Evidence mapPaperPMID 42440230Full record

ArticleLa Radiologia medica2026

Intratumoral and peritumoral CT radiomics combined with clinical and hematologic inflammatory markers for predicting lymph node metastasis in esophageal squamous cell carcinoma: a retrospective single-center study.

Xinmiao Yang, Hongfeng Niu, Ziqing Yang, Jingjing Ren, Xinrong Wang, Kan Deng, Qingxia Wu, Xiaohong Kang, Junqiang Zhao, Changhua Liang

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Article in La Radiologia medica, 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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10 authors.

Xinmiao YangDepartment of Radiology, The First Affiliated Hospital of Henan Medical University, Xinxiang, China.
Hongfeng NiuThe First Affiliated Hospital of Henan Medical University, Xinxiang, China.
Ziqing YangDepartment of Radiology, The First Affiliated Hospital of Henan Medical University, Xinxiang, China.
Jingjing RenDepartment of Radiology, The First Affiliated Hospital of Henan Medical University, Xinxiang, China.
Xinrong WangRadiology, Bayer Healthcare, Guangzhou, China.
Kan DengRadiology, Bayer Healthcare, Guangzhou, China.
Qingxia WuBeijing United Imaging Research Institute of Intelligent Imaging, Beijing, China.
Xiaohong KangDepartment of Oncology, The First Affiliated Hospital of Henan Medical University, Xinxiang, China.
Junqiang ZhaoThe First Affiliated Hospital of Henan Medical University, Xinxiang, China.
Changhua LiangDepartment of Radiology, The First Affiliated Hospital of Henan Medical University, Xinxiang, China. liangchanghua12345@163.com.

Funding

Henan Zhongyuan Medical Science and Technology Innovation and Development Foundation No. ZYYC2024MB
6 · The paper itself

Abstract

objectiveTo develop and validate a hybrid model integrating intratumoral (TR) and peritumoral (PTR) CT radiomics with clinical and hematologic inflammatory markers for predicting lymph node metastasis (LNM) in esophageal squamous cell carcinoma (ESCC).

methodsThis retrospective single-center cohort study included 304 patients with pathologically confirmed ESCC. Patients were randomly divided into a training cohort (n = 243) and a test cohort (n = 61) in an 8:2 ratio. Radiomics features were extracted from manually segmented three-dimensional volumes of interest (VOIs) on venous-phase thin-slice contrast-enhanced CT images. The PTR VOIs were defined as 1-, 2-, and 3-mm ring-shaped regions surrounding the TR VOI. Clinical data, hematologic inflammatory markers, and TR and PTR CT radiomics features were used to construct six categories of models: a clinical model, a hematologic model, TR + PTR radiomics models, a clinical + TR + PTR radiomics model, a hematologic + TR + PTR radiomics model, and a clinical + hematologic + TR + PTR hybrid model. Model performance was evaluated using receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA).

resultsThe overall LNM prevalence was 37.5% (114/304), including 37.9% (92/243) in the training cohort and 36.1% (22/61) in the test cohort. Multivariate analysis identified cN stage as an independent predictor for LNM (p < 0.05). Among the TR + PTR radiomics models, the TR + PTR

conclusionThe hybrid model based on TR and 1-mm PTR CT radiomics combined with clinical and hematologic inflammatory markers may serve as a promising noninvasive tool for preoperative individualized risk assessment of LNM in ESCC. However, this retrospective single-center study had a relatively small internal validation cohort and lacked external validation. Therefore, further multicenter studies with external validation are warranted to confirm the robustness and generalizability of the proposed model.

Indexed as

Computed tomographyEsophageal squamous cell carcinomaLymph node metastasisRadiomicsSquamous cell carcinoma

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.