ABSTRACT
The aim of the present study was to identify whether the quantitative metrics from pre-treatment (TX) non-Gaussian intravoxel incoherent motion (NGIVIM) diffusion weighted (DW-) and fast exchange regime (FXR) dynamic contrast enhanced (DCE)-MRI can predict patients with locoregional failure (LRF) in nasopharyngeal carcinoma (NPC). Twenty-nine NPC patients underwent pre-TX DW- and DCE-MRI on a 3T MR scanner. DW imaging data from primary tumors were fitted to monoexponential (ADC) and NGIVIM (D, D*, f, and K) models. The metrics Ktrans, ve, and τi were estimated using the FXR model. Cumulative incidence (CI) analysis and Fine-Gray (FG) modeling were performed considering death as a competing risk. Mean ve values were significantly different between patients with and without LRF (p = 0.03). Mean f values showed a trend towards the difference between the groups (p = 0.08). Histograms exhibited inter primary tumor heterogeneity. The CI curves showed significant differences for the dichotomized cutoff value of ADC ≤ 0.68 × 10-3 (mm2/s), D ≤ 0.74 × 10-3 (mm2/s), and f ≤ 0.18 (p < 0.05). τi ≤ 0.89 (s) cutoff value showed borderline significance (p = 0.098). FG's modeling showed a significant difference for the K cutoff value of ≤0.86 (p = 0.034). Results suggest that the role of pre-TX NGIVIM DW- and FXR DCE-MRI-derived metrics for predicting LRF in NPC than alone.
ABSTRACT
We assessed a priori aggressive features using quantitative diffusion-weighted imaging metrics to preclude an active surveillance management approach in patients with papillary thyroid cancer (PTC) with tumor size 1-2 cm. This prospective study enrolled 24 patients with PTC who underwent pretreatment multi-b-value diffusion-weighted imaging on a GE 3 T magnetic resonance imaging scanner. The apparent diffusion coefficient (ADC) metric was calculated from monoexponential model, and the perfusion fraction (f), diffusion coefficient (D), pseudo-diffusion coefficient (D*), and diffusion kurtosis coefficient (K) metrics were estimated using the non-Gaussian intravoxel incoherent motion model. Neck ultrasonography examination data were used to calculate tumor size. The receiver operating characteristic curve assessed the discriminative specificity, sensitivity, and accuracy between PTCs with and without features of tumor aggressiveness. Multivariate logistic regression analysis was performed on metrics using a leave-1-out cross-validation method. Tumor aggressiveness was defined by surgical histopathology. Tumors with aggressive features had significantly lower ADC and D values than tumors without tumor-aggressive features (P < .05). The absolute relative change was 46% in K metric value between the 2 tumor types. In total, 14 patients were in the critical size range (1-2 cm) measured by ultrasonography, and the ADC and D were significantly different and able to differentiate between the 2 tumor types (P < .05). ADC and D can distinguish tumors with aggressive histological features to preclude an active surveillance management approach in patients with PTC with tumors measuring 1-2 cm.