Evidence map›Paper›PMID 41543562›Full record

ArticleEuropean radiology2026

Preoperative colon cancer nodal staging using dual-energy CT and clinically derived features.

Changjiu He, Libo Lin, Ao Yang, Chuanyang Shao, Jun Wang, Yuxuan He, Shibei Hu, Peng Zhou, Xiaoli Tang, Xiaoli Chen

Abstract read
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In one paragraph

Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
4 · The record

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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

10 authors.

Changjiu He *Department of Radiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Libo Lin *Department of Radiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Ao YangDepartment of Radiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Chuanyang ShaoDepartment of Radiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Jun WangDepartment of Radiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Yuxuan HeDepartment of Radiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Shibei HuDepartment of Radiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Peng ZhouDepartment of Radiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China.
Xiaoli TangDepartment of Radiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China. 251623855@qq.com.
Xiaoli ChenDepartment of Radiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China. 20shenbaise@163.com.ORCID http://orcid.org/0000-0003-2919-6847

Funding

Beijing Medical and Health Public Welfare Foundation YWJKJJHKYJJ-KCYX2025001Excellent Youth Fund of Sichuan Cancer Hospital YB2025018
6 · The paper itself

Abstract

objectiveTo evaluate the potential of dual-energy CT (DECT) quantitative parameters and clinical characteristics in predicting pathological nodal (pN) stage in colon cancer. MATERIALS AND

methodsA total of 205 patients with pathologically confirmed colon cancer who underwent DECT were retrospectively enrolled and were randomly divided into training (n = 148) and test sets (n = 57) at a 7:3 ratio. The DECT quantitative parameters, including extracellular volume fraction (ECV), clinical characteristics, and Node Reporting and Data System (Node-RADS), were analyzed. Univariable and multivariable logistic regression analysis were used to construct the DECT model, Clinical_model, and Combined model. The diagnostic performance of the models was evaluated using the area under the receiver operating characteristic curve (AUC).

resultsCarbohydrate antigen 125 (CA125), carbohydrate antigen 242 (CA242), dual-energy index in venous phase (DEI_V), and ECV were independent factors for predicting pN+ (all p < 0.05). The Combined model (features: CA125, CA242, ECV, and DEI_V) showed significantly higher AUC than Node-RADS (0.845 vs. 0.727, p = 0.032), Clinical_model (features: CA125 and CA242) (0.845 vs. 0.692, p < 0.001), and DECT model (features: ECV and DEI_V) (0.845 vs. 0.774, p = 0.011) in the training set. The Combined model also demonstrated the highest AUC (0.849) in the test set. But there were no significant differences in AUC between the Combined model and Node-RADS (p = 0.158) in the test set.

conclusionThe combination of DECT quantitative parameters and clinical characteristics showed improved diagnostic performance in predicting pN stage in colon cancer. KEY POINTS: Question Does the combination of dual-energy CT (DECT) quantitative parameters and clinical characteristics predict pathological nodal (pN) stage in colon cancer? Findings The Combined model showed the highest AUC for predicting pN stage in the training set, but did not show better performance than Node-RADS in the test set. Clinical relevance The combination of DECT quantitative parameters and clinical characteristics may be useful for predicting pN stage in colon cancer as a noninvasive method.

Indexed as

Colonic NeoplasmsRadiography, Dual-Energy Scanned ProjectionTomography, X-Ray ComputedAdultAgedAged, 80 and overFemaleHumansLymphatic MetastasisLymph NodesMaleMiddle AgedNeoplasm StagingPreoperative CareReproducibility of ResultsRetrospective StudiesColonic neoplasmsLymph nodesPathologyTomography (X-ray computed)

Identifiers

PMID41543562

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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.