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Searching for the Lesion in "MRI-Normal" Neocortical Epilepsy-Plumb the Depths!

2009 Epilepsy Currents  
Focal cortical dysplasia (FCD) is often characterized by minor structural changes that may go unrecognized by standard radiological analysis.  ...  Lesions were classified into small and large using qualitative (detection on initial clinical assessment of conventional MRI) and quantitative (volume) criteria.  ...  Sulci were identified and labeled automatically using an algorithm based on a congregation of neural networks. Segmented FCD lesions and sulci were then simultaneously visualized in 3D.  ... 
doi:10.1111/j.1535-7511.2009.01328.x pmid:19936131 pmcid:PMC2778360 fatcat:7ltv6qonb5fy7gxcye56lk26fy

Surface-Based Texture and Morphological Analysis Detects Subtle Cortical Dysplasia [chapter]

Pierre Besson, Neda Bernasconi, Olivier Colliot, Alan Evans, Andrea Bernasconi
2008 Lecture Notes in Computer Science  
This paper presents a method to detect small FCD lesions on T1-MRI relying on surface-based features that model their textural and morphometric characteristics.  ...  Focal cortical dysplasia (FCD), a malformation of cortical development, is an important cause of pharmacoresistant epilepsy.  ...  This paper presents a new method for detecting small FCD lesions on T1weighted MRI that relies on surface-based features.  ... 
doi:10.1007/978-3-540-85988-8_77 fatcat:z4rsk4feovewthx7uciocf3wgy

Automated detection of cortical dysplasia type II in MRI-negative epilepsy

S.-J. Hong, H. Kim, D. Schrader, N. Bernasconi, B. C. Bernhardt, A. Bernasconi
2014 Neurology  
Objective: To detect automatically focal cortical dysplasia (FCD) type II in patients with extratemporal epilepsy initially diagnosed as MRI-negative on routine inspection of 1.5 and 3.0T scans.  ...  Methods: We implemented an automated classifier relying on surface-based features of FCD morphology and intensity, taking advantage of their covariance.  ...  Figure 2 2 Examples of automated focal cortical dysplasia type II detectionThe axial T1-weighted MRI sections show the region containing the focal cortical dysplasia (FCD) (dashed square).  ... 
doi:10.1212/wnl.0000000000000543 pmid:24898923 pmcid:PMC4114179 fatcat:7sc5gnkexjgzxllhyx3cnrp5mq

Detection of Epileptogenic Cortical Malformations with Surface-Based MRI Morphometry

Thomas Thesen, Brian T. Quinn, Chad Carlson, Orrin Devinsky, Jonathan DuBois, Carrie R. McDonald, Jacqueline French, Richard Leventer, Olga Felsovalyi, Xiuyuan Wang, Eric Halgren, Ruben Kuzniecky (+1 others)
2011 PLoS ONE  
Automated surface-based MRI morphometry, if used with optimized parameters, may be a valuable additional clinical tool to improve the detection of subtle or previously occult malformations and therefore  ...  Here we use an automated, surfacebased method for quantifying morphometric features related to epileptogenic cortical malformations to detect abnormal cortical thickness and blurred gray-white matter boundaries  ...  Discussion Using surface-based MRI methods and quantitative comparisons based on 6 morphological features in individual patients and a large normal control group, we found that cortical thickness and grey-white  ... 
doi:10.1371/journal.pone.0016430 pmid:21326599 pmcid:PMC3033882 fatcat:26hofbeokjgxfbgtt4aqydrlve

Automatic Detection of Focal Cortical Dysplasia Type II in MRI: Is the Application of Surface-Based Morphometry and Machine Learning Promising?

Zohreh Ganji, Mohsen Aghaee Hakak, Seyed Amir Zamanpour, Hoda Zare
2021 Frontiers in Human Neuroscience  
and ObjectivesFocal cortical dysplasia (FCD) is a type of malformations of cortical development and one of the leading causes of drug-resistant epilepsy.  ...  Morphological and intensity-based features were calculated for each cortical surface and inserted into an artificial neural network.  ...  Giorgio LoRusso for sharing his experiences with us.  ... 
doi:10.3389/fnhum.2021.608285 pmid:33679343 pmcid:PMC7933541 fatcat:fpdrv6wqurcmvgrehfbcgwuctm

