Discriminating orbital lymphoma from inflammation and correlating with histopathology using microstructure-based time-dependent diffusion MRI.

[BACKGROUND] Preoperative discrimination between orbital B-cell lymphoma and inflammatory lesions remains a significant challenge using conventional imaging. This study evaluates the potential of time-dependent diffusion MRI (td-dMRI) alongside diffusion-weighted imaging (DWI) to improve differential diagnosis.

[METHODS] Patients with suspected orbital tumors were prospectively enrolled between October 2023 and November 2024. All participants underwent td-dMRI using oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE) sequences on a 3 T scanner. Microstructural parameters-including cell diameter (d), cellularity, extracellular diffusivity (Dex), and intracellular volume fraction (Vin)-were derived. Correlations between apparent diffusion coefficient (ADC), d, cellularity, and histopathological metrics were assessed through quantitative morphometric analysis. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis.

[RESULTS] Forty-eight patients were enrolled (20 orbital MALT lymphoma, 28 inflammatory lesions). All parameters showed excellent interobserver agreement (ICCs: 0.82-0.93). Strong correlations were observed between histological cell diameter and d (r = 0.75), and between histological cellularity and both td-dMRI-derived cellularity (r = 0.71) and ADC (r = -0.74) (all p < 0.001). Lymphomas exhibited significantly lower ADC, d, and Dex, and higher Vin and cellularity compared to inflammatory lesions (all p < 0.01). Cellularity demonstrated the highest discriminative power (AUC = 0.87), followed by Vin (AUC = 0.82), while ADC showed moderate performance (AUC = 0.74). No significant differences in diagnostic efficacy were observed among the parameters.

[CONCLUSIONS] The td-dMRI provides highly reproducible, histologically correlated biomarkers that effectively differentiate orbital lymphoma from inflammatory lesions, thereby enabling orbital lesion risk-stratification and providing valuable non-invasive characterization to complement conventional ADC-based assessment for preoperative diagnosis of orbital lesions.