Advances in Image Processing for Epileptogenic Zone Detection with MRI

被引:4
|
作者
Uher, Daniel [1 ,3 ]
Drenthen, Gerhard S. [1 ,3 ]
Schijns, Olaf E. M. G. [2 ,3 ,4 ,5 ]
Colon, Albert J. [4 ,5 ]
Hofman, Paul A. M. [1 ,4 ,5 ]
van Lanen, Rick H. G. J. [2 ,3 ]
Hoeberigs, Christianne M. [1 ,4 ,5 ]
Jansen, Jacobus F. A. [1 ,3 ,4 ,5 ,6 ]
Backes, Walter H. [1 ,3 ]
机构
[1] Maastricht Univ, Dept Radiol & Nucl Med, Med Ctr, P Debyelaan 25, NL-6229 HX Maastricht, Netherlands
[2] Maastricht Univ, Dept Neurosurg, Med Ctr, P Debyelaan 25, NL-6229 HX Maastricht, Netherlands
[3] Maastricht Univ, Sch Mental Hlth & Neurosci MHeNs, Maastricht, Netherlands
[4] Kempenhaeghe, Acad Ctr Epileptol, Heeze, Netherlands
[5] Maastricht Univ, Med Ctr, Maastricht, Netherlands
[6] Eindhoven Univ Technol, Dept Elect Engn, Eindhoven, Netherlands
关键词
TEMPORAL-LOBE EPILEPSY; FOCAL CORTICAL DYSPLASIA; STATE FUNCTIONAL CONNECTIVITY; WHITE-MATTER INTEGRITY; FRACTIONAL ANISOTROPY; REGIONAL HOMOGENEITY; STATISTICAL-ANALYSIS; NORMALIZED FLAIR; T2; RELAXOMETRY; LOCALIZATION;
D O I
10.1148/radiol.220927
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Focal epilepsy is a common and severe neurologic disorder. Neuroimaging aims to identify the epileptogenic zone (EZ), preferably as a macroscopic structural lesion. For approximately a third of patients with chronic drug-resistant focal epilepsy, the EZ cannot be precisely identified using standard 3.0-T MRI. This may be due to either the EZ being undetectable at imaging or the seizure activity being caused by a physiologic abnormality rather than a structural lesion. Computational image processing has recently been shown to aid radiologic assessments and increase the success rate of uncovering suspicious regions by enhancing their visual conspicuity. While structural image analysis is at the forefront of EZ detection, physiologic image analysis has also been shown to provide valuable information about EZ location. This narrative review summarizes and explains the current state-of-the-art computational approaches for image analysis and presents their potential for EZ detection. Current limitations of the methods and possible future directions to augment EZ detection are discussed. (c) RSNA, 2023
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页数:12
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