Prediction of Surgical Outcomes in Normal Pressure Hydrocephalus by MR Elastography.

background and purposeNormal pressure hydrocephalus is a treatable cause of dementia associated with distinct mechanical property signatures in the brain as measured by MR elastography. In this study, we tested the hypothesis that specific anatomic features of normal pressure hydrocephalus are associated with unique mechanical property alterations. Then, we tested the hypothesis that summary measures of these mechanical signatures can be used to predict clinical outcomes. MATERIALS AND

methodsMR elastography and structural imaging were performed in 128 patients with suspected normal pressure hydrocephalus and 44 control participants. Patients were categorized into 4 subgroups based on their anatomic features. Surgery outcome was acquired for 68 patients. Voxelwise modeling was performed to detect regions with significantly different mechanical properties between each group. Mechanical signatures were summarized using pattern analysis and were used as features to train classification models and predict shunt outcomes for 2 sets of feature spaces: a limited 2D feature space that included the most common features found in normal pressure hydrocephalus and an expanded 20-dimensional (20D) feature space that included features from all 4 morphologic subgroups.

resultsBoth the 2D and 20D classifiers performed significantly better than chance for predicting clinical outcomes with estimated areas under the receiver operating characteristic curve of 0.66 and 0.77, respectively (

conclusionsMR elastography provides further insight into mechanical alterations in the normal pressure hydrocephalus brain and is a promising, noninvasive method for predicting surgical outcomes in patients with normal pressure hydrocephalus.