Imaging in Epilepsy: Current Clinical Practice and Future Directions

Abstract

Neuroimaging is an essential part of epilepsy diagnosis and management. In this review, we examine the shift in our understanding of epilepsy from a focal, lesional-centric process to a broader, network-based disorder and how it has affected the acquisition and interpretation of neuroimaging for epilepsy diagnosis and management. We discuss the current clinical practice of neuroimaging in epilepsy, both in terms of acquisitions and interpretation, through computed tomography, magnetic resonance imaging (including structural, diffusion, functional, and high-field), magnetoencephalography, and nuclear and metabolic imaging. Additionally, we look ahead to some of the latest research advances in both the acquisition and analysis of these different neuroimaging modalities to help promote the eventual goal of a consolidated, multi-modality imaging approach to understanding, diagnosing, and treating epilepsy.

Keywords

epilepsy - neuroimaging - MRI - MEG - PET

Publication History

Received: 18 July 2025

Accepted: 02 December 2025

Article published online:
07 January 2026

• References

• 1 Bernasconi A, Bernasconi N. The role of MRI in the treatment of drug-resistant focal epilepsy. Eur Neurol 2022; 85 (05) 333-341
• 2 Bernasconi N, Wang I. Emerging trends in neuroimaging of epilepsy. Epilepsy Curr 2021; 21 (02) 79-82
• 3 Krumholz A, Wiebe S, Gronseth GS. et al. Evidence-based guideline: management of an unprovoked first seizure in adults: report of the guideline development subcommittee of the American Academy of Neurology and the American Epilepsy Society. Neurology 2015; 84 (16) 1705-1713
• 4 Yoganathan K, Malek N, Torzillo E, Paranathala M, Greene J. Neurological update: structural and functional imaging in epilepsy surgery. J Neurol 2023; 270 (05) 2798-2808
• 5 Tavakol S, Royer J, Lowe AJ. et al. Neuroimaging and connectomics of drug-resistant epilepsy at multiple scales: From focal lesions to macroscale networks. Epilepsia 2019; 60 (04) 593-604
• 6 King MA, Newton MR, Jackson GD. et al. Epileptology of the first-seizure presentation: a clinical, electroencephalographic, and magnetic resonance imaging study of 300 consecutive patients. Lancet 1998; 352 (9133) 1007-1011
• 7 Crocker CE, Pohlmann-Eden B, Schmidt MH. Role of neuroimaging in first seizure diagnosis. Seizure 2017; 49: 74-78
• 8 Adams SM, Knowles PD. Evaluation of a first seizure. Am Fam Physician 2007; 75 (09) 1342-1347
• 9 Jallon P, Loiseau P, Loiseau J. l'Epilepsie) on behalf of GC (Coordination A du ROL de. Newly diagnosed unprovoked epileptic seizures: presentation at diagnosis in CAROLE study. Epilepsia 2001; 42 (04) 464-475
• 10 Daghistani R, Widjaja E. Role of MRI in patient selection for surgical treatment of intractable epilepsy in infancy. Brain Dev 2013; 35 (08) 697-705
• 11 Phal PM, Usmanov A, Nesbit GM. et al. Qualitative comparison of 3-T and 1.5-T MRI in the evaluation of epilepsy. AJR Am J Roentgenol 2008; 191 (03) 890-895
• 12 Coan AC, Kubota B, Bergo FPG, Campos BM, Cendes F. 3T MRI quantification of hippocampal volume and signal in mesial temporal lobe epilepsy improves detection of hippocampal sclerosis. AJNR Am J Neuroradiol 2014; 35 (01) 77-83
• 13 Jarosiewicz B, Morrell M. The RNS system: brain-responsive neurostimulation for the treatment of epilepsy. Expert Rev Med Devices 2021; 18 (02) 129-138
• 14 Nair DR, Laxer KD, Weber PB. et al; RNS System LTT Study. Nine-year prospective efficacy and safety of brain-responsive neurostimulation for focal epilepsy. Neurology 2020; 95 (09) e1244-e1256
• 15 Salanova V. Deep brain stimulation for epilepsy. Epilepsy Behav 2018; 88S: 21-24
• 16 Englot DJ, Chang EF, Auguste KI. Vagus nerve stimulation for epilepsy: a meta-analysis of efficacy and predictors of response. J Neurosurg 2011; 115 (06) 1248-1255
• 17 Salanova V, Sperling MR, Gross RE. et al; SANTÉ Study Group. The SANTÉ study at 10 years of follow-up: effectiveness, safety, and sudden unexpected death in epilepsy. Epilepsia 2021; 62 (06) 1306-1317
• 18 Wiebe S, Blume WT, Girvin JP, Eliasziw M. Effectiveness and Efficiency of Surgery for Temporal Lobe Epilepsy Study Group. A randomized, controlled trial of surgery for temporal-lobe epilepsy. N Engl J Med 2001; 345 (05) 311-318
• 19 Rathore C, Dickson JC, Teotónio R, Ell P, Duncan JS. The utility of 18F-fluorodeoxyglucose PET (FDG PET) in epilepsy surgery. Epilepsy Res 2014; 108 (08) 1306-1314
• 20 Benjamin CFA, Li AX, Blumenfeld H. et al. Presurgical language fMRI: clinical practices and patient outcomes in epilepsy surgical planning. Hum Brain Mapp 2018; 39 (07) 2777-2785
• 21 Benjamin CFA, Dhingra I, Li AX. et al. Presurgical language fMRI: technical practices in epilepsy surgical planning. Hum Brain Mapp 2018; 39 (10) 4032-4042
