Yibao Wang

Bio: Yibao Wang is an academic researcher from University of Pittsburgh. The author has contributed to research in topics: Tractography & Diffusion MRI. The author has an hindex of 5, co-authored 5 publications receiving 1019 citations.

Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy

Abstract: Diffusion MRI tractography has emerged as a useful and popular tool for mapping connections between brain regions. In this study, we examined the performance of quantitative anisotropy (QA) in facilitating deterministic fiber tracking. Two phantom studies were conducted. The first phantom study examined the susceptibility of fractional anisotropy (FA), generalized factional anisotropy (GFA), and QA to various partial volume effects. The second phantom study examined the spatial resolution of the FA-aided, GFA-aided, and QA-aided tractographies. An in vivo study was conducted to track the arcuate fasciculus, and two neurosurgeons blind to the acquisition and analysis settings were invited to identify false tracks. The performance of QA in assisting fiber tracking was compared with FA, GFA, and anatomical information from T1-weighted images. Our first phantom study showed that QA is less sensitive to the partial volume effects of crossing fibers and free water, suggesting that it is a robust index. The second phantom study showed that the QA-aided tractography has better resolution than the FA-aided and GFA-aided tractography. Our in vivo study further showed that the QA-aided tractography outperforms the FA-aided, GFA-aided, and anatomy-aided tractographies. In the shell scheme (HARDI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 30.7%, 32.6%, and 24.45% of the false tracks, respectively, while the QA-aided tractography has 16.2%. In the grid scheme (DSI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 12.3%, 9.0%, and 10.93% of the false tracks, respectively, while the QA-aided tractography has 4.43%. The QA-aided deterministic fiber tracking may assist fiber tracking studies and facilitate the advancement of human connectomics.

High-definition fiber tractography of the human brain: neuroanatomical validation and neurosurgical applications.

Abstract: BACKGROUND: High-definition fiber tracking (HDFT) is a novel combination of processing, reconstruction, and tractography methods that can track white matter fibers from cortex, through complex fiber crossings, to cortical and subcortical targets with subvoxel resolution. OBJECTIVE: To perform neuroanatomical validation of HDFT and to investigate its neurosurgical applications. METHODS: Six neurologically healthy adults and 36 patients with brain lesions were studied. Diffusion spectrum imaging data were reconstructed with a Generalized Q-Ball Imaging approach. Fiber dissection studies were performed in 20 human brains, and selected dissection results were compared with tractography. RESULTS: HDFT provides accurate replication of known neuroanatomical features such as the gyral and sulcal folding patterns, the characteristic shape of the claustrum, the segmentation of the thalamic nuclei, the decussation of the superior cerebellar peduncle, the multiple fiber crossing at the centrum semiovale, the complex angulation of the optic radiations, the terminal arborization of the arcuate tract, and the cortical segmentation of the dorsal Broca area. From a clinical perspective, we show that HDFT provides accurate structural connectivity studies in patients with intracerebral lesions, allowing qualitative and quantitative white matter damage assessment, aiding in understanding lesional patterns of white matter structural injury, and facilitating innovative neurosurgical applications. High-grade gliomas produce significant disruption of fibers, and low-grade gliomas cause fiber displacement. Cavernomas cause both displacement and disruption of fibers. CONCLUSION: Our HDFT approach provides an accurate reconstruction of white matter fiber tracts with unprecedented detail in both the normal and pathological human brain. Further studies to validate the clinical findings are needed.

Asymmetry, connectivity, and segmentation of the arcuate fascicle in the human brain

Abstract: The structure and function of the arcuate fascicle is still controversial. The goal of this study was to investigate the asymmetry, connectivity, and segmentation patterns of the arcuate fascicle. We employed diffusion spectrum imaging reconstructed by generalized q-sampling and we applied both a subject-specific approach (10 subjects) and a template approach (q-space diffeomorphic reconstruction of 30 subjects). We complemented our imaging investigation with fiber microdissection of five post-mortem human brains. Our results confirmed the highly leftward asymmetry of the arcuate fascicle. In the template, the left arcuate had a volume twice as large as the right one, and the left superior temporal gyrus provided five times more volume of fibers than its counterpart. We identified four cortical frontal areas of termination: pars opercularis, pars triangularis, ventral precentral gyrus, and caudal middle frontal gyrus. We found clear asymmetry of the frontal terminations at pars opercularis and ventral precentral gyrus. The analysis of patterns of connectivity revealed the existence of a strong structural segmentation in the left arcuate, but not in the right one. The left arcuate fascicle is formed by an inner or ventral pathway, which interconnects pars opercularis with superior and rostral middle temporal gyri; and an outer or dorsal pathway, which interconnects ventral precentral and caudal middle frontal gyri with caudal middle and inferior temporal gyri. The fiber microdissection results provided further support to our tractography studies. We propose the existence of primary and supplementary language pathways within the dominant arcuate fascicle with potentially distinct functional and lesional features.

