Multiparametric quantitative magnetic resonance imaging of uterine fibroids for prediction of growth rate—a pilot study

作者：Milica Medved, Carla Harmath, Hiba Siblini, Mihai Giurcanu, Kirti Kulkarni, Kevin M. Hellman, Obianuju Sandra Madueke-Laveaux · 发表于：Quantitative Imaging in Medicine and Surgery · 年份：2024 · DOI：10.21037/qims-23-1663 · 被引用次数：3 · 研究领域：Uterine Myomas and Treatments、Thyroid and Parathyroid Surgery、Endometriosis Research and Treatment

Background: Uterine fibroid (UF) growth rate and future morbidity cannot be predicted. This can lead to sub-optimal clinical management, with women being lost to follow-up and later presenting with severe disease that may require hospitalization, transfusions, and urgent surgical interventions. Multi-parametric quantitative magnetic resonance imaging (MRI) could provide a biomarker to predict growth rate facilitating better-informed disease management and better clinical outcomes. We assessed the ability of putative quantitative and qualitative MRI predictive factors to predict UF growth rate. Methods: Twenty women with UFs were recruited and completed baseline and follow-up MRI exams, 1-2.5 years apart. The subjects filled out symptom severity and health-related quality of life questionnaires at each visit. A standard clinical pelvic MRI non-contrast exam was performed at each visit, followed by a contrast-enhanced multi-parametric quantitative MRI (mp-qMRI) exam with T2, T2*, and apparent diffusion coefficient (ADC) mapping and dynamic contrast-enhanced MRI. Up to 3 largest fibroids were identified and outlined on the T2-weighted sequence. Fibroid morphology and enhancement patterns were qualitatively assessed on dynamic contrast-enhanced MRI. The UFs' volumes and average T2, T2*, and ADC values were calculated. Pearson correlation coefficients were calculated between UF growth rate and T2, T2*, ADC, and baseline volume. Multiple logistic regression and receiver operating c...