Novel surface features for automated detection of focal cortical dysplasias in paediatric epilepsy

Sophie Adler, Konrad Wagstyl, Roxana Gunny, Lisa Ronan, David Carmichael, J Helen Cross, Paul C. Fletcher, Torsten Baldeweg
2017 NeuroImage: Clinical  
We developed a classifier using surface-based features to identify focal abnormalities of cortical development in a paediatric cohort.  ...  Focal cortical dysplasias in our paediatric cohort were correctly identified with a higher sensitivity (73%) when novel features, based on our approach for detecting local cortical changes, were included  ...  Rolf Ypma for his advice on machine learning and Dr. Kirstie Whitaker for her advice on open science.  ... 
doi:10.1016/j.nicl.2016.12.030 pmid:28123950 pmcid:PMC5222951 fatcat:fsfxb5qo7vbqjobupjjzg75vca

Neuroimaging in Investigation of Patients With Epilepsy

Fernando Cendes
2013 Continuum. Lifelong Learning in Neurology  
Recent Findings: A proper MRI investigation of patients with focal epilepsy requires the use of specific protocols, selected based on identification of the region of onset by clinical and EEG information  ...  Among the several types of neocortical lesions, focal cortical dysplasias deserve especial attention because these lesions are often missed on routine MRIs.  ...  surface coils. 19, 20 Malformations of Cortical Development Focal cortical dysplasias.  ... 
doi:10.1212/01.con.0000431379.29065.d3 pmid:23739101 fatcat:t7zudalbkfbipcvrflmpti75zm

In Vivo Profiling of Focal Cortical Dysplasia on High-resolution MRI with Computational Models

Olivier Colliot, Samson B. Antel, Veronique B. Naessens, Neda Bernasconi, Andrea Bernasconi
2006 Epilepsia  
Purpose: On MRI, focal cortical dysplasia (FCD) is characterized by a combination of increased cortical thickness, hyperintense signal within the dysplastic lesion, and blurred transition between gray  ...  Our purpose was to investigate the pattern of occurrence of abnormal MRI characteristics in FCD by using a set of computational models and to generate quantitative lesion profiling.  ...  FIG. 1 . 1 Computational models of MRI characteristics of focal cortical dysplasia (FCD). For each feature, a three-dimensional map is created. Representative axial slices are shown.  ... 
doi:10.1111/j.1528-1167.2006.00379.x pmid:16417541 fatcat:2kh7glazabgkllpwp2yta2r3o4

Small focal cortical dysplasia lesions are located at the bottom of a deep sulcus

Pierre Besson, Frederick Andermann, Francois Dubeau, Andrea Bernasconi
2008 Brain  
Focal cortical dysplasia (FCD) is often characterized by minor structural changes that may go unrecognized by standard radiological analysis.  ...  Lesions were classified into small and large using qualitative (detection on initial clinical assessment of conventional MRI) and quantitative (volume) criteria.  ...  (A) Three-dimensional surface rendering of the MRI of a patient with right frontal focal cortical dysplasia.  ... 
doi:10.1093/brain/awn224 pmid:18812443 fatcat:xtse7b3hgre5jch7w6oab2hrti

Clinical Value of Machine Learning in the Automated Detection of Focal Cortical Dysplasia Using Quantitative Multimodal Surface-Based Features

Jia-Jie Mo, Jian-Guo Zhang, Wen-Ling Li, Chao Chen, Na-Jing Zhou, Wen-Han Hu, Chao Zhang, Yao Wang, Xiu Wang, Chang Liu, Bao-Tian Zhao, Jun-Jian Zhou (+1 others)
2019 Frontiers in Neuroscience  
Objective: To automatically detect focal cortical dysplasia (FCD) lesion by combining quantitative multimodal surface-based features with machine learning and to assess its clinical value.  ...  The morphology, intensity and function-based features characterizing FCD lesions were calculated vertex-wise on each cortical surface and fed to an artificial neural network.  ...  Focal cortical dysplasia constituted a broad spectrum of histopathological and clinical features ranging from FCD type I (small or subtle in conventional magnetic resonance imaging [MRI] ) to FCD type  ... 
doi:10.3389/fnins.2018.01008 pmid:30686974 pmcid:PMC6336916 fatcat:vi55kz35zvaiba4s4hckfkuupy

