Literature DB >> 18353687

A comparison of methods for the automated calculation of volumes and atrophy rates in the hippocampus.

J Barnes1, J Foster, R G Boyes, T Pepple, E K Moore, J M Schott, C Frost, R I Scahill, N C Fox.   

Abstract

Hippocampal atrophy rates have been used in a number of studies in Alzheimer's disease (AD) to assess disease progression and are being increasingly utilized as an outcome measure in clinical trials of new pharmaceutical agents. Owing to the labor-intensive nature of hippocampal segmentation, more automated approaches are required for such analysis. In this study we compared methods of automatically segmenting the hippocampus (single-person template and template library) on the baseline image in a group of probable AD (n=36) and control (n=19) subjects with serial images. Using the method that gave most similar results to manual, three automated methods of calculating change within the hippocampal region were compared: fluid change calculated using (1) Jacobian change or (2) region propagation and (3) boundary shift. Rates were compared with manual measures. We found that segmentation of baseline hippocampus was most accurate using a template library combined with morphological operations (intensity thresholding plus one conditional dilation). This gave a voxel similarity of 0.69 (0.05) and 0.72 (0.06) in controls and probable AD subjects respectively compared with manual measures. Atrophy rates within these regions were most similar to the manual rates using the boundary shift integral (mean difference from manual rate 0.03% (1.29) in controls and 0.48% (2.44) in AD). A template library segmentation approach, together with morphological operations, provides a segmentation accurate enough to quantify relative change over time. The change over time can then be calculated automatically using boundary shift or fluid measures, with boundary shift giving most similar results to manual.

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Year:  2008        PMID: 18353687     DOI: 10.1016/j.neuroimage.2008.01.012

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  41 in total

1.  Survey of protocols for the manual segmentation of the hippocampus: preparatory steps towards a joint EADC-ADNI harmonized protocol.

Authors:  Marina Boccardi; Rossana Ganzola; Martina Bocchetta; Michela Pievani; Alberto Redolfi; George Bartzokis; Richard Camicioli; John G Csernansky; Mony J de Leon; Leyla deToledo-Morrell; Ronald J Killiany; Stéphane Lehéricy; Johannes Pantel; Jens C Pruessner; H Soininen; Craig Watson; Simon Duchesne; Clifford R Jack; Giovanni B Frisoni
Journal:  J Alzheimers Dis       Date:  2011       Impact factor: 4.472

2.  Performing label-fusion-based segmentation using multiple automatically generated templates.

Authors:  M Mallar Chakravarty; Patrick Steadman; Matthijs C van Eede; Rebecca D Calcott; Victoria Gu; Philip Shaw; Armin Raznahan; D Louis Collins; Jason P Lerch
Journal:  Hum Brain Mapp       Date:  2012-05-19       Impact factor: 5.038

3.  Hippocampal shape is predictive for the development of dementia in a normal, elderly population.

Authors:  Hakim C Achterberg; Fedde van der Lijn; Tom den Heijer; Meike W Vernooij; M Arfan Ikram; Wiro J Niessen; Marleen de Bruijne
Journal:  Hum Brain Mapp       Date:  2013-09-03       Impact factor: 5.038

Review 4.  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

5.  Reduced sample sizes for atrophy outcomes in Alzheimer's disease trials: baseline adjustment.

Authors:  J M Schott; J W Bartlett; J Barnes; K K Leung; S Ourselin; N C Fox
Journal:  Neurobiol Aging       Date:  2010-08       Impact factor: 4.673

6.  A direct morphometric comparison of five labeling protocols for multi-atlas driven automatic segmentation of the hippocampus in Alzheimer's disease.

Authors:  Sean M Nestor; Erin Gibson; Fu-Qiang Gao; Alex Kiss; Sandra E Black
Journal:  Neuroimage       Date:  2012-11-07       Impact factor: 6.556

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

8.  Rapid automatic segmentation of the human cerebellum and its lobules (RASCAL)--implementation and application of the patch-based label-fusion technique with a template library to segment the human cerebellum.

Authors:  Katrin Weier; Vladimir Fonov; Karyne Lavoie; Julien Doyon; D Louis Collins
Journal:  Hum Brain Mapp       Date:  2014-04-28       Impact factor: 5.038

9.  Biomarkers for the clinical evaluation of the cognitively impaired elderly: amyloid is not enough.

Authors:  Linda K McEvoy; James B Brewer
Journal:  Imaging Med       Date:  2012-06

10.  Automatic segmentation of the hippocampus and the amygdala driven by hybrid constraints: method and validation.

Authors:  M Chupin; A Hammers; R S N Liu; O Colliot; J Burdett; E Bardinet; J S Duncan; L Garnero; L Lemieux
Journal:  Neuroimage       Date:  2009-02-21       Impact factor: 6.556

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