.

54. A system comprising: a spinal implant trial comprising: an expandable body comprising a first portion and a second portion, the first portion and the second portion each comprising a vertebral body facing surface; and a plurality of sensors positioned on the vertebral body facing surfaces of the first and second portions, the plurality of sensors configured to detect forces on the spinal implant trial at a plurality of locations on the vertebral body facing surfaces where the vertebral body facing surfaces are in contact with vertebral bodies in a patient’s vertebral disc space; and a computer having a memory and one or more processors, the one or more processors configured to receive data from the spinal implant trial and the memory configured to store the data from the spinal implant trial, wherein the one or more processors are further configured to: determine from the received data, a force profile representing forces between vertebral implant facing surfaces of the spinal implant trial and vertebral bodies of the patient; and display the force profile on a display.

55. The system of claim 54, the processor further configured to: determine from the received data a contact area of each of the vertebral implant facing surfaces of the spinal implant trial with the vertebral bodies of the patient

56. The system of claim 54, the processor further configured to: determine an expansion force of the vertebral implant facing surfaces of the spinal implant trial with the vertebral bodies of the patient during expansion of the spinal implant trial; and display the determined expansion force on the display.

57. The system of claim 56, the processor further configured to determine the expansion force based on a signal received from a torque sensor positioned on an expansion mechanism of the expandable body.

58. The system of claim 54, the processor further configured to: determine an end plate stress of the vertebral implant facing surfaces of the spinal implant trial with the vertebral bodies of the patient during expansion of the spinal implant trial; and display the determined end plate stress on the display.

59. The system of claim 58, the processor further configured to: determine an implant for implantation based on the determined end plate stress.

60. The system of claim 54, the processor further configured to: determine an optimal position of the spinal implant trial based on the force profile; and display the determined optimal position on the display.

61. The system of any of claims 56-60, wherein displayed data is updated continuously while the spinal implant trial is within the vertebral disc space of the patient.

62. The system of claim 54, the processor further configured to: correlate the received data with preoperative data stored in the memory; and determine an implant for implantation and a position of the determined implant based on the correlated received data and preoperative data.

63. The system of claim 54, wherein the memory is configured to store surgical procedure steps and the processor further configured to display the stored surgical procedure steps in a sequence on the display.

64. The system of claim 54, wherein the memory is further configured to store a preoperative plan and the processor is further configured to display the preoperative plan on the display.

65. The system of claim 64, wherein the preoperative plan includes a checklist of surgical goals.

66. The system of claim 54, wherein the processor is configured to receive data wirelessly.

67. The system of claim 54, wherein the processor is configured to receive data by near field transmission.

68. The system of claim 54, wherein the processor is configured to receive data by a wired connection with the spinal implant trial.

69. The system of claim 54, wherein the computer further comprises voice recognition software.

70. The system of claim 54 wherein the computer further comprises a touch screen.

71. The system of claim 54, wherein the computer further comprises a sterile cover.

72. A spinal implant trial with a plurality of sensors positioned on vertebral body facing surfaces, the plurality of sensors configured to detect forces on the spinal trial implant at a plurality of locations on the vertebral body facing surfaces where the vertebral body facing surfaces are in contact with vertebral bodies in a patient’s vertebral disc space.

73. The spinal implant trial of claim 72, wherein the spinal trial implant is configured to be adjustable in height and lordosis.

74. The spinal implant trial of claim 72, wherein the plurality of sensors are an array of sensors.

75. The spinal implant trial of claim 74, wherein the array of sensors are piezoelectric sensors.

76. The spinal implant trial of claim 72, wherein the spinal trial implant further comprises a communications mechanism to communicate the detected forces to an external device.

77. An expandable spinal implant trial, the expandable spinal trial implant comprising one or more sensors positioned on vertebral body facing surfaces.

78. The expandable spinal implant trial of claim 77, wherein the expandable spinal trial implant is configured to be adjustable in height and lordosis.

79. The expandable spinal implant trial of claim 78, wherein the one or more sensors are an array of sensors.

80. The expandable spinal implant trial of claim 79, wherein the array of sensors are piezoelectric sensors.

81. The expandable spinal implant trial of claim 79, wherein the array of sensors is configured to detect positions and pressures of a plurality of forces on the expandable spinal trial implant.

82. The expandable spinal implant trial of claim 77, wherein the plurality of sensors are configured to be removably positioned on the vertebral body facing surfaces.

83. A method of providing surgical decision support comprising: receiving, at a processor, preoperative data; receiving, at the processor, surgical data comprising intraoperative data including one or more dimensions of an interbody implant trial currently inserted in a spine of a patient and at least one stress measurement detected at the interbody implant trial; determining, based on the preoperative data and the intraoperative data, a risk grade of subsidence related to the interbody implant trial in the spine of the patient; and outputting, on a display, an indication of the determined risk grade for subsidence related to the one or more dimensions of the interbody implant trial currently inserted in the spine of the patient.

84. The method of claim 83, wherein the outputted indication of the determined risk grade is depicted on the display as one of a percentage, a tertile, a color map, or an image.

85. The method of claim 84, wherein the outputted indication of the determined risk grade is calculated as a tertile and depicted on the display as one of a green, yellow, or red indication.

86. The method of claim 83, wherein the determining a risk grade is performed by a machine learning algorithm.

87. The method of claim 83, wherein the machine learning algorithm receives as an input one or more postoperative outcomes to adapt to a performance or preference of a surgeon.

88. The method of claim 83, further comprising: outputting, on the display, the intraoperative data including the one or more dimensions of the interbody implant trial currently inserted in a spine of a patient.

89. The method of claim 88, wherein the one or more dimensions of the interbody implant trial include at least one of an implant height, a lordosis, and an implant footprint.

90. The method of claim 88, further comprising: outputting, on the display, a comparison of the one or more dimensions of in the interbody implant trial to dimensions of at least one implant of a predetermined set of available interbody implants.