Dose prediction in proton cancer therapy based on density maps from dual-energy CT using joint statistical image reconstruction

Maria Jose Medrano Matamoros; Xinyuan Chen; Tao Ge; Tianyu Zhao; Rui Liao; David G. Politte; Jeffrey F. Willamson; Bruce R. Whiting; Yao Hao; Baozhou Sun; Joseph A. O'Sullivan

doi:10.1117/12.2611801

4 April 2022 Dose prediction in proton cancer therapy based on density maps from dual-energy CT using joint statistical image reconstruction

Maria Jose Medrano Matamoros, Xinyuan Chen, Tao Ge, Tianyu Zhao, Rui Liao, David G. Politte, Jeffrey F. Willamson, Bruce R. Whiting, Yao Hao, Baozhou Sun, Joseph A. O'Sullivan

Author Affiliations +

Proceedings Volume 12031, Medical Imaging 2022: Physics of Medical Imaging; 1203119 (2022) https://doi.org/10.1117/12.2611801
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Abstract

Accuracy in proton range prediction is critical in proton therapy to ensure conformal tumor dose. Our lab proposed a joint statistical image reconstruction method (JSIR) based on a basis vector model (BVM) for estimation of stopping power ratio maps and demonstrated that it outperforms competing Dual Energy CT (DECT) methods. However, no study has been performed on the clinical utility of our method. Here, we study the resulting dose prediction error, the difference between the dose delivered to tissue based on the more accurate JSIR-BVM method and the planned dose based on Single Energy CT (SECT).

Conference Presentation

Citation Download Citation

Maria Jose Medrano Matamoros, Xinyuan Chen, Tao Ge, Tianyu Zhao, Rui Liao, David G. Politte, Jeffrey F. Willamson, Bruce R. Whiting, Yao Hao, Baozhou Sun, and Joseph A. O'Sullivan "Dose prediction in proton cancer therapy based on density maps from dual-energy CT using joint statistical image reconstruction", Proc. SPIE 12031, Medical Imaging 2022: Physics of Medical Imaging, 1203119 (4 April 2022); https://doi.org/10.1117/12.2611801

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