Publication: Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge
| dc.contributor.author | Cash, David M. | |
| dc.contributor.author | Frost, Chris D. | |
| dc.contributor.author | Iheme, Leonardo O. | |
| dc.contributor.author | Ünay, Devrim | |
| dc.contributor.author | Kandemir, Melek | |
| dc.contributor.author | Fripp, Jürgen | |
| dc.contributor.author | Salvado, Olivier | |
| dc.contributor.author | Bourgeat, Pierrick T. | |
| dc.contributor.author | Reuter, Martin | |
| dc.contributor.author | Fischl, Bruce R. | |
| dc.contributor.institution | Cash, David M., Dementia Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdom, Translational Imaging Group, University College London, London, United Kingdom | |
| dc.contributor.institution | Frost, Chris D., Dementia Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdom, Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, United Kingdom | |
| dc.contributor.institution | Iheme, Leonardo O., Department of Electrical and Electronic Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey | |
| dc.contributor.institution | Ünay, Devrim, Biomedical Engineering, Bahçeşehir Üniversitesi, Istanbul, Turkey | |
| dc.contributor.institution | Kandemir, Melek, Department of Neurology, Bayindir Hospital, Ankara, Turkey | |
| dc.contributor.institution | Fripp, Jürgen, Commonwealth Scientific and Industrial Research Organisation, Canberra, Australia | |
| dc.contributor.institution | Salvado, Olivier, Commonwealth Scientific and Industrial Research Organisation, Canberra, Australia | |
| dc.contributor.institution | Bourgeat, Pierrick T., Commonwealth Scientific and Industrial Research Organisation, Canberra, Australia | |
| dc.contributor.institution | Reuter, Martin, Department of Radiology, Massachusetts General Hospital, Boston, United States, MIT Computer Science & Artificial Intelligence Laboratory, Cambridge, United States | |
| dc.contributor.institution | Fischl, Bruce R., Department of Radiology, Massachusetts General Hospital, Boston, United States, MIT Computer Science & Artificial Intelligence Laboratory, Cambridge, United States | |
| dc.date.accessioned | 2025-10-05T16:29:52Z | |
| dc.date.issued | 2015 | |
| dc.description.abstract | Structural MRI is widely used for investigating brain atrophy in many neurodegenerative disorders, with several research groups developing and publishing techniques to provide quantitative assessments of this longitudinal change. Often techniques are compared through computation of required sample size estimates for future clinical trials. However interpretation of such comparisons is rendered complex because, despite using the same publicly available cohorts, the various techniques have been assessed with different data exclusions and different statistical analysis models. We created the MIRIAD atrophy challenge in order to test various capabilities of atrophy measurement techniques. The data consisted of 69 subjects (46 Alzheimer's disease, 23 control) who were scanned multiple (up to twelve) times at nine visits over a follow-up period of one to two years, resulting in 708 total image sets. Nine participating groups from 6 countries completed the challenge by providing volumetric measurements of key structures (whole brain, lateral ventricle, left and right hippocampi) for each dataset and atrophy measurements of these structures for each time point pair (both forward and backward) of a given subject. From these results, we formally compared techniques using exactly the same dataset. First, we assessed the repeatability of each technique using rates obtained from short intervals where no measurable atrophy is expected. For those measures that provided direct measures of atrophy between pairs of images, we also assessed symmetry and transitivity. Then, we performed a statistical analysis in a consistent manner using linear mixed effect models. The models, one for repeated measures of volume made at multiple time-points and a second for repeated direct measures of change in brain volume, appropriately allowed for the correlation between measures made on the same subject and were shown to fit the data well. From these models, we obtained estimates of the distribution of atrophy rates in the Alzheimer's disease (AD) and control groups and of required sample sizes to detect a 25% treatment effect, in relation to