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Apparent Diffusion Coefficient as a Predictor of Microwave Ablation Response in Thyroid Nodules: A Prospective Study
1Department of Radiology, Umraniye Training and Research Hospital, University of Health Sciences, Istanbul 34764, Turkey.
None:
Background: Microwave ablation (MWA) is an effective, minimally invasive therapy for benign thyroid nodules; however, the treatment response varies considerably. Identifying imaging biomarkers that can predict volumetric outcomes may optimize patient selection. Diffusion-weighted MRI (DW-MRI) offers a noninvasive assessment of tissue microstructure through apparent diffusion coefficient (ADC) measurements, which may correlate with ablation efficacy. Methods: In this prospective study, 48 patients with 50 cytologically confirmed benign thyroid nodules underwent diffusion-weighted magnetic resonance imaging (DW-MRI) before minimally invasive ablation (MWA). Baseline ADC values were measured, and nodule volumes were assessed by ultrasound at baseline and 1, 3, and 6 months postprocedure. The volume reduction ratio (VRR) was calculated, and associations with baseline variables were analyzed via Pearson correlation and multivariable linear regression. ROC curve analysis was used to evaluate the diagnostic performance of ADC in predicting significant volume reduction (VRR ≥ 50%). Results: Lower baseline ADC values were strongly correlated with greater VRR at 3 months (r = -0.525, p < 0.001) and 6 months (r = -0.564, p < 0.001). Multivariable regression revealed that the baseline ADC was the sole independent predictor of the 6-month VRR (β = -19.52, p = 0.0004). ROC analysis demonstrated excellent discriminative performance (AUC = 0.915; 95% CI: 0.847-0.971), with an ADC cutoff of 2.20 × 10-3 mm2/s yielding 90.9% sensitivity and 83.3% specificity for predicting a favorable volumetric response. Conclusions: Baseline ADC values derived from DW-MRI strongly predict volumetric response following microwave ablation of benign thyroid nodules. Incorporating ADC assessment into preprocedural evaluation may enhance patient selection and improve therapeutic outcomes.

