Magnetic resonance imaging pattern learning in temporal lobe epilepsy: Classification and prognostics

Annals of Neurology

Volumn 77, Issue 3, 2015, Pages 436-446

  Bernhardt, Boris C ^a   Hong, Seok Jun ^a   Bernasconi, Andrea ^a   Bernasconi, Neda ^a  

^a MCGILL UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ADOLESCENT; ADULT; AMYGDALOID NUCLEUS; ARTICLE; AUTOMATION; BRAIN ATROPHY; BRAIN MALFORMATION; CLINICAL CLASSIFICATION; COHORT ANALYSIS; CONTROLLED STUDY; DENTATE GYRUS; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; DISEASE CLASSIFICATION; ENTORHINAL CORTEX; FEBRILE CONVULSION; FEMALE; HIPPOCAMPUS; HISTOPATHOLOGY; HUMAN; HUMAN TISSUE; HYPERTROPHY; INCIDENCE; LEARNING ALGORITHM; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; MORPHOLOGY; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEAR MAGNETIC RESONANCE SCANNER; OUTCOME ASSESSMENT; PATHOGENESIS; PATTERN LEARNING; PREDICTIVE VALUE; PRIORITY JOURNAL; PROGNOSIS; RELAPSE; SINGLE BLIND PROCEDURE; SURFACE PROPERTY; TEMPORAL LOBE EPILEPSY; THREE DIMENSIONAL IMAGING; VOLUMETRY; ARTIFICIAL INTELLIGENCE; ATROPHY; CLASSIFICATION; EPILEPSY, TEMPORAL LOBE; IMAGE PROCESSING; MIDDLE AGED; PATHOLOGY; PROCEDURES; RECURRENT DISEASE; YOUNG ADULT;

ADOLESCENT; ADULT; AMYGDALA; ARTIFICIAL INTELLIGENCE; ATROPHY; ENTORHINAL CORTEX; EPILEPSY, TEMPORAL LOBE; FEMALE; HIPPOCAMPUS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; PROGNOSIS; RECURRENCE; YOUNG ADULT;

EID: 84923810067     PISSN: 03645134     EISSN: 15318249     Source Type: Journal    
DOI: 10.1002/ana.24341     Document Type: Article

References (48)

