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EP4179495A1 - Système de planification et de vérification de traitement pendant des procédures iort - Google Patents

Système de planification et de vérification de traitement pendant des procédures iort

Info

Publication number
EP4179495A1
EP4179495A1 EP21742508.1A EP21742508A EP4179495A1 EP 4179495 A1 EP4179495 A1 EP 4179495A1 EP 21742508 A EP21742508 A EP 21742508A EP 4179495 A1 EP4179495 A1 EP 4179495A1
Authority
EP
European Patent Office
Prior art keywords
tomography
dimensional scan
surgery
preoperative
computed
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP21742508.1A
Other languages
German (de)
English (en)
Inventor
Francesco COLLAMATI
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Instituto Nazionale di Fisica Nucleare INFN
Original Assignee
Instituto Nazionale di Fisica Nucleare INFN
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Instituto Nazionale di Fisica Nucleare INFN filed Critical Instituto Nazionale di Fisica Nucleare INFN
Publication of EP4179495A1 publication Critical patent/EP4179495A1/fr
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformations in the plane of the image
    • G06T3/14—Transformations for image registration, e.g. adjusting or mapping for alignment of images
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
    • G06T7/35—Determination of transform parameters for the alignment of images, i.e. image registration using statistical methods
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N5/00—Radiation therapy
    • A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
    • A61N5/1048—Monitoring, verifying, controlling systems and methods
    • A61N5/1049—Monitoring, verifying, controlling systems and methods for verifying the position of the patient with respect to the radiation beam
    • A61N2005/1061—Monitoring, verifying, controlling systems and methods for verifying the position of the patient with respect to the radiation beam using an x-ray imaging system having a separate imaging source
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N5/00—Radiation therapy
    • A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
    • A61N5/103—Treatment planning systems
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10081—Computed x-ray tomography [CT]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20076—Probabilistic image processing
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30068—Mammography; Breast
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30096—Tumor; Lesion

