Yu Zhao¹, Yurui Gao¹, Zhongliang Zu¹, Muwei Li¹, Kurt Schilling¹, Adam W. Anderson¹, Zhaohua Ding¹, and John C. Gore ^1
1Vanderbilt University Medical Center, Nashville, TN, United States

We propose a model-free method to detect BOLD signal changes in brain white matter (WM) without an assumption of a hemodynamic response function or a linear shift-invariant response as assumed in conventional general linear models. Instead, neural activations are measured by the synchrony of BOLD signals under constraints of the anisotropic architecture of WM fibers. A 60 subject sub-group sourced from the Human Connectome Project database was used to validate the proposed method at a group level. Our results demonstrate that the proposed method can probe neural activations in WM with high sensitivities and high specificities.

Yurui Gao¹, Yu Zhao², Kurt G Schilling², Muwei Li², Adam W Anderson¹, Zhaohua Ding¹, and John C Gore^2
1VANDERBILT UNIVERSITY, Nashville, TN, United States, ²Vanderbilt University Medical Center, Nashville, TN, United States

Correlations between BOLD signals from adjacent voxels in white matter (WM) are anisotropic and appear similar to metrics that describe functional connectivity in gray matter. We propose a method to measure the fiber-oriented correlation (FOC) between BOLD signals in WM. This method was implemented on both resting state and motor task fMRI data across 64 HCP subjects. The FOC map revealed WM areas apparently engaged in default mode network and visual function in both rest and task conditions. The motor task map also delineates the corticospinal tract. The proposed metric FOC may be valuable for investigating functional WM pathways.  

Leo R. Zekelman^1,2, Fan Zhang³, Nikos Makris^4,5, Jianzhong He³, Yuqian Chen^3,6, Tengfei Xue^3,6, Daniela Liera⁷, Daniel L. Drane^8,9,10, Yogesh Rathi^3,11, Alexandra J. Golby^1,3, and Lauren J. O'Donnell^3
1Department of Neurosurgery, Brigham and Women’s Hospital, Boston, MA, United States, ²Speech and Hearing Bioscience and Technology, Harvard Medical School, Boston, MA, United States, ³Department of Radiology, Brigham and Women’s Hospital, Boston, MA, United States, ⁴Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States, ⁵Department of Psychiatry and Neurology, A. Martinos Center for Biomedical Imaging, Boston, MA, United States, ⁶School of Computer Science, University of Sydney, Sydney, Australia, ⁷Harvard College, Cambridge, MA, United States, ⁸Department of Neurology, Emory University School of Medicine, Atlanta, GA, United States, ⁹Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, United States, ¹⁰Department of Neurology, University of Washington School of Medicine, Seattle, WA, United States, ¹¹Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, United States

Using dMRI and behavioral data from 809 participants in the Human Connectome Project, we examined how the microstructure of the white matter (WM) association tracts influences performance on assessments of semantic memory and emotion perception. WM tracts were extracted and measured using an automated WM tract atlas. We found the microstructure of left hemisphere tracts influenced semantic memory, while that of right hemisphere tracts influenced emotion perception performance. Furthermore, the microstructure of the left arcuate fasciculus influenced performance on both assessments. Our findings suggest WM tract microstructure relates to the opposing hemispheric dominance of language and theory of mind processing.

Pablo Antonio Stack-Sanchez¹, Alonso Ramirez-Manzanares¹, Arturo Gonzalez-Vega², Jose Luis Marroquin¹, and Luis Concha^3
1Computer Science, Centro de Investigación en Matemáticas A.C., Guanajuato, Mexico, ²Department of Chemical, Electronic and Biomedical Engineering, Division of Sciences and Engineering, University of Guanajuato, Guanajuato, Mexico, Leon, Mexico, ³Institute of Neurobiology, Universidad Nacional Autonoma de Mexico, Juriquilla, Mexico

The estimation of reliable parameters of multi-compartment models of water diffusivity is a challenging open problem, especially when low-SNR clinical-datasets are analyzed. The ill-posedness of the models requires fixing a subset of parameters in order to estimate the rest of them. We propose a simple and fast method where only averaged parameters are required (not voxelwise information is required). The method is based on the processing of powder-averaged data to estimate a robust value for the axon-bundle parallel-diffusivity. We test the robustness of the method on synthetic experiments and show the results on in-vivo human and ex-vivo rodent datasets.

