Multiparametric MRI differentiation of ovarian endometriomas and hemorrhagic cysts: Quantitative shading, ADC measurements, and morphological sign analysis

Ahmet Tuğrul Akkuş, Said Ali Atalay, Emre Özil, Fadime Güven
Acta radiologica (Stockholm, Sweden : 1987) · 2026 · pp. 2841851261489733 · doi:10.1177/02841851261489733 · PMID:42798275 · W7214460065
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A multiparametric MRI model combining quantitative shading, intralesional ADC, and lesion size significantly improved differentiation of ovarian endometriomas from hemorrhagic cysts compared to conventional subjective assessment.

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Abstract

BackgroundDifferentiating ovarian endometriomas from hemorrhagic cysts matters because their management differs.PurposeTo evaluate whether a multiparametric magnetic resonance imaging (MRI) approach improves differentiation of endometriomas from hemorrhagic cysts over conventional subjective assessment.Material and MethodsIn total, 83 hemorrhagic cystic ovarian lesions (45 endometriomas, 38 hemorrhagic cysts) on 1.5-T pelvic MRI were retrospectively evaluated by two independent blinded radiologists (with 20 and 7 years of experience in abdominopelvic and gynecological MRI) for quantitative T1 and T2 signal intensities (quantitative shading), intralesional and perilesional apparent diffusion coefficient (ADC), lesion size, and the T2 shading and dark-spot signs. ROC analysis, logistic regression, and inter-/intra-observer agreement were assessed, and models were compared with the DeLong test.ResultsEndometriomas were larger (55.0 vs. 40.7 mm; P = 0.007), had lower intralesional ADC (1.054 vs. 1.563 ×10-3 mm2/s; P = 0.002), and a greater T1-T2 signal difference (P < 0.001), which had the highest single-parameter accuracy (AUC = 0.799). There was no statistically significant difference in the T2 shadowing sign between the groups (91.1% vs. 81.6%; P = 0.342). The T2 dark-spot sign was specific (100%) but insensitive (24.4%). Perilesional ADC did not differ (P = 0.112) and showed poor inter-observer agreement (ICC = 0.064). A multiparametric model (quantitative shading, intralesional ADC, lesion size) outperformed conventional MRI (AUC = 0.894 vs. 0.670; DeLong P < 0.001), increasing sensitivity from 24.4% to 88.9% at comparable specificity.ConclusionA multiparametric model combining quantitative shading, intralesional ADC and lesion size significantly improved differentiation over conventional MRI, whereas perilesional ADC showed no diagnostic utility at 1.5 T.

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