Abstract
Background and ObjectivesFocal cortical dysplasia (FCD) is a type of malformations of cortical development and one of the leading causes of drug-resistant epilepsy. Postoperative results improve the diagnosis of lesions on structural MRIs. Advances in quantitative algorithms have increased the identification of FCD lesions. However, due to significant differences in size, shape, and location of the lesion in different patients and a big deal of time for the objective diagnosis of lesion as well as the dependence of individual interpretation, sensitive approaches are required to address the challenge of lesion diagnosis. In this research, a FCD computer-aided diagnostic system to improve existing methods is presented.MethodsMagnetic resonance imaging (MRI) data were collected from 58 participants (30 with histologically confirmed FCD type II and 28 without a record of any neurological prognosis). Morphological and intensity-based features were calculated for each cortical surface and inserted into an artificial neural network. Statistical examinations evaluated classifier efficiency.ResultsNeural network evaluation metrics—sensitivity, specificity, and accuracy—were 96.7, 100, and 98.6%, respectively. Furthermore, the accuracy of the classifier for the detection of the lobe and hemisphere of the brain, where the FCD lesion is located, was 84.2 and 77.3%, respectively.ConclusionAnalyzing surface-based features by automated machine learning can give a quantitative and objective diagnosis of FCD lesions in presurgical assessment and improve postsurgical outcomes.
Highlights
Focal cortical dysplasia (FCD) is inherently epileptogenic and can be an essential reason behind refractory epilepsy (Fauser et al, 2015)
In T1-weighted scans, cortical thickness malformations, blurring of gray matter–white matter (GM– WM) boundary, and abnormal sulcus structure are FCD lesion features, and in T2/fluid-attenuated inversion recovery (FLAIR) images, signal hyperintensity is seen in FCD and transmantle sign lesions, in FCD IIb (Barkovich et al, 1997; Wang et al, 2013b)
Focal cortical dysplasia is among the most important factors behind drug-resistant epilepsy, which is treatable by surgery
Summary
Focal cortical dysplasia (FCD) is inherently epileptogenic and can be an essential reason behind refractory epilepsy (Fauser et al, 2015). MR images of patients with FCD show in 60% of the cases gray matter thickness increasing, 74% GM– WM interface blurring, 63% white matter signal hyperintensity, 19% structural atrophy, and 34% other signal changes due to the transmantle sign (Colombo et al, 2003; Lerner et al, 2009). Sometimes, these features occur together and make the lesion more visible. A FCD computer-aided diagnostic system to improve existing methods is presented
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