• 22 Willmann O, Wennberg R, May T, Woermann FG, Pohlmann-Eden B. The contribution of 18F-FDG PET in preoperative epilepsy surgery evaluation for patients with temporal lobe epilepsy: a meta-analysis. Seizure 2007; 16 (06) 509-520
• 23 Alomar S, Jones J, Maldonado A, Gonzalez-Martinez J. The stereo-electroencephalography methodology. Neurosurg Clin N Am 2016; 27 (01) 83-95
• 24 Téllez-Zenteno JF, Hernández Ronquillo L, Moien-Afshari F, Wiebe S. Surgical outcomes in lesional and non-lesional epilepsy: a systematic review and meta-analysis. Epilepsy Res 2010; 89 (2-3): 310-318
• 25 DenOtter TD, Schubert J. Hounsfield Unit. In: StatPearls. StatPearls Publishing; 2025. . Accessed February 27, 2025 at: http://www.ncbi.nlm.nih.gov/books/NBK547721/
• 26 Pohlmann-Eden B, Newton M. First seizure: EEG and neuroimaging following an epileptic seizure. Epilepsia 2008; 49 (Suppl. 01) 19-25
• 27 Bernasconi A, Cendes F, Theodore WH. et al. Recommendations for the use of structural magnetic resonance imaging in the care of patients with epilepsy: a consensus report from the international league against epilepsy neuroimaging task force. Epilepsia 2019; 60 (06) 1054-1068
• 28 Ho K, Lawn N, Bynevelt M, Lee J, Dunne J. Neuroimaging of first-ever seizure: contribution of MRI if CT is normal. Neurol Clin Pract 2013; 3 (05) 398-403
• 29 Josephson CB, Rosenow F, Al-Shahi Salman R. Intracranial vascular malformations and epilepsy. Semin Neurol 2015; 35 (03) 223-234
• 30 Horn A, Li N, Dembek TA. et al. Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging. Neuroimage 2019; 184: 293-316
• 31 van Rooijen BD, Backes WH, Schijns OEMG, Colon A, Hofman PAM. Brain imaging in chronic epilepsy patients after depth electrode (stereoelectroencephalography) implantation: magnetic resonance imaging or computed tomography?. Neurosurgery 2013; 73 (03) 543-549
• 32 Plewes DB, Kucharczyk W. Physics of MRI: a primer. J Magn Reson Imaging 2012; 35 (05) 1038-1054
• 33 Pai A, Shetty R, Hodis B, Chowdhury YS. Magnetic Resonance Imaging Physics. In: StatPearls. StatPearls Publishing; 2025. . Accessed February 27, 2025 at: http://www.ncbi.nlm.nih.gov/books/NBK564320/
• 34 Babaeeghazvini P, Rueda-Delgado LM, Gooijers J, Swinnen SP, Daffertshofer A. Brain structural and functional connectivity: a review of combined works of diffusion magnetic resonance imaging and electro-encephalography. Front Hum Neurosci 2021; 15: 721206
• 35 Lucas A, Cornblath EJ, Sinha N. et al. Resting state functional connectivity demonstrates increased segregation in bilateral temporal lobe epilepsy. Epilepsia 2023; 64 (05) 1305-1317
• 36 Lucas A, Mouchtaris S, Cornblath EJ. et al. Subcortical functional connectivity gradients in temporal lobe epilepsy. Neuroimage Clin 2023; 38: 103418
• 37 Kronlage C, Heide EC, Hagberg GE. et al. MP2RAGE vs. MPRAGE surface-based morphometry in focal epilepsy. PLoS One 2024; 19 (02) e0296843
• 38 Lee EJ, Kim MG, Chung MS, Kim SO, Byun JS, Yim Y. Diagnosis of intracranial lesions using accelerated 3D T1 MPRAGE with wave-CAIPI technique: comparison with conventional 3D T1 MPRAGE. Sci Rep 2022; 12 (01) 21930
• 39 Santana LM, Valadares EJA, Rosa-Júnior M. Differential diagnosis of temporal lobe lesions with hyperintense signal on T2-weighted and FLAIR sequences: pictorial essay. Radiol Bras 2020; 53 (02) 129-136
• 40 Sudhyadhom A, Haq IU, Foote KD, Okun MS, Bova FJ. A high resolution and high contrast MRI for differentiation of subcortical structures for DBS targeting: the fast gray matter acquisition T1 inversion recovery (FGATIR). Neuroimage 2009; 47 (Suppl. 02) T44-T52
• 41 Grewal SS, Middlebrooks EH, Kaufmann TJ. et al. Fast gray matter acquisition T1 inversion recovery MRI to delineate the mammillothalamic tract for preoperative direct targeting of the anterior nucleus of the thalamus for deep brain stimulation in epilepsy. Neurosurg Focus 2018; 45 (02) E6
• 42 Hoch MJ, Shepherd TM. MRI-visible anatomy of the basal ganglia and thalamus. Neuroimaging Clin N Am 2022; 32 (03) 529-541
• 43 Widdess-Walsh P, Diehl B, Najm I. Neuroimaging of Focal Cortical Dysplasia. Accessed February 28, 2025 at: https://onlinelibrary.wiley.com/doi/10.1111/j.1552-6569.2006.00025.x
• 44 Alves IS, Coutinho AMN, Vieira APF. et al. Imaging aspects of the hippocampus. Radiographics 2022; 42 (03) 822-840
• 45 Porto L, Jurcoane A, Schwabe D, Hattingen E. Conventional magnetic resonance imaging in the differentiation between high and low-grade brain tumours in paediatric patients. Eur J Paediatr Neurol 2014; 18 (01) 25-29
• 46 Ellingson BM, Wen PY, Cloughesy TF. Evidence and context of use for contrast enhancement as a surrogate of disease burden and treatment response in malignant glioma. Neuro-oncol 2018; 20 (04) 457-471
