Oliver C. Kiersnowski¹, Gavin P. Winston^2,3, Emma Biondetti^1,4, Sarah Buck², Lorenzo Caciagli^2,5, John Duncan², Karin Shmueli¹, and Sjoerd B. Vos^6,7
1Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ²Department for Clinical and Experimental Epilepsy, University College London, London, United Kingdom, ³Department of Medicine, Division of Neurology, Queen's University, Kingston, ON, Canada, ⁴Institut du Cerveau – ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Université, Paris, France, ⁵Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States, ⁶Centre for Medical Image Computing, Computer Science Department, University College London, London, United Kingdom, ⁷Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom

Although temporal lobe epilepsy (TLE) results in widespread changes in MRI measures of tissue volume, diffusion and functional connectivity, changes in tissue composition in TLE have not been investigated with MRI. Quantitative susceptibility mapping (QSM) is sensitive to  changes in tissue composition, in particular to iron and myelin. Here, we show for the first time that QSM is sensitive to gray matter abnormalities in 31 patients with temporal lobe epilepsy (TLE) compared to 23 healthy controls, and showed significant susceptibility changes in the hippocampus in left TLE patients, and in the bilateral thalamus in both left and right TLE.  

Sami Obaid^1,2, Françcois Rheault^2,3, Manon Edde², Guido Guberman⁴, Etienne St-Onge², Jasmeen Sidhu², Alain Bouthillier⁵, Alessandro Daducci⁶, Dang Khoa Nguyen⁷, and Maxime Descoteaux^2
1Department of Neurosciences, Université de Montréal, Montréal, Quebec, Canada, Montréal, QC, Canada, ²Sherbrooke Connectivity Imaging Lab (SCIL), Université de Sherbrooke, Sherbrooke, Quebec, Canada, Sherbrooke, QC, Canada, ³Electrical Engineering, Vanderbilt University, Nashville, TN, United States, Nashville, TN, United States, ⁴Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada, Montreal, QC, Canada, ⁵Division of Neurosurgery, CHUM, Montréal, Quebec, Canada, Montreal, QC, Canada, ⁶Department of Computer Science, University of Verona, Verona, Italy, Verona, Italy, ⁷Service de Neurologie, CHUM, Montréal, Québec, Canada, Montreal, QC, Canada

Operculo-insular epilepsy (OIE) is a rare and under-diagnosed pathology due to its heterogeneous presentation. Interestingly, no studies have looked at the structural connectome in OIE. In this study, we used a cutting-edge diffusion MRI processing pipeline to evaluate the connectivity pattern of OIE. The filtering-based COMMIT weight obtained from surface-enhanced tractography was used as a marker of ‘connectivity strength’. We found an increase in ‘connectivity strength’ within the epileptic network of OIE.  Moreover, the pattern of connectivity was distinct from the one of TLE, potentially constituting a tool to help differentiate OIE from the closely related and challengingly distinguishable TLE.

Hiroyuki Tatekawa¹, Hiroyuki Uetani¹, Akifumi Hagiwara¹, and Noriko Salamon^1
1UCLA, Los Angeles, CA, United States

To assess associations between hypometabolic extensions of  FDG PET and DTI, including MD and FA, 36 unilateral hippocampal sclerosis were stratified into broad hypometabolic (n=26) and localized groups (n=10) by the extension of FDG hypometabolism beyond or within the temporal lobe. Gray matter (GM) ROIs and TBSS were used to compare MD of GM and FA of white matter (WM) between hemispheres ipsilateral and contralateral to epilepsy focus. Associations between hypometabolism and DTI alterations, including more widespread GM abnormalities for broad than localized groups and significantly decreased FA in the temporal and frontal WM for broad group, were identified.