Definitions

  • the present invention relates to the field of intraoperative radiotherapy and the processing of personalized treatment plans consistent with relevant criticalities and provides a computed method which allows obtaining, without resorting to traditional imaging techniques and therefore saving time, resources, and patient radiation dose, an intraoperative computed tomography or CT image which is representative of the intraoperative condition of the operated subject with sufficient precision for the purposes of processing a treatment plan or TPS (Treatment Planning System) in IORT.
  • TPS Treatment Planning System
  • IORT Intra Operative Radiation Therapy
  • radiation dose electrons or X-rays
  • the radiation dose electrons or X-rays
  • radiotherapy treatment parameters such as dose and energy of the particles to be used (i.e., the depth to be treated) is still carried out based on general tables, in stark contrast to the principle of personalized medicine, the true paradigm of modern medicine. Furthermore, even once the treatment has been carried out, there is currently no way to provide the patient with the aforesaid “dosimetry report” which takes into account his/her particular treatment case. The combination of all these effects causes IORT to be applied with global uncertainties (e.g., on the deposited dose) of around 10%.
  • TPS Treatment Planning System
  • the fundamental reason for this shortcoming is the unavailability of intraoperative imaging from which it is possible to obtain the “virtual patient” required for the TPS (Hensley FW. Present state and issues in IORT Physics. Radiation Oncology. 2017).
  • the first approach is to perform a true intraoperative imaging, for example by performing a CT or NMR on the patient at the end of the operation (Garcia-Vazquez V, Marinetto E, Guerra P, Valdivieso-Casique MF, Calvo FA, Alvarado-Vasquez E, et al. Assessment of intraoperative 3D imaging alternatives for IOERT dose estimation. Z Med Phys. 2017).
  • the invention consists of a computed method for obtaining a corrected or intraoperative tomography which corresponds to the state of the subject subjected to surgery.
  • the invention further consists of a method for processing treatment plans in lORT-type operations.
  • the latter method is based on the utilization of the above computed method to obtain a CT image of the patient at the end of the surgery and before the radiotherapy treatment. Such an image is then used as an input for a simulation algorithm of the physical treatment processes, allowing a map of the dose released to each organ to be obtained.
  • Figure 1 is a diagrammatic depiction of a first embodiment of the computed method of the invention.
  • Figure 2 is a diagrammatic depiction of a second embodiment of the computed method of the invention.
  • Figure 3 shows a diagrammatic depiction of a use mode of the computed method of the invention for processing treatment plans for IORT operations.
  • the present patent application relates to a procedure which allows obtaining a computed tomography or CT image which is representative of the intraoperative condition of the operated subject with sufficient precision for the purposes of processing a treatment plan or TPS (Treatment Planning System) in IORT.
  • the IORT operation generally comprises two main steps which are: the so-called surgery during which the removal of the diseased tissues occurs, and the actual radiotherapy treatment which consists in exposing the surrounding tissues to ionizing radiations: for brevity, these steps will be referred to as “surgery” and “radiotherapy” below, respectively.
  • Preoperative CT or preoperative tomography thus means the computed tomography image of the subject to be operated on generally acquired in the days preceding the surgery.
  • the invention suggests a computed method for correcting the preoperative CT in which the missing or modified volumetric information is corrected so as to create an “intraoperative CT” which best approximates the subject’s condition at the moment of the radiotherapy treatment or radiotherapy.
  • the computed method of the present patent application comprises the following main steps: a. Providing a preoperative tomography of the subject and a first three-dimensional scan of the region involved in the operation; b. Obtaining, from said preoperative tomography and first three- dimensional scan, information related to size and spacing of the voxels forming them; c. Calculating the average density of the subject in the region to be subjected to surgery from the preoperative tomography; d. Trying to find the space transformation which maximizes the alignment between said preoperative tomography and first three- dimensional scan; e. Applying said transformation to a second three-dimensional scan of the region involved in the surgery to obtain a three-dimensional scan aligned with the preoperative tomography; f.
  • empty voxels means the unit of volume not occupied by tissue of the subject to be subjected to the surgical treatment.
  • said first and second three-dimensional scans of the region involved in the operation coincide and are acquired at the end of the surgery or after the removal of the cancer tissue and in any case before the skin layer is restored.
  • said first three- dimensional scan is acquired prior to surgery while the second three- dimensional scan is acquired with reference to the same region at the end of the surgical stage intended as in the previous paragraph.
  • Said first and second three-dimensional scans of the region involved in the operation are preferably acquired by the same acquisition system and with the same position related to the individual to subject/subjected to surgery.
  • the mathematical transformation obtained at the end of step d is always applied to the second three-dimensional scan, whether this coincides with the first scan or not.
  • the preoperative CT of the patient (as per step a) can be acquired in the days preceding the treatment, as is normal practice for external beam radiotherapy, but also in the hours immediately preceding it, since the execution times of the correction algorithm of said CT are very fast ( ⁇ 10s). In this latter case, the accuracy of the resulting image with respect to the real morphology of the patient will be even greater.
  • step b The information related to the size and spacing of the voxels of the two images (preoperative CT and superficial scan) (step b) is necessary to map the two images, coming from very different technologies, on a common space, where the alignment can then be searched for.
  • Such features are easily obtained from both CT images (result of the features of the machinery used and reported in the metadata of the DICOM files) and surface scanning (result of the settings chosen for the scanning device).
  • the evaluation of the average density of the voxels in the zone involved in the surgery or which will be subjected to surgical modification (as per step c) is necessary to minimize the error of the preoperative CT correction procedure.
  • Such an evaluation can be obtained by cropping (both manual and possibly automated, for example by machine learning algorithms) of the zone on the preoperative CT image.
  • cropping both manual and possibly automated, for example by machine learning algorithms
  • Those skilled in the art will be able to determine the extent of said region involved in the surgery in order to obtain a significant average density value for the purposes of the suggested method.
  • said region will be limited to the breast itself rather than involving the entire thoracic image of the patient.
  • the transformation which maximizes the alignment of the surface scan with the preoperative CT is identified by means of stochastic algorithms, based for example (but not only) on Gradient Descent.
  • stochastic algorithms based for example (but not only) on Gradient Descent.
  • step e The application of said transformation to the volumetric scan leads to obtaining a volumetric scan which is homogeneous in the spatial coordinates and correctly aligned with the preoperative CT.
  • a CT image is obtained (therefore in an appropriate format, for example (but not exclusively) DICOM) which is representative of the anatomy modified during surgery (“intraoperative CT”), and which can then be used as an input for simulation algorithms, for example to obtain treatment plans.
  • the computed method suggested is used in a protocol aimed at processing treatment plans for IORT operations.
  • the treatment plan also known as TPS (Treatment Planning System)
  • TPS Treatment Planning System
  • the process is based on a morphological image of the patient (typically a CT), with which a “virtual patient” is created, on which the radiotherapist indicates the target of the therapy and the dose to be received by this volume.
  • This virtual patient is then used to perform computer simulations (pencil beam algorithms, Monte Carlo, etc.) which allow comparing various treatment configurations, with the aim of identifying the best compromise in terms of dosing to the tumor/dosing to healthy tissues.
  • the use of the computed method for processing treatment plans for IORT operations comprises the following main steps:
  • a first three-dimensional scan of the region involved in the operation is optionally acquired before surgery (step B‘).
  • Said first scan can advantageously be acquired directly with the patient on the operating bed and does not require cumbersome instrumentation or long acquisition times.
  • acquiring a three-dimensional scan takes less than 10 seconds.
  • Said preferred embodiment is diagrammatically depicted in Figure 3. The steps enclosed by the box can be performed during surgery, possibly in the same operating room. Step B‘ and the consequent obtaining of the three-dimensional scan are optional steps.
  • Clinical practice dictates that preoperative computed tomography is acquired approximately ten days or a week earlier than the surgery date. However, in principle it is possible to acquire the image even in the hours immediately before the operation since the processing times of the image are around 10s.
  • the three-dimensional scans (B, B‘) can be acquired by any instrument capable of carrying out three-dimensional scans with a spatial resolution of around at least one millimeter over an acquisition field of around least 30x30cm.
  • instruments capable of working even under difficult lighting conditions and/or in the presence of reflections are used.
  • a software algorithm is used, which is capable of mapping the two images on a homogeneous space, also identifying the transformation to be applied to the three- dimensional scan to maximize the alignment between this and the preoperative computed tomography.
  • a software algorithm is used, which takes the two images as an input, the preoperative CT and the three-dimensional scan, respectively, and is capable of “erasing” the pixels of the first to which the pixels of the post-surgery three- dimensional scan correspond, in which there is no more tissue or, on the contrary, to insert new pixels where required.
  • the simulation step (D) is a common practice in the physics of elementary particles and also in the applications thereof in the medical field, and consists in simulating the passage of the radiation of matter, the energy loss thereof, the generation of secondary particles, and all the processes which contribute to the dose release in the various organs.
  • the simulation algorithm consists of Monte Carlo software algorithms or simulation software based on the Monte Carlo method. Examples of these software are FLUKA and Geant4, commonly used in particle physics. Other possible examples of simulation algorithms are the Pencil Beam and Hybrid Monte Carlo algorithms.
  • Radiotherapy treatment means any therapeutic treatment with ionizing radiation, preferably electron beams of energy between 1-13 MeV.
  • the TPS is also capable of providing a precise “dosimetry report” related thereto, i.e., an account of how much dose has been transferred to each organ. In fact, this is a key medical document in order to plan any new treatments which the same patient may need later.
  • the computed method was tested by simulating a surgical treatment (or surgery) on a breast phantom.
  • a surface image (first three-dimensional scan) of the phantom was acquired.
  • the surgery was then simulated by removing a portion of the material forming the phantom itself.
  • a second three-dimensional scan was then acquired on the phantom already subjected to the modifications (surgery).
  • the ability to perform a three-dimensional scan with sufficient resolution and field of view for an anatomy “similar” to that expected was achieved by using the facial recognition sensor of a smartphone to acquire the profile of a silicone breast phantom. Both the resolution, and more generally, the logistics of the acquisition were verified to be compatible with the requirements of the technique.
  • step (d) software has been developed which is capable of taking the two images obtained by 3D scanning of the same phantom, align them, and use the second one to “correct” the first one according to the same criteria reported in step (f); however, in the absence of a true preoperative CT of the phantom, the 3D scan of the intact phantom was used instead of CT.
  • the alignment of the images was obtained by identifying the transformation which maximized the overlap, then applied to the post-surgery 3D scan.
  • the result obtained is a three-dimensional image of the post-surgery phantom which approximates an intraoperative CT.
  • the computed method was then applied to the practical case in order to process treatment plans for hypothetical IORT operations, thus including radiotherapy.
  • a Monte Carlo simulation in FLUKA was developed for a treatment with direct electrons at the surgical cavity.
  • the “corrected” image of the phantom was forcibly superimposed on a segmented CT of a patient, required to evaluate the dosing to the various organs.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Quality & Reliability (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Medical Informatics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Evolutionary Biology (AREA)
  • Probability & Statistics with Applications (AREA)
  • Radiation-Therapy Devices (AREA)
  • Programmable Controllers (AREA)
  • Supply And Distribution Of Alternating Current (AREA)
  • Apparatus For Radiation Diagnosis (AREA)

