Improving Access to Intracranial Volume Measurements for Clinical Use: Open-Source Method using Computed Tomography

Abstract

Introduction: Three-dimensional measurements of intracranial volume (ICV) can guide clinical management of brain and skull disorders. However, widespread clinical access is limited by the scarcity of software methods for analyzing CT scans, which are more available than MRI images, and the inaccessibility of proprietary and expensive commercial software. The presented method can calculate ICV from CT scans, using an open-source software, 3D Slicer. Methods: The open-source workflow was optimized with a data-driven approach to find the optimal parameters for ICV accuracy. The accuracy of the open-source method was determined by comparing it to commercial and proprietary software with CT scans of pediatric hydrocephalic macrocephaly patients with craniosynostosis undergoing total vault reconstruction (N = 5 patients,15 scans). Results: An open-source pipeline that combines an initial semi-automatic segmentation of a coronal CT reconstruction with a fully automatic segmentation minimizes the ICV error. The open-source method shows excellent agreement with both the commercial and proprietary software methods (R2 = 0.998 and 95% confidence interval of best-fit line slope: [0.986; 1.047], [0.985;1.066] respectively). The mean percent difference of ICV measurements of the open-source software from the commercial software was −0.56% [95% CI: −1.08%, −0.028%] and from the proprietary software was −0.07% [95% CI: −1.26%, 1.1%]. The mean percent difference of ICV measurements of the commercial software from the proprietary software was 0.36% [95% Confidence Interval: −0.61%, 1.32%]. Conclusions: This is the first study comparing an open-source method for measuring ICV with commercial and proprietary options. A high degree of fidelity was found, confirming this open-source method as a viable option for clinicians who are looking to incorporate ICV measurements into their practice.