Early diagnosis of dementia based on intersubject whole-brain dissimilarities

TY - GEN

T1 - Early diagnosis of dementia based on intersubject whole-brain dissimilarities

AU - Klein, S.

AU - Loog, M.

AU - Lijn, F. van der

AU - Heijer, T. den

AU - Hammers, A.

AU - de Bruijne, Marleen

AU - Lugt, A. van der

AU - Duin, R. P. W.

AU - Breteler, M. M. B.

AU - Niessen, W. J.

N1 - Conference code: 7

PY - 2010

Y1 - 2010

N2 - This article studies the possibility of detecting dementia in an early stage, using nonrigid registration of MR brain scans in combination with dissimilarity-based pattern recognition techniques. Instead of focussing on the shape of a single brain structure, we take into account the shape differences within the entire brain. Imaging data was obtained from a longitudinal, population based study of the elderly. A set of 29 subjects was identified, who were asymptomatic at the time of scanning, but were diagnosed as having dementia within 0.7 to 5 years after the scan, and a set of 29 age and gender matched healthy controls were selected. Each subject was registered to all other subjects, using a nonrigid registration algorithm. Based on statistics of the deformation field in the brain, a dissimilarity measure was calculated between each pair of subjects, yielding a 58×58 dissimilarity matrix. A kNN classifier was trained on the dissimilarity matrix and the performance was tested in a leave-one-out experiment. A classification accuracy of 81% was attained (spec. 83%, sens. 79%). This demonstrates the potential of whole-brain intersubject dissimilarities to aid in early diagnosis of dementia.

AB - This article studies the possibility of detecting dementia in an early stage, using nonrigid registration of MR brain scans in combination with dissimilarity-based pattern recognition techniques. Instead of focussing on the shape of a single brain structure, we take into account the shape differences within the entire brain. Imaging data was obtained from a longitudinal, population based study of the elderly. A set of 29 subjects was identified, who were asymptomatic at the time of scanning, but were diagnosed as having dementia within 0.7 to 5 years after the scan, and a set of 29 age and gender matched healthy controls were selected. Each subject was registered to all other subjects, using a nonrigid registration algorithm. Based on statistics of the deformation field in the brain, a dissimilarity measure was calculated between each pair of subjects, yielding a 58×58 dissimilarity matrix. A kNN classifier was trained on the dissimilarity matrix and the performance was tested in a leave-one-out experiment. A classification accuracy of 81% was attained (spec. 83%, sens. 79%). This demonstrates the potential of whole-brain intersubject dissimilarities to aid in early diagnosis of dementia.

U2 - 10.1109/ISBI.2010.5490366

DO - 10.1109/ISBI.2010.5490366

M3 - Article in proceedings

SN - 978-1-4244-4125-9

SP - 249

EP - 252

BT - 2010 IEEE International Symposium on Biomedical Imaging

PB - IEEE

T2 - 7th IEEE International Symposium on Biomedical Imaging

Y2 - 14 April 2010 through 17 April 2010

ER -