The MRI Spectrum of Gynecological Pelvic Masses
BACKGROUND: Gynecological pelvic masses comprise a wide spectrum of benign and malignant conditions. Accurate preoperative characterization is crucial for optimal management. Although ultrasonography is the initial imaging modality, magnetic resonance imaging (MRI) provides superior soft-tissue characterization and multiplanar assessment. OBJECTIVE: To evaluate the role of MRI in the characterization and differentiation of gynecological pelvic masses, using histopathology as the gold standard wherever available. MATERIALS AND METHODS: This observational study included 60 patients with gynecological pelvic masses detected clinically or on ultrasonography who subsequently underwent MRI pelvis. MRI sequences included T1-weighted, T2-weighted, diffusion-weighted, and contrast-enhanced imaging. Lesions were assessed for site of origin, morphology, internal characteristics, and extent, and MRI findings were correlated with histopathological diagnoses. RESULTS: Benign lesions constituted the majority of cases. Leiomyoma was the most common pathology, observed in 22 patients (36.7%), followed by adenomyosis in 12 patients (20.0%) and ovarian cysts (simple or hemorrhagic) in 11 patients (18.3%). Other benign lesions included dermoid cysts and tubal pathologies such as hydrosalpinx. Malignant lesions were identified in a smaller proportion of patients, with ovarian carcinoma being the most frequent malignancy (four cases, 6.7%), followed by endometrial carcinoma (three cases, 5.0%) and cervical carcinoma (one case, 1.7%). MRI correctly identified all ovarian lesions, including ovarian carcinomas, cysts, and dermoid cysts, as well as all cases of endometrial and cervical carcinoma. Overall, MRI demonstrated a sensitivity of 100%, specificity of 96.2%, and diagnostic accuracy of 96.7% in differentiating benign from malignant lesions. CONCLUSION: MRI is a highly accurate and reliable imaging modality for the evaluation of gynecological pelvic masses, offering excellent lesion characterization and differentiation, thereby significantly aiding clinical decision-making and preoperative planning.
Authors
- Bhoomi Modi
- Ashish Shukla (ORCID: https://orcid.org/0000-0002-7982-7013)
- Ranjeet Singh
- Manisha Gupta
- Sachi Mall
- Shipra Chaudhary
Institutions
- Santosh University (IN)
Publication Details
- Journal
- Cureus
- Published
- 2026-03-31
- DOI
- https://doi.org/10.7759/cureus.106177
- Primary Topic
- Ovarian cancer diagnosis and treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00