TY - JOUR
T1 - Cost function masking during normalization of brains with focal lesions
T2 - Still a necessity?
AU - Andersen, Sarah M.
AU - Rapcsak, Steven Z.
AU - Beeson, Pélagie M.
N1 - Funding Information:
The authors would like to thank Tiffany Son for her help with this research, and Matthew Brett for his practical advice. The work reported in this paper was supported by grants DC008286 and DC007646 from the National Institute on Deafness and Other Communication Disorders . This material is the result of work supported, in part, with resources at the Southern Arizona VA Health Care System, Tucson, AZ.
PY - 2010/10
Y1 - 2010/10
N2 - Although normalization of brain images is critical to the analysis of structural damage across individuals, loss of tissue due to focal lesions presents challenges to the available normalization algorithms. Until recently, cost function masking, as advocated by Brett and colleagues (2001), was the accepted method to overcome difficulties encountered when normalizing damaged brains; however, development of the unified segmentation approach for normalization in SPM5 (Ashburner & Friston, 2005) offered an alternative. Crinion et al. (2007) demonstrated this approach produced normalization results without cost function masking that appeared to be robust to lesion effects when tested using the same simulated lesions studied by Brett et al. (2001). The present study sought to confirm the validity of this approach in brains with focal damage due to vascular events. To do so, we examined outcomes of normalization using unified segmentation with and without cost function masking in 49 brain images with chronic stroke. Lesion masks were created using two approaches (precise and rough drawings of lesion boundaries), and normalization was implemented with both smoothed and unsmoothed versions of the masks. We found that failure to employ cost function masking produced less accurate results in real and simulated lesions, compared to masked normalization, both in terms of deformation field displacement and voxelwise intensity differences. Additionally, unmasked normalization led to significant underestimation of lesion volume relative to all four masking conditions, especially in patients with large lesions. Taken together, these findings suggest cost function masking is still necessary when normalizing brain images with chronic infarcts.
AB - Although normalization of brain images is critical to the analysis of structural damage across individuals, loss of tissue due to focal lesions presents challenges to the available normalization algorithms. Until recently, cost function masking, as advocated by Brett and colleagues (2001), was the accepted method to overcome difficulties encountered when normalizing damaged brains; however, development of the unified segmentation approach for normalization in SPM5 (Ashburner & Friston, 2005) offered an alternative. Crinion et al. (2007) demonstrated this approach produced normalization results without cost function masking that appeared to be robust to lesion effects when tested using the same simulated lesions studied by Brett et al. (2001). The present study sought to confirm the validity of this approach in brains with focal damage due to vascular events. To do so, we examined outcomes of normalization using unified segmentation with and without cost function masking in 49 brain images with chronic stroke. Lesion masks were created using two approaches (precise and rough drawings of lesion boundaries), and normalization was implemented with both smoothed and unsmoothed versions of the masks. We found that failure to employ cost function masking produced less accurate results in real and simulated lesions, compared to masked normalization, both in terms of deformation field displacement and voxelwise intensity differences. Additionally, unmasked normalization led to significant underestimation of lesion volume relative to all four masking conditions, especially in patients with large lesions. Taken together, these findings suggest cost function masking is still necessary when normalizing brain images with chronic infarcts.
KW - Cost function masking
KW - Normalization
KW - Structural MRI
KW - Unified segmentation
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U2 - 10.1016/j.neuroimage.2010.06.003
DO - 10.1016/j.neuroimage.2010.06.003
M3 - Article
C2 - 20542122
AN - SCOPUS:77955303792
SN - 1053-8119
VL - 53
SP - 78
EP - 84
JO - NeuroImage
JF - NeuroImage
IS - 1
ER -