• 47 Zhang H, Zhang B, Pan W. et al. Preoperative contrast-enhanced MRI in differentiating glioblastoma from low-grade gliomas in the cancer imaging archive database: a proof-of-concept study. Front Oncol 2022; 11: 761359
• 48 Geevarghese R, O'Gorman Tuura R, Lumsden DE, Samuel M, Ashkan K. Registration accuracy of CT/MRI fusion for localisation of deep brain stimulation electrode position: an imaging study and systematic review. Stereotact Funct Neurosurg 2016; 94 (03) 159-163
• 49 Barnaure I, Pollak P, Momjian S. et al. Evaluation of electrode position in deep brain stimulation by image fusion (MRI and CT). Neuroradiology 2015; 57 (09) 903-908
• 50 Lucas A, Scheid BH, Pattnaik AR. et al. iEEG-recon: a fast and scalable pipeline for accurate reconstruction of intracranial electrodes and implantable devices. Epilepsia 2024; 65 (03) 817-829
• 51 Soper DJ, Reich D, Ross A. et al. Modular pipeline for reconstruction and localization of implanted intracranial ECoG and sEEG electrodes. PLoS One 2023; 18 (07) e0287921
• 52 Billot B, Greve DN, Puonti O. et al; ADNI. SynthSeg: segmentation of brain MRI scans of any contrast and resolution without retraining. Med Image Anal 2023; 86: 102789
• 53 Arnold TC, Freeman CW, Litt B, Stein JM. Low-field MRI: clinical promise and challenges. J Magn Reson Imaging 2023; 57 (01) 25-44
• 54 Fischl B. FreeSurfer. Neuroimage 2012; 62 (02) 774-781
• 55 Ashburner J. SPM: a history. Neuroimage 2012; 62 (02) 791-800
• 56 Jenkinson M, Beckmann CF, Behrens TEJ, Woolrich MW, Smith SM. FSL. Neuroimage 2012; 62 (02) 782-790
• 57 Avants BB, Tustison NJ, Song G, Cook PA, Klein A, Gee JC. A reproducible evaluation of ANTs similarity metric performance in brain image registration. Neuroimage 2011; 54 (03) 2033-2044
• 58 Hadar PN, Kini LG, Coto C. et al. Clinical validation of automated hippocampal segmentation in temporal lobe epilepsy. Neuroimage Clin 2018; 20: 1139-1147
• 59 Whelan CD, Altmann A, Botía JA. et al. Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study. Brain 2018; 141 (02) 391-408
• 60 Lui YW, Chang PD, Zaharchuk G. et al. Artificial intelligence in neuroradiology: current status and future directions. AJNR Am J Neuroradiol 2020; 41 (08) E52-E59
• 61 Gleichgerrcht E, Munsell B, Keller SS. et al. Radiological identification of temporal lobe epilepsy using artificial intelligence: a feasibility study. Brain Commun 2021; 4 (02) fcab284
• 62 Aboian M, Bousabarah K, Kazarian E. et al. Clinical implementation of artificial intelligence in neuroradiology with development of a novel workflow-efficient picture archiving and communication system-based automated brain tumor segmentation and radiomic feature extraction. Front Neurosci 2022; 16: 860208
• 63 Detre JA. fMRI: applications in epilepsy. Epilepsia 2004; 45 (Suppl. 04) 26-31
• 64 Appel S, Duke ES, Martinez AR. et al. Cerebral blood flow and fMRI BOLD auditory language activation in temporal lobe epilepsy. Epilepsia 2012; 53 (04) 631-638
• 65 Mahdavi A, Azar R, Shoar MH, Hooshmand S, Mahdavi A, Kharrazi HH. Functional MRI in clinical practice: assessment of language and motor for pre-surgical planning. Neuroradiol J 2015; 28 (05) 468-473
• 66 O'Donnell CM, Anderson CT, Oleksy AJ, Swanson SJ. A comparison of neuropsychological outcomes following responsive neurostimulation and anterior temporal lobectomy in drug-resistant epilepsy. Brain Sci 2023; 13 (12) 1628
• 67 Chang EF, Englot DJ, Vadera S. Minimally invasive surgical approaches for temporal lobe epilepsy. Epilepsy Behav 2015; 47: 24-33
• 68 Bauer PR, Reitsma JB, Houweling BM, Ferrier CH, Ramsey NF. Can fMRI safely replace the Wada test for preoperative assessment of language lateralisation? A meta-analysis and systematic review. J Neurol Neurosurg Psychiatry 2014; 85 (05) 581-588
• 69 Arora J, Pugh K, Westerveld M, Spencer S, Spencer DD, Todd Constable R. Language lateralization in epilepsy patients: fMRI validated with the Wada procedure. Epilepsia 2009; 50 (10) 2225-2241
• 70 Sathe AV, Matias CM, Kogan M. et al. Resting-state fMRI can detect alterations in seizure onset and spread regions in patients with non-lesional epilepsy: a pilot study. Front Neuroimaging 2023; 2: 1109546
• 71 Sadjadi SM, Ebrahimzadeh E, Shams M, Seraji M, Soltanian-Zadeh H. Localization of epileptic foci based on simultaneous EEG-fMRI data. Front Neurol 2021; 12: 645594
• 72 Fernández-Seara MA, Wang J, Wang Z. et al. Imaging mesial temporal lobe activation during scene encoding: comparison of fMRI using BOLD and arterial spin labeling. Hum Brain Mapp 2007; 28 (12) 1391-1400
• 73 Zeng JY, Hu XQ, Xu JF, Zhu WJ, Wu HY, Dong FJ. Diagnostic accuracy of arterial spin-labeling MR imaging in detecting the epileptogenic zone: systematic review and meta-analysis. AJNR Am J Neuroradiol 2021; 42 (06) 1052-1060
