Patient-tailored multimodal neuroimaging, visualization and quantification of human intra-cerebral hemorrhage

In traumatic brain injury (TBI) and intracerebral hemorrhage (ICH), the heterogeneity of lesion sizes and types necessitates a variety of imaging modalities to acquire a comprehensive perspective on injury extent. Although it is advantageous to combine imaging modalities and to leverage their complementary benefits, there are difficulties in integrating information across imaging types. Thus, it is important that efforts be dedicated to the creation and sustained refinement of resources for multimodal data integration. Here, we propose a novel approach to the integration of neuroimaging data acquired from human patients with TBI/ICH using various modalities; we also demonstrate the integrated use of multimodal magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) data for TBI analysis based on both visual observations and quantitative metrics. 3D models of healthy-appearing tissues and TBIrelated pathology are generated, both of which are derived from multimodal imaging data. MRI volumes acquired using FLAIR, SWI, and T2 GRE are used to segment pathology. Healthy tissues are segmented using user-supervised tools, and results are visualized using a novel graphical approach called a ‘connectogram’, where brain connectivity information is depicted within a circle of radially aligned elements. Inter-region connectivity and its strength are represented by links of variable opacities drawn between regions, where opacity reflects the percentage longitudinal change in brain connectivity density. Our method for integrating, analyzing and visualizing structural brain changes due to TBI and ICH can promote knowledge extraction and enhance the understanding of mechanisms underlying recovery.

[1]  S. Jang,et al.  Recovery of an injured corticospinal tract during a critical period in a patient with intracerebral hemorrhage. , 2013, NeuroRehabilitation.

[2]  A. Toga,et al.  Comparison of acute and chronic traumatic brain injury using semi-automatic multimodal segmentation of MR volumes. , 2011, Journal of neurotrauma.

[3]  H. Moser,et al.  Imaging cortical association tracts in the human brain using diffusion‐tensor‐based axonal tracking , 2002, Magnetic resonance in medicine.

[4]  Elena I. Nica,et al.  Quantified MRI and cognition in TBI with diffuse and focal damage☆ , 2013, NeuroImage: Clinical.

[5]  C. Anderson,et al.  Guidelines for the Management of Spontaneous Intracerebral Hemorrhage: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association , 2010, Stroke.

[6]  S. Rombouts,et al.  Loss of ‘Small-World’ Networks in Alzheimer's Disease: Graph Analysis of fMRI Resting-State Functional Connectivity , 2010, PloS one.

[7]  K. Domen,et al.  Motor outcome for patients with acute intracerebral hemorrhage predicted using diffusion tensor imaging: an application of ordinal logistic modeling. , 2012, Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association.

[8]  D. Hanley,et al.  Longitudinal quantification and visualization of intracerebral haemorrhage using multimodal magnetic resonance and diffusion tensor imaging , 2015, Brain injury.

[9]  E Mark Haacke,et al.  Hemorrhagic shearing lesions in children and adolescents with posttraumatic diffuse axonal injury: improved detection and initial results. , 2003, Radiology.

[10]  Andrew Newberg,et al.  Neuroimaging of traumatic brain injury. , 2008, Seminars in neurology.