Qingqing Wen¹, Kang Wang², Yi-Cheng Hsu³, Yan Xu⁴, Yi Sun³, Dan Wu^1,2, and Yi Zhang^1,2
1Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, ²Department of Neurology, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China, ³MR Collaboration, Siemens Healthcare Ltd., Shanghai, China, ⁴Department of Neurosurgery, Zhejiang Provincial People's Hospital, HangZhou, China

  A 2-stage simulation method was proposed to estimate the leading contributor to the CEST contrast between disease and normal tissues. First, the proposed method generates a best Bloch-McConnell fit to the MTR_asym spectra of the normal brain tissues. Second, it alters only one exchange parameter in the Bloch-McConnell model to fit the MTR_asym spectra of disease tissues each time. The candidate parameter that yields the smallest error between simulated and experimental results is identified as the leading contributor to the CEST contrast. The proposed method was validated in numeric phantoms and 9 tuberous sclerosis complex (TSC)-associated epilepsy patients. 

Kiarash Ghassaban^1,2, Chao Chai³, Huiying Wang⁴, Tong Zhang³, Jinxia Zhu⁵, Xianchang Zhang⁵, E. Mark Haacke^1,2, and Shuang Xia^3
1Department of Radiology, Wayne State University, Detroit, MI, United States, ²SpinTech, Inc., Bingham Farms, MI, United States, ³Department of Radiology, Tianjin First Central Hospital, Tianjin, China, ⁴Department of Neurology, Tianjin Medical University General Hospital Airport Site, Tianjin, China, ⁵MR Collaboration, Siemens Healthcare Ltd, Beijing, China

Out of 29 idiopathic rapid eye movement behavior disorder (iRBD) patients and 28 age-matched healthy controls (HCs), 12 patients showed bilateral or unilateral loss of the N1 sign as opposed to two HCs with unilateral N1 loss. Additionally, both global and regional high susceptibility analyses showed significantly higher iron deposition in the right dentate nucleus (DN) along with significantly lower bilateral volume of the caudate nucleus in iRBD patients. These findings taken together with significant correlations between iron measurements and several cognitive and motor impairment scores may be indicative of biomarkers of an early neurodegenerative process in the iRBD patients.

Soroor Kalantari¹, Fardin Samadi Khosh Mehr², Mohammad Soltani¹, Mehdi Maghbooli³, Zahra Rezaei⁴, Soheila Borji¹, Behzad Memari¹, Mohammad Bayat¹, Behnaz Eslami⁵, and Hamidreza Saligheh Rad^6
1Department of Radiology, Zanjan University of Medical Science, Zanjan, Iran (Islamic Republic of), ²Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of), ³Department of Neurology, Zanjan University of Medical Science, Zanjan, Iran (Islamic Republic of), ⁴Department of Computer and Electrical Engineering, University of Kashan, Kashan, Iran (Islamic Republic of), ⁵Tehran Islamic Azad University, Tehran, Iran (Islamic Republic of), ⁶Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Department of Medical Physics and Biomedical Engineering, Tehran university of Medical Science, Tehran, Iran (Islamic Republic of)

This study aims to investigate the use of high-level de-noising and machine-learning methods applied on ASL-MRI dataset acquired at 1.5T, and in order to to find important regions in the brain for the classification of patients with AD and MCI and normal aging. Automated classification and prediction methods recognizing perfusion changes in specific subregions of the brain are applied to pseudo-continuous ASL-derived CBF-maps, predicting the diagnosis of Alzheimer's disease, mild cognitive impairment, and normal cognition. Due to alarming prevalence of AD, machine-learning approaches for ASL- MRI are used to develop computer-aided diagnosis (CAD) tools for clinical and screening targets, assisting early diagnosis of the AD process.

Ryan McNaughton¹, Hernan Jara^1,2, Chris Pieper², Julie Rollins³, Osamu Sakai², Laurie Douglass², Rebecca Fry³, Karl Kuban², and T. Michael O'Shea^3
1Boston University, Boston, MA, United States, ²Boston University Medical Center, Boston, MA, United States, ³University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, United States

Purpose: To describe the spectrum of MS-qMRI outcomes in the extremely preterm (EP) brain at adolescence and identify relationships expressed as a result of dysmaturation. Methods: Quantitative MR algorithms create maps of the T1, T2, PD, and spatial entropy (SE) for 341 EP born individuals using MR images obtained with the Tri-TSE pulse sequence at age 15 years. Results: The EP brain exhibits linear relationships of T1 and PD with SE, and T2 with cerebrospinal fluid (CSF) volume. Conclusion: MS-qMRI of the EP brain provides a comprehensive quantification of dysmaturation states, from white matter structure to CSF composition.

