Article

Comparison of Acute and Chronic Traumatic Brain Injury Using Semi-Automatic Multimodal Segmentation of MR Volumes

Laboratory of Neuro Imaging, University of California, Los Angeles, California 90095, USA.
Journal of neurotrauma (Impact Factor: 3.71). 07/2011; 28(11):2287-306. DOI: 10.1089/neu.2011.1920
Source: PubMed

ABSTRACT

Although neuroimaging is essential for prompt and proper management of traumatic brain injury (TBI), there is a regrettable and acute lack of robust methods for the visualization and assessment of TBI pathophysiology, especially for of the purpose of improving clinical outcome metrics. Until now, the application of automatic segmentation algorithms to TBI in a clinical setting has remained an elusive goal because existing methods have, for the most part, been insufficiently robust to faithfully capture TBI-related changes in brain anatomy. This article introduces and illustrates the combined use of multimodal TBI segmentation and time point comparison using 3D Slicer, a widely-used software environment whose TBI data processing solutions are openly available. For three representative TBI cases, semi-automatic tissue classification and 3D model generation are performed to perform intra-patient time point comparison of TBI using multimodal volumetrics and clinical atrophy measures. Identification and quantitative assessment of extra- and intra-cortical bleeding, lesions, edema, and diffuse axonal injury are demonstrated. The proposed tools allow cross-correlation of multimodal metrics from structural imaging (e.g., structural volume, atrophy measurements) with clinical outcome variables and other potential factors predictive of recovery. In addition, the workflows described are suitable for TBI clinical practice and patient monitoring, particularly for assessing damage extent and for the measurement of neuroanatomical change over time. With knowledge of general location, extent, and degree of change, such metrics can be associated with clinical measures and subsequently used to suggest viable treatment options.

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Available from: Andrei Irimia
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    • "Both studies (Strangman et al., 2010; Warner et al., 2010b) identified several structures, including the thalamus and hippocampus that are particularly affected by TBI and are of significant value when predicting clinical outcome. The automatic structural segmentation of MR brain scans of TBI patients remains, however, a difficult endeavour as most existing methods lack robustness towards TBI-related changes in anatomy (Irimia et al., 2011, 2012). In the acute phase contusions, the presence of blood, hydrocephalus and/or oedema can greatly affect the ability to accurately segment a brain. "
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    • "The WM model is translucent in each brain view to facilitate the visibility of anatomic details obviated in the MR volume slice displayed. See Irimia et al. (2011) for a detailed description of the neuroinformatics methodology used to generate these visualizations. "
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