Temporal lobe epilepsy: Differential pattern of damage in temporopolar cortex and white matter

Sankar, Tejas; Bernasconi, Neda; Kim, Ho‐Sung; Bernasconi, Andrea

doi:10.1002/hbm.20437

Cited by 35 publications

(19 citation statements)

References 78 publications

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“…The correct identification of hippocampal sclerosis with proton-attenuation MR images was achieved by using f 9 and f 3 , whereas a total of 9 T2-weighted MR image features were able to correctly classify the hippocampi. In a subsequent study, Sankar et al 46 discovered decreased gradient and f 9 features in patients with epilepsy, connoting a blurring of the temporopolar WM (65% sensitivity and 100% specificity for hippocampal atrophy versus 17% and 69% with visual assessment).…”

Section: Epilepsymentioning

confidence: 98%

Texture Analysis: A Review of Neurologic MR Imaging Applications

Kassner¹,

Thornhill²

2010

AJNR Am J Neuroradiol

358

265

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SUMMARY:Texture analysis describes a variety of image-analysis techniques that quantify the variation in surface intensity or patterns, including some that are imperceptible to the human visual system. Texture analysis may be particularly well-suited for lesion segmentation and characterization and for the longitudinal monitoring of disease or recovery. We begin this review by outlining the general procedure for performing texture analysis, identifying some potential pitfalls and strategies for avoiding them. We then provide an overview of some intriguing neuro-MR imaging applications of texture analysis, particularly in the characterization of brain tumors, prediction of seizures in epilepsy, and a host of applications to MS.ABBREVIATIONS: ABSV ϭ absolute gradient value; AIS ϭ acute ischemic stroke; ANN ϭ artificial neural network; CIS ϭ clinically isolated syndrome; d ϭ distance; DCE ϭ dynamic contrastenhanced; FCD ϭ focal cortical dysplasia; FLAIR ϭ fluid-attenuated inversion recovery; f x ϭ second-order gray-level co-occurrence feature number "x"; GLCM ϭ gray-level co-occurrence matrix; GM ϭ gray matter; HT ϭ hemorrhagic transformation; LDA ϭ linear discriminant analysis; MGL ϭ mean gray level; MGR ϭ mean gradient; MS ϭ multiple sclerosis; MTR ϭ magnetization transfer ratio; NAWM ϭ normal-appearing white matter; N g ϭ number of gray levels; PCA ϭ principal components analysis; PPMS ϭ primary-progressive MS; RLM ϭ run-length matrix; ROC ϭ receiver-operator characteristic; ROI ϭ region of interest; RRMS ϭ relapsing-remitting MS; rtPA ϭ recombinant tissue plasminogen activator; SPMS ϭ secondary-progressive MS; SVM ϭ support vector machine; ϭ direction; VGL ϭ variance of gray levels; VGR ϭ variance gradient; WM ϭ white matter

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Section: Epilepsymentioning

confidence: 98%

Texture Analysis: A Review of Neurologic MR Imaging Applications

Kassner¹,

Thornhill²

2010

AJNR Am J Neuroradiol

358

265

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“…Studies based on manual volumetric MRI analysis largely confirmed previous histological assessments, and provided a more comprehensive picture of the regional extent of structural abnormalities in TLE. Volumetric analysis demonstrated atrophy in multiple limbic structures, including the hippocampus, entorhinal cortex, amygdala (Cendes et al, 1993a,b; Bernasconi et al, 2001, 2003a,b), temporopolar, perirhinal, lateral temporal neocortices (Jutila et al, 2001; Moran et al, 2001; Sankar et al, 2008), and the thalamus (Dreifuss et al, 2001; Natsume et al, 2003; Bernhardt et al, 2012). In the hippocampus and thalamus, surface shape mapping has furthermore allowed localizing structural anomalies at a subregional level (Hogan et al, 2004; Kim et al, 2008; Bernhardt et al, 2012, in press).…”

Section: Regional Patterns Of Structural Pathologymentioning

confidence: 99%

Imaging structural and functional brain networks in temporal lobe epilepsy

Bernhardt¹,

Hong²,

Bernasconi³

et al. 2013

Front. Hum. Neurosci.

