Alteration of the anatomical covariance network after corpus callosotomy in pediatric intractable epilepsy


Autoři: Riyo Ueda aff001;  Hiroshi Matsuda aff003;  Noriko Sato aff004;  Masaki Iwasaki aff005;  Daichi Sone aff003;  Eri Takeshita aff007;  Yuko Shimizu-Motohashi aff007;  Akihiko Ishiyama aff007;  Takashi Saito aff007;  Hirofumi Komaki aff007;  Eiji Nakagawa aff007;  Kenji Sugai aff007;  Masayuki Sasaki aff007;  Yoshimi Kaga aff001;  Hiroshige Takeichi aff001;  Masumi Inagaki aff001
Působiště autorů: Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan aff001;  Division of Frontier Medicine and Pharmacy, Graduate School of Medical and Pharmaceutical Science, Chiba University, Chiba, Japan aff002;  Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Tokyo, Japan aff003;  Department of Radiology, National Center Hospital, National Center of Neurology and Psychiatry, Tokyo, Japan aff004;  Department of Neurosurgery, National Center Hospital, National Center of Neurology and Psychiatry, Tokyo, Japan aff005;  Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, England, United Kingdom aff006;  Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, Tokyo, Japan aff007;  Computational Engineering Applications Unit, RIKEN, Wako, Japan aff008
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pone.0222876

Souhrn

Purpose

This study aimed to use graph theoretical analysis of anatomical covariance derived from structural MRI to reveal how the gray matter connectivity pattern is altered after corpus callosotomy (CC).

Materials and methods

We recruited 21 patients with epilepsy who had undergone CC. Enrollment criteria were applied: (1) no lesion identified on brain MRI; (2) no history of other brain surgery; and (3) age not younger than 3 years and not older than 18 years at preoperative MRI evaluation. The most common epilepsy syndrome was Lennox-Gastaut syndrome (11 patients). For voxel-based morphometry, the normalized gray matter images of pre-CC and post-CC patients were analyzed with SPM12 (voxel-level threshold of p<0.05 [familywise error-corrected]). Secondly, the images of both groups were subjected to graph theoretical analysis using the Graph Analysis Toolbox with SPM8. Each group was also compared with 32 age- and sex-matched control patients without brain diseases.

Results

Comparisons between the pre- and post-CC groups revealed a significant reduction in seizure frequency with no change in mean intelligence quotient/developmental quotient levels. There was no relationship among the three groups in global network metrics or in targeted attack. A regional comparison of betweenness centrality revealed decreased connectivity to and from the right middle cingulate gyri and medial side of the right superior frontal gyrus and a partial shift in the distribution of betweenness centrality hubs to the normal location. Significantly lower resilience to random failure was found after versus before CC and versus controls (p = 0.0450 and p = 0.0200, respectively).

Conclusion

Graph theoretical analysis of anatomical covariance derived from structural imaging revealed two neural network effects of resection associated with seizure reduction: the reappearance of a structural network comparable to that in healthy children and reduced connectivity along the median line, including the middle cingulate gyrus.

Klíčová slova:

Central nervous system – Covariance – Epilepsy – Magnetic resonance imaging – Network analysis – Network resilience – Neural networks – Surgical and invasive medical procedures


Zdroje

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2019 Číslo 12