Sabha Ahmed¹, Jitender Saini¹, Nupur Pruthi², Alok Mohan Uppar², Rashmi Rao³, Kumar Madan³, Narayan Krishna Rolla³, and Indrajit Saha^3
1Neuroimaging and interventional radiology, NIMHANS, Bangalore, India, ²Neurosurgery, NIMHANS, Bangalore, India, ³Philips India Ltd, Bangalore, India

Imaging analysis of craniovertebral junction anomalies comprises of bony, ligament, vascular and spinal cord evaluation. MDCT falls short in the evaluation of the latter while conventional MRI does not offer optimal bone resolution. Novel Compressed SENSE accelerated Fast field echo resembling a CT using restricted echo-spacing (CS-FRACTURE) technique is a bid to overcome this shortcoming in routine clinical setup and we aim to explore the same.

Stefan E. Poirier^1,2, Neville Suskin³, Keith S. St. Lawrence^1,2, Christopher McIntyre^1,2,4, Jonathan D. Thiessen^1,2, J. Kevin Shoemaker⁵, and Udunna C. Anazodo^1,2
1Lawson Imaging, Lawson Health Research Institute, London, ON, Canada, ²Medical Biophysics, Western University, London, ON, Canada, ³Cardiology, Western University, London, ON, Canada, ⁴Lilibeth Caberto Kidney Clinical Research Unit, London Health Sciences Centre, London, ON, Canada, ⁵School of Kinesiology, Western University, London, ON, Canada

White matter (WM) breakdown is linked to cognitive impairment in coronary artery disease (CAD). We used diffusion MRI tractometry to assess the effects of cardiac disease, brain aging, and cardiac rehabilitation (CR) on regional WM macrostructure in brains of CAD patients. WM disruptions were found in CAD patients at baseline (pre-CR) compared to controls and in old controls compared to young controls. WM improvements, especially in regions linked to cognition, were observed in CAD patients following CR. Both cardiac disease and brain aging may contribute to WM dysfunction in CAD, and these WM disruptions may be favourably modified by CR.

Daniel Vallejo-Aldana¹, Arturo Gonzalez-Vega², Victor H Hernandez², Valeria Piazza³, Milvia Alata³, Jonathan Rafael-Patiño^4,5, Thomas Yu^4,6, Luis Concha⁷, and Alonso Ramirez-Manzanares^8
1Mathematics Department, Universidad de Guanajuato, Guanajuato, Mexico, ²Department of Chemical, Electronic and Biomedical Engineering, Division of Sciences and Engineering, University of Guanajuato, Leon, Mexico, ³Center of Research in Optics, Leon, Mexico, ⁴Signal Processing Lab 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, ⁵Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland, ⁶Medical Image Analysis Laboratory, Center for Biomedical Imaging (CIBM), University of Lausanne, Lausanne, Switzerland, ⁷Institute of Neurobiology, Universidad Nacional Autonoma de Mexico, Juriquilla, Mexico, ⁸Computer Science, Centro de Investigación en Matemáticas A.C., Guanajuato, Mexico

The estimation of intravoxel distributions of T2 values based on multi-echo MR data is a challenging task. Interestingly, the information above is quite useful to detect damage on brain tissue,  e.g. to estimate myelin-water-fraction changes associated with demyelination processes. Currently available methods typically require a long train of echoes, which are not always feasible to acquire. In this work we tackle this problem using state-of-the-art supervised learning convolutional networks to build a robust prediction model on very limited data ( 5 echoes and 4 TR). The methodology identifies myelin abnormalities in a rodent model of a neurological disorder with demyelination.

Natalie E. Phelan¹, Rajikha Raja², Aline Andres^3,4, and Xiawei Ou^2,3,4,5
1College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, United States, ²Department of Radiology, University of Arkansas for Medical Sciences, Little Rock, AR, United States, ³Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR, United States, ⁴Arkansas Children's Nutrition Center, Little Rock, AR, United States, ⁵Arkansas Children's Research Institute, Little Rock, AR, United States

This study examined potential relationships between maternal folate intake during pregnancy and neonatal brain white matter development. Healthy pregnant women were recruited at early pregnancy and their newborns underwent a brain MRI examination at ~2 weeks of age, including diffusion tensor imaging to assess white matter development. We found that folate intake during the second trimester of pregnancy positively correlated with fractional anisotropy (FA) values in brain white matter regions including the genu of corpus callosum and the external capsule. Our findings suggest positive impact of maternal folate intake during pregnancy on offspring brain white matter development.

