The Severity of Sensorimotor Tracts Degeneration May Predict Motor Performance in Chronic Stroke Patients, While Brain Structural Network Dysfunction May Not
Although the relationship between corticospinal tract (CST) fiber degeneration and motor outcome after stroke has been established, the relationship of sensorimotor cortical areas with CST fibers has not been clarified. Also limited research has been conducted on how abnormalities in brain structura...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-03-01
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| Series: | Frontiers in Neurology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fneur.2022.813763/full |
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| author | Loukas G. Astrakas Shasha Li Shasha Li Sabrina Elbach Sabrina Elbach A. Aria Tzika A. Aria Tzika |
| author_facet | Loukas G. Astrakas Shasha Li Shasha Li Sabrina Elbach Sabrina Elbach A. Aria Tzika A. Aria Tzika |
| author_sort | Loukas G. Astrakas |
| collection | DOAJ |
| description | Although the relationship between corticospinal tract (CST) fiber degeneration and motor outcome after stroke has been established, the relationship of sensorimotor cortical areas with CST fibers has not been clarified. Also limited research has been conducted on how abnormalities in brain structural networks are related to motor recovery. To address these gaps in knowledge, we conducted a diffusion tensor imaging (DTI) study with 12 chronic stroke patients (CSPs) and 12 age-matched healthy controls (HCs). We compared fractional anisotropy (FA) and mean diffusivity (MD) in 60 CST segments using the probabilistic sensorimotor area tract template (SMATT). Least Absolute Shrinkage and Selection Operator (LASSO) regressions were used to select independent predictors of Fugl-Meyer upper extremity (FM-UE) scores among FA and MD values of SMATT regions. The Graph Theoretical Network Analysis Toolbox was used to assess the structural network of each subject's brain. Global and nodal metrics were calculated, compared between the groups, and correlated with FM-UE scores. Mann–Whitney U-tests revealed reduced FA values in CSPs, compared to HCs, in many ipsilesional SMATT regions and in two contralesional regions. Mean FA value of the left (L.) primary motor cortex (M1)/supplementary motor area (SMA) region was predictive of FM-UE score (P = 0.004). Mean MD values for the L. M1/ventral premotor cortex (PMv) region (P = 0.001) and L. PMv/SMA region (P = 0.001) were found to be significant predictors of FM-UE scores. Network efficiency was the only global metric found to be reduced in CSPs (P = 0.006 vs. HCs). Nodal efficiency of the L. hippocampus, L. parahippocampal gyrus, L. fusiform gyrus (P = 0.001), and nodal local efficiency of the L. supramarginal gyrus (P < 0.001) were reduced in CSPs relative to HCs. No graph metric was associated with FM-UE scores. In conclusion, the integrity of CSTs connected to M1, SMA, and PMv were shown to be independent predictors of motor performance in CSPs, while stroke-induced topological changes in the brain's structural connectome may not be. A sensorimotor cortex-specific tract template can refine CST degeneration data and the relationship of CST degeneration with motor performance. |
| first_indexed | 2024-12-18T10:58:15Z |
| format | Article |
| id | doaj.art-ac7a78305e5943f18363665d58f2c9a0 |
| institution | Directory Open Access Journal |
| issn | 1664-2295 |
| language | English |
| last_indexed | 2024-12-18T10:58:15Z |
| publishDate | 2022-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neurology |
| spelling | doaj.art-ac7a78305e5943f18363665d58f2c9a02022-12-21T21:10:17ZengFrontiers Media S.A.Frontiers in Neurology1664-22952022-03-011310.3389/fneur.2022.813763813763The Severity of Sensorimotor Tracts Degeneration May Predict Motor Performance in Chronic Stroke Patients, While Brain Structural Network Dysfunction May NotLoukas G. Astrakas0Shasha Li1Shasha Li2Sabrina Elbach3Sabrina Elbach4A. Aria Tzika5A. Aria Tzika6Department of Medical Physics, Faculty of Medicine, University of Ioannina, Ioannina, GreeceDepartment of Radiology, Athinoula A. Martinos Center of Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesNMR Surgical Laboratory, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesDepartment of Radiology, Athinoula A. Martinos Center of Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesNMR Surgical Laboratory, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesDepartment of Radiology, Athinoula A. Martinos Center of Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesNMR Surgical Laboratory, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesAlthough the relationship between corticospinal tract (CST) fiber degeneration and motor outcome after stroke has been established, the relationship of sensorimotor cortical areas with CST fibers has not been clarified. Also limited research has been conducted on how abnormalities in brain structural networks are related to motor recovery. To address these gaps in knowledge, we conducted a diffusion tensor imaging (DTI) study with 12 chronic stroke patients (CSPs) and 12 age-matched healthy controls (HCs). We compared fractional anisotropy (FA) and mean diffusivity (MD) in 60 CST segments using the probabilistic sensorimotor area tract template (SMATT). Least Absolute Shrinkage and Selection Operator (LASSO) regressions were used to select independent predictors of Fugl-Meyer upper extremity (FM-UE) scores among FA and MD values of SMATT regions. The Graph Theoretical Network Analysis Toolbox was used to assess the structural network of each subject's brain. Global and nodal metrics were calculated, compared between the groups, and correlated with FM-UE scores. Mann–Whitney U-tests revealed reduced FA values in CSPs, compared to HCs, in many ipsilesional SMATT regions and in two contralesional regions. Mean FA value of the left (L.) primary motor cortex (M1)/supplementary motor area (SMA) region was predictive of FM-UE score (P = 0.004). Mean MD values for the L. M1/ventral premotor cortex (PMv) region (P = 0.001) and L. PMv/SMA region (P = 0.001) were found to be significant predictors of FM-UE scores. Network efficiency was the only global metric found to be reduced in CSPs (P = 0.006 vs. HCs). Nodal efficiency of the L. hippocampus, L. parahippocampal gyrus, L. fusiform gyrus (P = 0.001), and nodal local efficiency of the L. supramarginal gyrus (P < 0.001) were reduced in CSPs relative to HCs. No graph metric was associated with FM-UE scores. In conclusion, the integrity of CSTs connected to M1, SMA, and PMv were shown to be independent predictors of motor performance in CSPs, while stroke-induced topological changes in the brain's structural connectome may not be. A sensorimotor cortex-specific tract template can refine CST degeneration data and the relationship of CST degeneration with motor performance.https://www.frontiersin.org/articles/10.3389/fneur.2022.813763/fullchronic strokeFugl-Meyer upper extremity scalediffusion tensor imagingsensorimotor cortexgraph analysis |
| spellingShingle | Loukas G. Astrakas Shasha Li Shasha Li Sabrina Elbach Sabrina Elbach A. Aria Tzika A. Aria Tzika The Severity of Sensorimotor Tracts Degeneration May Predict Motor Performance in Chronic Stroke Patients, While Brain Structural Network Dysfunction May Not Frontiers in Neurology chronic stroke Fugl-Meyer upper extremity scale diffusion tensor imaging sensorimotor cortex graph analysis |
| title | The Severity of Sensorimotor Tracts Degeneration May Predict Motor Performance in Chronic Stroke Patients, While Brain Structural Network Dysfunction May Not |
| title_full | The Severity of Sensorimotor Tracts Degeneration May Predict Motor Performance in Chronic Stroke Patients, While Brain Structural Network Dysfunction May Not |
| title_fullStr | The Severity of Sensorimotor Tracts Degeneration May Predict Motor Performance in Chronic Stroke Patients, While Brain Structural Network Dysfunction May Not |
| title_full_unstemmed | The Severity of Sensorimotor Tracts Degeneration May Predict Motor Performance in Chronic Stroke Patients, While Brain Structural Network Dysfunction May Not |
| title_short | The Severity of Sensorimotor Tracts Degeneration May Predict Motor Performance in Chronic Stroke Patients, While Brain Structural Network Dysfunction May Not |
| title_sort | severity of sensorimotor tracts degeneration may predict motor performance in chronic stroke patients while brain structural network dysfunction may not |
| topic | chronic stroke Fugl-Meyer upper extremity scale diffusion tensor imaging sensorimotor cortex graph analysis |
| url | https://www.frontiersin.org/articles/10.3389/fneur.2022.813763/full |
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