Posterior vaginal wall prolapse (PVP), including enterocele and rectocele, is an enigmatic condition whosepathophysiology is poorly understood. ORWH, NICHD and NIDDK have each identified that female pelvicfloor disorders such as PVP are in critical need of pathophysiology research. Competing hypotheses havebeen proposed relating to the causal roles of endopelvic fascia or levator ani muscle failure. However, datato resolve these conflicts are not available and are needed to establish the relative contributions of fascialand muscular abnormalities to PVP. This study will test the mechanistic hypothesis that the occurrence ofPVP is not explained by a single mechanism but involves the interaction between fascial and muscleabnormalities. To test these hypotheses, we will recruit 75 cases with PVP and 75 controls of similar ageand race.
Aim 1. 'Fascia', we will use mid-sagittal MR images made during maximal Valsalva to documentthe posterior wall location and morphology in 4 regions influenced by fascial support: 1) location of theposterior vaginal apex, 2) length of the posterior vaginal wall, 3) changes in the inclination of the distalvaginal wall, and 4) location of the perineal body. By comparing measurements between cases and controls,we will determine the contributions of abnormalities in each region to the occurrence and size of PVP.
Aim2. 'Muscle', we will use multiplanar proton density MR scans to compare 1) presence of visible defects in thelevator ani muscles, 2) cross sectional areas of the muscle, as well as measuring and 3) pelvic musclecontraction force during a maximal contraction. Using these data we will determine the contribution ofmuscular abnormalities. We will then use statistical modeling to determine the relative contributions offascial versus muscular abnormalities.
Aim 3. 'Rectocele vs. Enterocele', we will test the strength ofassociation between the 4 fascial and 3 muscle abnormalities and the two types of PVP using general linearmodeling.
Aim 4, 'Biomechanical Modeling', we will use biomechanical analyses of fascia and muscleinteractions in computer-based models to investigate patterns of muscle and connective tissue support sitefailures that lead to PVP. These insights are needed to advance our understanding of disease mechanismsso that we can reduce the 30% recurrence rate of prolapse after surgery, and develop preventativestrategies to reduce the need for surgery in 200,000 women each year.
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