Medical physics · 2026
Comparison of two established approaches for generating Hounsfield look-up tables for CT-based SPR prediction.
СтатьяСравнительное исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Nakao Minoru, Schwengfelder Julian, Richter Christian, Peters Nils, Ozawa Shuichi
Аннотация
BACKGROUND: To ensure consistency in treatment planning across institutions, inter-center variations in Hounsfield look-up tables (HLUTs) have been evaluated using different methods in Japan and Europe. In Japan, the Hiroshima High-Precision Radiotherapy Cancer Center (HIPRAC) developed the computed tomography number calibration audit (HIPRAC-CTCA) based on a stoichiometric method, while in Europe, the European Particle Therapy Network (EPTN) implemented a method using validated tissue-equivalent inserts. Comparing these approaches is essential to improving consistency and reliability.
PURPOSE: This study aims to enhance the reliability of the HIPRAC method by comparing it with the EPTN consensus guide-based HLUT generation methods used in multi-institutional evaluations.
METHODS: HLUTs were generated using the HIPRAC and EPTN methods for both head and body phantom configurations. The HIPRAC-based HLUT was created by measuring CT numbers of tough lung and tough bone inserts, applying the stoichiometric method, and calculating the theoretical HLUTs for representative tissues based on the International Commission on Radiological Protection Publication 110. The EPTN-based HLUT was generated by measuring the CT numbers of validated tissue-equivalent inserts, calculating the CT numbers of human tissues using the stoichiometric method, and determining the HLUT through piecewise linear regression between CT numbers and stopping-power ratios (SPRs) for both tissue-equivalent inserts and human tissues. ΔSPR values were calculated by subtracting the EPTN-based HLUT from the HIPRAC-based HLUT and were categorized into lung, soft tissue, and bone groups. Representative brain tumor and prostate cancer cases were analyzed to evaluate spot-wise range shifts (ΔR80) when applying the two HLUTs.
RESULTS: Both methods showed good agreement in lung, soft tissue, and bone, with all ΔSPR values within ± 2% and mean differences ≤ 1%. In cortical bone, ΔSPR reached approximately 2%-3%, leading to minor range shifts. In the clinical case analysis, mean ΔR80 were -0.28 mm for the brain tumor case and -0.45 mm for the prostate cancer case, indicating that proton range differences between the two HLUTs were negligibly small.
CONCLUSIONS: The established HLUT generation methods for CT-based SPR prediction developed in Japan and Europe were compared and showed good agreement across all tissue types. Range differences in clinical cases were minor, and ΔSPR variations in cortical bone corresponded to negligible proton range deviations. These findings indicate that the European and Japanese approaches are practically equivalent and support the validity and reliability of the HIPRAC-CTCA method.
PURPOSE: This study aims to enhance the reliability of the HIPRAC method by comparing it with the EPTN consensus guide-based HLUT generation methods used in multi-institutional evaluations.
METHODS: HLUTs were generated using the HIPRAC and EPTN methods for both head and body phantom configurations. The HIPRAC-based HLUT was created by measuring CT numbers of tough lung and tough bone inserts, applying the stoichiometric method, and calculating the theoretical HLUTs for representative tissues based on the International Commission on Radiological Protection Publication 110. The EPTN-based HLUT was generated by measuring the CT numbers of validated tissue-equivalent inserts, calculating the CT numbers of human tissues using the stoichiometric method, and determining the HLUT through piecewise linear regression between CT numbers and stopping-power ratios (SPRs) for both tissue-equivalent inserts and human tissues. ΔSPR values were calculated by subtracting the EPTN-based HLUT from the HIPRAC-based HLUT and were categorized into lung, soft tissue, and bone groups. Representative brain tumor and prostate cancer cases were analyzed to evaluate spot-wise range shifts (ΔR80) when applying the two HLUTs.
RESULTS: Both methods showed good agreement in lung, soft tissue, and bone, with all ΔSPR values within ± 2% and mean differences ≤ 1%. In cortical bone, ΔSPR reached approximately 2%-3%, leading to minor range shifts. In the clinical case analysis, mean ΔR80 were -0.28 mm for the brain tumor case and -0.45 mm for the prostate cancer case, indicating that proton range differences between the two HLUTs were negligibly small.
CONCLUSIONS: The established HLUT generation methods for CT-based SPR prediction developed in Japan and Europe were compared and showed good agreement across all tissue types. Range differences in clinical cases were minor, and ΔSPR variations in cortical bone corresponded to negligible proton range deviations. These findings indicate that the European and Japanese approaches are practically equivalent and support the validity and reliability of the HIPRAC-CTCA method.