4D computed tomography imaging in radiotherapy

dosimetry

1. Population of 4D Computational Phantoms for CT Imaging Research and Dosimetry W. Paul Segars, PhD Carl E. Ravin Advanced Imaging Labs Duke University

2. Myocardial SPECT Digital phantom Emission Computed Tomography (ECT) X-ray CT Transmission Computed Tomography (TCT) Medical Imaging Simulation Computer model of SPECT scanner Images reconstructed from projections Computer model of X-ray CT scanner Images reconstructed from projections

3. Medical Imaging Simulation Advantages: Exact anatomy of the computer phantom is known providing a gold standard to evaluate and improve devices and techniques Computer phantoms can be altered easily to model different anatomies and medical situations providing a large population of subjects from which to perform research No need to worry about overexposing the phantom to radiation or being sued by the phantom (IRB approval not needed)

4. 4D e X tended CA rdiac - T orso (XCAT) Phantoms 4 Segars el al, 4D XCAT phantom for multimodality imaging research, Medical Physics, vol. 37 (9), 2010

5. 5 Detailed Brain Model based on MRI 4D XCAT Phantom Anatomy

6. 6 4D XCAT Phantom Anatomy Detail in the hands and feet Adding nervous and lymphatic systems

7. Cardiac and Respiratory Models Cardiac Model Based on 4D Tagged MRI and CT Respiratory Model Based on 4D CT 7

8. Imaging Simulations using the Computerized XCAT Phantoms 8

9. Population of 4D XCAT Phantoms Create a population of hundreds of detailed phantoms to represent the public at large from infancy to adulthood Optimize CT clinical applications, image quality vs. dose Each model is based on patient CT data from Duke Database Include cardiac and respiratory motions for 4D simulations First library of 4D phantoms 9 Segars el al, Population of anatomically variable 4D XCAT adult phantoms for imaging research and optimization, Medical Physics, vol. 40 (4), 2013

10. Phantom Construction Segment CT data to define initial base anatomy for the patient Map template to patient models using the segmented framework as a guide Morph the template to define unsegmented structures in the target patients (blood vessels, muscles, tendons, ligaments, etc) Check morphed phantom for anatomical accuracy 10

11. 11 LDDMM Method to Map the XCAT to the Patient

12. 12 Application of LDDMM to Create Patient-Specific Phantom

13. 13 New XCAT Phantoms

14. 58 Adult Phantoms 14

15. Adult Phantoms 15

16. 42 Pediatric Phantoms 16

17. Pediatric Phantoms 17

18. 18 Simulation of Male CT Data BMI: 21.9 BMI: 22.7 BMI: 28.5 BMI: 36.1 18

19. 19 Simulation of Female CT Data BMI: 18.2 BMI: 22.3 BMI: 28.6 BMI: 35.5 19

20. Simulation of 4D CT Data End-diastole End-systole End-expiration End-inspiration Cardiac Model Respiratory Model 20

21. Accurate Dose Estimation from CT Protocols 21 Chest Scan Abdomen Scan

22. Ultimate Goal 22 Create hundreds of models representing both genders with varying ages, heights, and weights encompassing the full range from pediatric to adult patients Optimize CT clinical applications in terms of image quality versus radiation dose Distribute the phantoms for research

23. Conclusions The phantoms developed in this work will have a widespread use in CT imaging research to quantitatively evaluate and improve imaging devices and techniques and to investigate the effects of anatomy and motion They can also be used to investigate patient and population-based dose correlations in CT and to enable prospective estimation of CT dose and radiation risk 23