Structural connectivity as a predictive factor for responsiveness to levetiracetam treatment in epilepsy.
Purpose: To investigate whether structural connectivity or glymphatic system function is a potential predictive factor for levetiracetam (LEV) response in patients with newly diagnosed epilepsy. Methods: We enrolled patients with newly diagnosed epilepsy who were administered LEV as initial monother...
| Published in: | Neuroradiology Vol. 66; no. 1; pp. 93 - 101 |
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| Main Authors: | , , |
| Format: | research tables/charts Journal Article |
| Published: |
Springer Nature
Jan2024
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=174559459&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 174559459 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00283940 NYZ jtl: Neuroradiology issn: 00283940 maglogo: N pubinfo: dt: Jan2024 vid: 66 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 174559459 173876877 174559459 174559459 10.1007/s00234-023-03261-3 174559459 ppf: 93 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Structural connectivity as a predictive factor for responsiveness to levetiracetam treatment in epilepsy. aug: au: Lee, Dong Ah Lee, Ho-Joon Park, Kang Min affil: https://ror.org/04xqwq985 Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, 48108, Busan, Korea sug: subj: Anticonvulsants Therapeutic Use Drug Efficacy Evaluation Functional Connectivity Epilepsy Drug Therapy Human Magnetic Resonance Imaging Neuroradiography ROC Curve Descriptive Statistics Multiple Logistic Regression Survival Analysis Epilepsy Prognosis Epilepsy Pathology Brain Physiology ab: Purpose: To investigate whether structural connectivity or glymphatic system function is a potential predictive factor for levetiracetam (LEV) response in patients with newly diagnosed epilepsy. Methods: We enrolled patients with newly diagnosed epilepsy who were administered LEV as initial monotherapy and underwent diffusion tensor imaging (DTI) at diagnosis. We categorized the patients into drug response. We used graph theory to calculate the network measures for structural connectivity based on the DTI scans in patients with epilepsy. Additionally, we evaluated glymphatic system function by calculating the DTI analysis along the perivascular space (DTI-ALPS) index based on DTI scans. Results: We enrolled 84 patients with epilepsy. The clinical factors and DTI-ALPS index did not differ between the groups. However, some of the structural connectivity measures significantly differ between the groups. The poor responders exhibited a higher mean clustering coefficient, global efficiency, and small-worldness index than the good responders (p = 0.003, p = 0.048, and p = 0.038, respectively). In the receiver operating characteristic curve analysis, the mean clustering coefficient exhibited the highest performance in predicting the responsiveness to LEV (area under the curve of 0.677). In the multiple logistic regression analysis, the mean clustering coefficient of the structural connectivity measures was the only significant predictor of LEV response (p = 0.014). Furthermore, in the survival analysis, the mean clustering coefficient was the only significant predictor of LEV response (p = 0.026). Conclusion: We demonstrated that structural connectivity is a potential predictive factor for responsiveness to LEV treatment in patients with newly diagnosed epilepsy. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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