Defining thresholds for changes in size of simulated T2-hyperintense brain lesions on the basis of qualitative comparisons

American Journal of Roentgenology

Volumn 180, Issue 1, 2003, Pages 65-69

  Melhem, Elias R ^a,b,c   Herskovits, Edward H ^a,d   Karli Oguz, Kader ^a   Golay, Xavier ^c   Hammoud, Dima A ^a   Fortman, Brian J ^a   Munter, Fletcher M ^a   Itoh, Ryuta ^a,c  

^a DEPARTMENT OF PATHOLOGY   (United States)

^b KENNEDY KRIEGER INSTITUTE   (United States)

^c HOSPITAL OF THE UNIVERSITY OF PENNSYLVANIA   (United States)

^d JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ARTICLE; BRAIN INJURY; COMPARATIVE STUDY; DATA ANALYSIS; DISEASE SIMULATION; FEMALE; HUMAN; IMAGE ANALYSIS; LOGISTIC REGRESSION ANALYSIS; MULTIPLE SCLEROSIS; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; QUALITATIVE ANALYSIS; SIMULATOR;

EID: 0037215629     PISSN: 0361803X     EISSN: None     Source Type: Journal    
DOI: 10.2214/ajr.180.1.1800065     Document Type: Article

References (37)

1. Miller DH. Magnetic resonance in monitoring the treatment of multiple sclerosis. Ann Neurol 1994;36[suppl]:S91-S94
2. Miller DH, Albert PS, Barkhof F, et al. Guidelines for the use of magnetic resonance techniques in monitoring the treatment of multiple sclerosis: US National MS Society Task Force. Ann Neurol 1996;39:6-16
3. Carswell H, MS researchers assess MRI as outcome tool. Diagn Imaging 1996;18:49-51
4. Zhao GJ, Li DK, Wolinsky JS, et al. Clinical and magnetic resonance imaging changes correlate in a clinical trial monitoring cyclosporine therapy for multiple sclerosis: The MS Study Group. J Neuroimaging 1997:7:1-7
5. D'yachkova Y, Petkau J, White R. Longitudinal analyses for magnetic resonance imaging outcomes in multiple sclerosis clinical trials. J Biopharm Stat 1997;7:501-531
6. Erickson BJ, Noseworthy JH. Value of magnetic resonance imaging in assessing efficacy in clinical trials of multiple sclerosis therapies. Mayo Clin Proc 1997;72:1080-1089
7. Evans AC, Frank JA, Antel J, Miller DH. The role of MRI in clinical trials of multiple sclerosis: Comparison of image processing techniques. Ann Neurol 1997;41:125-132
8. Filippi M, Horsfield MA, Ader HJ, et al. Guidelines for using quantitative measures of brain magnetic resonance imaging abnormalities in monitoring the treatment of multiple sclerosis. Ann Neurol 1998:43:499-506
9. Castelijns JA, Barkhof F. Magnetic resonance (MR) imaging as a marker for multiple sclerosis. Biomed Phannacother 1999;53:351-357
10. Stevenson VL, Miller DH. Magnetic resonance imaging in the monitoring of disease progression in multiple sclerosis. Mult Scler 1999;5:268-272
11. Molyneux PD, Miller DH, Filippi M, et al. The use of magnetic resonance imaging in multiple sclerosis treatment trials: Power calculations for annual lesion load measurement. J Neurol 2000;247:34-40
12. Verlhac S, Bemaudin F, Tortrat D, et al. Detection of cerebrovascular disease in patients with sickle cell disease using transcranial Doppler sonography: correlation with MRI, MRA and conventional angiography. Pediatr Radiol 1995:25[suppl]:S14-S19
13. Adams RJ. Stroke prevention and treatment in sickle cell disease. Arch Neurol 2001;58:565-568
14. Brown RT, Davis PC, Lambert R, Hsu L, Hopkins K, Eckman J. Neurocognitive functioning and magnetic resonance imaging in children with sickle cell disease. J Pediatr Psychol 2000:25:503-513
15. Levin HS, Williams DH, Eisenberg HM, High WM Jr, Guinto FC Jr. Serial MRI and neurobehavioral findings after mild to moderate closed head injury. J Neurol Neurosurg Psychiatry, 1992;55:255-262
16. Bryan RN, Wells SW, Miller TJ, et al. Infarctlike lesions in the brain: Prevalence and anatomic characteristics at MR imaging of the elderly - Data from the Cardiovascular Health Study. Radiology 1997;202:47-54