1. Bernasconi N, Bernasconi A, Caramanos Z, et al. Mesial temporal damage in temporal lobe epilepsy: a volumetric MRI study of the hippocampus, amygdala and parahippocampal region. Brain 2003; 126(pt 2): 462-469.
2. Cendes F, Andermann F, Gloor P, et al. Atrophy of mesial structures in patients with temporal lobe epilepsy: cause or consequence of repeated seizures? Ann Neurol 1993; 34: 795-801.
3. Kim H, Besson P, Colliot O, et al. Surface-based vector analysis using heat equation interpolation: a new approach to quantify local hippocampal volume changes. Med Image Comput Comput Assist Interv 2008; 11(pt 1): 1008-1015.
4. Hogan RE, Wang L, Bertrand ME, et al. MRI-based high-dimensional hippocampal mapping in mesial temporal lobe epilepsy. Brain 2004; 127(pt 8): 1731-1740.
5. Blumcke I, Thom M, Aronica E, et al. International consensus classification of hippocampal sclerosis in temporal lobe epilepsy: a Task Force report from the ILAE Commission on Diagnostic Methods. Epilepsia 2013; 54: 1315-1329.
6. Bernhardt BC, Kim H, Bernasconi N. Patterns of subregional mesiotemporal disease progression in temporal lobe epilepsy. Neurology 2013; 81: 1840-1847.
7. Wiebe S, Jette N. Pharmacoresistance and the role of surgery in difficult to treat epilepsy. Nat Rev Neurol 2012; 8: 669-677.
8. Elsharkawy AE, Alabbasi AH, Pannek H, et al. Long-term outcome after temporal lobe epilepsy surgery in 434 consecutive adult patients. J Neurosurg 2009; 110: 1135-1146.
9. Cohen-Gadol AA, Wilhelmi BG, Collignon F, et al. Long-term outcome of epilepsy surgery among 399 patients with nonlesional seizure foci including mesial temporal lobe sclerosis. J Neurosurg 2006; 104: 513-524.
10. Jutila L, Immonen A, Mervaala E, et al. Long term outcome of temporal lobe epilepsy surgery: analyses of 140 consecutive patients. J Neurol Neurosurg Psychiatry 2002; 73: 486-494.
11. de Tisi J, Bell GS, Peacock JL, et al. The long-term outcome of adult epilepsy surgery, patterns of seizure remission, and relapse: a cohort study. Lancet 2011; 378: 1388-1395.
12. Arruda F, Cendes F, Andermann F, et al. Mesial atrophy and outcome after amygdalohippocampectomy or temporal lobe removal. Ann Neurol 1996; 40: 446-450.
13. Engel J Jr, Van Ness PC, Rasmussen T, Ojemann LM. Outcome with respect to epileptic seizures. In: Engel J Jr, ed. Surgical treatment of the epilepsies. 2nd ed. New York, NY: Raven Press, 1993: 609-621.
14. Meencke HJ, Veith G. Hippocampal sclerosis in epilepsy. In: Lüders H, ed. Epilepsy surgery. New York, NY: Raven Press; 1991: 705-715.
15. Collins DL, Neelin P, Peters TM, Evans AC. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr 1994; 18: 192-205.
16. Sled JG, Zijdenbos AP, Evans AC. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 1998; 17: 87-97.
17. Watson C, Andermann F, Gloor P, et al. Anatomic basis of amygdaloid and hippocampal volume measurement by magnetic resonance imaging. Neurology 1992; 42: 1743-1750.
18. Bernasconi N, Bernasconi A, Andermann F, et al. Entorhinal cortex in temporal lobe epilepsy: a quantitative MRI study. Neurology 1999; 52: 1870-1876.
19. Styner M, Oguz I, Brechbuehler C, et al. Statistical shape analysis of brain structures using SPHARM-PDM. MICCAI Open Source Workshop. Copenhagen, Denmark; 2006.
20. Adler DH, Pluta J, Kadivar S, et al. Histology-derived volumetric annotation of the human hippocampal subfields in postmortem MRI. Neuroimage 2014; 84: 505-523.
21. Bernhardt BC, Kim H, Bernasconi N. Patterns of subregional mesiotemporal disease progression in temporal lobe epilepsy. Neurology 2013; 81: 1840-1847.
22. Kim H, Besson P, Colliot O, et al. Surface-based vector analysis using heat equation interpolation: a new approach to quantify local hippocampal volume changes. Med Image Comput Comput Assist Interv 2008; 11(pt 1): 1008-1015.
23. Hogan RE, Wang L, Bertrand ME, et al. MRI-based high-dimensional hippocampal mapping in mesial temporal lobe epilepsy. Brain 2004; 127: 1731-1740.
24. Duvernoy HM The human hippocampus functional anatomy, vas-cularization and serial sections with MRI. Berlin, Heidelberg, Germany: Springer-Verlag, 2005.
