Assessment of multiple sclerosis lesions with spherical harmonics comparison of MR imaging and pathologic findings

Radiology

Volumn 235, Issue 3, 2005, Pages 1036-1044

  Goldberg Zimring, Daniel ^a,b   Shalmon, Bruria ^c   Zou, Kelly H ^b,d   Azhari, Halm ^a   Nass, Dvora ^c   Achiron, Anat ^c,e  

^a TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

^b BRIGHAM AND WOMEN S HOSPITAL   (United States)

^c SHEBA MEDICAL CENTER   (Israel)

^d HARVARD MEDICAL SCHOOL   (United States)

^e TEL AVIV UNIVERSITY   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; AUTOPSY; CALCULATION; CLINICAL ARTICLE; COMPARATIVE STUDY; CONTROLLED STUDY; CORRELATION COEFFICIENT; DIAGNOSTIC ACCURACY; DIAGNOSTIC IMAGING; DIAGNOSTIC VALUE; DICE SIMILARITY COEFFICIENT; GEOMETRY; HISTOPATHOLOGY; HUMAN; HUMAN TISSUE; MULTIPLE SCLEROSIS; NUCLEAR MAGNETIC RESONANCE IMAGING; OBSERVER VARIATION; PATHOGENESIS; PRIORITY JOURNAL; QUANTITATIVE DIAGNOSIS; RANK SUM TEST; SPHERICAL HARMONICS; THREE DIMENSIONAL IMAGING; VOLUMETRY;

BRAIN; CADAVER; HUMANS; IMAGING, THREE-DIMENSIONAL; MATHEMATICS; MULTIPLE SCLEROSIS;

EID: 18944398303     PISSN: 00338419     EISSN: None     Source Type: Journal    
DOI: 10.1148/radiol.2353032071     Document Type: Article

References (31)

