eprintid: 10129988 rev_number: 21 eprint_status: archive userid: 608 dir: disk0/10/12/99/88 datestamp: 2021-06-22 10:58:16 lastmod: 2021-11-10 01:57:17 status_changed: 2021-06-22 10:58:16 type: article metadata_visibility: show creators_name: Archetti, D creators_name: Young, AL creators_name: Oxtoby, NP creators_name: Ferreira, D creators_name: Mårtensson, G creators_name: Westman, E creators_name: Alexander, DC creators_name: Frisoni, GB creators_name: Redolfi, A creators_name: for Alzheimer’s Disease Neuroimaging Initiative and EuroPOND Con, title: Inter-Cohort Validation of SuStaIn Model for Alzheimer's Disease ispublished: pub divisions: UCL divisions: B04 divisions: C05 divisions: F48 keywords: SuStain model, alzheiemer’s disease, inter-cohort validation, patient staging, patient subtyping note: Copyright © 2021 Archetti, Young, Oxtoby, Ferreira, Mårtensson, Westman, Alexander, Frisoni and Redolfi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. abstract: Alzheimer's disease (AD) is a neurodegenerative disorder which spans several years from preclinical manifestations to dementia. In recent years, interest in the application of machine learning (ML) algorithms to personalized medicine has grown considerably, and a major challenge that such models face is the transferability from the research settings to clinical practice. The objective of this work was to demonstrate the transferability of the Subtype and Stage Inference (SuStaIn) model from well-characterized research data set, employed as training set, to independent less-structured and heterogeneous test sets representative of the clinical setting. The training set was composed of MRI data of 1043 subjects from the Alzheimer's disease Neuroimaging Initiative (ADNI), and the test set was composed of data from 767 subjects from OASIS, Pharma-Cog, and ViTA clinical datasets. Both sets included subjects covering the entire spectrum of AD, and for both sets volumes of relevant brain regions were derived from T1-3D MRI scans processed with Freesurfer v5.3 cross-sectional stream. In order to assess the predictive value of the model, subpopulations of subjects with stable mild cognitive impairment (MCI) and MCIs that progressed to AD dementia (pMCI) were identified in both sets. SuStaIn identified three disease subtypes, of which the most prevalent corresponded to the typical atrophy pattern of AD. The other SuStaIn subtypes exhibited similarities with the previously defined hippocampal sparing and limbic predominant atrophy patterns of AD. Subject subtyping proved to be consistent in time for all cohorts and the staging provided by the model was correlated with cognitive performance. Classification of subjects on the basis of a combination of SuStaIn subtype and stage, mini mental state examination and amyloid-β1-42 cerebrospinal fluid concentration was proven to predict conversion from MCI to AD dementia on par with other novel statistical algorithms, with ROC curves that were not statistically different for the training and test sets and with area under curve respectively equal to 0.77 and 0.76. This study proves the transferability of a SuStaIn model for AD from research data to less-structured clinical cohorts, and indicates transferability to the clinical setting. date: 2021 date_type: published official_url: http://dx.doi.org/10.3389/fdata.2021.661110 oa_status: green full_text_type: pub pmcid: PMC8173213 language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 1871516 doi: 10.3389/fdata.2021.661110 pii: 661110 lyricists_name: Alexander, Daniel lyricists_name: Oxtoby, Neil lyricists_name: Young, Alexandra lyricists_id: DALEX06 lyricists_id: NOXTO55 lyricists_id: YOUNG96 actors_name: Kalinowski, Damian actors_id: DKALI47 actors_role: owner full_text_status: public publication: Frontiers in Big Data volume: 4 article_number: 661110 event_location: Switzerland citation: Archetti, D; Young, AL; Oxtoby, NP; Ferreira, D; Mårtensson, G; Westman, E; Alexander, DC; ... for Alzheimer’s Disease Neuroimaging Initiative and EuroPOND Con; + view all <#> Archetti, D; Young, AL; Oxtoby, NP; Ferreira, D; Mårtensson, G; Westman, E; Alexander, DC; Frisoni, GB; Redolfi, A; for Alzheimer’s Disease Neuroimaging Initiative and EuroPOND Con; - view fewer <#> (2021) Inter-Cohort Validation of SuStaIn Model for Alzheimer's Disease. Frontiers in Big Data , 4 , Article 661110. 10.3389/fdata.2021.661110 <https://doi.org/10.3389/fdata.2021.661110>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10129988/1/Alexander_Inter-Cohort%20Validation%20of%20SuStaIn%20Model%20for%20Alzheimer%E2%80%99s%20Disease_VoR.pdf