ReviewSichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition2025
[Application of Magnetic Resonance Imaging in the Diagnosis and Treatment of Middle Compartment Defect].
Review in Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Middle compartment defects, a common subtype of pelvic floor dysfunction (PFD), are primarily characterized by the prolapse of the uterus or vaginal vault. Magnetic resonance imaging (MRI) has emerged as a valuable diagnostic tool for PFD, offering superior soft tissue resolution while eliminating exposure to ionizing radiation. This review comprehensive summarizes current applications of MRI in the diagnosis and treatment of PFD, covering measurement methods, manifestations of three-level structural defects, postoperative efficacy evaluation, vaginal axial assessment, and evaluation of the mesh status. The authors suggest that MRI enables precise preoperative evaluation of three-level defects, thereby facilitating the development of personalized treatment plans. Additionally, MRI provides an accurate postoperative assessment of surgical outcomes and mesh status, offering a new basis for postoperative assessment. MRI demonstrates unique value in the diagnosis and treatment of middle compartment defects.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.