Publications by authors named "Lukas A Grajauskas"

5 Publications

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White Matter Neuroplasticity: Motor Learning Activates the Internal Capsule and Reduces Hemodynamic Response Variability.

Front Hum Neurosci 2020 26;14:509258. Epub 2020 Oct 26.

Simon Fraser University ImageTech Lab, Health Science and Innovation, Surrey Memorial Hospital, Fraser Health, Surrey, BC, Canada.

Numerous studies have noted the importance of white matter changes in motor learning, but existing literature only focuses on structural and microstructural MRI changes, as there are limited tools available for investigations of white matter function. One method that has gained recent prominence is the application of blood oxygen level dependent (BOLD) fMRI to white matter, with high-field scanners now being able to better detect the smaller hemodynamic changes present in this tissue type compared to those in the gray matter. However, fMRI techniques have yet to be applied to investigations of neuroplastic change with motor learning in white matter. White matter function represents an unexplored component of neuroplasticity and is essential for gaining a complete understanding of learning-based changes occurring throughout the whole brain. Twelve healthy, right-handed participants completed fine motor and gross motor tasks with both hands, using an MRI compatible computer mouse. Using a crossover design along with a prior analysis approach to establish WM activation, participants received a baseline scan followed by 2 weeks of training, returning for a midpoint and endpoint scan. The motor tasks were designed to be selectively difficult for the left hand, leading to a training effect only in that condition. Analysis targeted the comparison and detection of training-associated right vs left hand changes. A statistically significant improvement in motor task score was only noted for the left-hand motor condition. A corresponding change in the temporal characteristics of the white matter hemodynamic response was shown within only the right corticospinal tract. The hemodynamic response exhibited a reduction in the dispersion characteristics after the training period. To our knowledge, this is the first report of MRI detectable functional neuroplasticity in white matter, suggesting that modifications in temporal characteristics of white matter hemodynamics may underlie functional neuroplasticity in this tissue.
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http://dx.doi.org/10.3389/fnhum.2020.509258DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7649291PMC
October 2020

White Matter fMRI Activation Cannot Be Treated as a Nuisance Regressor: Overcoming a Historical Blind Spot.

Front Neurosci 2019 4;13:1024. Epub 2019 Oct 4.

Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, BC, Canada.

Despite past controversies, increasing evidence has led to acceptance that white matter activity is detectable using functional magnetic resonance imaging (fMRI). In spite of this, advanced analytic methods continue to be published that reinforce a historic bias against white matter activation by using it as a nuisance regressor. It is important that contemporary analyses overcome this blind spot in whole brain functional imaging, both to ensure that newly developed noise regression techniques are accurate, and to ensure that white matter, a vital and understudied part of the brain, is not ignored in functional neuroimaging studies.
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http://dx.doi.org/10.3389/fnins.2019.01024DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6787144PMC
October 2019

MRI-based evaluation of structural degeneration in the ageing brain: Pathophysiology and assessment.

Ageing Res Rev 2019 01 22;49:67-82. Epub 2018 Nov 22.

ImageTech Laboratory, Health Sciences and Innovation, Surrey Memorial Hospital, Surrey, British Columbia, Canada; Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada; Health Sciences and Innovation, Surrey Memorial Hospital, Surrey, British Columbia, Canada. Electronic address:

Advances in MRI technology have significantly contributed to our ability to understand the process of brain ageing, allowing us to track and assess changes that occur during normal ageing and neurological conditions. This paper focuses on reviewing structural changes of the ageing brain that are commonly seen using MRI, summarizing the pathophysiology, prevalence, and neuroanatomical distribution of changes including atrophy, lacunes, white matter lesions, and dilated perivascular spaces. We also review the clinically accessible methodology for assessing these MRI-based changes, covering visual rating scales, as well computer-aided and fully automated methods. Subsequently, we consider novel assessment methods designed to evaluate changes across the whole brain, and finally discuss new directions in this field of research.
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http://dx.doi.org/10.1016/j.arr.2018.11.004DOI Listing
January 2019

Toward MRI-based whole-brain health assessment: The brain atrophy and lesion index (BALI).

Aging Med (Milton) 2018 Jun 26;1(1):55-63. Epub 2018 Apr 26.

Health Sciences and Innovation Fraser Health Authority Surrey BC Canada.

There have been many attempts to assess the elements of age- and dementia- related neurodegenerative changes in the brain using MRI; however, traditionally assessments focus only on single deficit. Over the past few years, our group has worked to create and validate the Brain Atrophy and Lesion Index (BALI) as an MRI-based whole-brain structural degeneration rating scale. The BALI can be used for applications in aging and dementia across the entire brain and can be applied to common clinical MR images. As a whole-brain structural health assessment, the BALI gives a more representative picture of how the brain ages. During the aging process, multiple elements of degeneration accumulate and interact to overwhelm repair processes and cause high-level failure in the function of the brain. To reflect this process, the BALI combines the assessment of several neurodegeneration changes into one scale. The BALI evaluation can be performed quickly and has been validated for use by non-neuroradiology expert raters trained with the method. This review gives a brief overview of the content of the BALI; covers the development, refinement, and application of the method; and provides insights about future development and clinical implementation of MRI-based whole-brain health assessment in aging and dementia.
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http://dx.doi.org/10.1002/agm2.12014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6880668PMC
June 2018

MRI assessment of whole-brain structural changes in aging.

Clin Interv Aging 2017 9;12:1251-1270. Epub 2017 Aug 9.

Health Sciences and Innovation, ImageTech Laboratory, Fraser Health Authority, Surrey, BC, Canada.

Purpose: One of the central features of brain aging is the accumulation of multiple age-related structural changes, which occur heterogeneously in individuals and can have immediate or potential clinical consequences. Each of these deficits can coexist and interact, producing both independent and additive impacts on brain health. Many of the changes can be visualized using MRI. To collectively assess whole-brain structural changes, the MRI-based Brain Atrophy and Lesion Index (BALI) has been developed. In this study, we validate this whole-brain health assessment approach using several clinical MRI examinations.

Materials And Methods: Data came from three independent studies: the Alzheimer's Disease Neuroimaging Initiative Phase II (n=950; women =47.9%; age =72.7±7.4 years); the National Alzheimer's Coordinating Center (n=722; women =55.1%; age =72.7±9.9 years); and the Tianjin Medical University General Hospital Research database on older adults (n=170; women =60.0%; age =62.9±9.3 years). The 3.0-Tesla MRI scans were evaluated using the BALI rating scheme on the basis of T1-weighted (T1WI), T2-weighted (T2WI), T2-weighted fluid-attenuated inversion recovery (T2-FLAIR), and T2*-weighted gradient-recalled echo (T2*GRE) images.

Results: Atrophy and lesion changes were commonly seen in each MRI test. The BALI scores based on different sequences were highly correlated (Spearman >0.69; <0.00001). They were associated with age (>0.29; <0.00001) and differed by cognitive status (>26.48, <0.00001). T2-FLAIR revealed a greater level of periventricular (=29.09) and deep white matter (=26.65, <0.001) lesions than others, but missed revealing certain dilated perivascular spaces that were seen in T2WI (<0.001). Microhemorrhages occurred in 15.3% of the sample examined and were detected using only T2*GRE.

Conclusion: The T1WI- and T2WI-based BALI evaluations consistently identified the burden of aging and dementia-related decline of structural brain health. Inclusion of additional MRI tests increased lesion differentiation. Further research is to integrate MRI tests for a clinical tool to aid the diagnosis and intervention of brain aging.
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http://dx.doi.org/10.2147/CIA.S139515DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5557118PMC
March 2018