Literature DB >> 16934913

Automatic calculation of hippocampal atrophy rates using a hippocampal template and the boundary shift integral.

J Barnes1, R G Boyes, E B Lewis, J M Schott, C Frost, R I Scahill, N C Fox.   

Abstract

We describe a method of automatically calculating hippocampal atrophy rates on T1-weighted MR images without manual delineation of hippocampi. This method was applied to a group of Alzheimer's disease (AD) (n=36) and control (n=19) subjects and compared with manual methods (manual segmentation of baseline and repeat-image hippocampi) and semi-automated methods (manual segmentation of baseline hippocampi only). In controls, mean (S.D.) atrophy rates for manual, semi-automated, and automated methods were 18.1 (53.5), 15.3 (50.2) and 11.3 (50.4) mm3 loss per year, respectively. In AD patients these rates were 174.6 (106.5) 159.4 (101.2) and 172.1 (123.1) mm3 loss per year, respectively. The automated method was a significant predictor of disease (p=0.001) and gave similar group discrimination compared with both semi-automated and manual methods. The automated hippocampal analysis in this small study took approximately 20 min per hippocampal pair on a 3.4 GHz Intel Xeon server, whereas manual delineation of each hippocampal pair took approximately 90 min of operator-intensive labour. This method may be useful diagnostically or in studies where analysis of many scans may be required.

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Year:  2006        PMID: 16934913     DOI: 10.1016/j.neurobiolaging.2006.07.008

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


  14 in total

Review 1.  The role of medical imaging in defining CNS abnormalities associated with HIV-infection and opportunistic infections.

Authors:  David F Tate; Rola Khedraki; Daniel McCaffrey; Daniel Branson; Jeffrey Dewey
Journal:  Neurotherapeutics       Date:  2011-01       Impact factor: 7.620

2.  Longitudinal MRI atrophy biomarkers: relationship to conversion in the ADNI cohort.

Authors:  Shannon L Risacher; Li Shen; John D West; Sungeun Kim; Brenna C McDonald; Laurel A Beckett; Danielle J Harvey; Clifford R Jack; Michael W Weiner; Andrew J Saykin
Journal:  Neurobiol Aging       Date:  2010-08       Impact factor: 4.673

3.  Family history of Alzheimer disease predicts hippocampal atrophy in healthy middle-aged adults.

Authors:  O C Okonkwo; G Xu; N M Dowling; B B Bendlin; A Larue; B P Hermann; R Koscik; E Jonaitis; H A Rowley; C M Carlsson; S Asthana; M A Sager; S C Johnson
Journal:  Neurology       Date:  2012-05-16       Impact factor: 9.910

Review 4.  A meta-analysis of hippocampal atrophy rates in Alzheimer's disease.

Authors:  Josephine Barnes; Jonathan W Bartlett; Laura A van de Pol; Clement T Loy; Rachael I Scahill; Chris Frost; Paul Thompson; Nick C Fox
Journal:  Neurobiol Aging       Date:  2008-03-17       Impact factor: 4.673

Review 5.  The clinical use of structural MRI in Alzheimer disease.

Authors:  Giovanni B Frisoni; Nick C Fox; Clifford R Jack; Philip Scheltens; Paul M Thompson
Journal:  Nat Rev Neurol       Date:  2010-02       Impact factor: 42.937

Review 6.  Automated methods for hippocampus segmentation: the evolution and a review of the state of the art.

Authors:  Vanderson Dill; Alexandre Rosa Franco; Márcio Sarroglia Pinho
Journal:  Neuroinformatics       Date:  2015-04

7.  Improved Detection of Subtle Mesial Temporal Sclerosis: Validation of a Commercially Available Software for Automated Segmentation of Hippocampal Volume.

Authors:  J M Mettenburg; B F Branstetter; C A Wiley; P Lee; R M Richardson
Journal:  AJNR Am J Neuroradiol       Date:  2019-02-07       Impact factor: 3.825

Review 8.  Defining the human hippocampus in cerebral magnetic resonance images--an overview of current segmentation protocols.

Authors:  C Konrad; T Ukas; C Nebel; V Arolt; A W Toga; K L Narr
Journal:  Neuroimage       Date:  2009-05-15       Impact factor: 6.556

9.  Alzheimer's disease neuroimaging initiative: a one-year follow up study using tensor-based morphometry correlating degenerative rates, biomarkers and cognition.

Authors:  Alex D Leow; Igor Yanovsky; Neelroop Parikshak; Xue Hua; Suh Lee; Arthur W Toga; Clifford R Jack; Matt A Bernstein; Paula J Britson; Jeffrey L Gunter; Chadwick P Ward; Bret Borowski; Leslie M Shaw; John Q Trojanowski; Adam S Fleisher; Danielle Harvey; John Kornak; Norbert Schuff; Gene E Alexander; Michael W Weiner; Paul M Thompson
Journal:  Neuroimage       Date:  2009-04-15       Impact factor: 6.556

10.  High-throughput, fully automated volumetry for prediction of MMSE and CDR decline in mild cognitive impairment.

Authors:  Sanja Kovacevic; Michael S Rafii; James B Brewer
Journal:  Alzheimer Dis Assoc Disord       Date:  2009 Apr-Jun       Impact factor: 2.703

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