Publications

In the last two decades, the statistical analysis of shape has become an actively studied field and finds applications in a wide range of areas. In addition to algorithmic development, many researchers have distributed end-user orientated toolboxes, which further enable the utilization of the algorithms in an "off the shelf" fashion. However, there is little work on the evaluation and validation of these techniques, which poses a rather serious challenge when interpreting their results. To address this lack of validation, we design a validation framework and then use it to test some of the most widely used toolboxes. Our initial results show inconsistencies and disagreement among four different methods. We believe this type of analysis to be critical not only for the community of algorithm designers but also perhaps more importantly to researchers who use these tools without knowing the algorithm details and seek objective criteria for tool selection.

In this paper we propose a new method for shape analysis based on the depth-ordering of shapes. We use this depth-ordering to non-parametrically define depth with respect to a normal control population. This allows us to quantify differences with respect to "normality". We combine this approach with a permutation test allowing it to test for localized shape differences. The method is evaluated on a synthetically generated striatum dataset as well as on a real caudate dataset.

INTRODUCTION: The medial orbitofrontal cortex (mOFC) and rostral part of the anterior cingulate cortex (rACC) are brain regions that are important in the neural network involving emotional processing and decision making, as well as playing an important role in social behavior and interaction. Considering the schizophrenia dysconnectivity hypothesis, observed abnormalities in emotional response and social behavior in schizophrenia might be associated with connectivity abnormalities between mOFC and rACC. METHODS: Twenty-seven patients with chronic schizophrenia and 26 healthy controls were examined using diffusion tensor imaging (DTI). White matter properties in bilateral mOFC-rACC connections were examined using stochastic tractography, which has been shown to be among the most effective DTI methods for examining tracts between adjacent gray matter regions. RESULTS: Reductions in fractional anisotropy (FA) were observed in left anterior mOFC-rACC connections (p

Although diffusion tensor imaging (DTI) studies have reported fractional anisotropy (FA) abnormalities in multiple white matter (WM) regions in schizophrenia, relationship between abnormal FA and negative symptoms has not been fully explored. DTI data were acquired from twenty-four patients with chronic schizophrenia and twenty-five healthy controls. Regional brain abnormalities were evaluated by conducting FA comparisons in the cerebral and each lobar WMs between groups. Focal abnormalities were also evaluated with a voxel-wise tract specific method. Associations between structural WM changes and negative symptoms were assessed using the Scale for the Assessment of Negative Symptoms (SANS). The patient group showed decreased FA in the cerebrum, especially in the frontal lobe, compared with controls. A voxel-wise analysis showed FA decreases in almost all WM tracts in schizophrenia. Correlation analyses demonstrated negative relationships between FA in the cerebrum, particularly in the left hemisphere, and SANS global and global rating scores (Anhedonia-Asociality, Attention, and Affective-Flattening), and also associations between FA of left frontal lobe and SANS global score, Anhedonia-Asociality, and Attention. This study demonstrates that patients with chronic schizophrenia evince widespread cerebral FA abnormalities and that these abnormalities, especially in the left hemisphere, are associated with negative symptoms.

PURPOSE: To describe how B0 inhomogeneities can cause errors in proton resonance frequency (PRF) shift thermometry, and to correct for these errors. METHODS: With PRF thermometry, measured phase shifts are converted into temperature measurements through the use of a scaling factor proportional to the echo time, TE. However, B0 inhomogeneities can deform, spread, and translate MR echoes, potentially making the "true" echo time vary spatially within the imaged object and take on values that differ from the prescribed TE value. Acquisition and reconstruction methods able to avoid or correct for such errors are presented. RESULTS: Tests were performed in a gel phantom during sonication, and temperature measurements were made with proper shimming as well as with intentionally introduced B0 inhomogeneities. Errors caused by B0 inhomogeneities were observed, described, and corrected by the proposed methods. No statistical difference was found between the corrected results and the reference results obtained with proper shimming, while errors by more than 10% in temperature elevation were corrected for. The approach was also applied to an abdominal in vivo dataset. CONCLUSION: Field variations induce errors in measured field values, which can be detected and corrected. The approach was validated for a PRF thermometry application. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

OBJECT: Concussion is a common injury in ice hockey and a health problem for the general population. Traumatic axonal injury has been associated with concussions (also referred to as mild traumatic brain injuries), yet the pathological course that leads from injury to recovery or to long-term sequelae is still not known. This study investigated the longitudinal course of concussion by comparing diffusion MRI (dMRI) scans of the brains of ice hockey players before and after a concussion. METHODS: The 2011-2012 Hockey Concussion Education Project followed 45 university-level ice hockey players (both male and female) during a single Canadian Interuniversity Sports season. Of these, 38 players had usable dMRI scans obtained in the preseason. During the season, 11 players suffered a concussion, and 7 of these 11 players had usable dMRI scans that were taken within 72 hours of injury. To analyze the data, the authors performed free-water imaging, which reflects an increase in specificity over other dMRI analysis methods by identifying alterations that occur in the extracellular space compared with those that occur in proximity to cellular tissue in the white matter. They used an individualized approach to identify alterations that are spatially heterogeneous, as is expected in concussions. RESULTS: Paired comparison of the concussed players before and after injury revealed a statistically significant (p 0.05) common pattern of reduced free-water volume and reduced axial and radial diffusivities following elimination of free-water. These free-water-corrected measures are less affected by partial volumes containing extracellular water and are therefore more specific to processes that occur within the brain tissue. Fractional anisotropy was significantly increased, but this change was no longer significant following the free-water elimination. CONCLUSIONS: Concussion during ice hockey games results in microstructural alterations that are detectable using dMRI. The alterations that the authors found suggest decreased extracellular space and decreased diffusivities in white matter tissue. This finding might be explained by swelling and/or by increased cellularity of glia cells. Even though these findings in and of themselves cannot determine whether the observed microstructural alterations are related to long-term pathology or persistent symptoms, they are important nonetheless because they establish a clearer picture of how the brain responds to concussion.