• 74 Schertz M, Benzakoun J, Pyatigorskaya N. et al. Specificities of arterial spin labeling (ASL) abnormalities in acute seizure. J Neuroradiol 2020; 47 (01) 20-26
• 75 Matsuura K, Maeda M, Okamoto K. et al. Usefulness of arterial spin-labeling images in periictal state diagnosis of epilepsy. J Neurol Sci 2015; 359 (1-2): 424-429
• 76 Gaxiola-Valdez I, Singh S, Perera T, Sandy S, Li E, Federico P. Seizure onset zone localization using postictal hypoperfusion detected by arterial spin labelling MRI. Brain 2017; 140 (11) 2895-2911
• 77 Cox RW. AFNI: what a long strange trip it's been. Neuroimage 2012; 62 (02) 743-747
• 78 Smith SM, Beckmann CF, Andersson J. et al; WU-Minn HCP Consortium. Resting-state fMRI in the human connectome project. Neuroimage 2013; 80: 144-168
• 79 Adebimpe A, Bertolero M, Dolui S. et al; ALLFTD Consortium. ASLPrep: a platform for processing of arterial spin labeled MRI and quantification of regional brain perfusion. Nat Methods 2022; 19 (06) 683-686
• 80 Esteban O, Markiewicz CJ, Blair RW. et al. fMRIPrep: a robust preprocessing pipeline for functional MRI. Nat Methods 2019; 16 (01) 111-116
• 81 Eklund A, Nichols T, Andersson M, Knutsson H. Empirically investigating the statistical validity of SPM, FSL and AFNI for single subject fMRI analysis. In: 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).; 2015: 1376-1380
• 82 Bettus G, Ranjeva JP, Wendling F. et al. Interictal functional connectivity of human epileptic networks assessed by intracerebral EEG and BOLD signal fluctuations. PLoS One 2011; 6 (05) e20071
• 83 Boscolo Galazzo I, Storti SF, Barnes A. et al. Arterial spin labeling reveals disrupted brain networks and functional connectivity in drug-resistant temporal epilepsy. Front Neuroinform 2019; 12: 101
• 84 Centeno M, Carmichael DW. Network connectivity in epilepsy: resting state fMRI and EEG-fMRI contributions. Front Neurol 2014; 5: 93
• 85 Rahimzadeh H, Kamkar H, Ghafarian P. et al. Exploring ASL perfusion MRI as a substitutive modality for 18F-FDG PET in determining the laterality of mesial temporal lobe epilepsy. Neurol Sci 2024; 45 (05) 2223-2243
• 86 Mariajoseph FP, Muthusamy S, Amukotuwa S, Seneviratne U. Seizure-induced reversible MRI abnormalities in patients with single seizures: a systematic review. Epileptic Disord 2021; 23 (04) 552-562
• 87 Mariajoseph FP, Sagar P, Muthusamy S, Amukotuwa S, Seneviratne U. Seizure-induced reversible MRI abnormalities in status epilepticus: a systematic review. Seizure 2021; 92: 166-173
• 88 Budhram A, Britton JW, Liebo GB. et al. Use of diffusion-weighted imaging to distinguish seizure-related change from limbic encephalitis. J Neurol 2020; 267 (11) 3337-3342
• 89 Hübers A, Thoma K, Schocke M. et al. Acute DWI reductions in patients after single epileptic seizures - more common than assumed. Front Neurol 2018; 9: 550
• 90 Henderson JM. “Connectomic surgery”: diffusion tensor imaging (DTI) tractography as a targeting modality for surgical modulation of neural networks. Front Integr Nuerosci 2012; 6: 15
• 91 Potgieser ARE, Wagemakers M, van Hulzen ALJ, de Jong BM, Hoving EW, Groen RJM. The role of diffusion tensor imaging in brain tumor surgery: a review of the literature. Clin Neurol Neurosurg 2014; 124: 51-58
• 92 Ghaderi S, Mohammadi S, Fatehi F. Diffusion tensor imaging (DTI) biomarker alterations in brain metastases and comparable tumors: a systematic review of DTI and tractography findings. World Neurosurg 2024; 190: 113-129
• 93 Armocida D, Bianconi A, Zancana G. et al. DTI fiber-tracking parameters adjacent to gliomas: the role of tract irregularity value in operative planning, resection, and outcome. J Neurooncol 2025; 171 (01) 241-252
• 94 Yeh FC, Verstynen TD, Wang Y, Fernández-Miranda JC, Tseng WYI. Deterministic diffusion fiber tracking improved by quantitative anisotropy. PLoS One 2013; 8 (11) e80713
• 95 Glasser MF, Smith SM, Marcus DS. et al. The human connectome project's neuroimaging approach. Nat Neurosci 2016; 19 (09) 1175-1187
• 96 Kreilkamp BAK, Weber B, Richardson MP, Keller SS. Automated tractography in patients with temporal lobe epilepsy using TRActs constrained by underlying anatomy (TRACULA). Neuroimage Clin 2017; 14: 67-76
• 97 Mamah D, Chen S, Shimony JS, Harms MP. Tract-based analyses of white matter in schizophrenia, bipolar disorder, aging, and dementia using high spatial and directional resolution diffusion imaging: a pilot study. Front Psychiatry 2024; 15: 1240502
• 98 Tournier JD, Smith R, Raffelt D. et al. MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. Neuroimage 2019; 202: 116137
• 99 Cieslak M, Cook PA, He X. et al. QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data. Nat Methods 2021; 18 (07) 775-778
