Anterior temporal lobectomy (ATL) is a highly sucessful treatment for eliminating seizures in patients with temporal lobe epilepsy (TLE). However, ATL-induced cognitive decline is frequent and often severe, having a deleterious impact on quality of life and functional outcomes. Recently, stereotactic laser amygdalohippocampectomy (SLAH) has been introduced as a minimally-invasive alternative that could minimize risk of cognitive decline. However, it is unclear which patients would benefit from SLAH and in which cognitive domains. During the initial grant funding period, we demonstrated the clinical value of combining information from structural, diffusion and functional imaging to better characterize the neural networks that underlie preoperative language (re)organization and impairment in TLE. We propose that the same multimodal imaging (MMI) approach can be used to quantify risk for postoperative cognitive decline. In this competing renewal application we expand our research in several key ways. First, we address how MMI can be used to predict postoperative outcomes in three important cognitive domains: language, memory, and executive functioning. Second, we evaluate how MMI can be used to quantify risk for cognitive decline following ATL versus SLAH. In a preliminary analysis, we will also evaluate whether postoperative reorganization occurs in a subset of patients that may further influence cognitive outcomes. These goals will be accomplished using the following methods. First, neural activations will be examined in frontal, temporal, and parietal regions using task-related and resting state functional MRI (fMRI) to probe the brain networks that underlie language, memory, and executive functioning in patients with TLE. Second, the integrity of critical white matter fibe tracts will be quantified using an advanced diffusion technique, restriction spectrum imaging (RSI). Third, hippocampal volumes will be quantified from structural MRI (sMRI). Fourth, information from fMRI, RSI, and sMRI will be combined to predict individual risk for surgically-induced cognitive changes on measures of language, memory, and executive functioning. The goals of this renewal are perfectly aligned with the 2014 NINDS Benchmarks for Epilepsy Research (Part IV, Limit or prevent adverse consequences of seizures and their treatment across the lifespan), which encourage mitigating the effects of surgical interventions on cognitive co-morbidities in epilepsy. Our renewal directly addresses this request, striving to improve surgical decision-making, which will have an immediate and sustained impact on patient care. Epilepsy is a common neurological disease that costs the healthcare system approximately $15.5 billion annually and can negatively impact quality of life, employment, and health status. The current project has strong implications for public health because it strives to improve health outcomes in patients with epilepsy by using advanced, noninvasive technology to identify individual predictors of cognitive decline that can help to guide surgical decisions an possibly reduce morbidity associated with removal of eloquent cortex.
This project will investigate how advanced, non-invasive neuroimaging can be used to predict postoperative cognitive changes in patients with epilepsy as a function of the type of surgery they receive. This research will be accomplished by combining information from functional magnetic resonance imaging, advanced diffusion imaging, and structural MRI to understand which brain networks contribute to different cognitive skills and how different types of surgery would impact each skill. The information gained from this investigation may facilitate surgical planning and reduce the potential for postoperative cognitive decline in patients with epilepsy.
|Karunamuni, Roshan A; White, Nathan S; McDonald, Carrie R et al. (2017) Multi-component diffusion characterization of radiation-induced white matter damage. Med Phys 44:1747-1754|
|Delfanti, Rachel L; Piccioni, David E; Handwerker, Jason et al. (2017) Imaging correlates for the 2016 update on WHO classification of grade II/III gliomas: implications for IDH, 1p/19q and ATRX status. J Neurooncol 135:601-609|
|Chang, Yu-Hsuan A; Kemmotsu, Nobuko; Leyden, Kelly M et al. (2017) Multimodal imaging of language reorganization in patients with left temporal lobe epilepsy. Brain Lang 170:82-92|
|Karunamuni, Roshan A; Seibert, Tyler M; White, Nathan S et al. (2017) Abnormalities in hippocampal volume of glioma patients prior to radiotherapy. Acta Oncol 56:427-430|
|Graves, Lisa V; Moreno, Charles C; Seewald, Michelle et al. (2017) Effects of Age and Gender on Recall and Recognition Discriminability. Arch Clin Neuropsychol 32:972-979|
|Seibert, Tyler M; Karunamuni, Roshan; Kaifi, Samar et al. (2017) Cerebral Cortex Regions Selectively Vulnerable to Radiation Dose-Dependent Atrophy. Int J Radiat Oncol Biol Phys 97:910-918|
|Connor, Michael; Karunamuni, Roshan; McDonald, Carrie et al. (2017) Regional susceptibility to dose-dependent white matter damage after brain radiotherapy. Radiother Oncol 123:209-217|
|Reyes, Anny; Thesen, Thomas; Kuzniecky, Ruben et al. (2017) Amygdala enlargement: Temporal lobe epilepsy subtype or nonspecific finding? Epilepsy Res 132:34-40|
|Seibert, Tyler M; Karunamuni, Roshan; Bartsch, Hauke et al. (2017) Radiation Dose-Dependent Hippocampal Atrophy Detected With Longitudinal Volumetric Magnetic Resonance Imaging. Int J Radiat Oncol Biol Phys 97:263-269|
|Krishnan, A P; Karunamuni, R; Leyden, K M et al. (2017) Restriction Spectrum Imaging Improves Risk Stratification in Patients with Glioblastoma. AJNR Am J Neuroradiol 38:882-889|
Showing the most recent 10 out of 34 publications