OBJECT: The aim of this study was to examine the brain’s white matter microstructure by using MR diffusion tensor imaging (DTI) in ice hockey players with a history of clinically symptomatic concussion compared with players without a history of concussion. METHODS: Sixteen players with a history of concussion (concussed group; mean age 21.7 ± 1.5 years; 6 female) and 18 players without a history of concussion (nonconcussed group; mean age 21.3 ± 1.8 years, 10 female) underwent 3-T DTI at the end of the 2011-2012 Canadian Interuniversity Sports ice hockey season. Tract-based spatial statistics (TBSS) was used to test for group differences in fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and the measure "trace," or mean diffusivity. Cognitive evaluation was performed using the Immediate Postconcussion Assessment and Cognitive Test (ImPACT) and the Sport Concussion Assessment Tool-2 (SCAT2). RESULTS: TBSS revealed a significant increase in FA and AD, and a significant decrease in RD and trace in several brain regions in the concussed group, compared with the nonconcussed group (p 0.05). The regions with increased FA and decreased RD and trace included the right posterior limb of the internal capsule, the right corona radiata, and the right temporal lobe. Increased AD was observed in a small area in the left corona radiata. The DTI measures correlated with neither the ImPACT nor the SCAT2 scores. CONCLUSIONS: The results of the current study indicate that a history of concussion may result in alterations of the brain’s white matter microstructure in ice hockey players. Increased FA based on decreased RD may reflect neuroinflammatory or neuroplastic processes of the brain responding to brain trauma. Future studies are needed that include a longitudinal analysis of the brain’s structure and function following a concussion to elucidate further the complex time course of DTI changes and their clinical meaning.

Deficits in the execution of a sequence of movements are common in schizophrenia. Previous studies reported reduced functional activity in the motor cortex and cerebellum in schizophrenic patients with deficits in movement sequencing. The corticospinal tract (CST) and superior cerebellar peduncle (SCP) are fiber tracts that are involved in movement sequencing. However, the integrity of these tracts has not been evaluated in schizophrenic patients with respect to the performance of movement sequencing yet. Diffusion tensor magnetic resonance images (DT-MRI) were acquired from 24 patients with schizophrenia and 23 matched control subjects. Tractography was applied to reconstruct the CST and SCP and DT-MRI-specific parameters such as fractional anisotropy (FA) and radial diffusivity (RD) were reported. The patient group was further subdivided based on the score of sequencing of complex motor acts subscale of the Neurological Evaluation Scale into those with deficits in sequencing motor acts, the SQ(abn) group (n = 7), and those with normal performance, the SQ(norm) group (n = 17). Schizophrenia patients of the SQ(norm) subgroup had significantly reduced FA and increased RD values in the right CST in comparison to the control group; the SQ(abn) subgroup did not differ from the controls. However, the SQ(abn) subgroup showed impaired integrity of the left SCP, whereas the SQ(norm) subgroup did not. Abnormalities in the right CST in the SQ(norm) and in the left SCP in SQ(abn) groups suggest that the patients with SQ(abn) represent subgroups with distinct deficits. Moreover, these results demonstrate the involvement of the SCP in the pathogenesis of movement sequencing in schizophrenia.

Neuroimaging has played an important role in non-invasive diagnosis and differentiation of neurodegenerative disorders, such as Alzheimer’s disease and Mild Cognitive Impairment. Various features have been extracted from the neuroimaging data to characterize the disorders, and these features can be roughly divided into global and local features. Recent studies show a tendency of using local features in disease characterization, since they are capable of identifying the subtle disease-specific patterns associated with the effects of the disease on human brain. However, problems arise if the neuroimaging database involved multiple disorders or progressive disorders, as disorders of different types or at different progressive stages might exhibit different degenerative patterns. It is difficult for the researchers to reach consensus on what brain regions could effectively distinguish multiple disorders or multiple progression stages. In this study we proposed a Multi-Channel pattern analysis approach to identify the most discriminative local brain metabolism features for neurodegenerative disorder characterization. We compared our method to global methods and other pattern analysis methods based on clinical expertise or statistics tests. The preliminary results suggested that the proposed Multi-Channel pattern analysis method outperformed other approaches in Alzheimer’s disease characterization, and meanwhile provided important insights into the underlying pathology of Alzheimer’s disease and Mild Cognitive Impairment.

In a cohort of community-recruited elderly subjects with normal cognition at initial evaluation, we found that baseline fornix white matter (WM) microstructure was significantly correlated with early volumetric longitudinal tissue change across a region of interest (called fornix significant ROI, fSROI), which overlaps circuits known to be selectively vulnerable to Alzheimer’s dementia pathology. Other WM and gray matter regions had much weaker or non-existent associations with longitudinal tissue change. Tissue loss in fSROI was in turn a significant factor in a survival model of cognitive decline, as was baseline fornix microstructure. These findings suggest that WM deterioration in the fornix and tissue loss in fSROI may be the early beginnings of posterior limbic circuit and default mode network degeneration. We also found that gray matter baseline volumes in the entorhinal cortex and hippocampus predicted cognitive decline in survival models. But since GM regions did not also significantly predict brain-tissue loss, our results may imply a view in which early, prodromal deterioration appears as two quasi independent processes in white and gray matter regions of the limbic circuit crucial to memory.