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SU-E-J-121: A New 4D Radiotherapy Planning Strategy Using Synthesized Tumor-Motion-Compensated Computed Tomography
P Cohen1,1,2,3,1,1, D Li1,1,2,3,1,1, H Xie1,1,2,3,1,1
1Memorial Sloan-Kettering Cancer Center, New York, NY.
Medical Physics
|May 19, 2017
Summary
A 3.5D plan, which accounts for tumor motion, is equivalent to four-dimensional radiotherapy (4DRT) planning for lung lesions. This approach simplifies clinical workload while ensuring reliable tumor delineation and normal tissue representation.
Area of Science:
- Medical Imaging
- Radiation Oncology
- Radiotherapy Planning
Background:
- Tumor motion significantly impacts radiotherapy accuracy.
- Four-dimensional computed tomography (4DCT) addresses motion but is complex.
- Synthesized CT images offer a potential simplification for motion-compensated planning.
Purpose of the Study:
- To validate a four-dimensional radiotherapy (4DRT) planning method using a synthesized CT image.
- To assess its ability to compensate for tumor motion, rotation, deformation, and distortion.
- To ensure realistic normal tissue density in motion-tracking beam eye view.
Main Methods:
- Used 4DCT images from six patients with peripheral lung lesions.
- Developed a program to simulate motion-compensated tumors and create a static 3.5DCT image.
- Generated and compared 3DRT plans using 3.5DCT and 4DCT, employing integrated dose volume histograms (iDVH) and deformable image registration (DIR) for evaluation.
Main Results:
- Tumor volume variation within a breathing cycle was substantial (87%±46%).
- The synthesized 3.5DCT provided a more reliable averaged gross tumor volume (GTV) than individual phase CTs.
- 3.5D plans were equivalent to 4D plans, with minor differences primarily in low-dose regions (below D20%).
Conclusions:
- The 3.5D plan is a viable and equivalent alternative to 4D plans for peripheral lung lesions.
- This method significantly reduces clinical workload.
- It offers reliable tumor delineation and realistic normal tissue representation for motion-tracking radiotherapy.