• 100 Jensen JH, Helpern JA. MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR Biomed 2010; 23 (07) 698-710
• 101 Hui ES, Cheung MM, Qi L, Wu EX. Towards better MR characterization of neural tissues using directional diffusion kurtosis analysis. Neuroimage 2008; 42 (01) 122-134
• 102 Winston GP. The potential role of novel diffusion imaging techniques in the understanding and treatment of epilepsy. Quant Imaging Med Surg 2015; 5 (02) 279-287
• 103 Kasa LW, Peters T, Mirsattari SM, Jurkiewicz MT, Khan AR, AM Haast R. The role of the temporal pole in temporal lobe epilepsy: a diffusion kurtosis imaging study. Neuroimage Clin 2022; 36: 103201
• 104 Bonilha L, Lee CY, Jensen JH. et al. Altered microstructure in temporal lobe epilepsy: a diffusional kurtosis imaging study. AJNR Am J Neuroradiol 2015; 36 (04) 719-724
• 105 Zhang H, Schneider T, Wheeler-Kingshott CA, Alexander DC. NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage 2012; 61 (04) 1000-1016
• 106 Palombo M, Ianus A, Guerreri M. et al. SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI. Neuroimage 2020; 215: 116835
• 107 Kamiya K, Hori M, Aoki S. NODDI in clinical research. J Neurosci Methods 2020; 346: 108908
• 108 Giachetti I, Padelli F, Aquino D. et al. Role of NODDI in the MRI characterization of hippocampal abnormalities in temporal lobe epilepsy: clinico-histopathologic correlations. Neurology 2022; 98 (17) e1771-e1782
• 109 Huerta MM, Conway DS, Planchon SM. et al. Longitudinal myelin content measures of slowly expanding lesions using 7T MRI in multiple sclerosis. J Neuroimaging 2024; 34 (04) 451-458
• 110 Wen Q, Kelley DAC, Banerjee S. et al. Clinically feasible NODDI characterization of glioma using multiband EPI at 7 T. Neuroimage Clin 2015; 9: 291-299
• 111 Obusez EC, Lowe M, Oh SH. et al. 7T MR of intracranial pathology: preliminary observations and comparisons to 3T and 1.5T. Neuroimage 2018; 168: 459-476
• 112 Bubrick EJ, Gholipour T, Hibert M, Cosgrove GR, Stufflebeam SM, Young GS. 7T versus 3T MRI in the presurgical evaluation of patients with drug-resistant epilepsy. J Neuroimaging 2022; 32 (02) 292-299
• 113 De Ciantis A, Barba C, Tassi L. et al. 7T MRI in focal epilepsy with unrevealing conventional field strength imaging. Epilepsia 2016; 57 (03) 445-454
• 114 Oliveira ÍAF, Roos T, Dumoulin SO, Siero JCW, van der Zwaag W. Can 7T MPRAGE match MP2RAGE for gray-white matter contrast?. Neuroimage 2021; 240: 118384
• 115 Beck ES, Sati P, Sethi V. et al. Improved visualization of cortical lesions in multiple sclerosis using 7T MP2RAGE. AJNR Am J Neuroradiol 2018; 39 (03) 459-466
• 116 Okubo G, Okada T, Yamamoto A. et al. MP2RAGE for deep gray matter measurement of the brain: a comparative study with MPRAGE. J Magn Reson Imaging 2016; 43 (01) 55-62
• 117 Datta R, Bacchus MK, Kumar D. et al. Fast automatic segmentation of thalamic nuclei from MP2RAGE acquisition at 7 Tesla. Magn Reson Med 2021; 85 (05) 2781-2790
• 118 Hangel G, Kasprian G, Chambers S. et al. Implementation of a 7T epilepsy task force consensus imaging protocol for routine presurgical epilepsy work-up: effect on diagnostic yield and lesion delineation. J Neurol 2024; 271 (02) 804-818
• 119 Trattnig S, Springer E, Bogner W. et al. Key clinical benefits of neuroimaging at 7T. Neuroimage 2018; 168: 477-489
• 120 Visser F, Zwanenburg JJM, Hoogduin JM, Luijten PR. High-resolution magnetization-prepared 3D-FLAIR imaging at 7.0 Tesla. Magn Reson Med 2010; 64 (01) 194-202
• 121 Deniz CM. Parallel transmission for ultrahigh field MRI. Top Magn Reson Imaging 2019; 28 (03) 159-171
• 122 Williams SN, McElhinney P, Gunamony S. Ultra-high field MRI: parallel-transmit arrays and RF pulse design. Phys Med Biol 2023; 68 (02) 02TR02
• 123 Cui Q, Tosun D, Mukherjee P, Abbasi-Asl R. 7T MRI Synthesization from 3T Acquisitions. In: Linguraru MG, Dou Q, Feragen A. , et al., eds. Medical Image Computing and Computer Assisted Intervention – MICCAI 2024. Springer Nature Switzerland; 2024: 35-44
• 124 Li X, Wang L, Liu H. et al. Syn_SegNet: a joint deep neural network for ultrahigh-field 7T MRI synthesis and hippocampal subfield segmentation in routine 3T MRI. IEEE J Biomed Health Inform 2023; 27 (10) 4866-4877
• 125 Ivanov D, De Martino F, Formisano E. et al. Magnetic resonance imaging at 9.4 T: the Maastricht journey. Magn Reson Mater Biol Phys Med 2023; 36 (02) 159-173
• 126 van Lanen RHGJ, Uher D, Tse DHY. et al. In vivo 9.4 Tesla MRI of a patient with drug-resistant epilepsy: technical report. Acta Neurochir (Wien) 2025; 167 (01) 18
• 127 Boulant N, Mauconduit F, Gras V. et al. In vivo imaging of the human brain with the Iseult 11.7-T MRI scanner. Nat Methods 2024; 21 (11) 2013-2016
