Publications by Year: 2017

Diffusion tensor imaging (DTI) studies in chronic schizophrenia have found widespread but often inconsistent patterns of white matter abnormalities. These studies have typically used the conventional measure of fractional anisotropy, which can be contaminated by extracellular free-water. A recent free-water imaging study reported reduced free-water corrected fractional anisotropy (FA) in chronic schizophrenia across several brain regions, but limited changes in the extracellular volume. The present study set out to validate these findings in a substantially larger sample. Tract-based spatial statistics (TBSS) was performed in 188 healthy controls and 281 chronic schizophrenia patients. Forty-two regions of interest (ROIs), as well as average whole-brain FAand FW were extracted from free-water corrected diffusion tensor maps. Compared to healthy controls, reduced FAwas found in the chronic schizophrenia group in the anterior limb of the internal capsule bilaterally, the posterior thalamic radiation bilaterally, as well as the genu and body of the corpus callosum. While a significant main effect of group was observed for FW, none of the follow-up contrasts survived correction for multiple comparisons. The observed FAreductions in the absence of extracellular FW changes, in a large, multi-site sample of chronic schizophrenia patients, validate the pattern of findings reported by a previous, smaller free-water imaging study of a similar sample. The limited number of regions in which FAwas reduced in the schizophrenia group suggests that actual white matter tissue degeneration in chronic schizophrenia, independent of extracellular FW, might be more localized than suggested previously.

PURPOSE: Accurate segmentation of lung nodules is crucial in the development of imaging biomarkers for predicting malignancy of the nodules. Manual segmentation is time consuming and affected by inter-observer variability. We evaluated the robustness and accuracy of a publically available semiautomatic segmentation algorithm that is implemented in the 3D Slicer Chest Imaging Platform (CIP) and compared it with the performance of manual segmentation. METHODS: CT images of 354 manually segmented nodules were downloaded from the LIDC database. Four radiologists performed the manual segmentation and assessed various nodule characteristics. The semiautomatic CIP segmentation was initialized using the centroid of the manual segmentations, thereby generating four contours for each nodule. The robustness of both segmentation methods was assessed using the region of uncertainty (δ) and Dice similarity index (DSI). The robustness of the segmentation methods was compared using the Wilcoxon-signed rank test (pWilcoxon

We propose a method for the automated identification of key white matter fiber tracts for neurosurgical planning, and we apply the method in a retrospective study of 18 consecutive neurosurgical patients with brain tumors. Our method is designed to be relatively robust to challenges in neurosurgical tractography, which include peritumoral edema, displacement, and mass effect caused by mass lesions. The proposed method has two parts. First, we learn a data-driven white matter parcellation or fiber cluster atlas using groupwise registration and spectral clustering of multi-fiber tractography from healthy controls. Key fiber tract clusters are identified in the atlas. Next, patient-specific fiber tracts are automatically identified using tractography-based registration to the atlas and spectral embedding of patient tractography. Results indicate good generalization of the data-driven atlas to patients: 80% of the 800 fiber clusters were identified in all 18 patients, and 94% of the 800 fiber clusters were found in 16 or more of the 18 patients. Automated subject-specific tract identification was evaluated by quantitative comparison to subject-specific motor and language functional MRI, focusing on the arcuate fasciculus (language) and corticospinal tracts (motor), which were identified in all patients. Results indicate good colocalization: 89 of 95, or 94%, of patient-specific language and motor activations were intersected by the corresponding identified tract. All patient-specific activations were within 3mm of the corresponding language or motor tract. Overall, our results indicate the potential of an automated method for identifying fiber tracts of interest for neurosurgical planning, even in patients with mass lesions.

PURPOSE: This study was a systematic evaluation across different and prominent diffusion MRI models to better understand the ways in which scalar metrics are influenced by experimental factors, including experimental design (diffusion-weighted imaging [DWI] sampling) and noise. METHODS: Four diffusion MRI models-diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator MRI (MAP-MRI), and neurite orientation dispersion and density imaging (NODDI)-were evaluated by comparing maps and histogram values of the scalar metrics generated using DWI datasets obtained in fixed mouse brain with different noise levels and DWI sampling complexity. Additionally, models were fit with different input parameters or constraints to examine the consequences of model fitting procedures. RESULTS: Experimental factors affected all models and metrics to varying degrees. Model complexity influenced sensitivity to DWI sampling and noise, especially for metrics reporting non-Gaussian information. DKI metrics were highly susceptible to noise and experimental design. The influence of fixed parameter selection for the NODDI model was found to be considerable, as was the impact of initial tensor fitting in the MAP-MRI model. CONCLUSION: Across DTI, DKI, MAP-MRI, and NODDI, a wide range of dependence on experimental factors was observed that elucidate principles and practical implications for advanced diffusion MRI.

Diffusion MRI (dMRI) is the only noninvasive method for mapping white matter connections in the brain. We describe SlicerDMRI, a software suite that enables visualization and analysis of dMRI for neuroscientific studies and patient-specific anatomic assessment. SlicerDMRI has been successfully applied in multiple studies of the human brain in health and disease, and here, we especially focus on its cancer research applications. As an extension module of the 3D Slicer medical image computing platform, the SlicerDMRI suite enables dMRI analysis in a clinically relevant multimodal imaging workflow. Core SlicerDMRI functionality includes diffusion tensor estimation, white matter tractography with single and multi-fiber models, and dMRI quantification. SlicerDMRI supports clinical DICOM and research file formats, is open-source and cross-platform, and can be installed as an extension to 3D Slicer (www.slicer.org). More information, videos, tutorials, and sample data are available at dmri.slicer.org.