1. Kirshner HS, Tsai SI, Runge VM, Price AC. Magnetic resonance imaging and other techniques in the diagnosis of multiple sclerosis. Arch Neurol 1985; 42:859-863.
2. Newcombe J, Hawkins CP, Henderson CL, et al. Histopathology of multiple sclerosis lesions detected by magnetic resonance imaging in unfixed postmortem central nervous system tissue. Brain 1991; 114:1013-1023.
3. De Groot CJ, Bergers E, Kamphorst W, et al. Post-mortem MRI-guided sampling of multiple sclerosis brain lesions: increased yield of active demyelinating and (p)reactive lesions. Brain 2001; 124:1635-1645.
4. Goldberg-Zimring D, Azhari H, Miron S, Achiron A. 3D surface reconstruction of multiple sclerosis lesions using spherical harmonics. Magn Reson Med 2001; 46: 756-766.
5. Goldberg-Zimring D, Achiron A, Guttmann CRG, Azhari H. Three-dimensional analysis of the geometry of individual multiple sclerosis lesions: detection of shape changes over time using spherical harmonics. J Magn Reson Imaging 2003; 18:291-301.
6. Goldberg-Zimring D, Achiron A, Miron S, Faibel M, Azhari H. Automated detection and characterization of multiple sclerosis lesions in brain MR images. Magn Reson Imaging 1998; 16:311-318.
7. Styner M, Gerig G. Three-dimensional medial shape representation incorporating object variability. In: Proceedings of Computer Vision and Pattern Recognition CVPR. Vol 2. Kauai, Hawaii: IEEE Computer Society, 2001.
8. Gerig G, Styner M, Shenton ME, Lieberman JA. Shape versus size: improved understanding of the morphology of brain structures. In: Proceedings of the 4th International Conference on Medical Image Computing and Computer Assisted Intervention, Utrecht, the Netherlands. Heidelberg, Germany: Springer, 2001; 24-32.
9. Akima A. A new method of interpolating and smooth curve fitting based on local procedures. Assoc Comput Mach 1970; 17:589-602.
10. van Walderveen MA, Kamphorst W, Scheltens P, et al. Histopathologic correlate of hypointense lesions on T1-weighted spin-echo MRI in multiple sclerosis. Neurology 1998; 50:1282-1288.
11. Getty DJ, Seltzer SE, Tempany CM, Pickett RM, Swets JA, McNeil BJ. Prostate cancer: relative effects of demographic, clinical, histologic, and MR imaging variables on the accuracy of staging. Radiology 1997; 204:471-479.
12. Kurtz AB, Tsimikas JV, Tempany CM, et al. Diagnosis and staging of ovarian cancer: comparative values of Doppler and conventional US, CT, and MR imaging correlated with surgery and histopathologic analysis-report of the Radiology Diagnostic Oncology Group. Radiology 1999; 212:19-27.
13. Tempany CM, Zou KH, Silverman SG, Brown DL, Kurtz AB, McNeil BJ. Staging of advanced ovarian cancer: comparison of imaging modalities-report from the Radiological Diagnostic Oncology Group. Radiology 2000; 215:761-767.
14. Lin CC, Mudholkar GS. A simple test for normality against asymmetric alternatives. Biometrika 1980; 67:455-461.
15. Zou KH, Tempany CM, Fielding JR, Silverman SG. Original smooth receiver operating characteristic curve estimation from continuous data: statistical methods for analyzing the predictive value of spiral CT of ureteral stone. Acad Radiol 1998; 5:680-687.
16. Applegate KE, Tello R, Ying J. Hypothesis testing III: counts and medians. Radiology 2003; 228:603-608.
17. Zou KH, Tucali K, Silverman SG. Correlation and simple regression. Radiology 2003; 227:617-628.
18. Bharatha A, Hirose M, Hata N. Evaluation of three-dimensional finite element-based deformable registration of pre- and intra-operative prostate imaging. Med Phys 2001; 28:2551-2560.
19. Zijdenbos AP, Dawant BM, Margolin RA. Morphometric analysis of white matter lesions in MR images: method and validation. IEEE Trans Med Imaging 1994; 13:716-724.
20. Matthews WB, Compston A, Allen IV, Martyn CN. McAlpine's multiple sclerosis. London, England: Churchill Livingstone, 1991.
21. McAlpine D. The benign form of multiple sclerosis: a study based on 241 cases seen within 3 years of onset and followed up until the tenth year or more of the disease. Brain 1961; 84:186-203.
22. Kamber M, Shinghal R, Evans AC, Collins DC, Francis GS. Knowledge-based interpretation of magnetic resonance images: detecting multiple sclerosis lesions. Artif Intell Med 1993; 10:32-43.
23. Shepherd DI. Clinical features of multiple sclerosis in north-east Scotland. Acta Neurol Scand 1979; 60:218-230.
24. Fazekas F, Barkhof F, Filippi M. Unenhanced and enhanced magnetic resonance imaging in the diagnosis of multiple sclerosis. J Neurol Neurosurg Psychiatry 1998; 64(suppl 1):S2-S5.
25. McDonald WI, Compston A, Edan G, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the international panel on the diagnosis of multiple sclerosis. Ann Neurol 2001; 50:121-127.
26. Frohman EM, Goodin DS, Calabresi PA, et al. The utility of MRI in suspected MS: report of the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology. Neurology 2003; 61:602-611.
27. Brechbuhler C, Gerig G, Kubler O. Parameterization of closed surfaces for 3D shape description. Comput Vis Image Understanding 1995; 61:154-170.
28. Angenent S, Haker S, Tannenbaum A, Kikinis R. Laplace-Beltrami operator and brain surface flattening. IEEE Trans Med Imaging 1999; 18:700-711.
29. Haker S, Angenent S, Tannenbaum A, Halle M, Kikinis R. Conformal surface parameterization for texture mappings. IEEE Trans Vis Comput Graph 2000; 6:181-189.
30. van Waesberghe JH, Kamphorst W, De Groot CJ, et al. Axonal loss in multiple sclerosis lesions: magnetic resonance imaging insights into substrates of disability. Ann Neurol 1999; 46:747-754.
31. Jackson JD. Classical electrodynamics. New York, NY: Wiley, 1999.