• 128 Nie L, Li S, Wu B. et al. Advancements in 7T magnetic resonance diffusion imaging: Technological innovations and applications in neuroimaging. iRadiology 2024; 2 (04) 377-386
• 129 Le TT, Choi SH, Im GH. et al. Whole-brain BOLD responses to graded hypoxic challenges at 7 T, 9.4 T, and 15.2 T: Implications for ultrahigh-field functional and dynamic susceptibility contrast MRI. Magn Reson Med 2025; 94 (01) 262-277
• 130 Oliveira ÍAF, van der Zwaag W, Raimondo L, Dumoulin SO, Siero JCW. Comparing hand movement rate dependence of cerebral blood volume and BOLD responses at 7T. Neuroimage 2021; 226: 117623
• 131 Sotiropoulos SN, Hernández-Fernández M, Vu AT. et al. Fusion in diffusion MRI for improved fibre orientation estimation: An application to the 3T and 7T data of the Human Connectome Project. Neuroimage 2016; 134: 396-409
• 132 Shah P, Bassett DS, Wisse LEM. et al. Structural and functional asymmetry of medial temporal subregions in unilateral temporal lobe epilepsy: A 7T MRI study. Hum Brain Mapp 2019; 40 (08) 2390-2398
• 133 Singh SP. Magnetoencephalography: basic principles. Ann Indian Acad Neurol 2014; 17 (Suppl. 01) S107-S112
• 134 Carrette E, Stefan H. Evidence for the role of magnetic source imaging in the presurgical evaluation of refractory epilepsy patients. Front Neurol 2019; 10: 933
• 135 Murakami H, Wang ZI, Marashly A. et al. Correlating magnetoencephalography to stereo-electroencephalography in patients undergoing epilepsy surgery. Brain 2016; 139 (11) 2935-2947
• 136 Laohathai C, Ebersole JS, Mosher JC. et al. Practical fundamentals of clinical MEG interpretation in epilepsy. Front Neurol 2021; 12: 722986
• 137 Agarwal N, Krishnan B, Burgess RC, Prayson RA, Alexopoulos AV, Gupta A. Magnetoencephalographic characteristics of cortical dysplasia in children. Pediatr Neurol 2018; 78: 13-19
• 138 Ossenblok P, de Munck JC, Colon A, Drolsbach W, Boon P. Magnetoencephalography is more successful for screening and localizing frontal lobe epilepsy than electroencephalography. Epilepsia 2007; 48 (11) 2139-2149
• 139 De Tiège X, Bourguignon M, Piitulainen H, Jousmäki V. Sensorimotor mapping with MEG: an update on the current state of clinical research and practice with considerations for clinical practice guidelines. J Clin Neurophysiol 2020; 37 (06) 564-573
• 140 Bowyer SM, Zillgitt A, Greenwald M, Lajiness-O'Neill R. Language mapping with magnetoencephalography: an update on the current state of clinical research and practice with considerations for clinical practice guidelines. J Clin Neurophysiol 2020; 37 (06) 554-563
• 141 Hillebrand A, Barnes GR. A quantitative assessment of the sensitivity of whole-head MEG to activity in the adult human cortex. Neuroimage 2002; 16 (3 Pt 1): 638-650
• 142 Wilenius J, Lauronen L, Kirveskari E, Gaily E, Metsähonkala L, Paetau R. Interictal magnetoencephalography in parietal lobe epilepsy - comparison of equivalent current dipole and beamformer (SAMepi) analysis. Clin Neurophysiol Pract 2020; 5: 64-72
• 143 Sarvas J. Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem. Phys Med Biol 1987; 32 (01) 11-22
• 144 Alkawadri R, Burgess RC, Kakisaka Y, Mosher JC, Alexopoulos AV. Assessment of the utility of ictal magnetoencephalography in the localization of the epileptic seizure onset zone. JAMA Neurol 2018; 75 (10) 1264-1272
• 145 Fujiwara H, Greiner HM, Hemasilpin N. et al. Ictal MEG onset source localization compared to intracranial EEG and outcome: improved epilepsy presurgical evaluation in pediatrics. Epilepsy Res 2012; 99 (03) 214-224
• 146 Brookes MJ, Leggett J, Rea M. et al. Magnetoencephalography with optically pumped magnetometers (OPM-MEG): the next generation of functional neuroimaging. Trends Neurosci 2022; 45 (08) 621-634
• 147 Plis SM, Calhoun VD, Weisend MP, Eichele T, Lane T. MEG and fMRI fusion for nonlinear estimation of neural and BOLD signal changes. Front Neuroinform 2010; 4: 114
• 148 Hall EL, Robson SE, Morris PG, Brookes MJ. The relationship between MEG and fMRI. Neuroimage 2014; 102 (Pt 1): 80-91
• 149 Philiastides MG, Tu T, Sajda P. Inferring macroscale brain dynamics via fusion of simultaneous EEG-fMRI. Annu Rev Neurosci 2021; 44: 315-334
• 150 Leonardelli E, Fairhall SL. Similarity-based fMRI-MEG fusion reveals hierarchical organisation within the brain's semantic system. Neuroimage 2022; 259: 119405
• 151 Kostas D, Pang EW, Rudzicz F. Machine learning for MEG during speech tasks. Sci Rep 2019; 9 (01) 1609
• 152 Pantazis D, Adler A. MEG source localization via deep learning. Sensors (Basel) 2021; 21 (13) 4278
• 153 Franceschini S, Ambrosanio M, Autorino MM, Baselice F. A Deep Learning Solution for Brain Source Localization and Signal Reconstruction in Magnetoencephalography. In: 2024 IEEE International Conference on E-Health Networking, Application & Services (HealthCom).; 2024 :1–5.
