title: Multivariate classification of patients with Alzheimer's and dementia with Lewy bodies using high-dimensional cortical thickness measurements: an MRI surface-based morphometric study.
abstract: BACKGROUND
  Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) are the most common neurodegenerative dementia types. It is important to differentiate between them because of the differences in prognosis and treatment approaches.
  
  
  OBJECTIVE
  Investigate if sparse partial least squares (SPLS) classification of cortical thickness measurements could differentiate between AD and DLB.
  
  
  METHODS
  Two independent cohorts without MR-protocol alignment in Norway and Slovenia with 97 AD and DLB subjects were enrolled. Cortical thickness measurements acquired with Freesurfer were used in subsequent SPLS classification runs. The cohorts were analyzed separately and afterwards combined. The models were trained with leave-one-out cross validation and test datasets where used when available. To study the impact of MR-protocol alignment, the classifiers were additionally tested on sets drawn exclusively from the independent cohorts.
  
  
  RESULTS
  The obtained sensitivity/specificity/AUC values were 94.4/88.89/0.978 and 88.2/94.1/0.969 in the Norwegian and Slovenian cohorts, respectively. Both cohorts showed AD-associated pattern of thinning in mid-anterior temporal, occipital and subgenual cingulate cortex, whereas the pattern supportive for DLB included thinning in dorsal cingulate, posterior temporal and lateral orbitofrontal regions. When combining the cohorts, sensitivity/specificity/AUC were 82.1/85.7/0.948 for the training and 77.8/75/0.731 for the testing datasets with the same pattern-of-difference. The models tested on datasets drawn exclusively from the independent cohorts did not produce adequate accuracy.
  
  
  CONCLUSIONS
  SPLS classification of cortical thickness is a good method for differentiating between AD and DLB, relatively stable even for mixed data, but not when tested on completely independent data drawn from different cohorts (without MR-protocol alignment).
authors.affiliation: Centre for Age-Related Medicine, Stavanger University Hospital, PO Box 8100, 4068 Stavanger, Norway. alexander.vl.lebedev@gmail.com
authors.forename: Alexander V
authors.initials: AV
authors.lastname: Lebedev
authors.forename: E
authors.initials: E
authors.lastname: Westman
authors.forename: M K
authors.initials: MK
authors.lastname: Beyer
authors.forename: M G
authors.initials: MG
authors.lastname: Kramberger
authors.forename: C
authors.initials: C
authors.lastname: Aguilar
authors.forename: Z
authors.initials: Z
authors.lastname: Pirtosek
authors.forename: D
authors.initials: D
authors.lastname: Aarsland
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000000981:diagnostic imaging / Q000473:pathology*; D019540:Area Under Curve; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000000981:diagnostic imaging / Q000473:pathology*; D015331:Cohort Studies; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D020961:Lewy Body Disease / Q000000981:diagnostic imaging / Q000473:pathology*; D008279:Magnetic Resonance Imaging; D008297:Male; D015999:Multivariate Analysis; D011180:Postmortem Changes; D025341:Principal Component Analysis; D015899:Tomography, Emission-Computed, Single-Photon; D014326:Tropanes
chemical_list: D014326:Tropanes; C087552:2-carbomethoxy-8-(3-fluoropropyl)-3-(4-iodophenyl)tropane