Connectometry evaluation in patients undergoing carotid endarterectomy: an exploratory study
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This research investigated local brain connectivity changes following Carotid Endarterectomy (CEA) by connectometry. Seventeen subjects (15 males and 2 females, mean age 74.1 years), all eligible for CEA, were prospectively recruited in this exploratory study. On the same day within the week before the CEA, each patient underwent a cognitive evaluation with a Mini Mental State Examination (MMSE) and a Magnetic Resonance Imaging (MRI) exam that included a DTI sequence for the connectometry analysis. A second MMSE and the same MRI protocol were performed on follow-up, 3–6 months after CEA. The MMSE scores were analyzed using T-Student tests. The connectometry analysis was performed using a multiple regression model to consider the effect of CEA, choosing three different T-score threshold (T-threshold) values (1, 2 and 3). Results were considered statistically valid for p value adjusted for False Discovery Rate (p-FDR) < 0.05. Comparison of pre-CEA and post-CEA MMSE scores showed improvement of MMSE scores after CEA. Connectometry analysis revealed no areas of statistically significant increased connectivity related to CEA for T-threshold value = 1 and 2, but showed statistically significant increase of connectivity after CEA in both cerebellar hemispheres and corpus callosum for T-threshold value = 3 (p-FDR = 0.0106667). The network property analysis showed improved small worldness (2.14%), clustering coefficient (1.64%), local (1.94%) and global efficiency (0.56%), and reduced characteristic path length (−0.52%) after CEA. These results suggest that CEA is associated both with cognitive performance improvement and changes in interhemispheric local connectivity in the corpus callosum and cerebellum.
KeywordsCarotid endarterectomy DTI Connectometry
Compliance with ethical standards
Conflict of interest
All the authors declare that they have no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
- Abhinav, K., Yeh, F. C., El-Dokla, A., Ferrando, L. M., Chang, Y. F., Lacomis, D., Friedlander, R. M., & Fernandez-Miranda, J. C. (2014). Use of diffusion spectrum imaging in preliminary longitudinal evaluation of amyotrophic lateral sclerosis: development of an imaging biomarker. Frontiers in Human Neuroscience, 8, 270.CrossRefGoogle Scholar
- Carta, M. G., Lecca, M. E., Saba, L., Sanfilippo, R., Pintus, E., Cadoni, M., Sancassiani, F., Moro, M. F., Craboledda, D., Lo Giudice, C., Finco, G., Musu, M., & Montisci, R. (2015). Patients with carotid atherosclerosis who underwent or did not undergo carotid endarterectomy: outcome on mood, cognition and quality of life. BMC Psychiatry, 15, 277.CrossRefGoogle Scholar
- Chang, T. Y., Huang, K. L., Ho, M. Y., Ho, P. S., Chang, C. H., Liu, C. H., Chang, Y. J., Wong, H. F., Hsieh, I. C., Lee, T. H., & Liu, H. L. (2016). Graph theoretical analysis of functional networks and its relationship to cognitive decline in patients with carotid stenosis. Journal of Cerebral Blood Flow and Metabolism, 36(4), 808–818.CrossRefGoogle Scholar
- Chang, E. H., Argyelan, M., Aggarwal, M., Chandon, T. S., Karlsgodt, K. H., Mori, S., & Malhotra, A. K. (2017). The role of myelination in measures of white matter integrity: combination of diffusion tensor imaging and two-photon microscopy of CLARITY intact brains. NeuroImage, 147, 253–261.CrossRefGoogle Scholar
- Dharmakidari, S., Bhattacharya, P., & Chaturvedi, S. (2017). Carotid artery stenosis: medical therapy, surgery. and Stenting. Current Neurology and Neuroscience Reports, 17(10), 1–7.Google Scholar
- Johnston, S. C., O'Meara, E. S., Manolio, T. A., Lefkowitz, D., O'Leary, D. H., Goldstein, S., Carlson, M. C., Fried, L. P., & Longstreth, W. T., Jr. (2004). Cognitive impairment and decline are associated with carotid artery disease in patients without clinically evident cerebrovascular disease. Annals of Internal Medicine, 140(4), 237–247.CrossRefGoogle Scholar