25. Amunts K, Kedo O, Kindler M, et al. Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anat Embryol (Berl) 2005; 210: 343-352.
26. Insausti R, Tunon T, Sobreviela T, et al. The human entorhinal cortex: a cytoarchitectonic analysis. The J Comp Neurol 1995; 355: 171-198.
27. Duda RO, Hart PE, Stork DG. Pattern classification. 2nd ed. New York, NY: Wiley Interscience, 2001.
28. Halkidi M, Vazirgiannis M, Batistakis Y. Quality scheme assessment in the clustering process. In: Zighed D, Komorowski J, Żytkow J, eds. Principles of data mining and knowledge discovery. Berlin, Heidelberg, Germany: Springer, 2000: 265-276.
29. Worsley KJ, Taylor JE, Carbonell F, et al. SurfStat: a Matlab toolbox for the statistical analysis of univariate and multivariate surface and volumetric data using linear mixed effects models and random field theory. Neuroimage 2009; 47(SUPPL. 1):S102.
30. Chung MK, Worsley KJ, Nacewicz BM, et al. General multivariate linear modeling of surface shapes using SurfStat. Neuroimage 2010; 53: 491-505.
31. Worsley KJ, Andermann M, Koulis T, et al. Detecting changes in nonisotropic images. Hum Brain Mapp 1999; 8: 98-101.
32. Kim H, Mansi T, Bernasconi N, Bernasconi A. Surface-based multitemplate automated hippocampal segmentation: application to temporal lobe epilepsy. Med Image Anal 2012; 16: 1445-1455.
33. Gaillard WD, Cross JH, Duncan JS, et al. Epilepsy imaging study guideline criteria: commentary on diagnostic testing study guidelines and practice parameters. Epilepsia 2011; 52: 1750-1756.
34. Bellazzi R, Zupan B. Predictive data mining in clinical medicine: current issues and guidelines. Int J Med Inform 2008; 77: 81-97.
35. Keihaninejad S, Heckemann RA, Gousias IS, et al. Classification and lateralization of temporal lobe epilepsies with and without hippocampal atrophy based on whole-brain automatic MRI segmentation. PLoS One 2012; 7:e33096.
36. Duchesne S, Bernasconi N, Bernasconi A, Collins DL. MR-based neurological disease classification methodology: application to lateralization of seizure focus in temporal lobe epilepsy. Neuroimage 2006; 29: 557-566.
37. Focke NK, Yogarajah M, Symms MR, et al. Automated MR image classification in temporal lobe epilepsy. Neuroimage 2012; 59: 356-362.
38. Mueller SG, Young K, Hartig M, et al. A two-level multimodality imaging Bayesian network approach for classification of partial epilepsy: preliminary data. Neuroimage 2013; 71: 224-232.
39. Insausti R, Amaral DG, Cowan WM. The entorhinal cortex of the monkey: II. Cortical afferents. J Comp Neurol 1987; 264: 356-395.
40. Bartolomei F, Khalil M, Wendling F, et al. Entorhinal cortex involvement in human mesial temporal lobe epilepsy: an electrophysiologic and volumetric study. Epilepsia 2005; 46: 677-687.
41. Bernhardt BC, Worsley KJ, Besson P, et al. Mapping limbic network organization in temporal lobe epilepsy using morphometric correlations: insights on the relation between mesiotemporal connectivity and cortical atrophy. Neuroimage 2008; 42: 515-524.
42. Cendes F. Febrile seizures and mesial temporal sclerosis. Curr Opin Neurol 2004; 17: 161-164.
43. Cascino GD, Jack CR Jr, Parisi JE, et al. Magnetic resonance imaging-based volume studies in temporal lobe epilepsy: pathological correlations. Ann Neurol 1991; 30: 31-36.
44. Sofroniew MV Molecular dissection of reactive astrogliosis and glial scar formation. Trends Neurosci 2009; 32: 638-647.
45. Binder DK, Steinhauser C. Functional changes in astroglial cells in epilepsy. Glia 2006; 54: 358-368.
46. Kang TC, Kim DS, Kwak SE, et al. Epileptogenic roles of astroglial death and regeneration in the dentate gyrus of experimental temporal lobe epilepsy. Glia 2006; 54: 258-271.
47. Eriksson SH, Thom M, Bartlett PA, et al. PROPELLER MRI visualizes detailed pathology of hippocampal sclerosis. Epilepsia 2008; 49: 33-39.
48. Tellez-Zenteno JF, Dhar R, Wiebe S. Long-term seizure outcomes following epilepsy surgery: a systematic review and meta-analysis. Brain 2005; 128(pt 5): 1188-1198.