Evaluation of PD-L1 expression status in nasopharyngeal carcinoma by 18F-FDG PET/CT radiomics analysis

Background:We aimed to accurately and efficiently evaluate Programmed Death Ligand-1 (PD-L1) expression by relevant radiomic studies of fluoro-18fluorodeoxyglucose (18F-FDG) Positron Emission Tomography/Computed Tomography (PET/CT) images in nasopharyngeal carcinoma (NPC) patients.Materials and Methods: This retrospective study included 60 untreated NPC patients had PET/CT.Cohorts of training and validation were randomly selected among the patients.The CT and PET radiomic features from the training cohort were obtained and screened, to construct CT, PET and combined models.Finally, verification and comparative analysis were performed.Results: According to the analysis, the maximum Standardized Uptake Value (SUVmax) alone was the standalone predictive indicator of PD-L1 presence level, thus incorporated into the combined model.Among our training cohort, the CT, PET, and combined models' Area under Curve (AUC) values respectively were 0.837, 0.852, and 0.948, demonstrating excellent discrimination and calibration.However, the combined model had higher AUC values in the cohorts of training and validation, reaching AUCs of 0.948 and 0.802, respectively.Clinical decision curve analysis (DCA) further illustrated Combined model surpassed both the CT and PET models, attaining a benefit threshold probability of more than 5% and a net benefit (NB) of 0.450 at the optimal threshold probability.Conclusion: The combined predictive model based on relevant radiomic studies of PET/CT scans performed better than other models in assessing individualized PD-L1 expression in NPC.

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Journal
International Journal of Radiation Research
Published
2025-05-01
DOI
https://doi.org/10.61186/ijrr.23.2.26
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Evaluation of PD-L1 expression status in nasopharyngeal carcinoma by 18F-FDG PET/CT radiomics analysis

Shuai Yang, L Li, Heng Li, Yihong Li
International Journal of Radiation Research
Radiomics and Machine Learning in Medical Imaging
article

Evaluation of PD-L1 expression status in nasopharyngeal carcinoma by 18F-FDG PET/CT radiomics analysis

Shuai Yang, L Li, Heng Li, Yihong Li
article en

Abstract

Background:We aimed to accurately and efficiently evaluate Programmed Death Ligand-1 (PD-L1) expression by relevant radiomic studies of fluoro-18fluorodeoxyglucose (18F-FDG) Positron Emission Tomography/Computed Tomography (PET/CT) images in nasopharyngeal carcinoma (NPC) patients.Materials and Methods: This retrospective study included 60 untreated NPC patients had PET/CT.Cohorts of training and validation were randomly selected among the patients.The CT and PET radiomic features from the training cohort were obtained and screened, to construct CT, PET and combined models.Finally, verification and comparative analysis were performed.Results: According to the analysis, the maximum Standardized Uptake Value (SUVmax) alone was the standalone predictive indicator of PD-L1 presence level, thus incorporated into the combined model.Among our training cohort, the CT, PET, and combined models' Area under Curve (AUC) values respectively were 0.837, 0.852, and 0.948, demonstrating excellent discrimination and calibration.However, the combined model had higher AUC values in the cohorts of training and validation, reaching AUCs of 0.948 and 0.802, respectively.Clinical decision curve analysis (DCA) further illustrated Combined model surpassed both the CT and PET models, attaining a benefit threshold probability of more than 5% and a net benefit (NB) of 0.450 at the optimal threshold probability.Conclusion: The combined predictive model based on relevant radiomic studies of PET/CT scans performed better than other models in assessing individualized PD-L1 expression in NPC.

International Journal of Radiation ResearchVol. 23(2)
Mianyang Third People's Hospital (CN), First Affiliated Hospital of Guangzhou University of Chinese Medicine (CN), Sichuan Mianyang 404 Hospital (CN)
Good health and well-being
Openalex Percentile: Top 73%
Radiomics and Machine Learning in Medical Imaging
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Evaluation of PD-L1 expression status in nasopharyngeal carcinoma by 18F-FDG PET/CT radiomics analysis — Shuai Yang, L Li, et al. · International Journal of Radiation Research (2025) | TGRS Research Map | TGRS