Person: O'Donnell, Lauren
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O'Donnell
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Lauren
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O'Donnell, Lauren
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Publication Reconstruction of the arcuate fasciculus for surgical planning in the setting of peritumoral edema using two-tensor unscented Kalman filter tractography(Elsevier, 2015) Chen, Zhenrui; Tie, Yanmei; Olubiyi, Olutayo; Rigolo, Laura; Mehrtash, Alireza; Norton, Isaiah Hakim; Pasternak, Ofer; Rathi, Yogesh; Golby, Alexandra; O'Donnell, LaurenBackground: Diffusion imaging tractography is increasingly used to trace critical fiber tracts in brain tumor patients to reduce the risk of post-operative neurological deficit. However, the effects of peritumoral edema pose a challenge to conventional tractography using the standard diffusion tensor model. The aim of this study was to present a novel technique using a two-tensor unscented Kalman filter (UKF) algorithm to track the arcuate fasciculus (AF) in brain tumor patients with peritumoral edema. Methods: Ten right-handed patients with left-sided brain tumors in the vicinity of language-related cortex and evidence of significant peritumoral edema were retrospectively selected for the study. All patients underwent 3-Tesla magnetic resonance imaging (MRI) including a diffusion-weighted dataset with 31 directions. Fiber tractography was performed using both single-tensor streamline and two-tensor UKF tractography. A two-regions-of-interest approach was applied to perform the delineation of the AF. Results from the two different tractography algorithms were compared visually and quantitatively. Results: Using single-tensor streamline tractography, the AF appeared disrupted in four patients and contained few fibers in the remaining six patients. Two-tensor UKF tractography delineated an AF that traversed edematous brain areas in all patients. The volume of the AF was significantly larger on two-tensor UKF than on single-tensor streamline tractography (p < 0.01). Conclusions: Two-tensor UKF tractography provides the ability to trace a larger volume AF than single-tensor streamline tractography in the setting of peritumoral edema in brain tumor patients.Publication Visual Pathway Study Using In Vivo Diffusion Tensor Imaging Tractography to Complement Classic Anatomy(Oxford University Press (OUP), 2012) Wu, Wentao; Rigolo, Laura; O'Donnell, Lauren; Norton, Isaiah Hakim; Shriver, Sargent; Golby, AlexandraBACKGROUND: Knowledge of the individual course of the optic radiations (ORs) is important to avoid postoperative visual deficits. Cadaveric studies of the visual pathways are limited because it has not been possible to separate the OR from neighboring tracts accurately and results may not apply to individual patients. Diffusion tensor imaging studies may be able to demonstrate the relationships between the OR and neighboring fibers in vivo in individual subjects. OBJECTIVE: To use diffusion tensor imaging tractography to study the OR and the Meyer loop (ML) anatomy in vivo. METHODS: Ten healthy subjects underwent magnetic resonance imaging with diffusion imaging at 3 T. With the use of a fiducial-based diffusion tensor imaging tractography tool (Slicer 3.3), seeds were placed near the lateral geniculate nucleus to reconstruct individual visual pathways and neighboring tracts. Projections of the ORs onto 3-dimensional brain models were shown individually to quantify relationships to key landmarks. RESULTS: Two patterns of visual pathways were found. The OR ran more commonly deep in the whole superior and middle temporal gyri and superior temporal sulcus. The OR was closely surrounded in all cases by an inferior longitudinal fascicle and a parieto/occipito/temporo-pontine fascicle. The mean left and right distances between the tip of the OR and temporal pole were 39.8 ± 3.8 and 40.6 ± 5.7 mm, respectively. CONCLUSION: Diffusion tensor imaging tractography provides a practical complementary method to study the OR and the Meyer loop anatomy in vivo with reference to individual 3-dimensional brain anatomy.Publication fMRI-DTI modeling via landmark distance atlases for prediction and detection of fiber tracts(Elsevier BV, 2012) O'Donnell, Lauren; Rigolo, Laura; Norton, Isaiah; Wells, William; Westin, Carl-Fredrik; Golby, AlexandraThe overall goal of this research is the design of statistical atlas models that can be created from normal subjects, but may generalize to be applicable to abnormal brains. We present a new style of joint modeling of fMRI, DTI, and structural MRI. Motivated by the fact that a white matter tract and related cortical areas are likely to displace together in the presence of a mass lesion (brain tumor), in this work we propose a rotation and translation invariant model that represents the spatial relationship between fiber tracts and anatomic and functional landmarks. This landmark distance model provides a new basis for representation of fiber tracts and can be used for detection and prediction of fiber tracts based on landmarks. Our results indicate that the measured model is consistent across normal subjects, and thus suitable for atlas building. Our experiments demonstrate that the model is robust to displacement and missing data, and can be successfully applied to a small group of patients with mass lesions.Publication Fiber clustering versus the parcellation-based connectome(Elsevier BV, 2013) O'Donnell, Lauren; Golby, Alexandra; Westin, Carl-FredrikWe compare two strategies for modeling the connections of the brain's white matter: fiber clustering and the parcellation-based connectome. Both methods analyze diffusion magnetic resonance imaging fiber tractography to produce a quantitative description of the brain's connections. Fiber clustering is designed to reconstruct anatomically-defined white matter tracts, while the parcellation-based white matter segmentation enables the study of the brain as a network. From the perspective of white matter segmentation, we compare and contrast the goals and methods of the parcellation-based and clustering approaches, with special focus on reviewing the field of fiber clustering. We also propose a third category of new hybrid methods that combine the aspects of parcellation and clustering, for joint analysis of connection structure and anatomy or function. We conclude that these different approaches for segmentation and modeling of the white matter can advance the neuroscientific study of the brain's connectivity in complementary ways.Publication White matter tractography for neurosurgical planning: A topography-based review of the current state of the art(Elsevier, 2017) Essayed, Walid I.; Zhang, Fan; Unadkat, Prashin; Cosgrove, G. Rees; Golby, Alexandra; O'Donnell, LaurenWe perform a review of the literature in the field of white matter tractography for neurosurgical planning, focusing on those works where tractography was correlated with clinical information such as patient outcome, clinical functional testing, or electro-cortical stimulation. We organize the review by anatomical location in the brain and by surgical procedure, including both supratentorial and infratentorial pathologies, and excluding spinal cord applications. Where possible, we discuss implications of tractography for clinical care, as well as clinically relevant technical considerations regarding the tractography methods. We find that tractography is a valuable tool in variable situations in modern neurosurgery. Our survey of recent reports demonstrates multiple potentially successful applications of white matter tractography in neurosurgery, with progress towards overcoming clinical challenges of standardization and interpretation.Publication A Method for Clustering White Matter Fiber Tracts(American Society of Neuroradiology, 2006) O'Donnell, Lauren; Kubicki, Marek; Shenton, Martha; Dreusicke, M.H.; Grimson, W.E.L.; Westin, Carl-FredrikBACKGROUND/PURPOSE: Despite its potential for visualizing white matter fiber tracts in vivo, diffusion tensor tractography has found only limited applications in clinical research in which specific anatomic connections between distant regions need to be evaluated. We introduce a robust method for fiber clustering that guides the separation of anatomically distinct fiber tracts and enables further estimation of anatomic connectivity between distant brain regions. METHODS: Line scanning diffusion tensor images (LSDTI) were acquired on a 1.5T magnet. Regions of interest for several anatomically distinct fiber tracts were manually drawn; then, white matter tractography was performed by using the Runge-Kutta method to interpolate paths (fiber traces) following the major directions of diffusion, in which traces were seeded only within the defined regions of interest. Next, a fully automatic procedure was applied to fiber traces, grouping them according to a pairwise similarity function that takes into account the shapes of the fibers and their spatial locations. RESULTS: We demonstrated the ability of the clustering algorithm to separate several fiber tracts which are otherwise difficult to define (left and right fornix, uncinate fasciculus and inferior occipitofrontal fasciculus, and corpus callosum fibers). CONCLUSION: This method successfully delineates fiber tracts that can be further analyzed for clinical research purposes. Hypotheses regarding specific fiber connections and their abnormalities in various neuropsychiatric disorders can now be tested.