Migraine is a common neurological disease with a high prevalence and unsatisfactory treatment options. The specific pathophysiological mechanisms of migraine remain unclear, which restricts the development of effective treatments for this prevalent disorder. The aims of this study were to 1) compare the spontaneous brain activity differences between Migraine without Aura (MwoA) patients and healthy controls (HCs), using amplitude of low-frequency fluctuations (ALFF) calculation method, and 2) explore how an effective treatment (verum acupuncture) could modulate the ALFF of MwoA patients. One hundred MwoA patients and forty-six matched HCs were recruited. Patients were randomized to four weeks’ verum acupuncture, sham acupuncture, and waiting list groups. Patients had resting state BOLD-fMRI scan before and after treatment, while HCs only had resting state BOLD-fMRI scan at baseline. Headache intensity, headache frequency, self-rating anxiety and self-rating depression were used for clinical efficacy evaluation. Compared with HCs, MwoA patients showed increased ALFF in posterior insula and putamen/caudate, and reduced ALFF in rostral ventromedial medulla (RVM)/trigeminocervical complex (TCC). After longitudinal verum acupuncture treatment, the decreased ALFF of the RVM/TCC was normalized in migraine patients. Verum acupuncture and sham acupuncture have different modulation effects on ALFF of RVM/TCC in migraine patients. Our results suggest that impairment of the homeostasis of the trigeminovascular nociceptive pathway is involved in the neural pathophysiology of migraines. Effective treatments, such as verum acupuncture, could help to restore this imbalance.

Objective: Repetitive subconcussive head impacts (RSHI) may lead to structural, functional, and metabolic alterations of the brain. While differences between males and females have already been suggested following a concussion, whether there are sex differences following exposure to RSHI remains unknown. The aim of this study was to identify and to characterize sex differences following exposure to RSHI. Methods: Twenty-five collegiate ice hockey players (14 males and 11 females, 20.6 ± 2.0 years), all part of the Hockey Concussion Education Project (HCEP), underwent diffusion-weighted magnetic resonance imaging (dMRI) before and after the Canadian Interuniversity Sports (CIS) ice hockey season 2011-2012 and did not experience a concussion during the season. Whole-brain tract-based spatial statistics (TBSS) were used to compare pre- and postseason imaging in both sexes for fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). Pre- and postseason neurocognitive performance were assessed by the Immediate Post-Concussion Assessment and Cognitive Test (ImPACT). Results: Significant differences between the sexes were primarily located within the superior longitudinal fasciculus (SLF), the internal capsule (IC), and the corona radiata (CR) of the right hemisphere (RH). In significant voxel clusters (p < 0.05), decreases in FA (absolute difference pre- vs. postseason: 0.0268) and increases in MD (0.0002), AD (0.00008), and RD (0.00005) were observed in females whereas males showed no significant changes. There was no significant correlation between the change in diffusion scalar measures over the course of the season and neurocognitive performance as evidenced from postseason ImPACT scores. Conclusions: The results of this study suggest sex differences in structural alterations following exposure to RSHI. Future studies need to investigate further the underlying mechanisms and association with exposure and clinical outcomes.

Hydration is a key aspect of the skin that influences its physical and mechanical properties. Here, we investigate the interplay between molecular and macroscopic properties of the outer skin layer - the stratum corneum (SC) and how this varies with hydration. It is shown that hydration leads to changes in the molecular arrangement of the peptides in the keratin filaments as well as dynamics of C-H bond reorientation of amino acids in the protruding terminals of keratin protein within the SC. The changes in molecular structure and dynamics occur at a threshold hydration corresponding to ca. 85% relative humidity (RH). The abrupt changes in SC molecular properties coincide with changes in SC macroscopic swelling properties as well as mechanical properties in the SC. The flexible terminals at the solid keratin filaments can be compared to flexible polymer brushes in colloidal systems, creating long-range repulsion and extensive swelling in water. We further show that the addition of urea to the SC at reduced RH leads to similar molecular and macroscopic responses as the increase in RH for SC without urea. The findings provide new molecular insights to deepen the understanding of how intermediate filament organization responds to changes in the surrounding environment.

Low fat-free mass index (FFMI) is an independent risk factor for mortality in chronic obstructive pulmonary disease (COPD) not typically measured during routine care. In the present study, we aimed to derive fat-free mass from the pectoralis muscle area (FFM) and assess whether low FFMIis associated with all-cause mortality in COPD cases. We used data from two independent COPD cohorts, ECLIPSE and COPDGene.Two equal sized groups of COPD cases (n=759) from the ECLIPSE study were used to derive and validate an equation to calculate the FFMmeasured using bioelectrical impedance from PMA. We then applied the equation in COPD cases (n=3121) from the COPDGene cohort, and assessed survival. Low FFMIwas defined, using the Schols classification (FFMI