Abstract
Lymphovascular invasion (LVI) and perineural invasion (PNI) are important histopathological variables that are directly related to the survival and recurrence of patients with colorectal cancer (CRC). Preoperative prediction of LVI and PNI status in CRC is helpful in selecting patients requiring appropriate adjuvant therapy and evaluating prognosis. This study aimed to investigate the value of combining single-source dual-energy computed tomography (ssDECT)-derived parameters with extracellular volume (ECV) fraction for preoperative evaluation of LVI and PNI in CRC. This retrospective study included patients with CRC who underwent contrast-enhanced ssDECT. All diagnoses were confirmed through histopathology, and the patients were classified into positive and negative groups based on the presence of LVI/PNI. Clinical data were collected. In the arterial (AP), venous (VP) and delayed phases (DP), the ssDECT-derived parameters were measured by two radiologists. The measurement consistency was evaluated using intraclass correlation coefficients. Differences between the two groups were analyzed using the t-test, Mann-Whitney U test, or Chi-square test. Binary logistic regression was employed to construct models incorporating multiple parameters. The diagnostic performance of various parameters or models was assessed by analyzing receiver operating characteristic curves. In total, 118 patients with CRC were included in the study. Serum carcinoembryonic antigen levels, T and N stages, and histological grades differed between the two groups (all P<0.05). The ssDECT-derived parameters in the VP and DP of LVI/PNI-positive group were higher than those of -negative group (all P<0.05). The ECV fraction in the DP of LVI/PNI-positive group was higher than that of -negative group (P=0.001). Discriminating capability analysis demonstrated that the diagnostic efficacies of the DP parameters were superior to those of the VP parameters, and the normalized iodine concentration in the DP exhibited the best performance [area under the curve (AUC): 0.750; 95% confidence interval (CI): 0.648-0.852]. The combination of ECV DP with clinical and ssDECT-derived parameters demonstrated the highest discriminative capability (AUC: 0.857; 95% CI: 0.786-0.928). ssDECT-derived parameters and ECV fraction may serve as non-invasive tools for predicting the LVI/PNI status in CRC.
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