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KA-TMoE: A Deep Learning Method Using Time-Series CT Radiomics to Predict Post-Radiotherapy Rib Fractures in NSCLC Patients
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DOI：10.1016/j.ijrobp.2026.07.056.png)
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Abstract
En 中文
Rib fracture is a recognized clinical complication in medically inoperable patients with non-small cell lung cancer (NSCLC) undergoing stereotactic body radiotherapy (SBRT), leading to diminished quality of life and delayed recovery. There remains an unmet need for reliable tools to predict rib fracture risk to support individualized prognosis. This study aimed to develop and validate a deep learning model for predicting post-SBRT rib fractures using time-series CT radiomics.
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