• 154 Sun R, Zhang W, Bagić A, He B. Deep learning based source imaging provides strong sublobar localization of epileptogenic zone from MEG interictal spikes. Neuroimage 2023; 281: 120366
• 155 Shigemoto Y, Sone D, Kimura Y, Sato N, Matsuda H. Nuclear imaging in epilepsy: principles and progress. Epilepsy Seizure 2020; 12 (01) 40-48
• 156 Sarikaya I. PET studies in epilepsy. Am J Nucl Med Mol Imaging 2015; 5 (05) 416-430
• 157 Spencer SS. The relative contributions of MRI, SPECT, and PET imaging in epilepsy. Epilepsia 1994; 35 (Suppl. 06) S72-S89
• 158 Ergün EL, Saygi S, Yalnizoglu D, Oguz KK, Erbas B. SPECT-PET in epilepsy and clinical approach in evaluation. Semin Nucl Med 2016; 46 (04) 294-307
• 159 Traub-Weidinger T, Muzik O, Sundar LKS. et al. Utility of absolute quantification in non-lesional extratemporal lobe epilepsy using FDG PET/MR imaging. Front Neurol 2020; 11: 54
• 160 Lima CB, Silva MVCM, Pimenta RMC, Silva CDCM. The importance of PET-CT in the diagnosis of epilepsy/A importância do PET-CT no diagnóstico da epilepsia. Braz J Health Rev 2020; 3 (05) 14846-14858
• 161 Juhász C, Chugani DC, Muzik O. et al. Relationship between EEG and positron emission tomography abnormalities in clinical epilepsy. J Clin Neurophysiol 2000; 17 (01) 29-42
• 162 Struck AF, Hall LT, Floberg JM, Perlman SB, Dulli DA. Surgical decision making in temporal lobe epilepsy: a comparison of [(18)F]FDG-PET, MRI, and EEG. Epilepsy Behav 2011; 22 (02) 293-297
• 163 LoPinto-Khoury C, Sperling MR, Skidmore C. et al. Surgical outcome in PET-positive, MRI-negative patients with temporal lobe epilepsy. Epilepsia 2012; 53 (02) 342-348
• 164 Johnson R, Rizk G, Kaur H, Ibekwe H, Atta M, Gayed I. Refractory seizures: Prediction of outcome of surgical intervention based on results from PET-CT, PET-MRI and electroencephaolography. Neuroradiol J 2020; 33 (01) 57-65
• 165 la Fougère C, Rominger A, Förster S, Geisler J, Bartenstein P. PET and SPECT in epilepsy: a critical review. Epilepsy Behav 2009; 15 (01) 50-55
• 166 Bascuñana P, Brackhan M, Leiter I. et al. Divergent metabolic substrate utilization in brain during epileptogenesis precedes chronic hypometabolism. J Cereb Blood Flow Metab 2020; 40 (01) 204-213
• 167 Choi JY, Kim SJ, Hong SB. et al. Extratemporal hypometabolism on FDG PET in temporal lobe epilepsy as a predictor of seizure outcome after temporal lobectomy. Eur J Nucl Med Mol Imaging 2003; 30 (04) 581-587
• 168 Courtney MR, Antonic-Baker A, Chen Z. et al. Association of localizing ¹⁸F-FDG-PET hypometabolism and outcome following epilepsy surgery: systematic review and meta-analysis. Neurology 2024; 102 (09) e209304
• 169 Kini LG, Thaker AA, Hadar PN. et al. Quantitative ^[18]FDG PET asymmetry features predict long-term seizure recurrence in refractory epilepsy. Epilepsy Behav 2021; 116: 107714
• 170 Mason C, Gimblet GR, Lapi SE, Lewis JS. Novel tracers and radionuclides in PET imaging. Radiol Clin North Am 2021; 59 (05) 887-918
• 171 Rodnick ME, Hockley BG, Sherman P. et al. Novel fluorine-18 PET radiotracers based on flumazenil for GABAA imaging in the brain. Nucl Med Biol 2013; 40 (07) 901-905
• 172 Vivash L, Gregoire MC, Lau EW. et al. 18F-flumazenil: a γ-aminobutyric acid A-specific PET radiotracer for the localization of drug-resistant temporal lobe epilepsy. J Nucl Med 2013; 54 (08) 1270-1277
• 173 Finnema SJ, Toyonaga T, Detyniecki K. et al. Reduced synaptic vesicle protein 2A binding in temporal lobe epilepsy: A [¹¹ C]UCB-J positron emission tomography study. Epilepsia 2020; 61 (10) 2183-2193
• 174 Guo K, Cui B, Shang K. et al. Assessment of localization accuracy and postsurgical prediction of simultaneous ¹⁸F-FDG PET/MRI in refractory epilepsy patients. Eur Radiol 2021; 31 (09) 6974-6982
• 175 Poirier SE, Kwan BYM, Jurkiewicz MT. et al. An evaluation of the diagnostic equivalence of ¹⁸F-FDG-PET between hybrid PET/MRI and PET/CT in drug-resistant epilepsy: a pilot study. Epilepsy Res 2021; 172: 106583
• 176 Wang J, Guo K, Cui B, Hou Y, Zhao G, Lu J. Individual [¹⁸F]FDG PET and functional MRI based on simultaneous PET/MRI may predict seizure recurrence after temporal lobe epilepsy surgery. Eur Radiol 2022; 32 (06) 3880-3888
• 177 Ponisio MR, Zempel JM, Day BK. et al. The role of SPECT and PET in epilepsy. AJR Am J Roentgenol 2021; 216 (03) 759-768
• 178 Kim S, Mountz JM. SPECT imaging of epilepsy: an overview and comparison with F-18 FDG PET. Int J Mol Imaging 2011; 2011 (01) 813028
