Evidence map›Paper›PMID 41669464›Full record

ArticleQuantitative imaging in medicine and surgery2026

Diagnostic efficacy of dual-energy computed tomography-based fractal analysis for assessing extramural venous invasion/tumor deposits and peripheral nerve invasion in rectal cancer.

Changjiang Zhang, Yinglan Shu, Junfan Chen, Tianqi Feng, Lifeng Lu, Hongjing Wang, Weijuan Chen, Xinjie Liu, Yindeng Luo

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Article in Quantitative imaging in medicine and surgery, 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

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9 authors.

Changjiang Zhang *Department of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Yinglan Shu *Department of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Junfan ChenDepartment of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Tianqi FengDepartment of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Lifeng LuDepartment of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Hongjing WangDepartment of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Weijuan ChenDepartment of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xinjie Liu *Department of Radiology, Renji Hospital, School of Medicine, Chongqing University (The Fifth People's Hospital of Chongqing), Chongqing, China.
Yindeng Luo *Department of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.ORCID https://orcid.org/0000-0001-8720-8418

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Extramural venous invasion (EMVI), tumor deposits (TDs), and peripheral nerve invasion (PNI) are high-risk pathological features in patients with rectal cancer (RC), but their preoperative assessment with conventional computed tomography (CT) is limited. This study aimed to evaluate the value of dual-energy computed tomography (DECT)-based fractal analysis for predicting EMVI/TD and PNI in patients with RC. Methods: A total of 130 patients with histologically confirmed RC who underwent preoperative DECT were consecutively enrolled and divided into a retrospective development cohort (n=85) and a prospective validation cohort (n=45). Fractal dimensions (FDs) from conventional mixed-energy images (FD-Con), iodine maps [FD-iodine concentration (FD-IC)], and effective atomic number (Zeff) maps (FD-Zeff) were calculated. Patients were classified as PNI-positive/-negative and EMVI/TD-positive/-negative according to surgical pathology. Group comparisons, receiver operating characteristic (ROC) curve analysis, and multivariable logistic regression were used to identify independent predictors and build combined models, which were tested in the validation cohort. Results: Among the 130 patients, 59 were PNI-positive and 35 were EMVI/TD-positive. FD-IC and FD-Zeff were significantly higher in positive than in negative groups for both PNI and EMVI/TD (all P values ≤0.019). In the validation cohort, FD-IC and FD-Zeff achieved areas under the ROC curves (AUCs) of 0.752 and 0.771 for predicting PNI and 0.795 and 0.855 for predicting EMVI/TD, respectively. FD-IC was an independent risk factor for PNI [odds ratio (OR) =77.873; P=0.039], and FD-Zeff was an independent predictor of EMVI/TD (OR =1.109×10 Conclusions: DECT-based fractal analysis, particularly FD-IC and FD-Zeff, provides quantitative markers for preoperative prediction of PNI and EMVI/TD in patients with RC and improves diagnostic performance as compared with conventional CT-based fractal parameters.

Indexed as

computed tomography (CT)fractalsRectal cancer (RC)

Identifiers

PMID41669464
PMCPMC12883442

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