Objective and Impact Statement. We propose an automated method of predicting Normal Pressure Hydrocephalus (NPH) from CT scans. A deep convolutional network segments regions of interest from the scans. These regions are then combined with MRI information to predict NPH. To our knowledge, this is the first method which automatically predicts NPH from CT scans and incorporates diffusion tractography information for prediction. Introduction. Due to their low cost and high versatility, CT scans are often used in NPH diagnosis. No well-defined and effective protocol currently exists for analysis of CT scans for NPH. Evans’ index, an approximation of the ventricle to brain volume using one 2D image slice, has been proposed but is not robust. The proposed approach is an effective way to quantify regions of interest and offers a computational method for predicting NPH. Methods. We propose a novel method to predict NPH by combining regions of interest segmented from CT scans with connectome data to compute features which capture the impact of enlarged ventricles by excluding fiber tracts passing through these regions. The segmentation and network features are used to train a model for NPH prediction. Results. Our method outperforms the current state-of-the-art by 9 precision points and 29 recall points. Our segmentation model outperforms the current state-of-the-art in segmenting the ventricle, gray-white matter, and subarachnoid space in CT scans. Conclusion. Our experimental results demonstrate that fast and accurate volumetric segmentation of CT brain scans can help improve the NPH diagnosis process, and network properties can increase NPH prediction accuracy.

Introduction: Normal pressure hydrocephalus (NPH) is a debilitating, neurological condition that can lead to mental deterioration. With the diagnosis and treatment of NPH constantly evolving and its symptoms worsening with age, education for patients and their families is crucial. In this study, we aim to explore the potential educational benefits of a physician-led NPH support group. Methods: Between December 2015 and November 2018, six semiannual NPH support group meetings were held for patients and their families. Attendees, ages 20-90, completed a Likert scale-based survey designed to assess the support group's educational benefits using the following primary outcome variables: (1) subjective knowledge, (2) perceived utility/efficacy, and (3) patient satisfaction. Results: Our survey data suggests that patients and their family members agree on the efficacy of the support group in learning about NPH. They felt that the support group served its purpose and improved their comfort/knowledge regarding NPH. There was consensus about sustaining and maintaining the support group for the future. Of 65 survey responses, the composite average score of questions pertaining to subjective knowledge, perceived utility/efficacy, and patient satisfaction was 4.5 out of 5.0. Conclusion: We demonstrated that support groups are effective in educating the adult NPH population and their family/friends about NPH onset and treatment. Enhanced educational awareness for patients and families can help patients cope with their neurological condition and improve patient adherence to follow-up and physician recommendations.

No abstract