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Minimal Interval Resonance Imaging in Alzheimer's Disease (MIRIAD)

Publicily Available Scan Database

The MIRIAD dataset is a database of volumetric MRI brain-scans of Alzheimer's sufferers and healthy elderly people. Many scans were collected of each participant at intervals from 2 weeks to 2 years, the study was designed to investigate the feasibility of using MRI as an outcome measure  for clinical trials of Alzheimer's treatments. Including:

  1. To find the minimal interval over which trials would need to be conducted.
  2. To assess whether combining more than two scanning time points would increase statistical power and, if so, the optimal combination and timing of scans for trials of varying lengths.
  3. To provide a means of assessing the reproducibility of techniques within a single day and over short intervals where changes in individual's hydration and scanner fluctuations, but not pathological atrophy, might be expected.

These scans, together with demographic and psychological data, are now publicly available in anonymised form to aid researchers in developing new techniques for the analysis of serially acquired MRI.

Demographics and Scanning Timepoints
 Demographics
  Alzheimer's Disease
(N=46)
Controls
(N=23)
 Age at study entry (years)
 69.4±7.1 69.7±7.2
 Men  41%  52%
 Mean (SD) baseline MMSE
19.2±4
 29.4±0.8

All subjects were requested to attend seven imaging visits at 0, 2, 6, 14, 26, 38 and 52 weeks from baseline. 39 subjects who completed all these visits during the study attended a further scan at 18 months, 22 of these had a further scan at 24 months. At 0, 6 and 38 weeks two back-to-back scans were conducted.

Timing of visits
Mean interval days from baseline
0
16
43
98
180
270
365
552
730
(SD)
  (5)
(6)
(8)
(7)
(19)
(14) (18)
(10)
Subjects scanned 68
66
67
68
66
60
67
39
22
(patients) (45)
(44)
(45)
(46)
(44) (38)
(44)
(26)
(14)
Scans completed 133
66
130
68
66
117
67
39
22

All scans were conducted on the same 1.5 T Signa MRI scanner (GE Medical systems, Milwaukee, WI) and acquired by the same radiographer. Three-dimensional T1-weighted images were acquired with an IR-FSPGR (inversion recovery prepared fast spoiled gradient recalled) sequence, field of view 24 cm, 256 × 256 matrix, 124 1.5 mm coronal partitions, TR 15 ms, TE 5.4 ms, flip angle 15°, TI 650 ms.

Data use agreement

All data is available through the MIRIAD XNAT database.

By registering and downloading data from this site, users agree to the following:

  1. Users shall respect restrictions of access to sensitive data. Users will not attempt to identify the individuals whose images are included in the data set.
  2. Redistribution of these data to third parties is not permitted without prior agreement.
  3. Whilst every effort will be made to ensure the quality and completeness of the data, this cannot be guaranteed. Users employ these data at their own risk.
  4. Users must acknowledge the use of these data and data derived from this dataset when publicly presenting any findings or algorithms that benefited from their use. Such presentations include but are not limited to papers, books, book chapters, conference posters, and talks.
  5.  When publishing findings that benefit from these data, users agree to:
Downloading the Data

Scans

Images can be downloaded from the XNAT database by selecting the MIRIAD project followed by the Download Images action on the right.

For convenience a TAR file containing all the images can be downloaded here. (You must first log in to the XNAT database to access this.)

Psychology and demographic data

After logging in, on the MIRIAD XNAT page add the ClinicalAsessment and MR Sessions tabs if they aren't present by using the SELECT drop-down menu. The full dataset can be saved by selecting Spreadsheet in the Options drop-down menu at the right-hand side of the listing. Your browser should offer to save or open the resulting CSV file.

ClinicalAssessment gives MMSE for each visit and CDR score and sum of boxes at screening for Alzheimer's participants.

MR Sessions lists age at each scan (to two decimal places), group (AD/controls) and gender.

Blinding codes

The blinding codes from the MICCAI 2012 atrophy measurement challenge are available as a csv file.

