{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T16:10:56Z","timestamp":1753891856365,"version":"3.41.2"},"reference-count":36,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,10,31]],"date-time":"2022-10-31T00:00:00Z","timestamp":1667174400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurosci."],"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>To investigate the structural and network topological changes in the white matter (WM) in MMD patients with limb paresthesia by performing diffusion kurtosis imaging (DKI).<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and methods<\/jats:title><jats:p>A total of 151 MMD patients, including 46 with left-limb paresthesia (MLP), 52 with right-limb paresthesia (MRP), and 53 without paresthesia (MWP), and 28 healthy controls (HCs) underwent whole-brain DKI, while the surgical patients were reexamined 3-4 months after revascularization. The data were preprocessed to calculate the fractional anisotropy (FA) and mean kurtosis (MK) values. Voxel-wise statistics for FA and MK images were obtained by using tract-based spatial statistics (TBSS). Next, the whole-brain network was constructed, and global and local network parameters were analyzed using graph theory. All parameters were compared among the HC, MWP, MLP, and MRP groups, and changes in the MMD patients before and after revascularization were also compared.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The TBSS analysis revealed significant reductions in FA and MK in extensive WM regions in the three patient groups. In comparison with the MWP group, the MLP group showed reductions in FA and MK in both right and left WM, mainly in the right WM, while the MRP group mainly showed a reduction in FA in the left WM region and demonstrated no significant change in MK. The graph theoretical analysis showed decreased global network efficiency, increased characteristic path length, and increased sigma in the MWP, MRP, and MLP groups in comparison with the HC group. Among local network parameters, the nodal efficiency decreased in the bilateral MFG and IFGtriang, while the degree decreased in the MFG.L and bilateral IFGtriang. Patients with right-limb paresthesia showed the lowest nodal efficiency and degree in MFG.L and IFGtriang.L, while those with left-limb paresthesia showed the lowest nodal efficiency in MFG.R and IFGtriang.R and the lowest degree in IFGtriang.R.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>A DKI-based whole-brain structural and network analysis can be used to detect changes in WM damage and network topological changes in MMD patients with limb paresthesia. FA is more sensitive than MK in detecting WM injury, while MFG and IFGtriang are the key nodes related to the development of acroparesthesia.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fnins.2022.1029388","type":"journal-article","created":{"date-parts":[[2022,10,31]],"date-time":"2022-10-31T05:30:51Z","timestamp":1667194251000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["White matter structural and network topological changes in moyamoya disease with limb paresthesia: A study based on diffusion kurtosis imaging"],"prefix":"10.3389","volume":"16","author":[{"given":"Rujing","family":"Sun","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shi-Yu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sangma","family":"Xie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng-Gang","family":"Qiao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gong-Jie","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2022,10,31]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1016\/j.neuroimage.2014.06.021","article-title":"Methodological considerations on Tract-Based Spatial Statistics (TBSS).","volume":"100","author":"Bach","year":"2014","journal-title":"Neuroimage"},{"key":"B2","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1038\/nrn2575","article-title":"Complex brain networks: Graph theoretical analysis of structural and functional systems.","volume":"10","author":"Bullmore","year":"2009","journal-title":"Nat. Rev. Neurosci."},{"key":"B3","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1016\/j.cortex.2011.12.001","article-title":"Short frontal lobe connections of the human brain.","volume":"48","author":"Catani","year":"2012","journal-title":"Cortex"},{"key":"B4","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.brainresbull.2011.10.006","article-title":"Chronic brain hypoperfusion causes early glial activation and neuronal death, and subsequent long-term memory impairment.","volume":"87","author":"Cechetti","year":"2012","journal-title":"Brain Res. Bull."},{"key":"B5","doi-asserted-by":"publisher","first-page":"1245","DOI":"10.1002\/nbm.3374","article-title":"Optimization of white matter fiber tractography with diffusional kurtosis imaging.","volume":"28","author":"Glenn","year":"2015","journal-title":"NMR Biomed."