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198

153

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Early imaging studies in temporal lobe epilepsy (TLE) focused on the search for mesial temporal sclerosis, as its surgical removal results in clinically meaningful improvement in about 70% of patients. Nevertheless, a considerable subgroup of patients continues to suffer from post-operative seizures. Although the reasons for surgical failure are not fully understood, electrophysiological and imaging data suggest that anomalies extending beyond the temporal lobe may have negative impact on outcome. This hypothesis has revived the concept of human epilepsy as a disorder of distributed brain networks. Recent methodological advances in non-invasive neuroimaging have led to quantify structural and functional networks in vivo. While structural networks can be inferred from diffusion MRI tractography and inter-regional covariance patterns of structural measures such as cortical thickness, functional connectivity is generally computed based on statistical dependencies of neurophysiological time-series, measured through functional MRI or electroencephalographic techniques. This review considers the application of advanced analytical methods in structural and functional connectivity analyses in TLE. We will specifically highlight findings from graph-theoretical analysis that allow assessing the topological organization of brain networks. These studies have provided compelling evidence that TLE is a system disorder with profound alterations in local and distributed networks. In addition, there is emerging evidence for the utility of network properties as clinical diagnostic markers. Nowadays, a network perspective is considered to be essential to the understanding of the development, progression, and management of epilepsy.

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“…TA has potential for clinical use, providing information on many neurological disorders. Indeed, it has been used to study intracranial brain tumors, epilepsy, multiple sclerosis, Alzheimer's disease, and amyotrophic lateral sclerosis (ALS) …”

mentioning

confidence: 99%

Reliability of 3D texture analysis: A multicenter MRI study of the brain

Khan

Ishaque

et al. 2019

Magnetic Resonance Imaging

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Background Texture analysis (TA) is an image‐analysis technique that detects complex intervoxel statistical patterns. 3D TA has shown potential in detecting cerebral degeneration not perceptible to the human eye in many neurological disorders. The reliability of this method's application in a multicenter study is unknown. Purpose To assess the intrasite and intersite reliability of a novel 3D TA method from data acquired systematically from the Canadian ALS Neuroimaging Consortium (CALSNIC). Study Type Prospective multicenter data with harmonized MR sequence parameters acquired from five sites. Population Six healthy subjects. Field Strength 3T 3D‐MPRAGE and 3D‐SPGR T1‐weighted MRI of the brain. Assessment Voxel‐based 3D TA was performed on the whole brain to produce texture maps. Statistical Tests Intra‐ and intersite reliability of texture features was assessed using a two‐way mixed‐effects model for intraclass correlation coefficients (ICC). ICCs were calculated in a region‐of‐interest (ROI) analysis of predetermined anatomically relevant areas. A voxelwise approach was used to assess the whole brain. Results In the ROI analyses, intrasite reliability was excellent (ICC > 0.75) across most regions and texture features (autocorrelation [autoc], contrast [contr], energy [energ]). Intersite reliability was excellent for most regions with autoc, ranging from fair to excellent for contr, and ICCs ranging from poor to good (<0.40–0.75) for energ. Voxelwise analyses revealed a large range in ICC across the brain for both intrasite and intersite ICCs (0.0–0.90), with higher reliability in the cortical gray matter compared with deeper subcortical structures. Data Conclusion Overall, the reliability of 3D TA was highly dependent on texture feature, region studied, and method of analysis (ROI or voxelwise). Intrasite reproducibility was good to excellent, and better than intersite. ROI‐based analyses present higher reliability in comparison with voxelwise analyses. Autoc has overall excellent reliability. These factors might be considered when designing future 3D TA studies. Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:1200–1209.

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Temporal lobe epilepsy: Differential pattern of damage in temporopolar cortex and white matter

Cited by 35 publications

References 78 publications

Texture Analysis: A Review of Neurologic MR Imaging Applications

Texture Analysis: A Review of Neurologic MR Imaging Applications

Imaging structural and functional brain networks in temporal lobe epilepsy

Reliability of 3D texture analysis: A multicenter MRI study of the brain

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