Nareen Anwar¹, Wesley J Tucker², Nancy Puzziferri³, Jake Samuel², Vlad G Zaha³, Ildiko Lingvay³, Jaime Almandoz³, Jing Wang², Edward A Gonzales², Matthew Brothers², Michael Douglas Nelson², and Binu P Thomas^2,3
1The University of Texas at Dallas, Richardson, TX, United States, ²The University of Texas at Arlington, Arlington, TX, United States, ³University of Texas Southwestern Medical Center, Dallas, TX, United States

Obesity is an ongoing epidemic that is associated with cognitive dysfunction and is a prominent precursor to a variety of neurogenerative diseases. Bariatric surgery is an effective and long-term weight loss strategy that can improve neurocognitive function. However, the mechanisms that drive these improvements are unknown. In this study, magnetic resonance imaging (MRI) is utilized to assess changes in cerebral metabolic rate of oxygen (CMRO₂) levels in bariatric surgery candidates before and after their surgery. These values are compared with normal healthy weight controls of a similar age and reassessed after 2 weeks and 14 weeks. 

Maxime Chamberland¹, Dmitri Shastin^1,2, Sila Genc¹, Khalid Hamandi^1,3, William P. Gray^1,2, Chantal M.W Tax¹, and Derek K. Jones^1
1Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom, ²Department of Neurosurgery, University Hospital Wales, Cardiff, United Kingdom, ³Department of Neurology, University Hospital of Wales, Cardiff, United Kingdom

Most clinical diffusion MRI (dMRI) applications rely on statistical comparisons between large groups of patients and healthy controls to infer altered tissue state. For clinicians and researchers studying small datasets, rare cases, or individual patients, this approach is clearly inappropriate. We recently developed a framework to advance dMRI-based tractometry towards single-subject analysis. By 1) operating on the manifold of white matter pathways and by 2) learning normative microstructural features to better discriminate patients from controls, our framework successfully identified idiosyncrasies in patterns along brain white matter pathways in individuals with focal cortical dysplasia (FCD).

Jeong-Won Jeong¹, Soumyanil Banerjee², Min-Hee Lee¹, Nolan O'Hara³, Csaba Juhasz¹, Eishi Asano¹, and Ming Dong^2
1Pediatrics, Wayne State University, Detroit, MI, United States, ²Computer Science, Wayne State University, Detroit, MI, United States, ³Translational Neuroscience Program, Wayne State University, Detroit, MI, United States

We propose a deep learning-based DWI connectome (DWIC) analytic method, characterized by convolutional neural network combined with graph convolutional network. This method trained DWIC features to predict the severity of expressive and receptive language impairment, defined by the clinical evaluation of language fundamentals test. It outperformed other state-of-the-art deep learning approaches in predicting the expressive/receptive language scores in children with focal epilepsy. It also demonstrated the smallest prediction error without a noticeable variation in the random permutation test. Further investigation is warranted to determine the feasibility of a DWIC-based prognostic biomarker of language impairment in clinical practice.  

Wenjing Zhang¹, Tao Yu², Mengyuan Xu¹, Chengmin Yang¹, Naici Liu¹, Su Lui¹, and Haibo Qu^3
1Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, ²Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China, ³Department of Radiology, Key Laboratory of Obstetric & Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, National Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, China

In the present study, a data-driven analysis of structural MRI data was conducted with pediatric epilepsy patients. We first resolve neurobiological heterogeneity based on neuroanatomical features, and then investigate the clinical relevance of using MRI data to predict seizure relapse status after treatment in each identified patient subgroup. Our study limits the influence of treatment and course of illness effects, potentially enhancing the ability to identify illness-specific biomarkers that delineate patient subgroups, and can also be used to evaluate the utility of such biomarkers in predicting illness progression and treatment response.

