COVID-19's Lasting Impact: Tissue Microstructural Impairment
Poster No:
176
Submission Type:
Abstract Submission
Authors:
Kiran Thapaliya1, Sonya Marshall-Gradisnik2, Maira Inderyas1, Leighton Barnden3
Institutions:
1NCNED, Griffith University, Southport, QLD, 2Griffith University, Gold coast, QLD, 3Griffith University, Southport, Queensland
First Author:
Co-Author(s):
Introduction:
Recently, SARS-CoV-2, the virus responsible for COVID-19, has infected over 760 million people worldwide, leading to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) syndrome 2. It has been shown that 10% of people infected with COVID-19 virus develop into long COVID 1. Studies have shown that individuals with long COVID report symptoms such as brain fog and memory problems, suggesting that brain dysfunction may be affected by the virus 3.
Therefore, the specific aim of this study was to investigate brain dysfunction in long COVID patients compared with healthy controls with no previous COVID-19 infection using a multi-modal MRI approach, including T1-weighted, T2-weighted and diffusion tensor imaging (DTI).
Therefore, the specific aim of this study was to investigate brain dysfunction in long COVID patients compared with healthy controls with no previous COVID-19 infection using a multi-modal MRI approach, including T1-weighted, T2-weighted and diffusion tensor imaging (DTI).
Methods:
The study was approved by the Griffith University Human Research Ethics Committee (ID: 2022/666). All the methods were carried out in accordance with the relevant guidelines and regulations adhering to the Helsinki Declaration. Written informed consent was obtained from all participants, and we recruited 19 long COVID participants and 16 healthy controls with no COVID-19 infection.
All the MRI data for the participants was acquired using a 3T Prisma MRI scanner (Siemens Healthcare, Erlangen, Germany) with a 64-channel receive head coil. T1-weighted data (T1w) was acquired using magnetization-prepared rapid acquisition gradient echo sequence (MPRAGE) with repetition time (TR)= 1900 ms, echo time (TE) = 2.32 ms, inversion times = 900 ms, flip angles (FA) = 9o, and spatial resolution = 0.9 mm3, with matrix size = 176 × 240 × 256. T2 weighted (T2w) data using TR=4100 ms, TE=408 ms, with variable flip angle, spatial resolution = 0.9 mm3, with matrix size= 176 × 256 × 256.
DTI data was acquired using 2-shell acquisition protocols: 30 directions at b =1000 s/mm2 and 66 directions at b=2500 s/mm2, along with nine b=0 scans. Other settings were repetition time/echo time = 4100/75 ms, field of view (FOV) = 244 × 244, matrix = 122 × 122, voxel dimension of 2.0 mm3 and 66 slices.
The T1w and T2w MRI data was pre-processed using a workflow described in 4 to generate whole brain T1w/T2w ratio maps. DTI data was processed using MRtrix3 (https://www.mrtrix.org/) and FSL similar to our previous findings5. DTI parameters fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), mean diffusivity (MD) were calculated using 'dtifit' available in FSL 6.
Voxel-based statistical analysis of the T1w/T2w ratio map, FA, AD, MD and RD of the two groups was performed with SPM12. For each, to test for group differences, a two-sample T test was performed controlling for age and gender. Voxel clusters in the T statistic map were defined using p-value of 0.001 and a cluster size of 60 voxels. Statistical inference was measured with the false discovery rate corrected cluster p value.
All the MRI data for the participants was acquired using a 3T Prisma MRI scanner (Siemens Healthcare, Erlangen, Germany) with a 64-channel receive head coil. T1-weighted data (T1w) was acquired using magnetization-prepared rapid acquisition gradient echo sequence (MPRAGE) with repetition time (TR)= 1900 ms, echo time (TE) = 2.32 ms, inversion times = 900 ms, flip angles (FA) = 9o, and spatial resolution = 0.9 mm3, with matrix size = 176 × 240 × 256. T2 weighted (T2w) data using TR=4100 ms, TE=408 ms, with variable flip angle, spatial resolution = 0.9 mm3, with matrix size= 176 × 256 × 256.
DTI data was acquired using 2-shell acquisition protocols: 30 directions at b =1000 s/mm2 and 66 directions at b=2500 s/mm2, along with nine b=0 scans. Other settings were repetition time/echo time = 4100/75 ms, field of view (FOV) = 244 × 244, matrix = 122 × 122, voxel dimension of 2.0 mm3 and 66 slices.
The T1w and T2w MRI data was pre-processed using a workflow described in 4 to generate whole brain T1w/T2w ratio maps. DTI data was processed using MRtrix3 (https://www.mrtrix.org/) and FSL similar to our previous findings5. DTI parameters fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), mean diffusivity (MD) were calculated using 'dtifit' available in FSL 6.
Voxel-based statistical analysis of the T1w/T2w ratio map, FA, AD, MD and RD of the two groups was performed with SPM12. For each, to test for group differences, a two-sample T test was performed controlling for age and gender. Voxel clusters in the T statistic map were defined using p-value of 0.001 and a cluster size of 60 voxels. Statistical inference was measured with the false discovery rate corrected cluster p value.
Results:
T1w/T2w: Long COVID vs HC
The voxel-based group comparison showed T1w/T2w signal ratio was significantly higher in precentral (pfdr<0.001) and middle temporal gyrus (pfdr=0.005) in long COVID condition compared to healthy controls (see Figure 1).
DTI: Long COVID vs HC
The mean diffusivity was significantly lower in the dentate regions (pfdr=0.041) in long COVID condition compared with healthy controls (see Figure 2).
The voxel-based group comparison showed T1w/T2w signal ratio was significantly higher in precentral (pfdr<0.001) and middle temporal gyrus (pfdr=0.005) in long COVID condition compared to healthy controls (see Figure 1).
DTI: Long COVID vs HC
The mean diffusivity was significantly lower in the dentate regions (pfdr=0.041) in long COVID condition compared with healthy controls (see Figure 2).
·Figure 1 T1w/T2w signal intensity is significantly higher in A) the precentral and B) the middle temporal gyrus) in long COVID condition compared with healthy controls with no previous COVID-19 infect
·Figure 2 Mean diffusivity (MD) was significantly lower in the dentate regions of long COVID condition compared with healthy controls.
Conclusions:
This study provides evidence that people with long COVID condition have impaired tissue microstructural alterations, highlighting the need for long-term neurological monitoring of people living with this condition.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Higher Cognitive Functions:
Higher Cognitive Functions Other 2
Keywords:
Cerebellum
Cognition
Neurological
Other - long COVID
1|2Indicates the priority used for review
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Provide references using APA citation style.
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WHO Coronavirus (COVID-19) Dashboard. (n.d.). Retrieved September 29, 2022, from https://covid19.who.int