Sarah Reeve^1,2, Mark Parker^2,3, James Rioux^1,2,4, Elena Adela Cora^4,5, Chris Bowen^1,2,4, Steven Beyea^1,2,4,6, and David Volders^4,5
1Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada, ²Biomedical Translational Imaging Centre, QEII Health Sciences Centre, Halifax, NS, Canada, ³Medicine, Dalhousie University, Halifax, NS, Canada, ⁴Diagnostic Radiology, Dalhousie University, Halifax, NS, Canada, ⁵Diagnostic Imaging, Nova Scotia Health, Halifax, NS, Canada, ⁶School of Biomedical Engineering, Dalhousie University, Halifax, NS, Canada

MRI of the paranasal sinuses with bSSFP sequences is not typically performed due to prohibitive exam times and the prevalence of artifacts caused by off-resonance effects. We have shown that bSSFP images acquired in under 2 minutes using high-performance gradients at low field resist banding artifacts and demonstrate SNR and resolution sufficient to delineate relevant structures. This is supported by high SNR values in tissues and fluid-filled spaces, and low SNR in the air-filled maxillary sinus. 2-minute scan times compete with CT for clinical work flow and demonstrate the potential of MRI for high throughput sinus pathology evaluation.

Yongsheng Chen¹, Alexandar Bezanovski¹, Sadaf Saba¹, Vince Marceau¹, Yang Xuan², Mariam Tariq¹, Xue Yang¹, and Jun Li^1
1Neurology, Wayne State University School of Medicine, Detroit, MI, United States, ²Radiology, Wayne State University School of Medicine, Detroit, MI, United States

Human sciatic nerve morphometrics were measured for nerve volume, fascicle volume, and fascicle density using a 3D gradient echo sequence with an in-plane resolution of 0.15 x 0.15 mm². Metrics from healthy controls showed a moderate correlation of nerve and fascicle volumes with body mass index but not with age. There was a strong correlation between nerve volume and the clinical score of disease severity in patients with hereditary neuropathy with liability to pressure palsies.

Yongsheng Chen¹, Yimin Shen², Daniel Moiseev¹, Zafar Wazir¹, Bo Hu¹, and Jun Li^1
1Neurology, Wayne State University School of Medicine, Detroit, MI, United States, ²Radiology, Wayne State University School of Medicine, Detroit, MI, United States

Quantitative MRI (qMRI) methods were developed to measure T1, T2, proton density, and MTR of mouse sciatic nerve in-vivo. Pmp22+/- mouse, an animal model of hereditary neuropathy with liability to pressure palsies (HNPP), was imaged at 3- and 6-month of age. The imaging demonstrated an increase of MTR, and a decrease of proton density and T1 in the Pmp22+/- nerves, compared with those in wild-type nerves. These qMRI changes correlate with the growth of HNPP pathology – tomacula formed by excessive myelin folding over time. Ongoing experiment is to determine the pathological and molecular substrates responsible for the qMRI findings.

Brian Ma¹, Lara Bartels^1,2, Christian Kames^1,2, Yuting Zhang³, Alexander Weber^1,4, and Alexander Rauscher^1,2,4,5
1UBC MRI Research Centre, University of British Columbia, Vancouver, BC, Canada, ²Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada, ³Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing, China, ⁴Division of Neurology, Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada, ⁵Department of Radiology, University of British Columbia, Vancouver, BC, Canada

We performed quantitative susceptibility mapping (QSM) of the posterior limb of internal capsule (PLIC) in human neonates. As the PLIC is one of the earliest structures to myelinate, it is clearly visible as a hypointense structure on QSM.  This work investigates the potential as a marker for brain health in neonates. There were no significant differences in magnetic susceptibility of the PLIC between healthy controls, injured preterm, and injured term neonates.

Chenyang Li¹, Henry Rusinek¹, Jingyun Chen^1,2, Louisa Bokacheva², Alok Vedvyas², Arjun Masurkar², Thomas Wisniewski², E.Mark Haacke³, and Yulin Ge^1
1Department of Radiology, NYU Grossman School of Medicine, New York, NY, United States, ²Department of Neurology, NYU Grossman School of Medicine, New York, NY, United States, ³Department of Radiology, Wayne State University School of Medicine, Detroit, MI, United States

High resolution SWI images provide unique contrast to small venous vasculature. The conspicuity of small veins on SWI venography, such as deep medullary vein in white matter (WM), is susceptible to venous blood oxygenation level changes. This study demonstrates a significant association between WM venous density and neurodegenerative feature characterized by brain atrophy in the elderly, but no significant association of WM venous density to white matter hyperintensities (WMHs) load. Further clinical correlative analysis revealed a significant correlation of WM venous density to semantic fluency and different stages of cognitive status.