Laleh Eskandarian^1,2, Safak Parlak³, Gokce Ayhan⁴, Irsel Tezer⁴, Serap Saygi⁴, and Kader Karli Oguz^2,3
1Neuroscience Department, Bilkent University, Ankara, Turkey, ²National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara, Turkey, ³Faculty of Medicine, Department of Radiology, Hacettepe University, Ankara, Turkey, ⁴Faculty of Medicine, Department of Neurology, Hacettepe University, Ankara, Turkey

This study investigates morphological alterations in patients with left temporal lobe epilepsy (TLE) due to ipsilateral antero-inferior temporal lobe meningoencephalocele (TLM). Compared with healthy control (HC)s, cortical thickness was increased extensively in both cerebral hemispheres with reduction in a few regions, most remarkably in the left temporal lobe. Both amygdala were significantly bigger in the patients compared with HCs. No difference was found in hippocampi and thalami between patients and HCs or between hemispheres within the patient group. No relation was found between these significant alterations and duration of disease.

Alireza Fallahi¹, Neda Mohammadi-Mobarakeh², Narges Hosseini Tabatabaei³, Mohammad Pooyan⁴, Jafar Mehvari-Habibabadi⁵, Mohammad-Reza Ay², and Mohammad-Reza Nazem-Zadeh^2
1Shahed University, Tehran, Iran (Islamic Republic of), ²Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of), ³Brain and Spinal Cord Injury Research Centre, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of), ⁴Biomedical Engineering Department, Shahed University, Tehran, Iran (Islamic Republic of), ⁵dr.mehvari@hotmail.com, Isfahan, Iran (Islamic Republic of)

In this study, a decision making method was developed for determination epileptogenicity in mesial temporal lobe epilepsy (mTLE) patients using different neuroimaging markers including hippocampal volume, and FLAIR (Fluid Attenuated Inversion Recovery) intensity and MD (Mean Diffusivity) value in hippocampus, FA (Fractional anisotropy) in posteroinferior cingulum, and FA in crus of fornix from MRI images of T1, FLAIR, and DTI (diffusion tensor imaging). The aim of this study is to creating an automated classification algorithm using decision tree and random forest methods. Result of applied method detected essential rules for prediction of laterality in individual mTLE patients.

Hui Huang¹, Miao Zhang², Wei Liu³, Jia Wang¹, Lihong Tang¹, Qikang Li¹, Biao Li², and Jie Luo^1
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, ²Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, ³Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

Both PET and T2 relaxometry could provide complementary information of the epileptogenic zone, which could add value to presurgical planning of epilepsy patients. This study investigated evaluted the performance of hippocampual asymmetry measures from volumetry, T2 relaxometry and ¹⁸F-FDG PET in lateralization for MR negative left from right temporal TLE. We also investigated how hippocampal subfield alterations of T2 relaxometry and ¹⁸F-FDG-PET. Our experimental results showed the combination of T2 relaxometry and PET could complement each other in lateralization for MR-negative LTLE.

Xinyue Wan¹, Xiaorui Su¹, Simin Zhang¹, Qiyong Gong¹, and Qiang Yue^2
1Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, ²Department of Radiology, West China Hospital of Sichuan University, Chengdu, China

The neurobiochemical mechanisms of Generalized tonic-clonic seizures (GTCS) patients' brains and the effects of antiepileptic drugs (AEDs) on metabolism are not yet clear. The purpose of this study was to use MRS to explore metabolic alterations of bilateral Dorsolateral prefrontal cortex (DLPFC) in pre-/post-treatment GTCS patients. We included 23 initially diagnosed GTCS patients and 23 healthy controls (HC). The metabolite level (n-acetyl aspartate, creatine) in DLPFC of GTCS patients was changed compared with that of healthy control, and AEDs had an effect on the metabolites concentration, which may explain the neurobiochemical mechanism.

Baptiste MOREL^1,2, Anne Sophie Piegay¹, Maximilien Perivier¹, Sandra Obry¹, Bénédicte Maréchal^3,4,5, Gian Franco Piredda^3,4,5, Tom Hilbert^3,4,5, Tobias Kober^3,4,5, Clovis Tauber⁶, Pierre Castelnau⁶, and Jean Philippe Cottier^1
1CHU de Tours, Tours, France, ²UMR 1253, iBrain, Université de Tours, INSERM, Tours, France, ³Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, ⁴Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ⁵LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ⁶INSERM U1253, Tours, France

In the initial exploration of children with focal epilepsy of unknown cause, MRI is useful. To increase the sensitivity of the MRI, we have defined a postprocessing Morphometric Analysis Program allowed obtaining automatically both volumetry and T1 relaxometry values in 38 brain regions. Deviations from reference ranges – previously established from a cohort of healthy subjects – help radiologists to quantify brain abnormalities undetected in brain MRI in more than 80% of our cases.

