A treatment planning study of urethra-sparing intensity-modulated proton therapy for localized prostate cancer

PHYSICS & IMAGING IN RADIATION ONCOLOGY(2021)

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摘要
Background and Purpose: Urethra-sparing radiation therapy for localized prostate cancer can reduce the risk of radiation-induced genitourinary toxicity by intentionally underdosing the periurethral transitional zone. We aimed to compare the clinical impact of a urethra-sparing intensity-modulated proton therapy (US-IMPT) plan with that of conventional clinical plans without urethral dose reduction. Materials and Methods: This study included 13 patients who had undergone proton beam therapy. The prescribed dose was 63 GyE in 21 fractions for 99% of the clinical target volume. To compare the clinical impact of the US-IMPT plan with that of the conventional clinical plan, tumor control probability (TCP) and normal tissue complication probability (NTCP) were calculated with a generalized equivalent uniform dose-based Lyman-Kutcher model using dose volume histograms. The endpoints of these model parameters for the rectum, bladder, and urethra were fistula, contraction, and urethral stricture, respectively. Results: The mean NTCP value for the urethra in US-IMPT was significantly lower than that in the conventional clinical plan (0.6% vs. 1.2%, p < 0.05). There were no statistically significant differences between the conventional and US-IMPT plans regarding the mean minimum dose for the urethra with a 3-mm margin, TCP value, and NTCP value for the rectum and bladder. Additionally, the target dose coverage of all plans in the robustness analysis was within the clinically acceptable range. Conclusions: Compared with the conventional clinically applied plans, US-IMPT plans have potential clinical advantages and may reduce the risk of genitourinary toxicities, while maintaining the same TCP and NTCP in the rectum and bladder.
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关键词
Urethra-sparing radiotherapy, Prostate cancer, Intensity-modulated proton therapy, Tumor control probability, Normal tissue complication probability
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