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Identification of Laminar Composition in Cerebral Cortex Using Low-Resolution Magnetic Resonance Images and Trust Region Optimization Algorithm

J. Jamárik, L. Vojtíšek, V. Churová, T. Kašpárek, D. Schwarz

. 2021 ; 12 (1) : . [pub] 20211223

Jazyk angličtina Země Švýcarsko

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/bmc22010402

Grantová podpora
17-33136A Ministry of Health Czech Republic

Pathological changes in the cortical lamina can cause several mental disorders Visualization of these changes in vivo would enhance their diagnostics Recently a framework for visualizing cortical structures by magnetic resonance imaging MRI has emerged This is based on mathematical modeling of multi component T1 relaxation at the sub voxel level This work proposes a new approach for thei

Citace poskytuje Crossref.org

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$a Jamárik, Jakub $u Department of Psychiatry, Faculty of Medicine, Masaryk University, 625 00 Brno, Czech Republic $1 https://orcid.org/0000000288622001
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$a Identification of Laminar Composition in Cerebral Cortex Using Low-Resolution Magnetic Resonance Images and Trust Region Optimization Algorithm / $c J. Jamárik, L. Vojtíšek, V. Churová, T. Kašpárek, D. Schwarz
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$a Pathological changes in the cortical lamina can cause several mental disorders. Visualization of these changes in vivo would enhance their diagnostics. Recently a framework for visualizing cortical structures by magnetic resonance imaging (MRI) has emerged. This is based on mathematical modeling of multi-component T1 relaxation at the sub-voxel level. This work proposes a new approach fo $a Pathological changes in the cortical lamina can cause several mental disorders. Visualization of these changes in vivo would enhance their diagnostics. Recently a framework for visualizing cortical structures by magnetic resonance imaging (MRI) has emerged. This is based on mathematical modeling of multi-component T1 relaxation at the sub-voxel level. This work proposes a new approach for their estimation. The approach is validated using simulated data. Sixteen MRI experiments were carried out on healthy volunteers. A modified echo-planar imaging (EPI) sequence was used to acquire 105 individual volumes. Data simulating the images were created, serving as the ground truth. The model was fitted to the data using a modified Trust Region algorithm. In single voxel experiments, the estimation accuracy of the T1 relaxation times depended on the number of optimization starting points and the level of noise. A single starting point resulted in a mean percentage error (MPE) of 6.1%, while 100 starting points resulted in a perfect fit. The MPE was <5% for the signal-to-noise ratio (SNR) ≥ 38 dB. Concerning multiple voxel experiments, the MPE was <5% for all components. Estimation of T1 relaxation times can be achieved using the modified algorithm with MPE < 5%. $a Pathological changes in the cortical lamina can cause several mental disorders Visualization of these changes in vivo would enhance their diagnostics Recently a framework for visualizing cortical structures by magnetic resonance imaging MRI has emerged This is based on mathematical modeling of multi component T1 relaxation at the sub voxel level This work proposes a new approach for thei
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$a Churová, Vendula $u Department of Simulation Medicine, Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, 625 00 Brno, Czech Republic $1 https://orcid.org/0000000291021872
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$a Schwarz, Daniel $u Department of Simulation Medicine, Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, 625 00 Brno, Czech Republic $1 https://orcid.org/0000000272610022 $7 ola2002146812
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