Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloHippocampal subfield atrophies in converted and not-converted mild cognitive impairments patients by a Markov random fields algorithm
Anno di pubblicazione2016
FormatoCartaceo
Autore/iVasta R.; Augimeri A.; Cerasa A.; Nigro S.; Gramigna V.; Nonnis M.; Rocca F.; Zito G.; Quattrone A.
Affiliazioni autoriNeuroimaging Unit, Institute of Bioimaging and Molecular Physiology-CNR, Germaneto (CZ), Italy; Institute of Neurology, University "Magna Graecia", Germaneto (CZ), Italy; Università degli Studi "Magna Graecia", Dipartimento di Scienze Mediche e Chirurgiche, Germaneto (CZ), Italy; Laboratory of Electrophysiology for Translational neuroScience (LET'S), ISTC, National Research Council at 'S. Giovanni Calibita' Fatebenefratelli Hospital, Rome, Italy
Autori CNR e affiliazioni
  • MATTEO NONNIS
  • ROBERTA VASTA
  • ANTONIO AUGIMERI
  • SALVATORE NIGRO
  • ALDO QUATTRONE
  • ANTONIO CERASA
  • FEDERICO ROCCA
Lingua/e
  • inglese
AbstractAlthough measurement of total hippocampal volume is considered as an important hallmark of Alzheimer's disease (AD), recent evidence demonstrated that atrophies of hippocampal subregions might be more sensitive in predicting this neurodegenerative disease. The vast majority of neuroimaging papers investigating this topic are focused on the difference between AD and patients with mild cognitive impairment (MCI), not considering the impact of MCI patients who will or not convert in AD. For this reason, the aim of this study was to determine if measurements of hippocampal subfields provide advantages over total hippocampal volume for discriminating these groups. Hippocampal subfields volumetry was extracted in 55 AD, 32 converted and 89 not-converted MCI (c/nc-MCI) and 47 healthy controls, using an atlas-based automatic algorithm based on Markov random fields embedded in the Freesurfer framework. To evaluate the impact of hippocampal atrophy in discriminating the insurgence of AD-like phenotypes we used three classification methods: Support Vector Machine, Naïve Bayesian Classifier and Neural Networks Classifier. Taking into account only the total hippocampal volume, all classification models, reached a sensitivity of about 66% in discriminating between c-MCI and nc-MCI. Otherwise, classification analysis considering all segmenting subfields increased accuracy to diagnose c-MCI from 68% to 72%. This effect resulted to be strongly dependent upon atrophies of the subiculum and presubiculum. Our multivariate analysis revealed that the magnitude of the difference considering hippocampal subfield volumetry, as segmented by the considered atlas-based automatic algorithm, offers an advantage over hippocampal volume in distinguishing early AD from nc-MCI.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da566
Pagine a574
Pagine totali-
RivistaCurrent Alzheimer research (Print)
Attiva dal 2004
Editore: Bentham Science Publishers - Hilversum
Paese di pubblicazione: Paesi Bassi
Lingua: inglese
ISSN: 1567-2050
Titolo chiave: Current Alzheimer research (Print)
Titolo proprio: Current Alzheimer research. (Print)
Numero volume della rivista13
Fascicolo della rivista5
DOI10.2174/1567205013666160120151457
Verificato da referee-
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • Scopus (Codice:2-s2.0-84964009920)
  • ISI Web of Science (WOS) (Codice:000373458700010)
  • PubMed (Codice:26787291)
Parole chiaveAtrophy, Automated segmentation, Classification models, Freesurfer, Hippocampal subfields, Mild cognitive impairment, Volumetry
Link (URL, URI)http://www.scopus.com/inward/record.url?eid=2-s2.0-84964009920&partnerID=q2rCbXpz
Titolo parallelo-
Licenza-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • IBFM — IBFM - Sede secondaria di Germaneto
Moduli/Attività/Sottoprogetti CNR
  • ME.P02.028.001 : Neuroimaging clinico dei disordini neurodegenerativi del movimento
Progetti Europei-
Allegati