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World J Gastrointest Oncol. May 15, 2026; 18(5): 115303
Published online May 15, 2026. doi: 10.4251/wjgo.v18.i5.115303
Preoperative spectral computed tomography multi-parameter prediction of postoperative complications in colorectal cancer: A single-center retrospective cohort study
Zhi-Lin Wu, Rong-Wei Yang, Qing Zhao, Li Deng, Hong-Lian Li, Rui Duan
Rui Duan, Hong-Lian Li, Rong-Wei Yang, Zhi-Lin Wu, Department of Radiology, The People’s Hospital of Chongqing Liangping District, Chongqing 405200, China
Li Deng, Department of Radiology, Ping An Haoyi Chongqing Medical Imaging Centre Co., Ltd., Chongqing 400000, China
Qing Zhao, Department of Radiology, Chongqing Hospital of Traditional Chinese Medicine Orthopedics, Chongqing 405200, China
Co-first authors: Rui Duan and Hong-Lian Li.
Co-corresponding authors: Rong-Wei Yang and Zhi-Lin Wu.
Author contributions: Duan R and Li HL contributed to study design, data collection, spectral computed tomography image analysis, statistical analysis, and manuscript drafting; Deng L and Zhao Q participated in image post-processing, parameter measurement, clinical data verification, and follow-up assessment. Yang RW and Wu ZL (co-corresponding authors) supervised the study, provided methodological guidance, critical manuscript revision, and secured funding support. All authors approved the final manuscript. Duan R and Li HL contributed equally to this work as co-first authors. Yang RW and Wu ZL are designated as co-corresponding authors due to their equally essential and complementary roles. Yang RW provided overall supervision and methodological guidance, while Wu ZL led project coordination, funding acquisition, and manuscript revision. Both authors significantly contributed to study design, interpretation, and final approval. This dual designation reflects shared leadership, ensures efficient communication, and aligns with collaborative research practices.
Institutional review board statement: This study was reviewed and approved by the Institutional Review Board of the People’s Hospital of Chongqing Liangping District (Approval No. 2025 LLSC08).
Informed consent statement: Because this study involved a retrospective review of existing medical records and imaging data, the requirement for informed consent was waived by the Institutional Review Board of the People’s Hospital of Chongqing Liangping District.
Conflict-of-interest statement: The authors declare that there are no conflicts of interest related to this study.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Data sharing statement: No additional data are available.
Corresponding author: Zhi-Lin Wu, MD, Associate Chief Physician, Department of Radiology, The People’s Hospital of Chongqing Liangping District, No. 16 Bigui Road, Shuanggui Street, Chongqing 405200, China. 18290567599@163.com
Received: October 31, 2025
Revised: November 26, 2025
Accepted: February 2, 2026
Published online: May 15, 2026
Processing time: 195 Days and 1 Hours
Abstract
BACKGROUND

Postoperative complications in colorectal cancer surgery occur in 20%-50% of patients, significantly impacting recovery and prognosis. Traditional clinical prediction models have limited efficacy for preoperative risk assessment. Spectral computed tomography (CT) provides quantitative parameters including iodine concentration (IC) that may improve complication prediction, though systematic studies remain limited.

AIM

To investigate the value of preoperative spectral CT multi-parameters in predicting postoperative complications in colorectal cancer, establish a predictive model, and provide scientific evidence for preoperative risk stratification and individualized treatment strategy formulation.

METHODS

A retrospective cohort analysis was conducted on clinical data and preoperative spectral CT imaging data of 195 colorectal cancer patients from March 2022 to August 2025. Abdominal dual-phase enhanced scanning was performed using a GE Revolution CT spectral scanner, measuring parameters including tumor IC, normalized IC (NIC), effective atomic number, and spectral attenuation curve slope. Postoperative complications were assessed using the Clavien-Dindo classification system. Univariate and multivariate logistic regression analyses were used to screen independent predictive factors, establish a predictive model, and evaluate its performance.

RESULTS

Among 195 patients, 16 developed postoperative complications with an incidence rate of 8.2%. Patients in the complication group had significantly lower arterial phase and portal venous phase (PV) tumor IC, NIC, effective atomic number, and spectral attenuation curve slope compared to the non-complication group (P < 0.001). Multivariate analysis identified 5 independent predictive factors: Age [odds ratio (OR) = 1.042, P = 0.023], albumin (OR = 0.881, P = 0.007), PV tumor NIC (OR < 0.001, P < 0.001), tumor-nodes-metastasis stage (OR = 3.274, P = 0.030), and intraoperative blood loss (OR = 1.003, P = 0.009). The combined predictive model had an area under the curve of 0.843 (95% confidence interval: 0.789-0.897), with sensitivity of 75.3% and specificity of 80.3%. Bootstrap internal validation showed a bias-corrected C-index of 0.821, demonstrating good stability.

CONCLUSION

Preoperative spectral CT multi-parameters have important value in predicting postoperative complications in colorectal cancer. PV tumor NIC is the most valuable imaging predictive factor. The predictive model established by combining clinical indicators has good predictive efficacy and can be used for preoperative risk stratification and individualized treatment strategy formulation.

Keywords: Spectral computed tomography; Colorectal cancer; Postoperative complications; Predictive model; Normalized iodine concentration; Risk stratification

Core Tip: This study developed a preoperative model combining spectral computed tomography parameters and clinical factors to predict postoperative complications in colorectal cancer. The portal venous phase normalized iodine concentration was identified as the most valuable imaging biomarker. The integrated model showed good discrimination (area under the curve = 0.843) and calibration (C-index = 0.821), providing a noninvasive tool for preoperative risk stratification and individualized perioperative management in colorectal cancer patients.

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