Evidence map›Paper›PMID 42862502›Full record

ArticleEuropean radiology experimental2026

CT-based multi-station lymph-node radiomics for preoperative prediction of lymph node metastasis in colorectal cancer: a proof-of-concept comparison with primary-tumor radiomics.

Zejin Lin, Jue Wang, Hairong Chen, Qun Bao, Ming Xu, Shang Yang, Hanxiao Zhang, Guang-Zhong Yang, Peng Sun

Abstract readComparative Study
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Zejin Lin *Department of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID http://orcid.org/0009-0009-9185-0054
Jue Wang *Department of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Hairong Chen *Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Qun BaoDepartment of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ming XuDepartment of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shang YangDepartment of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Hanxiao ZhangShanghai Key Laboratory of Flexible Medical Robotics, Tongren Hospital, Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China. hanxiao.zhang@sjtu.edu.cn.
Guang-Zhong YangShanghai Key Laboratory of Flexible Medical Robotics, Tongren Hospital, Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China.
Peng SunDepartment of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. SP2082@shtrhospital.com.

Funding

Open Project of the Shanghai Key Laboratory of Flexible Medical Robotics SKLFMR-0210Shanghai Tongren Hospital Medical-Engineering Collaboration Project lhyjzx2024-xm02the 2026 Central Government-Supported Public Hospital Reform and High-Quality Development Project 202614XMTR04the Natural Science Foundation of Shanghai 25ZR1402276
6 · The paper itself

Abstract

objectiveAccurate preoperative prediction of lymph node metastasis (LNM) in colorectal cancer remains challenging using conventional CT assessment. This proof-of-concept study compared CT-based multi-station lymph-node radiomics with primary-tumor radiomics for patient-level preoperative prediction of LNM. MATERIALS AND

methodsThis single-center retrospective study included patients with pathologically confirmed colorectal cancer who underwent preoperative contrast-enhanced CT and surgical resection. Patients were divided into training and validation cohorts. Radiomics features were extracted from the primary tumor and visible regional lymph nodes across multiple nodal stations. Three radiomics strategies were developed and compared: primary-tumor radiomics, multi-station lymph-node radiomics, and combined radiomics. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration analysis, decision curve analysis, and five-fold cross-validation. Pairwise AUCs were compared using the DeLong test. A clinical-radiomic model was further constructed by integrating the optimal radiomics strategy with preoperative clinical variables.

resultsIn the validation cohort, the multi-station lymph-node radiomics model outperformed the primary-tumor radiomics model for predicting LNM (AUC, 0.864 versus 0.637; p = 0.0055). The combined radiomics model achieved an AUC of 0.840, without significant improvement over the lymph-node model (p = 0.2211). After integration with clinical variables, the clinical-radiomic model achieved an AUC of 0.879.

conclusionCT-based multi-station lymph-node radiomics showed significantly higher validation performance than primary-tumor radiomics for patient-level preoperative LNM prediction in colorectal cancer. However, this single-center proof-of-concept model is not ready for direct clinical implementation and requires multicenter external validation before clinical translation. KEY POINTS: Question Can CT-based multi-station lymph-node radiomics improve preoperative nodal metastasis prediction beyond primary-tumor radiomics in patients with surgically treated colorectal cancer? Findings Multi-station lymph-node radiomics achieved higher validation performance than primary-tumor radiomics for patient-level prediction of pathological lymph-node metastasis in colorectal cancer. Relevance statement CT-based multi-station lymph-node radiomics may support individualized preoperative nodal risk stratification in colorectal cancer, but multicenter validation and prospective evaluation are required before clinical translation.

Indexed as

Colorectal NeoplasmsLymphatic MetastasisLymph NodesTomography, X-Ray ComputedAgedFemaleHumansMaleMiddle AgedProof of Concept StudyRadiomicsRetrospective StudiesColorectal neoplasmsLymphatic metastasisRadiomicsRisk assessmentTomography (x-ray computed)

Identifiers

PMID42862502
PMCPMC13658740

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.