healthy ageing, with 95% significance and 80% power over follow-up periods of 6, 12, and 24. months. Uncertainty in these estimates, and head-to-head comparisons between techniques, were carried out using the bootstrap. The lateral ventricles provided the most stable measurements, followed by the brain. The hippocampi had much more variability across participants, likely because of differences in segmentation protocol and less distinct boundaries. Most methods showed no indication of bias based on the short-term interval results, and direct measures provided good consistency in terms of symmetry and transitivity. The resulting annualized rates of change derived from the model ranged from, for whole brain: - 1.4% to - 2.2% (AD) and - 0.35% to - 0.67% (control), for ventricles: 4.6% to 10.2% (AD) and 1.2% to 3.4% (control), and for hippocampi: - 1.5% to - 7.0% (AD) and - 0.4% to - 1.4% (control). There were large and statistically significant differences in the sample size requirements between many of the techniques. The lowest sample sizes for each of these structures, for a trial with a 12. month follow-up period, were 242 (95% CI: 154 to 422) for whole brain, 168 (95% CI: 112 to 282) for ventricles, 190 (95% CI: 146 to 268) for left hippocampi, and 158 (95% CI: 116 to 228) for right hippocampi. This analysis represents one of the most extensive statistical comparisons of a large number of different atrophy measurement techniques from around the globe. The challenge data will remain online and publicly available so that other groups can assess their methods. © 2015 Elsevier B.V., All rights reserved. | |
| dc.identifier.doi | 10.1016/j.neuroimage.2015.07.087 | |
| dc.identifier.endpage | 164 | |
| dc.identifier.issn | 10959572 | |
| dc.identifier.issn | 10538119 | |
| dc.identifier.pubmed | 26275383 | |
| dc.identifier.scopus | 2-s2.0-84942250272 | |
| dc.identifier.startpage | 149 | |
| dc.identifier.uri | https://doi.org/10.1016/j.neuroimage.2015.07.087 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14719/12656 | |
| dc.identifier.volume | 123 | |
| dc.language.iso | en | |
| dc.publisher | Academic Press Inc. apjcs@harcourt.com | |
| dc.relation.oastatus | All Open Access | |
| dc.relation.oastatus | Green Accepted Open Access | |
| dc.relation.oastatus | Green Final Open Access | |
| dc.relation.oastatus | Green Open Access | |
| dc.relation.oastatus | Hybrid Gold Open Access | |
| dc.relation.source | NeuroImage | |
| dc.subject.authorkeywords | Ge Signa | |
| dc.subject.authorkeywords | Alzheimer Disease | |
| dc.subject.authorkeywords | Article | |
| dc.subject.authorkeywords | Brain Atrophy | |
| dc.subject.authorkeywords | Brain Size | |
| dc.subject.authorkeywords | Comparative Study | |
| dc.subject.authorkeywords | Controlled Study | |
| dc.subject.authorkeywords | Follow Up | |
| dc.subject.authorkeywords | Hippocampus | |
| dc.subject.authorkeywords | Human | |
| dc.subject.authorkeywords | Lateral Brain Ventricle | |
| dc.subject.authorkeywords | Major Clinical Study | |
| dc.subject.authorkeywords | Measurement Repeatability | |
| dc.subject.authorkeywords | Neuroimaging | |
| dc.subject.authorkeywords | Nuclear Magnetic Resonance Imaging | |
| dc.subject.authorkeywords | Nuclear Magnetic Resonance Scanner | |
| dc.subject.authorkeywords | Priority Journal | |
| dc.subject.authorkeywords | Radiological Parameters | |
| dc.subject.authorkeywords | Radiological Procedures | |
| dc.subject.authorkeywords | Randomized Controlled Trial (topic) | |
| dc.subject.authorkeywords | Aged | |
| dc.subject.authorkeywords | Atrophy | |
| dc.subject.authorkeywords | Brain | |
| dc.subject.authorkeywords | Computer Assisted Diagnosis | |
| dc.subject.authorkeywords | Female | |
| dc.subject.authorkeywords | Male | |
| dc.subject.authorkeywords | Middle Aged | |
| dc.subject.authorkeywords | Pathology | |
| dc.subject.authorkeywords | Procedures | |
| dc.subject.authorkeywords | Reproducibility | |
| dc.subject.authorkeywords | Statistical Analysis | |
| dc.subject.authorkeywords | Aged | |
| dc.subject.authorkeywords | Alzheimer Disease | |
| dc.subject.authorkeywords | Atrophy | |
| dc.subject.authorkeywords | Brain | |
| dc.subject.authorkeywords | Data Interpretation, Statistical | |
| dc.subject.authorkeywords | Female | |
| dc.subject.authorkeywords | Hippocampus | |
| dc.subject.authorkeywords | Humans | |
