Advanced Targeting Using Image Deformation. Justin Keister, MS DABR Aurora Health Care Kenosha, WI

Transcription

1 Advanced Targeting Using Image Deformation Justin Keister, MS DABR Aurora Health Care Kenosha, WI

2 History of Targeting The advance of IMRT and CT simulation has changed how targets are identified in radiation therapy. GTV, CTV, PTV, and ITVs are now commonly used in radiation therapy. How does a physician identify their targets? Many use previous diagnostic imaging studies to help identify their targets at the time of CT simulation.

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4 PET/CT for CT simulation Many clinics have moved to using PET/CT studies for diagnostic imaging workup. PET has become the gold standard for metabolic diagnostic information with certain types of cancers. PET/CT provides challenges for CT simulation because patient immobilization setup can be uncomfortable. The long scan time, smaller bore sizes, and the devices used for immobilization can make PET/CT prohibitive for use in simulation.

5 Diagnostic Information from PET PET has proven to be a critically useful tool for target identification in Radiation Therapy. PET provides information about the metabolically active tissues that comprise targets. PET also provides limited information about motion management. PET studies take into account tissue motion throughout the length of study, usually about 30 mins. This can function as a time elongated ITV.

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8 Use of PET for Targeting With metabolic information so useful, it is natural for physicians to want to incorporate it in targeting. The gold standard for this is PET/CT simulation. If PET/CT simulation study is not an option for the patient, fusion of PET data to the CT simulation study is an alternative for physicians. Limitations with this method for target identification is it does not take into account changes to the patient between the diagnostic study and the CT simulation.

9 Fusion of Studysets Rigid Fusion of diagnostic studysets historically has been the only option and is the standard for gleaning diagnostic information onto the CT simulation data. Immobilization in treatment position necessitates that, frequently, the diagnostic imaging will not align with rigid fusion onto the CT simulation dataset. RIGID FUSION

10 How does a physician resolve this dilemma?

11 Deformation is an alternative When a patient is imaged in a different position for a diagnostic image study than the CT simulation study, deformation can be used to derive information about the target volume from the diagnostic studyset.

12 What is Deformation? Deformation is the process of applying an algorithm to an image studyset or a defined volume within an image studyset to stretch and move the voxels so that it matches the overlayed images of an equal volume.

13 Deformation Not Applied Outer Box CT Sim Inner Box Diagnostic CT

14 Deformation Applied Outer Box CT Sim Inner Box Diagnostic CT

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16 B Splines algorithm The B Splines algorithm is most commonly used for imaging CT studysets. The two most commonly used commercial software platforms for applying deformations in radiation therapy are MimVista TM and Velocity TM. Each software vendor has proprietary application of the B Splines algorithm for image deformation.

17 Applying Deformation Our experience with applying deformation is within the Velocity TM software platform using their proprietary Deformable Multipass algorithm. The algorithm has two input basis from the user, the rigid registration and the deformation volume. Rigid registration and choice of deformation volume substantially effect the output and success of deformation.

18 Medical Physicist s Role in Deformation Applying our mathematical background, knowledge of cross sectional anatomy, and clinical background is where the physicist becomes the medical physicist. Deformation evaluation is as much an art as it is a science and medical physicist has a skillset that is suitable to this process.

19 Issues Surrounding Deformation The first thing to consider when fusing multiple studysets is whether or not to use deformation. When considering whether or not to use deformation, one must consider the location of the volume of interest, the position of the patient in both image sets, and the size of the volume of interest. The goal should always be rigid fusion, as it reduces uncertainty. Example of this is intercranial fusion.

20 Issues Surrounding Deformation (Con t) Because deformation involves changing one image set to match another, it assumes that there are no changes between anatomy between studysets (no major weight loss/gain, no major volumetric change to target, etc) This is frequently not the case, especially with a long duration between a PET workup and CT simulation. Surgery and chemotherapy in between can have major anatomic effects on the patient.

21 Issues Surrounding Deformation Due to difference between patient studies, deformation can lead to artifact, creation of false structures, blurring, and mismatch of known structures in the body. The physicist has to understand the deformation process to be the expert in evaluating and answering questions regarding deformation as it applies to fusion.

22 Examples of deformation failure Inside Box Deformed PET/CT Outside Box CT simulation Massive stomach/intestinal volume changes. Deformation fails

23 Diagnostic CT/PET Scan Deformed PET on CT Simulation The patient s arms were up in CT sim vs. down in CT/PET scan. Deformation clearly fails.

24 Evaluating Deformation Evaluating deformation is an evolving skillset and like anything else, it is a learning process. There are many considerations that go into fusing multiple images and the use of deformation.

25 Quantitative vs. Qualitative Measure of Success Physicists tend to want to apply a quantitative measure of success to an evaluation process. With deformation, there is no proven quantitative measure to currently apply and the evaluation process necessitates a subjective qualitative review by the physicist.

26 Qualitative Components to Evaluation Visual Analysis of Input Parameters (Rigid Fusion and Deformation Volume) Vector and Grid Review of Deformation Grid Alignment of Identifiable Anatomic Structures (best done with CT to CT overlay) Visual Analysis of CT resolution and artifact

27 Qualitative Components to Evaluation Comparison of Volumes between rigid and deformed scans for critical structures and target volumes. Conformality Index of Comparible Structures

28 Managing the Imperfect Art of Deformation Despite the components to evaluation, there is no perfect way to evaluate deformation to verify certainty of the volumes and positioning of deformed targets. Uncertainty must be accepted with target structures.

29 Example of issues surrounding deformation evaluation Blue structure is 5.0 SUV from PET/CT on 6/1/16 Green structure is 5.0 SUV deformed structure to CT sim on 10/17/16 Rigid volume is 15 cc. Deformed is 6.7 cc.

30 Uncertainty in Targeting How is uncertainty best managed in targeting? MARGINS!! By comparing volumes and using a spherical volume assumption, one can margin for uncertainty.

31 Potential Future Considerations For deformation that creates a volume to volume overlay of CT studysets, a gamma comparison analysis of HU values between the two volumes of interest may be useful in the future. This may provide another quantitative component to analysis, but qualitative measures are still needed to make sure that deformation doesn t ignore crucial patient data that can negate postive quantitative results.

32 In Summary Deformation has become an important tool that physics and dosimetry can use for assistance in targeting. The physicist has an important role in defining the use of deformation. There is further development to be done with deformation to ensure safe and accurate use in patient targeting.

33 THANK YOU FOR YOUR ATTENTION AND FEEDBACK!