Contributions
Abstract: EP1518
Type: Poster Sessions
Abstract Category: Pathology and pathogenesis of MS - MRI and PET
Background: Recent work showed a vast structural grey matter networks reorganization in patients with multiple sclerosis (MS) and depicted quantifiable longitudinal patterns of increased local clustering, increased modularity and long-range disconnection. These are detectable even beyond clinical markers of disease progression as measured with established MRI pipelines. The use of higher magnetic fields (i.e. at 7 Tesla, 7T) opens up important possibilities to detect more sensitively structural dynamics in the grey and white matter and ongoing subtle neuroinflammatory processes in early MS. However it is not yet clear which advantages for the quantification of network behavior adds up the 7T imaging in comparison to the state-of-the-art scanning procedures at 3 Tesla.
Methods: Seven relapsing remitting MS patients (disease duration < 3 years) were scanned at 3 Tesla and 7 Tesla, no more than 48 h apart. Signal-to-Noise Ratio (SNR) and Contrast-to-Noise-Ration (CNR) values were calculated. All images were processed using the standard pipeline in FreeSurfer to compute regional measures of cortical thickness (CT). Structural network covariance was determined from the regional CT values based on the Desikan-Killiany atlas. Thereafter we applied the graph theoretical framework for the quantification of the grey matter structural topology at the local, modular and global network level (modularity, clustering coefficient, transitivity and global and local efficiencies).
Results: While 3 and 7 Tesla MRI revealed comparable values for assessing cortical thickness, only one single region (left posterior cingulate) showed significant cortical thinning at 7T in comparison to 3T images after the correction for multiple comparisons (p = 0.01, T = 5.76). The network analysis, however, showed increases in modularity (p < 0.001, T = 8.8), clustering (p < 0.001, T = 9.1), transitivity (p < 0.001, T = 25.4) and local efficiency (p < 0.001, T = 6.9) at 7T but no changes in global efficiency (p > 0.02, T = 1.6). At 7 T the MR images presented lower SNR and CNR than the 3T data (p = 0.01, T = 3.5).
Conclusion: Although there are only subtle differences for the quantification of cortical thickness between 3- and 7T imaging, the derived network measures differ considerably. Further studies are needed to determine the interrelationship of structural integrity and network parameters as derived from 7T imaging for the characterization of the disease processes and neuroinflammation.
Disclosure: Nothing to Disclose
Abstract: EP1518
Type: Poster Sessions
Abstract Category: Pathology and pathogenesis of MS - MRI and PET
Background: Recent work showed a vast structural grey matter networks reorganization in patients with multiple sclerosis (MS) and depicted quantifiable longitudinal patterns of increased local clustering, increased modularity and long-range disconnection. These are detectable even beyond clinical markers of disease progression as measured with established MRI pipelines. The use of higher magnetic fields (i.e. at 7 Tesla, 7T) opens up important possibilities to detect more sensitively structural dynamics in the grey and white matter and ongoing subtle neuroinflammatory processes in early MS. However it is not yet clear which advantages for the quantification of network behavior adds up the 7T imaging in comparison to the state-of-the-art scanning procedures at 3 Tesla.
Methods: Seven relapsing remitting MS patients (disease duration < 3 years) were scanned at 3 Tesla and 7 Tesla, no more than 48 h apart. Signal-to-Noise Ratio (SNR) and Contrast-to-Noise-Ration (CNR) values were calculated. All images were processed using the standard pipeline in FreeSurfer to compute regional measures of cortical thickness (CT). Structural network covariance was determined from the regional CT values based on the Desikan-Killiany atlas. Thereafter we applied the graph theoretical framework for the quantification of the grey matter structural topology at the local, modular and global network level (modularity, clustering coefficient, transitivity and global and local efficiencies).
Results: While 3 and 7 Tesla MRI revealed comparable values for assessing cortical thickness, only one single region (left posterior cingulate) showed significant cortical thinning at 7T in comparison to 3T images after the correction for multiple comparisons (p = 0.01, T = 5.76). The network analysis, however, showed increases in modularity (p < 0.001, T = 8.8), clustering (p < 0.001, T = 9.1), transitivity (p < 0.001, T = 25.4) and local efficiency (p < 0.001, T = 6.9) at 7T but no changes in global efficiency (p > 0.02, T = 1.6). At 7 T the MR images presented lower SNR and CNR than the 3T data (p = 0.01, T = 3.5).
Conclusion: Although there are only subtle differences for the quantification of cortical thickness between 3- and 7T imaging, the derived network measures differ considerably. Further studies are needed to determine the interrelationship of structural integrity and network parameters as derived from 7T imaging for the characterization of the disease processes and neuroinflammation.
Disclosure: Nothing to Disclose