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DOI 10.1002/acm2.70075

Медицинская библиотека · Journal of applied clinical medical physics · 2025

Diagnostic image-based treatment planning for online adaptive ultra-hypofractionated prostate cancer radiotherapy with MR-Linac.

Xu Yuan, Lu Ningning, Li Qiao, Men Kuo, Zhao Xinming, Dai Jianrong

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Аннотация

PURPOSE: A new workflow was investigated for Elekta Unity MR-Linac by removing the computed tomography (CT)-simulation step and using diagnostic CT (DCT) for reference plan generation.

MATERIALS AND

METHODS

Ten patients with ultra-hypofractionated prostate cancer treated with magnetic resonance imaging (MRI)-guided adaptive radiotherapy were retrospectively enrolled. Targets and organs at risk (OARs) were recontoured on DCT, and Hounsfield unit conversions to relative electron density were calibrated for DCT. Reference plans were reoptimized and recalculated using DCT for Unity. Subsequent adaptive plans were designed through an adapt-to-shape workflow to edit targets and OARs via daily MRI to generate a new treatment plan. Bulk electron density information for Unity adaptive plan was compared between planning CT (PCT) and DCT for volumes of interest. Dosimetric parameters were evaluated between PCT- and DCT-based reference and adaptive plans for target coverage and OAR dose constraints.

RESULTS

Bulk relative electron density differences between PCT and DCT were within ±1% for targets and OARs, excepting the rectum. PCT and DCT-based reference plans did not significantly differ in mean target coverages or for OARs in dosimetric difference except for V36 Gy of the rectum. PCT- and DCT-based adaptive plans did not significantly differ for most dosimetric parameters of targets and OARs except for V29 Gy and V36 Gy of the rectum, V18.1 Gy of the bladder, and D50% of the urethra.

CONCLUSIONS

By removing the CT simulation step, it is feasible to use DCT for designing reference and adaptive plans in the Unity ATS workflow. The workflow increased adaptive radiotherapy efficiency and decreased patient waiting time and additional radiation dose.

Для цитирования: Xu Yuan, Lu Ningning, Li Qiao, Men Kuo, Zhao Xinming, Dai Jianrong. Diagnostic image-based treatment planning for online adaptive ultra-hypofractionated prostate cancer radiotherapy with MR-Linac.. Journal of applied clinical medical physics. 2025. DOI: 10.1002/acm2.70075.

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