Pretreatment MRI Parameters as Predictive Biomarkers for Hormonal Therapy Response in Adenomyosis: A Comprehensive Analysis

Objectives To evaluate whether pretreatment magnetic resonance imaging (MRI) parameters can predict response to hormonal therapy in patients with adenomyosis. Methods This retrospective study included 78 patients with MRI-diagnosed adenomyosis who underwent pelvic MRI before hormonal therapy between October 2018 and July 2025. Quantitative MRI parameters included T2 signal intensity ratios, diffusion-weighted imaging (DWI) signal intensity ratios, normalized apparent diffusion coefficient (ADC), and uterine morphological parameters. Adenomyosis subtypes were classified according to the modified Kishi criteria. Clinical response was evaluated 3–6 months after treatment initiation based on improvements in dysmenorrhea and/or hemoglobin levels. Results Of the 78 patients, 32 received gonadotropin-releasing hormone (GnRH) agonist or antagonist therapy, and 46 received dienogest (DNG). In the GnRH cohort, 31 of the 32 patients achieved treatment effectiveness. In the DNG cohort, 30 patients achieved treatment effectiveness, and 16 did not. MRI-based adenomyosis subtype, lesion distribution, and uterine morphological parameters were not significantly associated with treatment effectiveness in DNG-treated patients. However, absolute ADC values were significantly higher in the effective group (1.03 vs. 0.89 ×10⁻³ mm²/s, P = 0.036), as was the ADC signal intensity ratio relative to the endometrium (ADC signal intensity ratio [SIR _endo ]: 0.92 vs. 0.85, P = 0.034). Receiver operating characteristic curve analysis demonstrated moderate discrimination between both parameters (area under the curve = 0.70). Optimal cut-off values were 0.951 × 10⁻³ mm²/s for ADC and 0.952 for ADC SIR _endo . Conclusion Quantitative diffusion MRI parameters were associated with DNG treatment effectiveness, whereas conventional morphological features were not. Diffusion-weighted MRI may provide complementary imaging biomarkers for adenomyosis stratification.