• 179 Traub-Weidinger T, Arbizu J, Barthel H. et al. EANM practice guidelines for an appropriate use of PET and SPECT for patients with epilepsy. Eur J Nucl Med Mol Imaging 2024; 51 (07) 1891-1908
• 180 von Oertzen TJ, Mormann F, Urbach H. et al. Prospective use of subtraction ictal SPECT coregistered to MRI (SISCOM) in presurgical evaluation of epilepsy. Epilepsia 2011; 52 (12) 2239-2248
• 181 Bianchin MM, Wichert-Ana L, Velasco TR, Martins APP, Sakamoto AC. Imaging epilepsy with SISCOM. Nat Rev Neurol 2011; 7 (04) 1-2
• 182 Devous Sr MD, Thisted RA, Morgan GF, Leroy RF, Rowe CC. SPECT brain imaging in epilepsy: a meta-analysis. J Nucl Med 1998; 39 (02) 285-293
• 183 Newton MR, Berkovic SF, Austin MC, Rowe CC, McKay WJ, Bladin PF. SPECT in the localisation of extratemporal and temporal seizure foci. J Neurol Neurosurg Psychiatry 1995; 59 (01) 26-30
• 184 Kim DW, Lee SK, Moon HJ, Jung KY, Chu K, Chung CK. Surgical treatment of nonlesional neocortical epilepsy: long-term longitudinal study. JAMA Neurol 2017; 74 (03) 324-331
• 185 Perissinotti A, Niñerola-Baizán A, Rubí S. et al. PISCOM: a new procedure for epilepsy combining ictal SPECT and interictal PET. Eur J Nucl Med Mol Imaging 2018; 45 (13) 2358-2367
• 186 Yassin A, El-Salem K, Al-Mistarehi AH. et al. Use of innovative SPECT techniques in the presurgical evaluation of patients with nonlesional extratemporal drug-resistant epilepsy. Mol Imaging 2021; 2021: 6614356
• 187 Kuzniecky R. Clinical applications of MR spectroscopy in epilepsy. Neuroimaging Clin N Am 2004; 14 (03) 507-516
• 188 Gonen OM, Moffat BA, Desmond PM, Lui E, Kwan P, O'Brien TJ. Seven-tesla quantitative magnetic resonance spectroscopy of glutamate, γ-aminobutyric acid, and glutathione in the posterior cingulate cortex/precuneus in patients with epilepsy. Epilepsia 2020; 61 (12) 2785-2794
• 189 Ende GR, Laxer KD, Knowlton RC. et al. Temporal lobe epilepsy: bilateral hippocampal metabolite changes revealed at proton MR spectroscopic imaging. Radiology 1997; 202 (03) 809-817
• 190 Cendes F, Knowlton RC, Novotny E. et al. Magnetic resonance spectroscopy in epilepsy: clinical issues. Epilepsia 2002; 43 (s1): 32-39
• 191 Hadar PN, Kini LG, Nanga RPR. et al. Volumetric glutamate imaging (GluCEST) using 7T MRI can lateralize nonlesional temporal lobe epilepsy: a preliminary study. Brain Behav 2021; 11 (08) e02134
• 192 Lucas A, Nanga RPR, Hadar P. et al. Mapping hippocampal glutamate in mesial temporal lobe epilepsy with glutamate weighted CEST (GluCEST) imaging. Hum Brain Mapp 2023; 44 (02) 549-558
• 193 Davis KA, Nanga RPR, Das S. et al. Glutamate imaging (GluCEST) lateralizes epileptic foci in nonlesional temporal lobe epilepsy. Sci Transl Med 2015; 7 (309) 309ra161
• 194 Hagiwara A, Bydder M, Oughourlian TC. et al. Sodium MR neuroimaging. AJNR Am J Neuroradiol 2021; 42 (11) 1920-1926
• 195 Azilinon M, Makhalova J, Zaaraoui W. et al. Combining sodium MRI, proton MR spectroscopic imaging, and intracerebral EEG in epilepsy. Hum Brain Mapp 2023; 44 (02) 825-840
• 196 Ridley B, Marchi A, Wirsich J. et al. Brain sodium MRI in human epilepsy: Disturbances of ionic homeostasis reflect the organization of pathological regions. Neuroimage 2017; 157: 173-183
• 197 Sheikh SR, Nair D, Gross RE, Gonzalez-Martinez J. Tracking a changing paradigm and the modern face of epilepsy surgery: a comprehensive and critical review on the hunt for the optimal extent of resection in mesial temporal lobe epilepsy. Epilepsia 2019; 60 (09) 1768-1793
• 198 Moraes MFD, de Castro Medeiros D, Mourao FAG, Cancado SAV, Cota VR. Epilepsy as a dynamical system, a most needed paradigm shift in epileptology. Epilepsy Behav 2021; 121 (Pt B): 106838
• 199 Stacey W, Kramer M, Gunnarsdottir K. et al. Emerging roles of network analysis for epilepsy. Epilepsy Res 2020; 159: 106255
• 200 Spencer SS. Neural networks in human epilepsy: evidence of and implications for treatment. Epilepsia 2002; 43 (03) 219-227
• 201 Rubinov M, Sporns O. Complex network measures of brain connectivity: uses and interpretations. Neuroimage 2010; 52 (03) 1059-1069
• 202 Kini LG, Bernabei JM, Mikhail F. et al. Virtual resection predicts surgical outcome for drug-resistant epilepsy. Brain 2019; 142 (12) 3892-3905
• 203 Říha P, Doležalová I, Mareček R. et al. Multimodal combination of neuroimaging methods for localizing the epileptogenic zone in MR-negative epilepsy. Sci Rep 2022; 12 (01) 15158