Evidence map›Paper›PMID 42137157›Full record

ArticleFrontiers in oncology2026

Whole-volume apparent diffusion coefficient histogram analysis for prediction of programmed cell death ligand 1 expression in periampullary carcinomas: a preliminary study.

Lei Bi, Qun Xie, Juntao Zhang, Shifeng Cai, Ximing Wang, Xiaodong Li

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Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Lei BiDepartment of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Qun XieDepartment of Radiology, Women & Children's Health Care Hospital of Linyi, Linyi, China.
Juntao ZhangDepartment of Medical Affairs for Pharmaceutical Diagnostics, GE Healthcare, Shanghai, China.
Shifeng CaiDepartment of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Ximing WangDepartment of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Xiaodong LiDepartment of Radiology, Linyi People's Hospital, Linyi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To assess the possibility of employing whole-volume ADC histogram analysis for predicting programmed cell death ligand 1 (PD-L1) expression in periampullary carcinomas (PCs). Materials and methods: We retrospectively evaluated imaging records of 65 patients with PC who received pancreaticoduodenectomy in our hospital. PD-L1 expression was systematically categorized as positive or negative based on the tumor proportion score (TPS), immune cell score (ICS), and the combined positive score (CPS), with an immunohistochemistry assay. Univariate analysis was conducted to assess differences in parameters between PD-L1-positive and PD-L1-negative groups. Spearman's correlation analysis was utilized to explore associations between variables and PD-L1 expression. Receiver operating characteristic (ROC) analysis was performed to evaluate the differential diagnostic performance of parameters in distinguishing two groups. Results: Several ADC histogram parameters were significantly different between PD-L1-positive and PD-L1-negative group, and showed significant correlations with PD-L1 expression, most notably the 5th and 10th percentiles. In TPS grouping, the 5th percentile demonstrated the highest area under the curve (AUC) of 0.690, which was improved to 0.740 when combined with tumor size and carbohydrate antigen 19-9. In ICS grouping, the 10th percentile showed the highest AUC of 0.690, which was improved to 0.772 when integrated with the degree of differentiation. In CPS grouping, the 5th percentile demonstrated the highest AUC of 0.694, which was improved to 0.752 when combined with tumor size and carcinoembryonic antigen. Conclusion: Whole-volume ADC histogram parameters of primary tumors hold great potential in predicting PD-L1 expression in PCs.

Indexed as

apparent diffusion coefficientdiffusion weighted imaginghistogram analysisperiampullary carcinomaprogrammed cell death ligand 1

Identifiers

PMID42137157
PMCPMC13167477

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