Focal Cortical Dysplasia (FCD) lesion analysis with complex diffusion approach

Jeny Rajan, K. Kannan, C. Kesavadas, Bejoy Thomas
2009 Computerized Medical Imaging and Graphics  
Identification of Focal Cortical Dysplasia (FCD) can be difficult due to the subtle MRI changes.  ...  This computer aided detection technique using complex diffusion approach can help detect focal cortical dysplasia in patients with epilepsy.  ...  Acknowledgements The authors thank Dr.P.Sankara Sarma, Additional Professor of Biostatistics, SCTIMST, Trivandrum for advising on the statistical calculation in the paper.  ... 
doi:10.1016/j.compmedimag.2009.05.004 pmid:19560319 fatcat:c3hjjmazj5ebno5muaw5udabtq

Planning stereoelectroencephalography using automated lesion detection: Retrospective feasibility study

Konrad Wagstyl, Sophie Adler, Birgit Pimpel, Aswin Chari, Kiran Seunarine, Sara Lorio, Rachel Thornton, Torsten Baldeweg, Martin Tisdall
2020 Epilepsia  
A neural network classifier was applied to cortical features from MRI data from three cohorts. (1) The network was trained and cross-validated using 34 patients with visible focal cortical dysplasias (  ...  We have created a framework for incorporation of deep-learning-based MRI lesion detection into sEEG implantation planning.  ...  The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, or the Department of Health. T.B. is supported by GOSH Children's Charity.  ... 
doi:10.1111/epi.16574 pmid:32533794 fatcat:6utedvptyjckray6pwswdsfuwi

Interpretable surface-based detection of focal cortical dysplasias: a MELD study [article]

Hannah Spitzer, Mathilde Ripart, Kirstie Whitaker, Antonio Napolitano, Luca De Palma, Alessandro De Benedictis, Stephen Foldes, Zachary Humphreys, Kai Zhang, Wenhan Hu, Jiajie Mo, Marcus Likeman (+62 others)
2021 medRxiv   pre-print
A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI.  ...  We created a neural network for FCD detection based on 33 surface-based features.  ...  Discussion We present an interpretable, fully automated pipeline for surface-based detection of focal cortical dysplasias, which has been validated on a large withheld test cohort, incorporating data from  ... 
doi:10.1101/2021.12.13.21267721 fatcat:kr6oqk3mmbhydjwlrymdom533u

Quantitative surface analysis of combined MRI and PET enhances detection of focal cortical dysplasias

Yee-Leng Tan, Hosung Kim, Seunghyun Lee, Tarik Tihan, Lawrence Ver Hoef, Susanne G. Mueller, Anthony James Barkovich, Duan Xu, Robert Knowlton
2018 NeuroImage  
We aimed to automatically detect subtle or visually-unidentifiable FCDs by building a classifier based on an optimized cortical surface sampling of combined MRI and PET features.  ...  Focal cortical dysplasias (FCDs) often cause pharmacoresistant epilepsy, and surgical resection can lead to seizure-freedom.  ...  The authors have no commercial, financial, or other relationship related to the subject of this paper that could constitute or suggest a conflict of interest.  ... 
doi:10.1016/j.neuroimage.2017.10.065 pmid:29097316 pmcid:PMC5748006 fatcat:6fb6skyff5gqfkiqucwtu2qofq

Towards in vivo focal cortical dysplasia phenotyping using quantitative MRI

Sophie Adler, Sara Lorio, Thomas S. Jacques, Barbora Benova, Roxana Gunny, J. Helen Cross, Torsten Baldeweg, David W. Carmichael
2017 NeuroImage: Clinical  
Focal cortical dysplasias (FCDs) are a range of malformations of cortical development each with specific histopathological features.  ...  Keywords: Focal cortical dysplasia Biophysical tissue properties Histology Radiology MRI Quantitative mapping qMRI Quantitative MRI Epilepsy surgery Malformation of cortical development A B S T R A C T  ...  Novel surface features for automated detection of focal cortical dysplasias in paediatric epilepsy. Neuroimage. Clin. 18-27. http://dx.doi.org/10. 1016/j.nicl.2016.12.030.  ... 
doi:10.1016/j.nicl.2017.04.017 pmid:28491496 pmcid:PMC5413300 fatcat:5hm4i3da25eqffud5my67p5w3q
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