Pelvic Mass Lesions in Females: Tissue Characterization Capability of MRI
Journal Title: Journal of Clinical and Diagnostic Research - Year 2017, Vol 11, Issue 7
Abstract
Introduction: Magnetic Resonance Imaging (MRI) of adult female pelvis is a well-established tool in the evaluation of uteroovarian lesions and is often used to supplement ultrasonography. The need for diagnostic surgical intervention has largely been eclipsed with the advent of MRI, which has become the imaging modality of choice for characterization of pelvic masses. Aim: To assess the role of MRI in female pelvic mass lesions and to exploit the tissue characterization capability of MRI. Materials and Methods: A prospective observational study was done on all patients referred to Department of Radiodiagnosis, Krishna Hospital, Karad, for MRI pelvis with clinically suspected uterine and adnexal masses or with indeterminate diagnosis on ultrasonography. Study was conducted between September 2014 to August 2016 with a sample size of 100 patients. All patients were scanned using 1.5 Tesla Seimens Avanto (Tim+Dot) scanner with Body matrix coil Tim. Histopathology was taken as gold standard. Results on continuous measurements were presented on Mean±SD (Min-Max) and results on categorical measurements were presented in Number (%). Results: Among 100 cases, on MRI, the maximum number of patients was having uterine lesions (48) followed by ovarian lesions (40), inconclusive adnexal/ovarian lesions (6), adnexal lesions (4). Two patients had normal findings. This correlated well with histopathology results, which showed the maximum number of patients were having uterine lesions (48) followed by ovarian lesions (41), adnexal lesions (5). Normal findings were observed in two patients. Conclusion: Due to excellent depiction of pelvic anatomy, non-invasiveness and absence of ionizing radiation, MRI is an excellent tool for assessment of utero-ovarian disorders, for detecting and characterization of various diseases, and staging patients with carcinomas where accurate diagnosis will make an impact on their surgical and medical management planning.
Authors and Affiliations
Pramod Ramchand Shaha, Rahul Khetawat, Kulamani Sahoo, Ashish Garg, Mohd. Abbas Ilyas, Gaurav Khairnar, Sahil Garg, Shree Hari Budgemwar
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