Evidence map›Paper›PMID 41212337›Full record

ArticleDiscover oncology2025

The value of dual-energy CT radiomics in evaluating vascular maturity and prognosis in clear cell renal cell carcinoma.

Ruobing Li, Kun Li, Zhongyuan Li, Peiji Song, Xue Bing, Haitao Sun, Aimei Ouyang

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In one paragraph

Article in Discover oncology, 2025. 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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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ruobing LiShandong First Medical University, Jinan, 250117, China.
Kun LiDepartment of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, 250013, China.
Zhongyuan LiDepartment of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, 250013, China.
Peiji SongDepartment of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, 250013, China.
Xue BingDepartment of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, 250013, China.
Haitao SunDepartment of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, 250013, China.
Aimei OuyangDepartment of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, 250013, China. 13370582510@163.com.

Funding

the Department of Science and Technology of Shandong Province YDZX2021012the Jinan Municipal Health Commission 202019036
6 · The paper itself

Abstract

purposeThis study aims to develop an integrated model based on dual-energy CT (DECT) radiomic features to predict vascular maturity and progression-free survival (PFS) in patients with clear cell renal cell carcinoma (ccRCC).

methodsA total of 87 ccRCC patients who underwent resection were randomly divided into training (n = 60) and validation (n = 27) groups at a 7:3 ratio. Radiomics models (single/multi-energy sequences), a clinical model, and a combined model were developed to predict vascular maturity (CD34+/α-SMA+ cells). Additionally, 17 patients were recruited from Center II as an external validation cohort for the multi-energy sequence models. A nomogram combining the radiomic score (Rad-score) and clinical features was constructed to visually predict patients’ PFS. Kaplan-Meier survival analysis assessed PFS differences between high and low CD34+/α-SMA+ cell groups.

resultsThe median values of CD34+/α-SMA+ cells served as the cutoff for vascular maturity classification. The combined model demonstrated excellent performance, achieving an AUC of 0.967 in the validation set and 0.764 in the external validation set. Among the radiomics models, the multi-energy sequences model performed best, with an AUC of 0.833 in the validation set and 0.736 in the external validation set. Kaplan-Meier survival analysis revealed statistically significant PFS differences between CD34+/α-SMA+ cell groups.

conclusionsThe combined model integrating Rad-score and clinical features showed promising predictive ability for assessing vascular maturity and PFS between CD34+/α-SMA+ groups in patients with ccRCC.

Indexed as

Clear cell renal cell carcinomaDiagnostic biomarkerDual-energy CTRadiomics

Identifiers

PMID41212337
PMCPMC12602836

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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 OpenQuestion graph.