Shannon Kolind

 
Prospective Graduate Students / Postdocs

This faculty member is currently not actively recruiting graduate students or Postdoctoral Fellows, but might consider co-supervision together with another faculty member.

Associate Professor

Research Interests

brain
Imaging
MRI
medical physics
multiple sclerosis
myelin
Neurological Disease
spinal cord

Relevant Degree Programs

Affiliations to Research Centres, Institutes & Clusters

 
 

Research Methodology

MRI

Great Supervisor Week Mentions

Each year graduate students are encouraged to give kudos to their supervisors through social media and our website as part of #GreatSupervisorWeek. Below are students who mentioned this supervisor since the initiative was started in 2017.

 

Shannon is a great supervisor because of her perceptive ability to identify the unique needs of different students. By recognizing different styles, interests, abilities, and backgrounds, Shannon creates an environment tailored to each individual, where they can flourish.

Adam Dvorak (2019)

 

I offer my heartfelt thanks to Drs. Shannon Kolind and Anthony Traboulsee, who have taught me more than I could ever have learned in a classroom. They have provided me with unconditional support and care, and encouraged critical thinking and professional growth. Even with their busy schedules, they regularly met with me to ensure that I was meeting my goals and had all necessary resources. I am very grateful for their mentorship, trust and guidance! #GreatSupervisor week at #UBC.

Lisa Eunyoung Lee (2018)

 

Graduate Student Supervision

Doctoral Student Supervision

Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.

Investigating cognitive impairment in multiple sclerosis using myelin water imaging (2021)

Cognitive impairment is a common symptom in multiple sclerosis (MS) that presents in up to 70% of patients. Cognitive symptoms in MS typically manifest as deficits in attention, memory and/or processing speed, with processing speed being most frequently affected. MS-related cognitive impairment represents a major burden as it can significantly lower quality of life and is a main contributor to unemployment.Conventional magnetic resonance imaging (MRI) with T1-weighted and T2-weighted contrast is the mainstay of MS diagnosis and monitoring. However, conventional MRI is limited in that it is qualitative, lacks biological specificity and correlates poorly with clinical and cognitive status. In contrast, myelin water imaging (MWI) is an advanced MRI technique that measures the signal from water in the myelin bilayers, providing a quantitative myelin-specific measurement (myelin water fraction, MWF). The aim of this thesis is to investigate the relationship between myelin damage and cognitive performance in MS using MWI.First, we demonstrate that MWF in normal appearing white matter (NAWM) was significantly associated with processing speed performance in MS in 3 a priori selected white matter tracts associated with cognition. Next, we show that the relationship between NAWM MWF and cognitive performance extends to additional cognitive domains in a larger cohort. Finally, rather than selecting brain regions a priori, we employed an assumption-free data driven approach using permutation testing to show that myelin damage extent and anatomical location is unique to the cognitive domain being investigated, with greater myelin damage in these regions in cognitively impaired versus cognitively preserved patients. Further, we demonstrate that the severity and spatial extent of myelin damage in cognitive domain-specific white matter regions is strongly associated with cognitive performance.This thesis demonstrates that there is a strong relationship between the location and severity of myelin damage and MS-related cognitive impairment. As the treatment landscape for MS moves toward the development of remyelination therapies, understanding the role of myelin pathology in cognitive symptoms is critical for translating findings to clinical trials. These results also highlight the promise of MWI for monitoring myelin changes and their relationship to cognitive worsening and improvement when investigating new therapies.

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Master's Student Supervision

Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.

Investigating how demyelination is reflected using advanced magnetic resonance imaging in Susac syndrome and multiple sclerosis (2021)

Conventional magnetic resonance imaging (MRI) is a useful qualitative clinical tool for diagnosing and monitoring neurodegenerative diseases. However, it is not capable of measuring diffuse and microstructural changes in normal-appearing white matter (NAWM). Advanced MRI can quantitatively describe the microenvironment in NAWM. Myelin water imaging (MWI) is a technique that uses multi-component T2 relaxation to quantify the amount of myelin present within a region of interest. The resulting measurement is termed the myelin water fraction (MWF) and has been shown to correlate with histological myelin measurements. The standard deviation of the MWF is thought to represent the heterogeneity of myelin within a region of interest. By dividing the standard deviation of the MWF by the mean MWF, the coefficient of variation is calculated. Known as the myelin heterogeneity index (MHI), this is thought to be the most sensitive measure derived from MWI since it captures both myelin damage and variability. Diffusion basis spectrum imaging (DBSI) is another quantitative MRI technique that detects the diffusion of water. DBSI separates the isotropic and anisotropic diffusion components within each voxel and uses the degree and direction of water molecule movements to describe the microstructure. Importantly to this study, the measure radial diffusivity is thought to negatively correlate with myelin content. I apply MWI and DBSI to Susac syndrome (SuS), a rare demyelinating disease often mistaken for the more common demyelinating disease multiple sclerosis (MS), and find that both advanced MRI techniques describe diffuse myelin damage seen in SuS, but not in MS or healthy controls. This suggests a newly identified pathology of SuS. I next focused on characterizing the 3 aforementioned MWI metrics (mean, standard deviation or MHI) in MS. The measures differentiated MS from healthy controls and correlated with disability due to MS. Different stages of the disease were better characterized by different metrics, depending on the amount, uniformity, and extent of myelin damage. Lastly, MWI discerned longitudinal changes in MS over 2 years. This thesis shows that advanced MRI techniques are able to measure microstructural damage not detectable by clinical MRI and furthers the understanding of pathologies of two demyelinating diseases.

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Application of myelin water imaging to detect diffuse white matter damage in multiple sclerosis (2019)

While conventional magnetic resonance imaging (MRI) is qualitatively useful for the diagnosis and clinical management of multiple sclerosis (MS), it has limitations in terms of detecting specific myelin loss and diffuse damage in the normal-appearing white matter. A non-conventional MRI technique, called myelin water imaging (MWI) can be achieved using multicomponent T₂ relaxation to provide a quantitative in vivo measurement of myelin, termed myelin water fraction (MWF). MWF has been proposed as a candidate MR marker of myelin content in the central nervous system. In this study, I present the application of MWI to gain a deeper insight into the diffuse white matter damage in MS. First, we found lower myelin content and higher myelin heterogeneity in brain and cervical spinal cord, as well as correlations between myelin heterogeneity and clinical disability in cervical spinal cord in progressive MS compared to healthy controls. We also found myelin abnormalities in the regional and global white matter in progressive solitary sclerosis, which has recently been proposed as a potential variant of MS. Finally, we demonstrated good global white matter MWF reproducibility (coefficient of variation = 2.77 %; Pearson’s r = 0.91, p
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Current Students & Alumni

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