Rethinking the Role of the Middle Longitudinal Fascicle in Language and Auditory Pathways

Abstract: The middle longitudinal fascicle (MdLF) was originally described in the monkey brain as a pathway that interconnects the superior temporal and angular gyri. Only recently have diffusion tensor imaging studies provided some evidence of its existence in humans, with a connectivity pattern similar to that in monkeys and a potential role in the language system. In this study, we combine high-angular-resolution fiber tractography and fiber microdissection techniques to determine the trajectory, cortical connectivity, and a quantitative analysis of the MdLF. Here, we analyze diffusion spectrum imaging (DSI) studies in 6 subjects (subject-specific approach) and in a template of 90 DSI studies (NTU-90 Atlas). Our tractography and microdissection results show that the human MdLF differs significantly from the monkey. Indeed, the human MdLF interconnects the superior temporal gyrus with the superior parietal lobule and parietooccipital region, and has only minor connections with the angular gyrus. On the basis of the roles of these interconnected cortical regions, we hypothesize that, rather than a language-related tract, the MdLF may contribute to the dorsal "where" pathway of the auditory system.

Correction: Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy

Abstract: In the Materials and Methods, the paragraph after Equation 3 contains several errors that were introduced during production. The third sentence of that paragraph should read "the nearby voxels include (32, 12, 16), (32, 12, 17), (32, 13, 16), (32, 13, 17), (33, 12, 16), (33, 12, 17), (33, 13, 16), and (33, 13, 17)." In the fifth sentence of that paragraph, half of the equation is missing. Please see the full equation here: http://plosone.org/corrections/pone.0080713.e000.cn.tif There are also errors in Table 1. Please refer to the corrected Table 1 here: http://plosone.org/corrections/pone.0080713.t001.cn.tif

The connectomics of brain disorders

Abstract: Pathological perturbations of the brain are rarely confined to a single locus; instead, they often spread via axonal pathways to influence other regions. Patterns of such disease propagation are constrained by the extraordinarily complex, yet highly organized, topology of the underlying neural architecture; the so-called connectome. Thus, network organization fundamentally influences brain disease, and a connectomic approach grounded in network science is integral to understanding neuropathology. Here, we consider how brain-network topology shapes neural responses to damage, highlighting key maladaptive processes (such as diaschisis, transneuronal degeneration and dedifferentiation), and the resources (including degeneracy and reserve) and processes (such as compensation) that enable adaptation. We then show how knowledge of network topology allows us not only to describe pathological processes but also to generate predictive models of the spread and functional consequences of brain disease.

The challenge of mapping the human connectome based on diffusion tractography

Abstract: Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.

Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy

Abstract: Diffusion MRI tractography has emerged as a useful and popular tool for mapping connections between brain regions. In this study, we examined the performance of quantitative anisotropy (QA) in facilitating deterministic fiber tracking. Two phantom studies were conducted. The first phantom study examined the susceptibility of fractional anisotropy (FA), generalized factional anisotropy (GFA), and QA to various partial volume effects. The second phantom study examined the spatial resolution of the FA-aided, GFA-aided, and QA-aided tractographies. An in vivo study was conducted to track the arcuate fasciculus, and two neurosurgeons blind to the acquisition and analysis settings were invited to identify false tracks. The performance of QA in assisting fiber tracking was compared with FA, GFA, and anatomical information from T1-weighted images. Our first phantom study showed that QA is less sensitive to the partial volume effects of crossing fibers and free water, suggesting that it is a robust index. The second phantom study showed that the QA-aided tractography has better resolution than the FA-aided and GFA-aided tractography. Our in vivo study further showed that the QA-aided tractography outperforms the FA-aided, GFA-aided, and anatomy-aided tractographies. In the shell scheme (HARDI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 30.7%, 32.6%, and 24.45% of the false tracks, respectively, while the QA-aided tractography has 16.2%. In the grid scheme (DSI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 12.3%, 9.0%, and 10.93% of the false tracks, respectively, while the QA-aided tractography has 4.43%. The QA-aided deterministic fiber tracking may assist fiber tracking studies and facilitate the advancement of human connectomics.

White matter fiber tractography: why we need to move beyond DTI.

Abstract: Object Diffusion-based MRI tractography is an imaging tool increasingly used in neurosurgical procedures to generate 3D maps of white matter pathways as an aid to identifying safe margins of resection. The majority of white matter fiber tractography software packages currently available to clinicians rely on a fundamentally flawed framework to generate fiber orientations from diffusion-weighted data, namely diffusion tensor imaging (DTI). This work provides the first extensive and systematic exploration of the practical limitations of DTI-based tractography and investigates whether the higher-order tractography model constrained spherical deconvolution provides a reasonable solution to these problems within a clinically feasible timeframe. Methods Comparison of tractography methodologies in visualizing the corticospinal tracts was made using the diffusion-weighted data sets from 45 healthy controls and 10 patients undergoing presurgical imaging assessment. Tensor-based and constrained spherical deconvolut...