Lijing Xin^1,2, Philippe Reymond³, José Boto³, Serge Vulliemoz⁴, Francois Lazeyras ⁵, and Maria Isabel Vargas^3
1CIBM Center for Biomedical Imaging, Lausanne, Switzerland, ²Animal Imaging and Technology, EPFL, Lausanne, Switzerland, ³Division of Neuroradiology, Diagnostic Department of Geneva University Hospitals and University of Geneva, Geneva, Switzerland, ⁴Division of Neurology, Neurosciences Department of Geneva University Hospitals and University of Geneva, Geneva, Switzerland, ⁵Center for Biomedical Imaging of Geneva and University of Geneva, Geneva, Switzerland

This study is aim to evaluate the neurochemical characteristics of pathological tissues by 1H MRS in patient with epilepsy at 7T. In comparison to the contralateral side, lesions in focal cortical dysplasia demonstrated significantly reduced macromolecule and N-acetyl aspartate, significantly increased total choline and glycine + myo-inositol, and a distinct reduction trend of glutamate. We conclude that performing MRS at high magnetic field offered the potential to reveal novel metabolic alterations in epilepsy lesions that may help to further understand the underlying pathophysiology of the disease.  

Austin Bazydlo¹, Steven Kecskemeti², Aaron Cochrane³, Thomas Gorman⁴, Bas Rokers⁵, Douglas Dean^1,6, C. Shawn Green³, and Andrew Alexander^1,2,7
1Medical Physics, UW-Madison, Madison, WI, United States, ²Waisman Center for Brain Imaging, UW-Madison, Madison, WI, United States, ³Psychology, UW-Madison, Madison, WI, United States, ⁴Psychology, Indiana University-Bloomington, Bloomington, IN, United States, ⁵Psychology, NYU-Abu Dhabi, Abu Dhabi, United Arab Emirates, ⁶Pediatrics, UW-Madison, Madison, WI, United States, ⁷Psychiatry, UW-Madison, Madison, WI, United States

Two video games, Need for Speed and Guitar Hero, were used as training tasks for two groups of college-aged, typically developing participants over 4 weeks and 10 total hours of training. Imaging was acquired before and after the first training session and upon completion of the last training session. The robust MPnRAGE sequence, which produces hundreds of T1 contrasts, was used to generate quantitative R1 maps. Longitudinal changes of R1 were observed in several parietal and temporal lobe areas, which may indicate a neuroplastic response due to video game training. 

Ronald J Beyers¹, Adil Bashir¹, and Thomas S Denney^1
1MRI Research Center, Auburn University, Auburn University, AL, United States

The growing occurrence of Alzheimer’s disease (AD) and other cognitive debilitating disease drive the need for improved neuro MRI methods at 7 Tesla.  Here we present an agile multi-frequency magnetization transfer (MFMT) method for improved high resolution 3D MRI of the human hippocampus at 7T.  Demonstration of MFMT on healthy volunteers quantified improved hippocampal contrast by a factor of 2.06 (p < 0.004).

Salem Alkhateeb¹, Tales Santini², Regina Leckie², nadim farhat², Peter J Gianaros², Anna L Marsland², Stephen B Manuck², and Tamer S Ibrahim^2
1Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States, ²University of Pittsburgh, Pittsburgh, PA, United States

As hippocampal volume has been extensively utilized as a diagnosing tool to confirm diagnosis of many neurological disorders, this study aims to employ the high resolution 7T data to segment the hippocampal subfields then correlate their volumes with the age of healthy adults’ population.  The region encompassing the subregions left DG, CA2, and CA3 showed significant correlation with age, with a volume variation of approximately -1% per year. Other regions presented a trend towards reductions that did turn into significant. Future work will investigate if differences in the hippocampus subfields are correlated with cognitive performance in this population.