Tags

Type your tag names separated by a space and hit enter

An MRI-based index to measure the severity of Alzheimer's disease-like structural pattern in subjects with mild cognitive impairment.

Abstract

BACKGROUND

Structural magnetic resonance imaging (MRI) is sensitive to neurodegeneration and can be used to estimate the risk of converting to Alzheimer's disease (AD) in individuals with mild cognitive impairment (MCI). Brain changes in AD and prodromal AD involve a pattern of widespread atrophy. The use of multivariate analysis algorithms could enable the development of diagnostic tools based on structural MRI data. In this study, we investigated the possibility of combining multiple MRI features in the form of a severity index.

METHODS

We used baseline MRI scans from two large multicentre cohorts (AddNeuroMed and ADNI). On the basis of volumetric and cortical thickness measures at baseline with AD cases and healthy control (CTL) subjects as training sets, we generated an MRI-based severity index using the method of orthogonal projection to latent structures (OPLS). The severity index tends to be close to 1 for AD patients and 0 for CTL subjects. Values above 0.5 indicate a more AD-like pattern. The index was then estimated for subjects with MCI, and the accuracy of classification was investigated.

RESULTS

Based on the data at follow-up, 173 subjects converted to AD, of whom 112 (64.7%) were classified as AD-like and 61 (35.3%) as CTL-like.

CONCLUSION

We found that joint evaluation of multiple brain regions provided accurate discrimination between progressive and stable MCI, with better performance than hippocampal volume alone, or a limited set of features. A major challenge is still to determine optimal cut-off points for such parameters and to compare their relative reliability.

Links

  • PMC Free PDF
  • PMC Free Full Text
  • FREE Publisher Full Text
  • Authors+Show Affiliations

    ,

    Institute of Clinical Medicine, Unit of Neurology, University of Eastern Finland, University Hospital of Kuopio, Kuopio, Finland. gabriela.spulber@ki.se

    , , , , , , , , , , ,

    Source

    Journal of internal medicine 273:4 2013 Apr pg 396-409

    MeSH

    Aged
    Aged, 80 and over
    Algorithms
    Alzheimer Disease
    Brain
    Cognitive Dysfunction
    Disease Progression
    Female
    Follow-Up Studies
    Humans
    Image Processing, Computer-Assisted
    Magnetic Resonance Imaging
    Male
    Middle Aged
    Neuropsychological Tests
    Reproducibility of Results
    Severity of Illness Index

    Pub Type(s)

    Comparative Study
    Journal Article
    Multicenter Study
    Randomized Controlled Trial
    Research Support, N.I.H., Extramural
    Research Support, Non-U.S. Gov't

    Language

    eng

    PubMed ID

    23278858

    Citation

    Spulber, G, et al. "An MRI-based Index to Measure the Severity of Alzheimer's Disease-like Structural Pattern in Subjects With Mild Cognitive Impairment." Journal of Internal Medicine, vol. 273, no. 4, 2013, pp. 396-409.
    Spulber G, Simmons A, Muehlboeck JS, et al. An MRI-based index to measure the severity of Alzheimer's disease-like structural pattern in subjects with mild cognitive impairment. J Intern Med. 2013;273(4):396-409.
    Spulber, G., Simmons, A., Muehlboeck, J. S., Mecocci, P., Vellas, B., Tsolaki, M., ... Westman, E. (2013). An MRI-based index to measure the severity of Alzheimer's disease-like structural pattern in subjects with mild cognitive impairment. Journal of Internal Medicine, 273(4), pp. 396-409. doi:10.1111/joim.12028.
    Spulber G, et al. An MRI-based Index to Measure the Severity of Alzheimer's Disease-like Structural Pattern in Subjects With Mild Cognitive Impairment. J Intern Med. 2013;273(4):396-409. PubMed PMID: 23278858.
    * Article titles in AMA citation format should be in sentence-case
    TY - JOUR T1 - An MRI-based index to measure the severity of Alzheimer's disease-like structural pattern in subjects with mild cognitive impairment. AU - Spulber,G, AU - Simmons,A, AU - Muehlboeck,J-S, AU - Mecocci,P, AU - Vellas,B, AU - Tsolaki,M, AU - Kłoszewska,I, AU - Soininen,H, AU - Spenger,C, AU - Lovestone,S, AU - Wahlund,L-O, AU - Westman,E, AU - ,, Y1 - 2013/01/30/ PY - 2012/10/25/accepted PY - 2013/1/3/entrez PY - 2013/1/3/pubmed PY - 2013/5/8/medline SP - 396 EP - 409 JF - Journal of internal medicine JO - J. Intern. Med. VL - 273 IS - 4 N2 - BACKGROUND: Structural magnetic resonance imaging (MRI) is sensitive to neurodegeneration and can be used to estimate the risk of converting to Alzheimer's disease (AD) in individuals with mild cognitive impairment (MCI). Brain changes in AD and prodromal AD involve a pattern of widespread atrophy. The use of multivariate analysis algorithms could enable the development of diagnostic tools based on structural MRI data. In this study, we investigated the possibility of combining multiple MRI features in the form of a severity index. METHODS: We used baseline MRI scans from two large multicentre cohorts (AddNeuroMed and ADNI). On the basis of volumetric and cortical thickness measures at baseline with AD cases and healthy control (CTL) subjects as training sets, we generated an MRI-based severity index using the method of orthogonal projection to latent structures (OPLS). The severity index tends to be close to 1 for AD patients and 0 for CTL subjects. Values above 0.5 indicate a more AD-like pattern. The index was then estimated for subjects with MCI, and the accuracy of classification was investigated. RESULTS: Based on the data at follow-up, 173 subjects converted to AD, of whom 112 (64.7%) were classified as AD-like and 61 (35.3%) as CTL-like. CONCLUSION: We found that joint evaluation of multiple brain regions provided accurate discrimination between progressive and stable MCI, with better performance than hippocampal volume alone, or a limited set of features. A major challenge is still to determine optimal cut-off points for such parameters and to compare their relative reliability. SN - 1365-2796 UR - https://www.unboundmedicine.com/medline/citation/23278858/An_MRI_based_index_to_measure_the_severity_of_Alzheimer's_disease_like_structural_pattern_in_subjects_with_mild_cognitive_impairment_ L2 - https://doi.org/10.1111/joim.12028 DB - PRIME DP - Unbound Medicine ER -