Utilizing imaging features of preoperative gadoxetic acid-enhanced MRI for predicting lymphovascular invasion in colorectal cancer liver metastases and exploring its impact on survival.

内容摘要

To construct an imaging model based on preoperative gadoxetic acid- enhanced MRI for predicting lymphovascular invasion (LVI) in colorectal cancer liver metastases (CRLM) and explore its impact on survival. A total of 91 patients with CRLM were retrospectively enrolled in this study. The liver lesions were categorized into two groups, with LVI and without LVI by pathological examination. The long diameter, vascular penetration sign, peritumoral hepatobiliary phase (HBP) hypointensity and other qualitative signs were evaluated. The mean value and standard deviation (SD) value of signal intensity (SI) of the liver lesion and the region with 5-mm tumor expansion were recorded. The relative enhancement rate (RER) was calculated on each phase. Univariate and multivariate logistic regression were used to construct the imaging model (LVI model) for predicting LVI in CRLM. Each liver lesion in all the patients was assessed using the LVI model to classify patients into predicted LVI-negative or predicted LVI-positive groups. The vascular penetration sign (odds ratio [OR]&#x2009;=&#x2009;30.052, p<0.001) and SD of tumor on HBP (SDTumor-HBP)(OR&#x2009;=&#x2009;1.004, p&#x2009;=&#x2009;0.026) were used to construct the imaging model for predicting LVI and the AUC of the model was 0.874 (95%CI:0.747-1.000). The liver recurrence-free survival (LRFS) of 22 predicted LVI-positive patients was significantly lower than that of 69 predicted LVI-negative patients (median 9.0 vs. 28.0 months, p&#x2009;=&#x2009;0.028). The overall survival (OS) of predicted LVI-positive patients was significantly lower than that of predicted LVI-negative patients (median 21.0 vs. 63.0 months, p&#x2009;=&#x2009;0.001). The imaging model based on vascular penetration sign and SDTumor-HBP has good efficiency in predicting lymphovascular invasion and survival in patients with CRLM.