Magnetic Resonance Imaging in Pelvic Endometriosis: Imaging Characteristics and Anatomical Distribution at a Tertiary Care Study
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This study evaluated MRI characteristics and anatomical distribution of pelvic endometriosis in 25 patients, finding ovarian involvement most frequent and MRI reliable for diagnosis and mapping, especially for deep infiltrating disease.
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Abstract
CONTEXT: Endometriosis is a chronic gynecological disorder, characterized by the presence of functional endometrial glands and stroma outside the uterine cavity. It commonly presents with pelvic pain and infertility and may involve ovarian, peritoneal, and deep pelvic structures. Although laparoscopy remains the gold standard for diagnosis, magnetic resonance imaging (MRI) has emerged as a valuable noninvasive modality for detection and preoperative mapping, particularly in deep infiltrating disease. AIMS: To evaluate the characteristic MRI features of pelvic endometriosis and to analyze the anatomical distribution and imaging spectrum of lesions in affected patients. SUBJECTS AND METHODS: This retrospective, observational study included 25 female patients clinically or sonographically suspected of endometriosis who were referred to the department of radiodiagnosis at a tertiary care center between May 2023 and April 2024. All the patients underwent pelvic ultrasound followed by MRI on a 3.0-T system using sequences. STATISTICAL ANALYSIS USED: Mean ± standard deviation, frequency, and percentages. RESULTS: The mean age was 32 ± 5 years, with 44% of patients in the 26-30 years' age group. The most common symptom was pelvic pain with dysmenorrhea (44%), followed by infertility (20%). Ovarian involvement was most frequent site, identified in 56% of patients (36% unilateral and 20% bilateral). Deep infiltrating endometriosis was seen in 32% of cases. CONCLUSIONS: MRI is a reliable and comprehensive imaging modality for diagnosing and mapping pelvic endometriosis. It is particularly valuable in detecting deep infiltrating disease and in guiding preoperative assessment by accurately delineating lesion distribution and signal characteristics.
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- europepmc
- last seen: 2026-06-25T06:14:32.897245+00:00
- openalex
- last seen: 2026-06-25T06:08:12.940401+00:00
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