Graham W Johnson1,2,3, Derek J Doss1,2,3, Dario J Englot1,2,3,4,5,6,7. 1. Departments of Biomedical Engineering at Vanderbilt University. 2. Vanderbilt University Institute of Imaging Science at Vanderbilt University Medical Center. 3. Vanderbilt University Institute for Surgery and Engineering. 4. Electrical and Computer Engineering at Vanderbilt University. 5. Departments of Neurological Surgery. 6. Neurology. 7. Radiology and Radiological Sciences at Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Abstract
PURPOSE OF REVIEW: Patients with focal drug-resistant epilepsy (DRE) sometimes continue to have seizures after surgery. Recently, there is increasing interest in using advanced network analyses (connectomics) to better understand this problem. Connectomics has changed the way researchers and clinicians view DRE, but it must be applied carefully in a hypothesis-driven manner to avoid spurious results. This review will focus on studies published in the last 18 months that have thoughtfully used connectomics to advance our fundamental understanding of network dysfunction in DRE - hopefully for the eventual direct benefit to patient care. RECENT FINDINGS: Impactful recent findings have centered on using patient-specific differences in network dysfunction to predict surgical outcome. These works span functional and structural connectivity and include the modalities of functional and diffusion magnetic resonance imaging (MRI) and electrophysiology. Using functional MRI, many groups have described an increased functional segregation outside of the surgical resection zone in patients who fail surgery. Using electrophysiology, groups have reported network characteristics of resected tissue that suggest whether a patient will respond favorably to surgery. SUMMARY: If we can develop accurate models to outline functional and structural network characteristics that predict failure of standard surgical approaches, then we can not only improve current clinical decision-making; we can also begin developing alternative treatments including network approaches to improve surgical success rates.
PURPOSE OF REVIEW: Patients with focal drug-resistant epilepsy (DRE) sometimes continue to have seizures after surgery. Recently, there is increasing interest in using advanced network analyses (connectomics) to better understand this problem. Connectomics has changed the way researchers and clinicians view DRE, but it must be applied carefully in a hypothesis-driven manner to avoid spurious results. This review will focus on studies published in the last 18 months that have thoughtfully used connectomics to advance our fundamental understanding of network dysfunction in DRE - hopefully for the eventual direct benefit to patient care. RECENT FINDINGS: Impactful recent findings have centered on using patient-specific differences in network dysfunction to predict surgical outcome. These works span functional and structural connectivity and include the modalities of functional and diffusion magnetic resonance imaging (MRI) and electrophysiology. Using functional MRI, many groups have described an increased functional segregation outside of the surgical resection zone in patients who fail surgery. Using electrophysiology, groups have reported network characteristics of resected tissue that suggest whether a patient will respond favorably to surgery. SUMMARY: If we can develop accurate models to outline functional and structural network characteristics that predict failure of standard surgical approaches, then we can not only improve current clinical decision-making; we can also begin developing alternative treatments including network approaches to improve surgical success rates.
Authors: Saramati Narasimhan; Keshav B Kundassery; Kanupriya Gupta; Graham W Johnson; Kristin E Wills; Sarah E Goodale; Kevin Haas; John D Rolston; Robert P Naftel; Victoria L Morgan; Benoit M Dawant; Hernán F J González; Dario J Englot Journal: Epilepsia Date: 2020-09-18 Impact factor: 5.864
Authors: Sara Larivière; Yifei Weng; Reinder Vos de Wael; Jessica Royer; Birgit Frauscher; Zhengge Wang; Andrea Bernasconi; Neda Bernasconi; Dewi V Schrader; Zhiqiang Zhang; Boris C Bernhardt Journal: Epilepsia Date: 2020-05-26 Impact factor: 5.864
Authors: Olivia Foesleitner; Benjamin Sigl; Victor Schmidbauer; Karl-Heinz Nenning; Ekaterina Pataraia; Lisa Bartha-Doering; Christoph Baumgartner; Susanne Pirker; Doris Moser; Michelle Schwarz; Johannes A Hainfellner; Thomas Czech; Christian Dorfer; Georg Langs; Daniela Prayer; Silvia Bonelli; Gregor Kasprian Journal: J Neurosurg Date: 2020-07-03 Impact factor: 5.115
Authors: Yujiang Wang; Nishant Sinha; Gabrielle M Schroeder; Sriharsha Ramaraju; Andrew W McEvoy; Anna Miserocchi; Jane de Tisi; Fahmida A Chowdhury; Beate Diehl; John S Duncan; Peter N Taylor Journal: Epilepsia Date: 2020-06-26 Impact factor: 6.740