Intravoxel incoherent motion-derived histogram analysis for quantitative evaluation of tumor budding and prognostic stratification in rectal cancer.

Abstract

To determine the value of intravoxel incoherent motion (IVIM) for quantitative tumor budding (TB) evaluation and prognostic stratification in patients with rectal cancer (RC). This study enrolled 189 RC patients (training set 148, validation set 41) who underwent IVIM and were subsequently treated surgically within 2 weeks between January 2022 and April 2023. Hematoxylin-eosin staining was used for TB scoring. IVIM metrics were calculated on MRI images using biexponential fitting and histogram analysis. Differences in IVIM histogram metrics between the low-intermediate grade budding (Bd 1 + 2) and the high-grade budding (Bd 3) were analyzed. Multivariate logistic regression analysis was used to build the Combined model. The area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance of the IVIM histogram metrics and the Combined model. Kaplan-Meier analysis was employed to estimate disease-free and overall survival rates for patients. Multivariate logistic analysis showed that the D_25th percentile, D_75th percentile, D_90th percentile, and D_95th percentile were independent predictors of Bd 3 (all p < 0.05). The Combined model incorporating these four factors had the best diagnostic performance, with the AUC, sensitivity, and specificity of 0.852, 73.02%, and 82.35% in the training set and 0.856, 75.00%, and 86.21% in the validation set. Furthermore, the score of the Combined model was significantly associated with worse 2-year overall survival (hazard ratio 6.804, 95% confidence interval 2.214 to 20.909, p = 0.001). The IVIM histogram metrics could distinguish different TB grades and be used as a preoperative risk stratification tool. Questions Does intravoxel incoherent motion based on histogram analysis predict tumor budding grades and its prognosis in patients with rectal cancer? Findings The histogram metrics of slow diffusion coefficient are an independent prediction factor of high-grade tumor budding and a risk factor of poor 2-year overall survival. Clinical relevance This combined model, based on slow diffusion coefficient, is a reliable tool for preoperative predicting 2-year overall survival in patients with rectal cancer, contributing to risk stratification and individual treatment.