Associations of Cerebral Blood Flow Patterns With Gray and White Matter Structure in Patients With Temporal Lobe Epilepsy

被引:4
作者
Ngo, Alexander [1 ]
Royer, Jessica [1 ]
Rodriguez-Cruces, Raul [1 ]
Xie, Ke [1 ]
Dekraker, Jordan [1 ]
Auer, Hans [1 ]
Tavakol, Shahin [1 ]
Lam, Jack [1 ]
Schrader, Dewi V. [2 ]
Dudley, Roy W. R. [3 ]
Bernasconi, Andrea [1 ]
Bernasconi, Neda [1 ]
Frauscher, Birgit [1 ]
Lariviere, Sara [4 ]
Bernhardt, Boris C. [1 ]
机构
[1] McGill Univ, Montreal Neurol Inst & Hosp, Dept Neurol & Neurosurg, Montreal, PQ, Canada
[2] Univ British Columbia, Dept Pediat, Vancouver, BC, Canada
[3] McGill Univ, Montreal Childrens Hosp, Dept Pediat Surg, Montreal, PQ, Canada
[4] Harvard Med Sch, Brigham & Womens Hosp, Ctr Brain Circuit Therapeut, Boston, MA USA
基金
加拿大健康研究院;
关键词
MR; PERFUSION; ABNORMALITIES; HYPOPERFUSION; NETWORK; ATROPHY;
D O I
10.1212/WNL.0000000000209528
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background and Objectives Neuroimaging studies in patients with temporal lobe epilepsy (TLE) show widespread brain network alterations beyond the mesiotemporal lobe. Despite the critical role of the cerebrovascular system in maintaining whole-brain structure and function, changes in cerebral blood flow (CBF) remain incompletely understood in the disease. Here, we studied whole-brain perfusion and vascular network alterations in TLE and assessed its associations with gray and white matter compromises and various clinical variables. Methods We included individuals with and without pharmaco-resistant TLE who underwent multimodal 3T MRI, including arterial spin labelling, structural, and diffusion-weighted imaging. Using surface-based MRI mapping, we generated individualized cortico-subcortical profiles of perfusion, morphology, and microstructure. Linear models compared regional CBF in patients with controls and related alterations to morphological and microstructural metrics. We further probed interregional vascular networks in TLE, using graph theoretical CBF covariance analysis. The effects of disease duration were explored to better understand the progressive changes in perfusion. We assessed the utility of perfusion in separating patients with TLE from controls using supervised machine learning. Results Compared with control participants (n = 38; mean +/- SD age 34.8 +/- 9.3 years; 20 females), patients with TLE (n = 24; mean +/- SD age 35.8 +/- 10.6 years; 12 females) showed widespread CBF reductions predominantly in fronto-temporal regions (Cohen d -0.69, 95% CI -1.21 to -0.16), consistent in a subgroup of patients who remained seizure-free after surgical resection of the seizure focus. Parallel structural profiling and network-based models showed that cerebral hypoperfusion may be partially constrained by gray and white matter changes (8.11% reduction in Cohen d) and topologically segregated from whole-brain perfusion networks (area under the curve -0.17, p < 0.05). Negative effects of progressive disease duration further targeted regional CBF profiles in patients (r = -0.54, 95% CI -0.77 to -0.16). Perfusion-derived classifiers discriminated patients from controls with high accuracy (71% [70%-82%]). Findings were robust when controlling for several methodological confounds. Discussion Our multimodal findings provide insights into vascular contributions to TLE pathophysiology affecting and extending beyond mesiotemporal structures and highlight their clinical potential in epilepsy diagnosis. As our work was cross-sectional and based on a single site, it motivates future longitudinal studies to confirm progressive effects, ideally in a multicentric setting.
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页数:13
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共 57 条
[1]   Efficiency and cost of economical brain functional networks [J].
Achard, Sophie ;
Bullmore, Edward T. .
PLOS COMPUTATIONAL BIOLOGY, 2007, 3 (02) :174-183
[2]   CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING [J].
BENJAMINI, Y ;
HOCHBERG, Y .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) :289-300
[3]   Longitudinal and cross-sectional analysis of atrophy in pharmacoresistant temporal lobe epilepsy [J].
Bernhardt, B. C. ;
Worsley, K. J. ;
Kim, H. ;
Evans, A. C. ;
Bernasconi, A. ;
Bernasconi, N. .
NEUROLOGY, 2009, 72 (20) :1747-1754
[4]   The Spectrum of Structural and Functional Imaging Abnormalities in Temporal Lobe Epilepsy [J].
Bernhardt, Boris C. ;
Bernasconi, Andrea ;
Liu, Min ;
Hong, Seok-Jun ;
Caldairou, Benoit ;
Goubran, Maged ;
Guiot, Marie C. ;
Hall, Jeff ;
Bernasconi, Neda .
ANNALS OF NEUROLOGY, 2016, 80 (01) :142-153
[5]  
BrainStat, about us
[6]   Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain [J].
Bullmore, ET ;
Suckling, J ;
Overmeyer, S ;
Rabe-Hesketh, S ;
Taylor, E ;
Brammer, MJ .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 1999, 18 (01) :32-42
[7]   Variational Bayesian Inference for a Nonlinear Forward Model [J].
Chappell, Michael A. ;
Groves, Adrian R. ;
Whitcher, Brandon ;
Woolrich, Mark W. .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2009, 57 (01) :223-236
[8]   Micapipe: A pipeline for multimodal neuroimaging and connectome analysis [J].
Cruces, Raul R. ;
Royer, Jessica ;
Herholz, Peer ;
Lariviere, Sara ;
De Wael, Reinder Vos ;
Paquola, Casey ;
Benkarim, Oualid ;
Park, Bo-yong ;
Degre-Pelletier, Janie ;
Nelson, Mark C. ;
DeKraker, Jordan ;
Leppert, Ilana R. ;
Tardif, Christine ;
Poline, Jean -Baptiste ;
Concha, Luis ;
Bernhardt, Boris C. .
NEUROIMAGE, 2022, 263
[9]   Cortical surface-based analysis - I. Segmentation and surface reconstruction [J].
Dale, AM ;
Fischl, B ;
Sereno, MI .
NEUROIMAGE, 1999, 9 (02) :179-194
[10]   Automated hippocampal unfolding for morphometry and subfield segmentation with HippUnfold [J].
DeKraker, Jordan ;
Haast, Roy A. M. ;
Yousif, Mohamed D. ;
Karat, Bradley ;
Lau, Jonathan C. ;
Kohler, Stefan ;
Khan, Ali R. .
ELIFE, 2022, 11