Semiautomatic brain region extraction: a method of parcellating brain regions from structural magnetic resonance images

Structural MR imaging has become essential to the evaluation of regional brain changes in both healthy aging and disease-related processes. Several methods have been developed to measure structure size and regional brain volumes, but many of these methods involve substantial manual tracing and/or la...

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Veröffentlicht in:NeuroImage (Orlando, Fla.) Fla.), 2004-08, Vol.22 (4), p.1492-1502
Hauptverfasser: Dade, L.A, Gao, F.Q, Kovacevic, N, Roy, P, Rockel, C, O'Toole, C.M, Lobaugh, N.J, Feinstein, A, Levine, B, Black, S.E
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Sprache:eng
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Zusammenfassung:Structural MR imaging has become essential to the evaluation of regional brain changes in both healthy aging and disease-related processes. Several methods have been developed to measure structure size and regional brain volumes, but many of these methods involve substantial manual tracing and/or landmark identification. We present a new technique, semiautomatic brain region extraction (SABRE), for the rapid and reliable parcellation of cortical and subcortical brain regions. We combine the SABRE parcellation with tissue compartment segmentation [NeuroImage 17 (2002) 1087] to produce measures of gray matter (GM), white matter (WM), ventricular CSF, and sulcal CSF for 26 brain regions. Because SABRE restricts user input to a few easily identified landmarks, inter-rater reliability is high for all volumes, with all coefficients between 0.91 and 0.99. To assess construct validity, we contrasted SABRE-derived volumetric data from healthy young and older adults. Results from the SABRE parcellation and tissue segmentation showed significant differences in multiple brain regions in keeping with regional atrophy described in the literature by researchers using lengthy manual tracing methods. Our findings show that SABRE is a reliable semiautomatic method for assessing regional tissue volumes that provides significant timesavings over purely manual methods, yet maintains information about individual cortical landmarks.
ISSN:1053-8119
1095-9572
DOI:10.1016/j.neuroimage.2004.03.023