- Liapis, C. D., Bell, P. R., Mikhailidis, D., Sivenius, J., Nicolaides, A., Fernandes e Fernandes, J., Biasi, G., Norgren, L., & ESVS Guidelines Collaborators. ESVS guidelines. (2009). Invasive treatment for carotid stenosis: Indications, techniques. European Journal of Vascular and Endovascular Surgery, 37(4 Suppl), 1–19.CrossRefGoogle Scholar
- Lin, C. J., Chang, F. C., Chou, K. H., Tu, P. C., Lee, Y. H., Lin, C. P., Wang, P. N., & Lee, I. H. (2016). Intervention versus aggressive medical therapy for cognition in severe asymptomatic carotid stenosis. AJNR. American Journal of Neuroradiology. 2016 Apr 28. [Epub ahead of print].Google Scholar
- Moftakhar, R., Turk, A. S., Niemann, D. B., Hussain, S., Rajpal, S., Cook, T., Geraghty, M., Aagaard-Kienitz, B., Turski, P. A., & Newman, G. C. (2005). Effects of carotid or vertebrobasilar stent placement on cerebral perfusion and cognition. AJNR. American Journal of Neuroradiology, 26(7), 1772–1780.PubMedGoogle Scholar
- Moneta, G. L., Edwards, J. M., Chitwood, R. W., Taylor, L. M., Jr., Lee, R. W., Cummings, C. A., & Porter, J. M. (1993). Correlation of north American symptomatic carotid endarterectomy trial (NASCET) angiographic definition of 70% to 99% internal carotid artery stenosis with duplex scanning. Journal of Vascular Surgery, 17(1), 152–157.CrossRefGoogle Scholar
- Olvet, D. M., Delaparte, L., Yeh, F. C., DeLorenzo, C., McGrath, P. J., Weissman, M. M., Adams, P., Fava, M., Deckersbach, T., McInnis, M. G., Carmody, T. J., Cooper, C. M., Kurian, B. T., Lu, H., Toups, M. S., Trivedi, M. H., & Parsey, R. V. (2016). A comprehensive examination of white matter tracts and connectometry in major depressive disorder. Depression and Anxiety, 33(1), 56–65.CrossRefGoogle Scholar
- Romascano, D., Meskaldji, D. E., Bonnier, G., Simioni, S., Rotzinger, D., Lin, Y. C., Menegaz, G., Roche, A., Schluep, M., Pasquier, R. D., Richiardi, J., Van De Ville, D., Daducci, A., Sumpf, T., Fraham, J., Thiran, J. P., Krueger, G., & Granziera, C. (2015). Multicontrast connectometry: a new tool to assess cerebellum alterations in early relapsing-remitting multiple sclerosis. Human Brain Mapping, 36(4), 1609–1619.CrossRefGoogle Scholar
- Saba, L., Yuan, C., Hatsukami, T. S., Balu, N., Qiao, Y., DeMarco, J. K., Saam, T., Moody, A. R., Li, D., Matouk, C. C., Johnson, M. H., Jäger, H. R., Mossa-Basha, M., Kooi, M. E., Fan, Z., Saloner, D., Wintermark, M., Mikulis, D. J., & Wasserman, B. A. (2018). Vessel wall imaging study group of the American society of neuroradiology. Carotid artery wall imaging: perspective and guidelines from the ASNR vessel wall imaging study group and expert consensus recommendations of the American society of neuroradiology. AJNR. American Journal of Neuroradiology, 39(2), E9–E31.CrossRefGoogle Scholar
- Sobhani S, Rahmani F, Aarabi MH, Sadr AV (2017) Exploring white matter microstructure and olfaction dysfunction in early parkinson disease: diffusion MRI reveals new insight. Brain Imaging and Behavior. 2017 Nov 13. https://doi.org/10.1007/s11682-017-9781-0. [Epub ahead of print].
- Wang, T., Xiao, F., Wu, G., Fang, J., Sun, Z., Feng, H., Zhang, J., & Xu, H. (2017a). Impairments in brain perfusion, metabolites, functional connectivity, and cognition in severe asymptomatic carotid stenosis patients: an integrated MRI study. Neural Plasticity., 2017, 8738714.PubMedPubMedCentralGoogle Scholar
- Yeh, F. C., Tang, P. F., & Tseng, W. Y. (2013a). Diffusion MRI connectometry automatically reveals affected fiber pathways in individuals with chronic stroke. Neuroimage Clinical, 2, 912–921.Google Scholar
- Yeh, F. C., Vettel, J. M., Singh, A., Poczos, B., Grafton, S. T., Erickson, K. I., Tseng, W. I., & Verstynen, T. D. (2016b). Quantifying differences and Similrities in whole-brain white matter architecture using local connectome fingerprints. PLoS Computational Biology, 12(11), e1005203.CrossRefGoogle Scholar