(Wednesday, 8/1/2018) 10:00 AM - 10:30 AM
Room: Exhibit Hall | Forum 2
Purpose: CBCT is commonly used for localization on a Linac with kV imaging systems. However, the soft tissue contrast in CBCT is rather limited for localizing tumors in the soft tissue. On-board MRI has been developed to address this issue, but its availability in clinics is rather limited. This study explores the feasibility of using prior images and deformable registration to generate on-board contrast enhanced images to improve the soft tissue contrast for target localization in radiation therapy.
Methods: Contrast enhanced CT images acquired during simulation were deformably registered to the CBCT using a B-spline based deformable registration method. The CT images were then deformed based on the registration to generate estimated on-board contrast enhanced CT images for target localization. 8 liver, 7 prostate, and 7 breast patients data with 65 fractions of CBCT were used in the study to investigate the feasibility of the method. We evaluated: (1) whether the registration and margin design in clinical practice is sufficient to ensure the coverage of the on-board tumor volume; (2) the potential for margin optimization based on the synthetic CT.
Results: (1). Most of the tumor volume defined by the on-board synthetic CT images was covered by the PTV based on the shifts applied in clinical practice. The under-dosed cases are correlated with interfraction deviation in long treatment course, small PTV volume, and insufficient PTV margin. (2). the synthetic images allowed the reduction of PTV margin up to 6mm, 4mm, and 1.5 mm for liver, prostate and breast patients, respectively, which led to more normal tissue sparing.
Conclusion: Our studies demonstrated the feasibilities of generating on-board synthetic CT images for target localization in soft tissue. Further studies are warranted to incorporate registration uncertainties in the workflow to optimize the localization accuracy and margin design.
Funding Support, Disclosures, and Conflict of Interest: NIH Grant No: R01 CA-184173.
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