| dc.subject.authorkeywords | Image Interpretation, Computer-assisted | |
| dc.subject.authorkeywords | Magnetic Resonance Imaging | |
| dc.subject.authorkeywords | Male | |
| dc.subject.authorkeywords | Middle Aged | |
| dc.subject.authorkeywords | Reproducibility Of Results | |
| dc.subject.indexkeywords | Alzheimer disease | |
| dc.subject.indexkeywords | Article | |
| dc.subject.indexkeywords | brain atrophy | |
| dc.subject.indexkeywords | brain size | |
| dc.subject.indexkeywords | comparative study | |
| dc.subject.indexkeywords | controlled study | |
| dc.subject.indexkeywords | follow up | |
| dc.subject.indexkeywords | hippocampus | |
| dc.subject.indexkeywords | human | |
| dc.subject.indexkeywords | lateral brain ventricle | |
| dc.subject.indexkeywords | major clinical study | |
| dc.subject.indexkeywords | measurement repeatability | |
| dc.subject.indexkeywords | neuroimaging | |
| dc.subject.indexkeywords | nuclear magnetic resonance imaging | |
| dc.subject.indexkeywords | nuclear magnetic resonance scanner | |
| dc.subject.indexkeywords | priority journal | |
| dc.subject.indexkeywords | radiological parameters | |
| dc.subject.indexkeywords | radiological procedures | |
| dc.subject.indexkeywords | randomized controlled trial (topic) | |
| dc.subject.indexkeywords | aged | |
| dc.subject.indexkeywords | atrophy | |
| dc.subject.indexkeywords | brain | |
| dc.subject.indexkeywords | computer assisted diagnosis | |
| dc.subject.indexkeywords | female | |
| dc.subject.indexkeywords | male | |
| dc.subject.indexkeywords | middle aged | |
| dc.subject.indexkeywords | pathology | |
| dc.subject.indexkeywords | procedures | |
| dc.subject.indexkeywords | reproducibility | |
| dc.subject.indexkeywords | statistical analysis | |
| dc.subject.indexkeywords | Aged | |
| dc.subject.indexkeywords | Alzheimer Disease | |
| dc.subject.indexkeywords | Atrophy | |
| dc.subject.indexkeywords | Brain | |
| dc.subject.indexkeywords | Data Interpretation, Statistical | |
| dc.subject.indexkeywords | Female | |
| dc.subject.indexkeywords | Hippocampus | |
| dc.subject.indexkeywords | Humans | |
| dc.subject.indexkeywords | Image Interpretation, Computer-Assisted | |
| dc.subject.indexkeywords | Magnetic Resonance Imaging | |
| dc.subject.indexkeywords | Male | |
| dc.subject.indexkeywords | Middle Aged | |
| dc.subject.indexkeywords | Reproducibility of Results | |
| dc.title | Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge | |
| dc.type | Article | |
| dcterms.references | Ashburner, John T., Unified segmentation, NeuroImage, 26, 3, pp. 839-851, (2005), Avants, Brian B., Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain, Medical Image Analysis, 12, 1, pp. 26-41, (2008), Barnes, Josephine, Increased hippocampal atrophy rates in AD over 6 months using serial MR imaging, Neurobiology of Aging, 29, 8, pp. 1199-1203, (2008), Benzinger, Tammie L.S., Regional variability of imaging biomarkers in autosomal dominant Alzheimer's disease, Proceedings of the National Academy of Sciences of the United States of America, 110, 47, pp. E4502-E4509, (2013), Bernal-Rusiel, Jorge L., Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models, NeuroImage, 66, pp. 249-260, (2013), Black, Ronald S., Scales as outcome measures for Alzheimer's disease, Alzheimer's and Dementia, 5, 4, pp. 324-339, (2009), Boccardi, Marina, Survey of protocols for the manual segmentation of the hippocampus: Preparatory steps towards a joint EADC-ADNI harmonized protocol, Journal of Alzheimer's Disease, 26, SUPPL. 3, pp. 61-75, (2011), Camara Rey, Oscar, Accuracy assessment of global and local atrophy measurement techniques with realistic simulated longitudinal Alzheimer's disease images, NeuroImage, 42, 2, pp. 696-709, (2008), Cardoso, Jorge Jorge, STEPS: Similarity and Truth Estimation for Propagated Segmentations and its application to hippocampal segmentation and brain parcelation, Medical Image Analysis, 17, 6, pp. 671-684, (2013), Collins, Donald Louis, Animal: Validation and application of nonlinear registration-based segmentation, International Journal of Pattern Recognition and Artificial Intelligence, 11, 8, pp. 1271-1294, (1997) | |
| dspace.entity.type | Publication | |
| local.indexed.at | Scopus | |
| person.identifier.scopus-author-id | 57568259500 | |
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