},{"key":"B6","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1016\/j.neuroimage.2013.04.056","article-title":"Structural connectomics in brain diseases.","volume":"80","author":"Griffa","year":"2013","journal-title":"Neuroimage"},{"key":"B7","doi-asserted-by":"publisher","first-page":"989","DOI":"10.1016\/j.neuroimage","article-title":"Topography of the human corpus callosum revisited-comprehensive fiber tractography using diffusion tensor magnetic resonance imaging.","volume":"32","author":"Hofer","year":"2006","journal-title":"Neuroimage"},{"key":"B8","doi-asserted-by":"publisher","first-page":"e94095","DOI":"10.1371\/journal.pone.0094095","article-title":"Disturbed small-world networks and neurocognitive function in frontal lobe low-grade glioma patients.","volume":"9","author":"Huang","year":"2014","journal-title":"PLoS One"},{"key":"B9","doi-asserted-by":"publisher","first-page":"825","DOI":"10.1006\/nimg.2002.1132","article-title":"Improved optimization for the robust and accurate linear registration and motion correction of brain images.","volume":"17","author":"Jenkinson","year":"2002","journal-title":"Neuroimage"},{"key":"B10","doi-asserted-by":"publisher","first-page":"698","DOI":"10.1002\/nbm.1518","article-title":"MRI quantification of non-Gaussian water diffusion by kurtosis analysis.","volume":"23","author":"Jensen","year":"2010","journal-title":"NMR Biomed."},{"key":"B11","doi-asserted-by":"publisher","first-page":"1893","DOI":"10.3174\/ajnr.A2683","article-title":"Changes in integrity of normal-appearing white matter in patients with Moyamoya disease: A diffusion tensor imaging study.","volume":"32","author":"Jeong","year":"2011","journal-title":"AJNR Am. J. Neuroradiol."},{"key":"B12","doi-asserted-by":"publisher","first-page":"1432","DOI":"10.3174\/ajnr.A4728","article-title":"Characteristics of diffusional kurtosis in chronic ischemia of adult Moyamoya disease: Comparing diffusional kurtosis and diffusion tensor imaging.","volume":"37","author":"Kazumata","year":"","journal-title":"AJNR Am. J. Neuroradiol."},{"key":"B13","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1161\/STROKEAHA.114.007407","article-title":"Chronic ischemia alters brain microstructural integrity and cognitive performance in adult Moyamoya disease.","volume":"46","author":"Kazumata","year":"2015","journal-title":"Stroke"},{"key":"B14","doi-asserted-by":"publisher","first-page":"654","DOI":"10.1016\/j.wneu.2015.11.100","article-title":"Investigating brain network characteristics interrupted by covert white matter injury in patients with Moyamoya disease: Insights from graph theoretical analysis.","volume":"89","author":"Kazumata","year":"","journal-title":"World Neurosurg."},{"key":"B15","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.cortex.2018.05.017","article-title":"White matter neuro-plasticity in mental arithmetic: Changes in hippocampal connectivity following arithmetic drill training.","volume":"114","author":"Klein","year":"2018","journal-title":"Cortex"},{"key":"B16","doi-asserted-by":"publisher","first-page":"1056","DOI":"10.1016\/S1474-4422(08)70240-0","article-title":"Moyamoya disease: Current concepts and future perspectives.","volume":"7","author":"Kuroda","year":"2008","journal-title":"Lancet Neurol."},{"key":"B17","doi-asserted-by":"publisher","first-page":"1058","DOI":"10.1161\/01.str.29.5.1058","article-title":"White matter changes in the gerbil brain under chronic cerebral hypoperfusion.","volume":"29","author":"Kurumatani","year":"1998","journal-title":"Stroke"},{"key":"B18","doi-asserted-by":"publisher","first-page":"198701","DOI":"10.1103\/PhysRevLett.87.198701","article-title":"Efficient behavior of small-world networks.","volume":"87","author":"Latora","year":"2001","journal-title":"Phys. Rev. Lett."},{"key":"B19","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1002\/mrm.21725","article-title":"Estimation of the orientation distribution function from diffusional kurtosis imaging.","volume":"60","author":"Lazar","year":"2008","journal-title":"Magn. Reson. Med."},{"key":"B20","doi-asserted-by":"publisher","first-page":"895","DOI":"10.1093\/pm\/pnab227","article-title":"Cerebral white matter alterations revealed by multiple diffusion metrics in cervical spondylotic patients with pain: A TBSS study.","volume":"23","author":"Li","year":"2021","journal-title":"Pain Med."},{"key":"B21","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1016\/j.neubiorev.2017.03.018","article-title":"Small-world human brain networks: Perspectives and challenges.","volume":"77","author":"Liao","year":"2017","journal-title":"Neurosci. Biobehav. Rev."