Publications

An overview of the MIRIAD demographics and publications is published in Malone et al. 2013 NeuroImage Volume 70 Pages 33–36 doi:10.1016/j.neuroimage.2012.12.044

The following list of publications which have made use of the data may be of use to researchers with particular interests:

 Atrophy in dementia
Boyes et al. (2006), NeuroImage
Cerebral atrophy measurements using Jacobian integration
Gutiérrez-Galve et al. (2009) Dement Geriatr Cogn Patterns of Cortical Thickness according to APOE Genotype in Alzheimer's Disease
Ridgway et al. (2009) NeuroImage
Issues with threshold masking in voxel-based morphometry of atrophied brains
Cardoso et al. (2009) MICCAI 2009 Improved Maximum a Posteriori Cortical Segmentation by Iterative Relaxation of Priors
Anderson et al. (2012) Neurobiol Aging Gray matter atrophy rate as a marker of disease progression in AD
 Medial–temporal lobe atrophy
Barnes et al. (2005) Dement Geriatr Cogn Does Alzheimer's Disease Affect Hippocampal Asymmetry? Evidence from a Cross-Sectional and Longitudinal Volumetric MRI Study
Barnes et al. (2007) Neurobiol Aging Automatic calculation of hippocampal atrophy rates using a hippocampal template and the boundary shift integral
Barnes et al. (2007) J Comput Assist Tomo Automated measurement of hippocampal atrophy using fluid-registered serial MRI in AD and controls
Ridha et al. (2007) Arch Neurol-Chicago Application of automated medial temporal lobe atrophy scale to Alzheimer disease
Barnes et al. (2008) NeuroImage A comparison of methods for the automated calculation of volumes and atrophy rates in the hippocampus
Barnes et al. (2008) Neurobiol Aging
Increased hippocampal atrophy rates in AD over 6 months using serial MR imaging
Barnes et al. (2010) NeuroImage Head size, age and gender adjustment in MRI studies: A necessary nuisance?
Leung et al. (2010) NeuroImage Automated cross-sectional and longitudinal hippocampal volume measurement in mild cognitive impairment and Alzheimer's disease
Simulation studies
Schweiger et al. (2005) MICCAI 2005 An Inverse Problem Approach to the Estimation of Volume Change
Camara-Rey et al. (2006) MICCAI 2006 Simulation of Local and Global Atrophy in Alzheimer's Disease Studies
Camara et al. (2006) IEEE T Med Imaging Phenomenological Model of Diffuse Global and Regional Atrophy Using Finite-Element Methods
Camara-Rey et al. (2006) MICCAI 2006 Simulation of Acquisition Artefacts in MR Scans: Effects on Automatic Measures of Brain Atrophy
Camara et al. (2007) MICCAI 2007
Accuracy Assessment of Global and Local Atrophy Measurement Techniques with Realistic Simulated Longitudinal Data
Camara et al. (2008) NeuroImage Accuracy assessment of global and local atrophy measurement techniques with realistic simulated longitudinal Alzheimer's disease images
 Clinical trials design
Whitwell et al. (2004) Magn Reson Imaging Using nine degrees-of-freedom registration to correct for changes in voxel size in serial MRI studies
Schott et al. (2005) Neurology Measuring atrophy in Alzheimer disease A serial MRI study over 6 and 12 months
Schott et al. (2006) J Neurol Combining short interval MRI in Alzheimer's disease
Frost et al. (2008) Stat Med Optimizing the design of clinical trials where the outcome is a rate. Can estimating a baseline rate in a run-in period increase efficiency?
Schott et al. (2008) Neuropsychologia Neuropsychological correlates of whole brain atrophy in Alzheimer's disease
 Methods comparison
Smith et al. (2007) NeuroImage Longitudinal and cross-sectional analysis of atrophy in Alzheimer's disease: Cross-validation of BSI, SIENA and SIENAX
Clarkson et al. (2011) NeuroImage A comparison of voxel and surface based cortical thickness estimation methods
Acknowledgements

This dataset is made available through the support of the UK Alzheimer's Society. The original data collection was funded through an unrestricted educational grant from GlaxoSmithKline and funding from the UK Alzheimer's Society (to Dr Schott) and the Medical Research Council (to Professor Fox). Professor Ourselin receives funding from the EPSRC (EP/H046410/1) and the Comprehensive Biomedical Research Centre (CBRC) Strategic Investment Award (Ref. 168). Dr Ridgway is supported by the Medical Research Council [grant number MR/J014257/1]. This work was supported by the National Institute for Health Research (NIHR) Biomedical Research Unit in Dementia based at University College London Hospitals (UCLH), University College London (UCL). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. The Dementia Research Centre is an Alzheimer's Research UK (ARUK) Coordinating Centre. The Wellcome Trust Centre for Neuroimaging is supported by core funding from the Wellcome Trust [grant number 091593/Z/10/Z]. We are grateful to the MIRIAD participants and funders for their willingness to share these data.