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DoseBridge model advances proton therapy dose prediction

Researchers have developed DoseBridge, a novel denoising diffusion bridge model designed for predicting radiation doses in lung intensity-modulated proton therapy (IMPT). Unlike previous models that primarily relied on CT images, DoseBridge incorporates beam geometry information through a spatially aligned beam mask. Evaluated on 52 lung cancer patients, the model demonstrated superior performance in dose prediction accuracy and similarity metrics compared to existing deep-learning approaches. The findings suggest DoseBridge could serve as a valuable planning prior for lung IMPT, though further validation on larger patient cohorts is recommended. AI

IMPACT This research could lead to more accurate and personalized radiation therapy planning, improving patient outcomes in cancer treatment.

RANK_REASON The cluster contains an academic paper detailing a new model for a specific medical application. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

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DoseBridge model advances proton therapy dose prediction

COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Zerun Zhang, Xiaoda Cong, Xiangkun Xu, Peter Y. Chen, Xuanfeng Ding ·

    DoseBridge: Denoising Diffusion Bridge Model for Dose Prediction in Lung Intensity-Modulated Proton Therapy

    arXiv:2608.10173v1 Announce Type: new Abstract: Most radiotherapy dose-prediction models use only CT images and anatomical structures, although intensity-modulated proton therapy (IMPT) dose also depends strongly on beam geometry and available clinical datasets are often small. W…