},{"key":"B22","doi-asserted-by":"publisher","first-page":"16876","DOI":"10.1523\/JNEUROSCI.4136-10.2010","article-title":"Diffusion tensor tractography reveals abnormal topological organization in structural cortical networks in Alzheimer\u2019s disease.","volume":"30","author":"Lo","year":"2010","journal-title":"J. Neurosci."},{"key":"B23","doi-asserted-by":"publisher","first-page":"2307","DOI":"10.1212\/wnl.57.12.2307","article-title":"Normal-appearing white matter in ischemic leukoaraiosis: A diffusion tensor MRI study.","volume":"57","author":"O\u2019Sullivan","year":"2001","journal-title":"Neurology"},{"key":"B24","doi-asserted-by":"publisher","first-page":"246","DOI":"10.3174\/ajnr.A6392","article-title":"MR diffusional kurtosis imaging-based assessment of brain microstructural changes in patients with Moyamoya disease before and after revascularization.","volume":"41","author":"Qiao","year":"2020","journal-title":"AJNR Am. J. Neuroradiol."},{"key":"B25","doi-asserted-by":"publisher","first-page":"1059","DOI":"10.1016\/j.neuroimage.2009.10.003","article-title":"Complex network measures of brain connectivity: Uses and interpretations.","volume":"52","author":"Rubinov","year":"2010","journal-title":"Neuroimage"},{"key":"B26","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.neuroimage.2014.03.026","article-title":"Improved DTI registration allows voxel-based analysis that outperforms tract-based spatial statistics.","volume":"94","author":"Schwarz","year":"2014","journal-title":"Neuroimage"},{"key":"B27","doi-asserted-by":"publisher","first-page":"1498","DOI":"10.1016\/j.acra.2005.01.014","article-title":"Highly diffusion-sensitized tensor imaging of unilateral cerebral arterial occlusive disease.","volume":"26","author":"Shiraishi","year":"2005","journal-title":"AJNR Am. J. Neuroradiol."},{"key":"B28","doi-asserted-by":"publisher","first-page":"683","DOI":"10.1016\/j.tics.2013.09.012","article-title":"Network hubs in the human brain.","volume":"17","author":"van den Heuvel","year":"2013","journal-title":"Trends Cogn. Sci."},{"key":"B29","doi-asserted-by":"publisher","first-page":"15915","DOI":"10.1523\/JNEUROSCI.2874-10.2010","article-title":"Aberrant frontal and temporal complex network structure in schizophrenia: A graph theoretical analysis.","volume":"30","author":"van den Heuvel","year":"2010","journal-title":"J. Neurosci."},{"key":"B30","doi-asserted-by":"publisher","first-page":"2222","DOI":"10.1016\/j.neuroimage.2012.02.018","article-title":"The human connectome project: A data acquisition perspective.","volume":"62","author":"Van Essen","year":"2012","journal-title":"Neuroimage"},{"key":"B31","doi-asserted-by":"publisher","first-page":"635","DOI":"10.1007\/s00429-017-1508-x","article-title":"Probabilistic atlas of fiber crossings for variability reduction of anisotropy measures.","volume":"223","author":"Volz","year":"2018","journal-title":"Brain Struct. Funct."},{"key":"B32","doi-asserted-by":"publisher","first-page":"386","DOI":"10.3389\/fnhum.2015.00386","article-title":"GRETNA: A graph theoretical network analysis toolbox for imaging connectomics.","volume":"9","author":"Wang","year":"2015","journal-title":"Front. Hum. Neurosci."},{"key":"B33","doi-asserted-by":"publisher","first-page":"16900","DOI":"10.1038\/s41598-020-73746-1","article-title":"Motor cortex gliomas induces microstructural changes of large fiber tracts revealed by TBSS.","volume":"10","author":"Wang","year":"2020","journal-title":"Sci. Rep."},{"key":"B34","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1038\/30918","article-title":"Collective dynamics of \u2018small-world\u2019 networks.","volume":"393","author":"Watts","year":"1998","journal-title":"Nature"},{"key":"B35","doi-asserted-by":"publisher","first-page":"693","DOI":"10.2147\/JPR.S289165","article-title":"Abnormal brain connectivity in carpal tunnel syndrome assessed by graph theory.","volume":"14","author":"Xing","year":"2021","journal-title":"J. Pain Res."},{"key":"B36","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1097\/WCO.0b013e32833aa567","article-title":"Graph theoretical modeling of brain connectivity.","volume":"23","author":"Yong","year":"2010","journal-title":"Curr. Opin. Neurol."}],"container-title":["Frontiers in Neuroscience"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnins.2022.1029388\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,31]],"date-time":"2022-10-31T05:30:54Z","timestamp":1667194254000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnins.2022.1029388\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,31]]},"references-count":36,"alternative-id":["10.3389\/fnins.2022.1029388"],"URL":"https:\/\/doi.org\/10.3389\/fnins.2022.1029388","relation":{},"ISSN":["1662-453X"],"issn-type":[{"type":"electronic","value":"1662-453X"}],"subject":[],"published":{"date-parts":[[2022,10,31]]},"article-number":"1029388"}}