Effect of Multishell Diffusion MRI Acquisition Strategy and Parcellation Scale on Rich-Club Organization of Human Brain Structural Networks
The majority of network studies of human brain structural connectivity are based on single-shell diffusion-weighted imaging (DWI) data. Recent advances in imaging hardware and software capabilities have made it possible to acquire multishell (b-values) high-quality data required for better character...
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MDPI AG
2021-05-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/11/6/970 |
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| author | Maedeh Khalilian Kamran Kazemi Mahshid Fouladivanda Malek Makki Mohammad Sadegh Helfroush Ardalan Aarabi |
| author_facet | Maedeh Khalilian Kamran Kazemi Mahshid Fouladivanda Malek Makki Mohammad Sadegh Helfroush Ardalan Aarabi |
| author_sort | Maedeh Khalilian |
| collection | DOAJ |
| description | The majority of network studies of human brain structural connectivity are based on single-shell diffusion-weighted imaging (DWI) data. Recent advances in imaging hardware and software capabilities have made it possible to acquire multishell (b-values) high-quality data required for better characterization of white-matter crossing-fiber microstructures. The purpose of this study was to investigate the extent to which brain structural organization and network topology are affected by the choice of diffusion magnetic resonance imaging (MRI) acquisition strategy and parcellation scale. We performed graph-theoretical network analysis using DWI data from 35 Human Connectome Project subjects. Our study compared four single-shell (b = 1000, 3000, 5000, 10,000 s/mm<sup>2</sup>) and multishell sampling schemes and six parcellation scales (68, 200, 400, 600, 800, 1000 nodes) using five graph metrics, including small-worldness, clustering coefficient, characteristic path length, modularity and global efficiency. Rich-club analysis was also performed to explore the rich-club organization of brain structural networks. Our results showed that the parcellation scale and imaging protocol have significant effects on the network attributes, with the parcellation scale having a substantially larger effect. Regardless of the parcellation scale, the brain structural networks exhibited a rich-club organization with similar cortical distributions across the parcellation scales involving at least 400 nodes. Compared to single b-value diffusion acquisitions, the deterministic tractography using multishell diffusion imaging data consisting of shells with b-values higher than 5000 s/mm<sup>2</sup> resulted in significantly improved fiber-tracking results at the locations where fiber bundles cross each other. Brain structural networks constructed using the multishell acquisition scheme including high b-values also exhibited significantly shorter characteristic path lengths, higher global efficiency and lower modularity. Our results showed that both parcellation scale and sampling protocol can significantly impact the rich-club organization of brain structural networks. Therefore, caution should be taken concerning the reproducibility of connectivity results with regard to the parcellation scale and sampling scheme. |
| first_indexed | 2024-03-10T10:58:12Z |
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| id | doaj.art-10dea99a7d94421f941d090e9f195120 |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-10T10:58:12Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-10dea99a7d94421f941d090e9f1951202023-11-21T21:42:34ZengMDPI AGDiagnostics2075-44182021-05-0111697010.3390/diagnostics11060970Effect of Multishell Diffusion MRI Acquisition Strategy and Parcellation Scale on Rich-Club Organization of Human Brain Structural NetworksMaedeh Khalilian0Kamran Kazemi1Mahshid Fouladivanda2Malek Makki3Mohammad Sadegh Helfroush4Ardalan Aarabi5Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 7155713876, IranDepartment of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 7155713876, IranDepartment of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 7155713876, IranLaboratory of Functional Neuroscience and Pathologies (LNFP), University Research Center (CURS), University Hospital, 80054 Amiens, FranceDepartment of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 7155713876, IranLaboratory of Functional Neuroscience and Pathologies (LNFP), University Research Center (CURS), University Hospital, 80054 Amiens, FranceThe majority of network studies of human brain structural connectivity are based on single-shell diffusion-weighted imaging (DWI) data. Recent advances in imaging hardware and software capabilities have made it possible to acquire multishell (b-values) high-quality data required for better characterization of white-matter crossing-fiber microstructures. The purpose of this study was to investigate the extent to which brain structural organization and network topology are affected by the choice of diffusion magnetic resonance imaging (MRI) acquisition strategy and parcellation scale. We performed graph-theoretical network analysis using DWI data from 35 Human Connectome Project subjects. Our study compared four single-shell (b = 1000, 3000, 5000, 10,000 s/mm<sup>2</sup>) and multishell sampling schemes and six parcellation scales (68, 200, 400, 600, 800, 1000 nodes) using five graph metrics, including small-worldness, clustering coefficient, characteristic path length, modularity and global efficiency. Rich-club analysis was also performed to explore the rich-club organization of brain structural networks. Our results showed that the parcellation scale and imaging protocol have significant effects on the network attributes, with the parcellation scale having a substantially larger effect. Regardless of the parcellation scale, the brain structural networks exhibited a rich-club organization with similar cortical distributions across the parcellation scales involving at least 400 nodes. Compared to single b-value diffusion acquisitions, the deterministic tractography using multishell diffusion imaging data consisting of shells with b-values higher than 5000 s/mm<sup>2</sup> resulted in significantly improved fiber-tracking results at the locations where fiber bundles cross each other. Brain structural networks constructed using the multishell acquisition scheme including high b-values also exhibited significantly shorter characteristic path lengths, higher global efficiency and lower modularity. Our results showed that both parcellation scale and sampling protocol can significantly impact the rich-club organization of brain structural networks. Therefore, caution should be taken concerning the reproducibility of connectivity results with regard to the parcellation scale and sampling scheme.https://www.mdpi.com/2075-4418/11/6/970structural connectivityrich-club organizationmultiscale parcellationmultishell samplingfiber trackingDWI |
| spellingShingle | Maedeh Khalilian Kamran Kazemi Mahshid Fouladivanda Malek Makki Mohammad Sadegh Helfroush Ardalan Aarabi Effect of Multishell Diffusion MRI Acquisition Strategy and Parcellation Scale on Rich-Club Organization of Human Brain Structural Networks Diagnostics structural connectivity rich-club organization multiscale parcellation multishell sampling fiber tracking DWI |
| title | Effect of Multishell Diffusion MRI Acquisition Strategy and Parcellation Scale on Rich-Club Organization of Human Brain Structural Networks |
| title_full | Effect of Multishell Diffusion MRI Acquisition Strategy and Parcellation Scale on Rich-Club Organization of Human Brain Structural Networks |
| title_fullStr | Effect of Multishell Diffusion MRI Acquisition Strategy and Parcellation Scale on Rich-Club Organization of Human Brain Structural Networks |
| title_full_unstemmed | Effect of Multishell Diffusion MRI Acquisition Strategy and Parcellation Scale on Rich-Club Organization of Human Brain Structural Networks |
| title_short | Effect of Multishell Diffusion MRI Acquisition Strategy and Parcellation Scale on Rich-Club Organization of Human Brain Structural Networks |
| title_sort | effect of multishell diffusion mri acquisition strategy and parcellation scale on rich club organization of human brain structural networks |
| topic | structural connectivity rich-club organization multiscale parcellation multishell sampling fiber tracking DWI |
| url | https://www.mdpi.com/2075-4418/11/6/970 |
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