Development and validation of MRI-derived deep learning score for non-invasive prediction of PD-L1 expression and prognostic stratification in head and neck squamous cell carcinoma

Development and validation of MRI-derived deep learning score for non-invasive prediction of PD-L1 expression and prognostic stratification in head and neck squamous cell carcinoma

Abstract Background Immunotherapy has revolutionized the treatment landscape for head and neck squamous cell carcinoma (HNSCC) and PD-L1 combined positivity score (CPS) scoring is recommended as a biomarker for immunotherapy. Therefore, this study aimed to develop an MRI-based deep learning score (D...

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Bibliographic Details
Main Authors: Cong Ding, Yue Kang, Fan Bai, Genji Bai, Junfang Xian
Format: Article
Language:English
Published: BMC 2025-02-01
Series:Cancer Imaging
Subjects:
Magnetic resonance imaging
Deep learning
PD-L1 expression
Immunotherapy
Head and neck squamous cell carcinoma
Online Access:https://doi.org/10.1186/s40644-025-00837-5
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https://doi.org/10.1186/s40644-025-00837-5

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