17. Manolio TA, Kronmal RA, Burke GL, et al. Magnetic resonance abnormalities and cardiovascular disease in older adults: The Cardiovascular Health Study. Stroke 1994:25:318-327
18. Bryan RN, Manolio TA, Schertz LD, et al. A method for using MR to evaluate the effects of cardiovascular disease on the brain: The Cardiovascular Health Study. AJNR 1994;15:1625-1633
19. Kikinis R, Shenton ME, Gerig G, et al. Routine quantitative analysis of brain and cerebrospinal fluid spaces with MR imaging. J Magn Reson Imaging 1992;2:619-629
20. Mitchell JR, Karlik SJ, Lee DH, Eliasziw M, Rice GP, Fenster A. The variability of manual and computer assisted quantification of multiple sclerosis lesion volumes. Med Phys 1996;23:85-97
21. Filippi M, van Waesberghe JH, Horsfield MA, et al. Interscanner variation in brain MRI lesion load measurements in MS: Implications for clinical trials. Neurology 1997;49:371-377
22. Filippi M, Marciano N, Capra R, et al. The effect of imprecise repositioning on lesion volume measurements in patients with multiple sclerosis. Neurology 1997;49:274-276
23. Rovaris M, Gawne-Cain ML, Sormani MP, Miller DH, Filippi M. The effect of repositioning on brain MRI lesion load assessment in multiple sclerosis: Reliability of subjective quality criteria. J Neurol 1998;245:273-275
24. Rovaris M, Gawne-Cain ML, Wang L, Miller DH. A comparison of conventional and fast spin-echo sequences for the measurement of lesion load in multiple sclerosis using a semi-automated contour technique. Neuroradiology 1997:39:161-165
25. Udupa JK, Wei L, Samarasekera S, Miki Y, van Buchem MA, Grossman RI. Multiple sclerosis lesion quantification using fuzzy-connectedness principles. IEEE Trans Med Imaging 1997;16:598-609
26. Molyneux PD, Tubridy N, Parker GJ, et al. The effect of section thickness on MR lesion detection and quantification in multiple sclerosis. AJNR 1998;19:1715-1720
27. Gallagher HL, MacManus DG, Webb SL, Miller DH. A reproducible repositioning method for serial magnetic resonance imaging studies of the brain in treatment trials for multiple sclerosis. J Magn Reson Imaging 1997;7:439-441
28. Hajnal JV, Saeed N, Soar EJ, Oatridge A, Young IR, Bydder GM. A registration and interpolation procedure for subvoxel matching of serially acquired MR images. J Comput Assist Tomogr 1995;19:289-296
29. Tofts PS, Barker GJ, Filippi M, Gawne-Cain M, Lai M. An oblique cylinder contrast-adjusted (OCCA) phantom to measure the accuracy of MRI brain lesion volume estimation schemes in multiple sclerosis. Magn Reson Imaging 1997;15:183-192
30. Herskovits EH, Itoh R, Melhem ER. Accuracy for detection of simulated lesions: Comparison of fluid-attenuated inversion-recovery, proton density-weighted, and T2-weighted synthetic brain MR imaging. AJR 2001;176:1313-1318
31. In den Kleef JJE, Cuppen JJM. RLSQ: TI, T2, and rho calculations, combining ratios and least squares. Magn Reson Med 1987:5:513-524
32. Droege RT, Wiener SN, Rzeszotarski MS, et al. Nuclear magnetic resonance: A gray scale model for head images. Radiology 1983;148:763-771
33. Sperber GO, Ericsson A, Hemmingsson A, Jung B, Thuomas KA. Improved formulae for signal amplitudes in repeated NMR sequences: Applications in NMR imaging. Magn Reson Med 1986;3:685-698
34. Melki PS, Jolesz FA, Mulkem RV. Partial RF echo planar imaging with the FAISE method. II. Contrast equivalence with spin-echo sequences. Magn Reson Med 1992;26:342-354
35. Constable RT, Anderson AW, Zhong J, Gore JC. Factors influencing contrast in fast spin-echo MR imaging. Magn Reson Imaging 1992;10:497-511
36. Melki PS, Mulkem RV, Panych LP, et al. Comparing the FAISE method with conventional dual-echo sequences. J Magn Reson Imaging 1991;1:319-326
37. Constable RT, Gore JC. The loss of small objects in variable TE imaging: Implications for FSE, RARE, and EPI. Magn Reson Med 1992;28:9-24