Tags

Type your tag names separated by a space and hit enter

Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: results from ADNI.
Neuroimage 2009; 44(4):1415-22N

Abstract

High-dimensional pattern classification was applied to baseline and multiple follow-up MRI scans of the Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with mild cognitive impairment (MCI), in order to investigate the potential of predicting short-term conversion to Alzheimer's Disease (AD) on an individual basis. MCI participants that converted to AD (average follow-up 15 months) displayed significantly lower volumes in a number of grey matter (GM) regions, as well as in the white matter (WM). They also displayed more pronounced periventricular small-vessel pathology, as well as an increased rate of increase of such pathology. Individual person analysis was performed using a pattern classifier previously constructed from AD patients and cognitively normal (CN) individuals to yield an abnormality score that is positive for AD-like brains and negative otherwise. The abnormality scores measured from MCI non-converters (MCI-NC) followed a bimodal distribution, reflecting the heterogeneity of this group, whereas they were positive in almost all MCI converters (MCI-C), indicating extensive patterns of AD-like brain atrophy in almost all MCI-C. Both MCI subgroups had similar MMSE scores at baseline. A more specialized classifier constructed to differentiate converters from non-converters based on their baseline scans provided good classification accuracy reaching 81.5%, evaluated via cross-validation. These pattern classification schemes, which distill spatial patterns of atrophy to a single abnormality score, offer promise as biomarkers of AD and as predictors of subsequent clinical progression, on an individual patient basis.

Authors+Show Affiliations

Department of Radiology, Section of Biomedical Image Analysis, University of Pennsylvania, School of Medicine, Philadelphia, PA 19104, USA.No affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

19027862

Citation

Misra, Chandan, et al. "Baseline and Longitudinal Patterns of Brain Atrophy in MCI Patients, and Their Use in Prediction of Short-term Conversion to AD: Results From ADNI." NeuroImage, vol. 44, no. 4, 2009, pp. 1415-22.
Misra C, Fan Y, Davatzikos C. Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: results from ADNI. Neuroimage. 2009;44(4):1415-22.
Misra, C., Fan, Y., & Davatzikos, C. (2009). Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: results from ADNI. NeuroImage, 44(4), pp. 1415-22. doi:10.1016/j.neuroimage.2008.10.031.
Misra C, Fan Y, Davatzikos C. Baseline and Longitudinal Patterns of Brain Atrophy in MCI Patients, and Their Use in Prediction of Short-term Conversion to AD: Results From ADNI. Neuroimage. 2009 Feb 15;44(4):1415-22. PubMed PMID: 19027862.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: results from ADNI. AU - Misra,Chandan, AU - Fan,Yong, AU - Davatzikos,Christos, Y1 - 2008/11/05/ PY - 2008/07/24/received PY - 2008/10/13/revised PY - 2008/10/16/accepted PY - 2008/11/26/pubmed PY - 2009/3/27/medline PY - 2008/11/26/entrez SP - 1415 EP - 22 JF - NeuroImage JO - Neuroimage VL - 44 IS - 4 N2 - High-dimensional pattern classification was applied to baseline and multiple follow-up MRI scans of the Alzheimer's Disease Neuroimaging Initiative (ADNI) participants with mild cognitive impairment (MCI), in order to investigate the potential of predicting short-term conversion to Alzheimer's Disease (AD) on an individual basis. MCI participants that converted to AD (average follow-up 15 months) displayed significantly lower volumes in a number of grey matter (GM) regions, as well as in the white matter (WM). They also displayed more pronounced periventricular small-vessel pathology, as well as an increased rate of increase of such pathology. Individual person analysis was performed using a pattern classifier previously constructed from AD patients and cognitively normal (CN) individuals to yield an abnormality score that is positive for AD-like brains and negative otherwise. The abnormality scores measured from MCI non-converters (MCI-NC) followed a bimodal distribution, reflecting the heterogeneity of this group, whereas they were positive in almost all MCI converters (MCI-C), indicating extensive patterns of AD-like brain atrophy in almost all MCI-C. Both MCI subgroups had similar MMSE scores at baseline. A more specialized classifier constructed to differentiate converters from non-converters based on their baseline scans provided good classification accuracy reaching 81.5%, evaluated via cross-validation. These pattern classification schemes, which distill spatial patterns of atrophy to a single abnormality score, offer promise as biomarkers of AD and as predictors of subsequent clinical progression, on an individual patient basis. SN - 1095-9572 UR - https://www.unboundmedicine.com/medline/citation/19027862/Baseline_and_longitudinal_patterns_of_brain_atrophy_in_MCI_patients_and_their_use_in_prediction_of_short_term_conversion_to_AD:_results_from_ADNI_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S1053-8119(08)01125-7 DB - PRIME DP - Unbound Medicine ER -