Quantitative Intracerebral Hemorrhage Localization

Abstract

Background and purpose: The location of intracerebral hemorrhage (ICH) is currently described in a qualitative way; we provide a quantitative framework for estimating ICH engagement and its relevance to stroke outcomes.

Methods: We analyzed 111 patients with ICH from the Minimally Invasive Surgery Plus Recombinant-Tissue Plasminogen Activator for Intracerebral Evacuation (MISTIE) II clinical trial. We estimated ICH engagement at a population level using image registration of computed tomographic scans to a template and a previously labeled atlas. Predictive regions of National Institutes of Health Stroke Scale and Glasgow Coma Scale stroke severity scores, collected at enrollment, were estimated.

Results: The percent coverage of the ICH by these regions strongly outperformed the reader-labeled locations. The adjusted R(2) almost doubled from 0.129 (reader-labeled model) to 0.254 (quantitative location model) for National Institutes of Health Stroke Scale and more than tripled from 0.069 (reader-labeled model) to 0.214 (quantitative location model). A permutation test confirmed that the new predictive regions are more predictive than chance: P<0.001 for National Institutes of Health Stroke Scale and P<0.01 for Glasgow Coma Scale.

Conclusions: Objective measures of ICH location and engagement using advanced computed tomographic imaging processing provide finer, objective, and more quantitative anatomic information than that provided by human readers.

Clinical trial registration: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00224770.

Keywords: Glasgow Coma Scale; cerebral hemorrhage; stroke; tomography, x-ray computed.

© 2015 American Heart Association, Inc.

Figures

Figure 1. ICH engagement prevalence

The proportion of patients with ICH engaging a voxel is represented in a 3D histogram (right side of image is left side of brain) overlaid on an MRI T1 template. There is a higher prevalence of ICH on the left side of the brain, localized in the middle of the brain, with few extensions in the anterior and posterior areas. The interactive version of this figure is located at http://muschellij2.github.io/CT_Pipeline/index.html.

Figure 2. Highest Predictive Region (HPR) Analysis

Panels (A) and (B) correspond to the HPR for the top-performing model for NIHSS and GCS scores. The HPR in (A) represents a p-value threshold of .0100 (19047 voxels) for the voxel-wise p-value of ICH on NIHSS. The HPR in (B) represents 1000 with the lowest p-values for the voxel-wise ICH on GCS score regressions. Panels (C) and (D) plot the HPR coverage and severity score relationship (red-linear fit, blue-LOESS fit). The larger the HPR coverage the higher (more severe) the NIHSS and the lower (deeper unconsciousness) the GCS.