MR imaging of brain volumes: Evaluation of a fully automatic software

American Journal of Neuroradiology

Volumn 32, Issue 2, 2011, Pages 408-412

  Ambarki, Khalid ^a   Wahlin A ^a   Birgander, R ^a   Eklund, A ^a   Malm, J ^a  

^a UMEÅ UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

AGED; ARTICLE; AUTOMATION; BRAIN SIZE; CLINICAL ARTICLE; CLINICAL EVALUATION; COMPUTER PROGRAM; CONTROLLED STUDY; FEMALE; HUMAN; HYDROCEPHALUS; LINEAR REGRESSION ANALYSIS; MALE; NUCLEAR MAGNETIC RESONANCE IMAGING;

AGED; AGING; BRAIN; FEMALE; HUMANS; HYDROCEPHALUS; LINEAR MODELS; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; REFERENCE STANDARDS; REPRODUCIBILITY OF RESULTS; SOFTWARE;

EID: 79951614962     PISSN: 01956108     EISSN: 1936959X     Source Type: Journal    
DOI: 10.3174/ajnr.A2275     Document Type: Article

References (28)

1. Ambarki K, Israelsson H, Wahlin A, et al. Brain ventricular size in healthy elderly: comparison between Evans index and volume measurement. Neurosurgery 67:94-99, discussion 99
2. Yoshita M, Fletcher E, Harvey D, et al. Extent and distribution of white matter hyperintensities in normal aging, MCI, and AD. Neurology 2006;67:2192-98
3. 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
4. Desikan RS, Cabral HJ, Fischl B, et al. Temporoparietal MR imaging measures of atrophy in subjects with mild cognitive impairment that predict subsequent diagnosis of Alzheimer disease. AJNR Am J Neuroradiol 2009;30:532-38
5. Fjell AM, Amlien IK, Westlye LT, et al. Mini-mental state examination is sensitive to brain atrophy in Alzheimer's disease. Dement Geriatr Cogn Disord 2009;28:252-58
6. Henneman WJ, Sluimer JD, Barnes J, et al. Hippocampal atrophy rates in Alzheimer disease: added value over whole brain volume measures. Neurology 2009;72:999-1007
7. Zeidman LA, Ankenbrandt WJ, Du H, et al. Growth rate of non-operated meningiomas. J Neurol 2008;255:891-95
8. Condon B, Patterson J, Wyper D, et al. Use of magnetic resonance imaging to measure intracranial cerebrospinal fluid volume. Lancet 1986;1:1355-57
9. Kohn MI, Tanna NK, Herman GT, et al. Analysis of brain and cerebrospinal fluid volumes with MR imaging. Part I. Methods, reliability, and validation. Radiology 1991;178:115-22
10. Anbeek P, Vincken KL, van Osch MJ, et al. Automatic segmentation of different-sized white matter lesions by voxel probability estimation. Med Image Anal 2004;8:205-15
11. Wen W, Sachdev P. The topography of white matter hyperintensities on brain MRI in healthy 60- to 64-year-old individuals. Neuroimage 2004;22:144-54
12. Admiraal-Behloul F, van den Heuvel DM, Olofsen H, et al. Fully automatic segmentation of white matter hyperintensities in MR images of the elderly. Neuroimage 2005;28:607-17
13. Maillard P, Delcroix N, Crivello F, et al. An automated procedure for the assessment of white matter hyperintensities by multispectral (T1, T2, PD) MRI and an evaluation of its between-centre reproducibility based on two large community databases. Neuroradiology 2008;50:31-42
14. Lehmann M, Douiri A, Kim LG, et al. Atrophy patterns in Alzheimer's disease and semantic dementia: a comparison of FreeSurfer and manual volumetric measurements. Neuroimage 2010;49:2264-74. Epub 2009 Oct 27
15. Relkin N, Marmarou A, Klinge P, et al. Diagnosing idiopathic normal-pressure hydrocephalus. Neurosurgery 2005;57:S4-16, discussion ii-v
16. Malm J, Eklund A. Idiopathic normal pressure hydrocephalus. Pract Neurol 2006;6:14-27
17. Ambarki K, Israelsson H, Wåhlin A, et al. Brain ventricular size in healthy elderly: comparison between Evans index and volume measurement. Neurosurgery 2010;67:94-99; discussion 99
18. Evans W. An encephalographic ratio for estimating ventricular enlargement and cerebral atrophy. Arch Neurol Psychiatry 1942;47:931-37
19. Jasperse B, Valsasina P, Neacsu V, et al. Intercenter agreement of brain atrophy measurement in multiple sclerosis patients using manually-editedSIENAand SIENAX. J Magn Reson Imaging 2007;26:881-85
20. Palm WM, Walchenbach R, Bruinsma B, et al. Intracranial compartment volumes in normal pressure hydrocephalus: volumetric assessment versus outcome. AJNR Am J Neuroradiol 2006;27:76-79
21. van den Heuvel DM, ten Dam VH, de Craen AJ, et al. Measuring longitudinal white matter changes: comparison of a visual rating scale with a volumetric measurement. AJNR Am J Neuroradiol 2006;27:875-78
22. Palm WM, Saczynski JS, van der Grond J, et al. Ventricular dilation: association with gait and cognition. Ann Neurol 2009;66:485-93
23. Huppertz HJ, Kroll-Seger J, Kloppel S, et al. Intra- and interscanner variability of automated voxel-based volumetry based on a 3D probabilistic atlas of human cerebral structures. Neuroimage 2010;49:2216-24. Epub 2009 Oct 28
24. Barkhof F, Scheltens P. Imaging of white matter lesions. Cerebrovasc Dis 2002;13(suppl 2):21-30
25. Piguet O, Ridley LJ, Grayson DA, et al. Comparing white matter lesions on T2 and FLAIR MRI in the Sydney Older Persons Study. Eur J Neurol 2005;12:399-402
26. van Straaten EC, Fazekas F, Rostrup E, et al. Impact of white matter hyperintensities scoring method on correlations with clinical data: the LADIS study. Stroke 2006;37:836-40. Epub 2006 Jan 26
27. Klauschen F, Goldman A, Barra V, et al. Evaluation of automated brain MR image segmentation and volumetry methods. Hum Brain Mapp 2009;30:1310-27
28. Cocosco C, Kollokian V, Kwan R-S, et al. BrainWeb: online interface to a 3D MRI simulated brain database. In: Proceedings of the Third International Conference on Functional Mapping of the Human Brain. Copenhagen, Denmark. May 19-23, 1997