Microstructural mapping of time-dependent diffusion MRI for predicting lymphovascular invasion in rectal cancer: a proof-of-concept investigation

OBJECTIVE: To evaluate the value of time-dependent diffusion MRI (td-dMRI) derived microstructural parameters for predicting lymphovascular invasion (LVI) in rectal cancer. MATERIALS AND METHODS: Eighty-four resectable rectal cancer patients (stage T1, T2, T3a, T3b, and T4a) who underwent preoperative td-dMRI between March 2023 and June 2025 without neoadjuvant therapy were enrolled. Manual segmentation of tumors was performed by an experienced radiologist on each tumor's largest cross-sectional area. Microstructural parameters (intracellular volume fraction (ICVF), cell diameter, extracellular diffusivity and cellularity) were fitted using the limited spectrally edited diffusion model implemented in MATLAB (MathWorks, Inc.). Apparent diffusion coefficient (ADC) values at different diffusion times, relative ADC, ADC ratio, and MRI-reported extramural vascular invasion (EMVI) were also evaluated. Mann-Whitney U test was used to evaluate parameter differences between LVI-positive and LVI-negative. Logistic regression and receiver operating characteristic (ROC) curves (with DeLong test) were used to identify predictors of LVI and diagnostic performance. RESULTS: Of 84 participants (median age, 66 years; IQR, 60-70 years; 50 male), 30 were LVI-positive and 54 LVI-negative. ICVF, cell diameter, and cellularity were significantly higher in LVI-positive cases (all p < 0.05). MRI-EMVI (OR = 3.251), ICVF (OR = 8.137), and cellularity (OR = 1.159) were independent risk factors of LVI. The combined model integrating MRI-reported EMVI, cellularity, and ICVF achieved an area under the ROC curve (AUC) of 0.860, outperforming individual parameters including MRI-reported EMVI (AUC = 0.730), ICVF (AUC = 0.815), cellularity (AUC = 0.792) and ADC measurements (AUC = 0.631-0.710) (all p < 0.05). CONCLUSION: td-dMRI-derived parameters, especially ICVF and cellularity combined with MRI-reported EMVI, show potential as noninvasive biomarkers for LVI prediction in rectal cancer. CRITICAL RELEVANCE STATEMENT: This study develops a preoperative time-dependent diffusion MRI-based microstructure parameters model that diagnoses and predicts lymphovascular invasion of rectal cancer, improving diagnostic accuracy and advancing personalized treatment strategies in clinical radiology. KEY POINTS: The time-dependent diffusion MRI-derived microstructural parameters model and clinical data for predicting lymphovascular invasion in rectal cancer. The combined model outperforms single-modality models with 0.860 AUC and 96.3% specificity. The combined model provides a noninvasive, reliable tool for personalized lymphovascular invasion diagnosis and treatment planning.