Abstract

La présente invention concerne une procédure qui permet d'obtenir, sans recourir à des techniques d'imagerie classiques, une image de tomodensitométrie (CT) qui est représentative de l'état peropératoire du sujet opéré avec une précision suffisante pour le traitement d'un plan de traitement ou d'un TPS (système de planification de traitement) dans l'IORT.
EP21742508.1A 2020-07-07 2021-06-24 Système de planification et de vérification de traitement pendant des procédures iort Pending EP4179495A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
IT102020000016387A IT202000016387A1 (it) 2020-07-07 2020-07-07 Sistema di pianificazione e verifica del trattamento durante procedure iort
PCT/IB2021/055616 WO2022009014A1 (fr) 2020-07-07 2021-06-24 Système de planification et de vérification de traitement pendant des procédures iort

Publications (1)

Publication Number Publication Date
EP4179495A1 true EP4179495A1 (fr) 2023-05-17

Family

ID=72885840

Family Applications (1)

Application Number Title Priority Date Filing Date
EP21742508.1A Pending EP4179495A1 (fr) 2020-07-07 2021-06-24 Système de planification et de vérification de traitement pendant des procédures iort

Country Status (3)

Country Link
EP (1) EP4179495A1 (fr)
IT (1) IT202000016387A1 (fr)
WO (1) WO2022009014A1 (fr)

Also Published As

Publication number Publication date
IT202000016387A1 (it) 2022-01-07
WO2022009014A1 (fr) 2022-01-13

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