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: 4.25). 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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    ABSTRACT: Mild traumatic brain injury (mTBI) appears as low contrast lesions in magnetic resonance (MR) imaging. Standard automated detection approaches cannot detect the subtle changes caused by the lesions. The use of context has become integral for the detection of low contrast objects in images. Context is any information that can be used for object detection but is not directly due to the physical appearance of an object in an image. In this paper new low level static and dynamic context features are proposed and integrated into a discriminative voxel level classifier to improve the detection of mTBI lesions. Visual features, including multiple texture measures, are used to give an initial estimate of a lesion. From the initial estimate novel proximity and directional distance contextual features are calculated and used as features for another classifier. This feature takes advantage of spatial information given by the initial lesion estimate using only the visual features. Dynamic context is captured by the proposed posterior marginal edge distance context feature, which measures the distance from a hard estimate of the lesion at a previous time point. The approach is validated on a temporal mTBI rat model dataset and shown to have improved dice score and convergence compared to other state-of-the-art approaches. Analysis of feature importance and versatility of the approach on other datasets are also provided.
    IEEE transactions on bio-medical engineering 07/2014; · 2.15 Impact Factor
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    ABSTRACT: Abstract Objective: To demonstrate a set of approaches using diffusion tensor imaging (DTI) tractography whereby pathology-affected white matter (WM) fibres in patients with intracerebral haemorrhage (ICH) can be selectively visualized. Methods: Using structural neuroimaging and DTI volumes acquired longitudinally from three representative patients with ICH, the spatial configuration of ICH-related trauma is delineated and the WM fibre bundles intersecting each ICH lesion are identified and visualized. Both the extent of ICH lesions as well as the proportion of WM fibres intersecting the ICH pathology are quantified and compared across subjects. Results: This method successfully demonstrates longitudinal volumetric differences in ICH lesion load and differences across time in the percentage of fibres which intersect the primary injury. Conclusions: Because neurological conditions such as intracerebral haemorrhage (ICH) frequently exhibit pathology-related effects which lead to the exertion of mechanical pressure upon surrounding tissues and, thereby, to the deformation and/or displacement of WM fibres, DTI fibre tractography is highly suitable for assessing longitudinal changes in WM fibre integrity and mechanical displacement.
    Brain Injury 12/2014; · 1.86 Impact Factor
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    ABSTRACT: The integration of longitudinal brain structure analysis with neurointensive care strategies continues to be a substantial difficulty facing the traumatic brain injury (TBI) research community. For patient-tailored case analysis, it remains challenging to establish how lesion profile modulates longitudinal changes in cortical structure and connectivity, as well as how these changes lead to behavioral, cognitive and neural dysfunction. Additionally, despite the clinical potential of morphometric and connectomic studies, few analytic tools are available for their study in TBI. Here we review the state of the art in structural and connectomic neuroimaging for the study of TBI and illustrate a set of recently-developed, patient-tailored approaches for the study of TBI-related brain atrophy and alterations in morphometry as well as inter-regional connectivity. The ability of such techniques to quantify how injury modulates longitudinal changes in cortical shape, structure and circuitry is highlighted. Quantitative approaches such as these can be used to assess and monitor the clinical condition and evolution of TBI victims, and can have substantial translational impact, especially when used in conjunction with measures of neuropsychological function.
    Journal of neurosurgical sciences 01/2014; 58:129-144. · 0.78 Impact Factor


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May 17, 2014