Imaging shows Alzheimer’s decline

Researchers at the Florey have invented a breakthrough imaging technique to describe in micro-detail the brain degeneration occurring in people with early Alzheimer’s and the full-blown disease.

Using the Siemens 3T Trio scanner at the Florey node of the National Imaging Facility (NIF), researchers have identified the precise locations of brain degeneration in a cohort of living Alzheimer’s patients. The work is important as it sheds new light on the underlying cognitive degeneration in Alzheimer’s, helping us focus our efforts to slow the decline.

To develop the technique, the team analysed brain scans from 177 Australians as part of the Australian Imaging, Biomarkers and Lifestyle study, who were either healthy, had an early form of Alzheimer’s or had the full-blown disease.

The brain pathways identified by the team have all been implicated in Alzheimer’s disease previously; those known to be crucial for memory formation, emotion and reasoning.

Alzheimer’s disease is usually thought to be caused by abnormal production and buildup of a peptide called amyloid beta.

Professor Alan Connelly, who led the study, said, “Interestingly, the mildly affected patients with low amyloid had more fibre degeneration in particular brain regions than those with high amyloid levels. This suggests that firstly, specific degeneration of certain brain areas will not necessarily be useful in predicting which mildly impaired individuals will progress to Alzheimer’s disease, and secondly that degeneration of this pathway is related to cognitive impairment, regardless of the buildup of the amyloid peptide.

“This is an important advance for a field still struggling to come to grips with what exactly causes Alzheimer’s. Our study shows we still have a way to go in interrogating the natural history of this insidious disease,” Alan says.

Lead author Remika Mito says, “This study was conducted by comparing the averages of each group of patients against each other, in order to give us the most statistically, and biologically, relevant results. In the future, we want to be able to compare an individual patient against a normal, healthy standard, to see how far along the disease trajectory they are. Or we could compare back to their previous scans to determine what effect a new medication is having as part of a clinical trial for example.”

Remika recently explained her results in an online abstract for Brain. If you would like to more about the details of the study, head over to Youtube to view Remika explain her work.

 

This story was contributed by the Florey Institute of Neuroscience and Mental Health. 

National Network of Trusted Data Repositories

During 2017 the National Imaging Facility (NIF) nodes at the University of Western Australia (UWA), University of Queensland (UQ), University of New South Wales (UNSW) and Monash University collaborated on a national project to enhance the quality, durability and reliability of data generated by NIF through the Trusted Data Repository project.

●        Quality pertains to a NIF user’s expectation that an animal, plant or material can be scanned and from that data reliable outcomes/characterisations can be obtained (e.g. signal, volume, morphology) over time and across NIF sites.

●        Durability refers to guaranteed long-term availability of the data.

●        Reliability means that the data is useful for future researchers, i.e. stored in one or more open data formats and with sufficient evidential metadata.

The Project, Delivering durable, reliable, high-quality image data, was jointly funded by the Australian National Data Service (ANDS) and Research Data Services (RDS). It was motivated both by NIF’s desire to enhance the quality of the data associated with the use of its facilities, and the desire of ANDS/RDS to facilitate the establishment of Trusted Data Repositories that enable access to data for at least 10 years and includes metadata that documents both the quality of the data and its provenance.

A trusted data repository service is essential for sharing data and ensures that project data created and used by researchers is “managed, curated, and archived in such a way to preserve the initial investment in collecting them” and that the data “remain useful and meaningful into the future” (https://www.coretrustseal.org).

The scope of the Project was limited to MRI data with the understanding that the developed requirements and trusted data repository services could be adapted to, or serve as a basis for other instruments/modalities.

The key outcomes from the Project include:

  1. The NIF agreed process for acquiring trusted data (NAP) – Lists the requirements that must be satisfied to obtain high-quality data, i.e. NIF-certified data, suitable for ingestion in a NIF trusted data repository service. They cover provisioning of a unique instrument identifier, instrument registration with Research Data Australia (https://researchdata.ands.org.au), quality control (QC), quality assurance measures, requisite metadata (including cross-reference to the QC data),  the process by which data is moved from the instrument to the digital repository service and the format(s) of the data.
  2. The NIF requirements for a trusted data repository service – Provides a platform-agnostic checklist of requirements that a basic NIF trusted data repository service should satisfy, including: identification of data by a unique Project identifier, ingestion of data from NIF-compliant instruments, authentication via the Australian Access Federation (https://aaf.edu.au), interoperability and easy deployment across NIF nodes.
  3. Implementations of trusted data repository services for two exemplars:
    1. Preclinical MRI data (with mouse brain data as an example) acquired across three NIF nodes—UNSW, UQ and UWA—using a Bruker BioSpec 9.4T MRI. The services have been implemented using the open source MyTardis/ImageTrove (https://www.mytardis.org) platform.
    2. Clinical ataxia MRI data acquired using a Siemens Skyra 3T MRI scanner in support of a Monash-proposed International Ataxia Imaging Repository (IAIR). The service has been Implemented using the open source XNAT (https://www.xnat.org) platform.

Software developed to support the implementation of the repository services includes: Docker (https://www.docker.com) Compose scripts to permit easy deployment at differents sites, client-side scripts for uploading NIF-certified data to ImageTrove/MyTardis and an XNAT plugin for uploading non-DICOM files.

  1. Assessments of the resulting trusted data repository services against a relevant international metric, the CoreTrustSeal (https://www.coretrustseal.org) Core Trustworthy Data Repositories Requirements.

For NIF users and the broader imaging research community the benefits and impact of this Project include:

  • Reliable and durable access to data
  • Improved reliability of research outputs and the provenance associated with it
  • Making NIF data more FAIR (Findable, Accessible, Interoperable, Reusable – https://www.ands.org.au/working-with-data/the-fair-data-principles)
  • Easier linkages between publications and data
  • Stronger research partnerships

For research institutions they include:

  • Enhanced reputation management
  • A means by which to comply with the Australian Code for the Responsible Conduct of Research
  • Enhanced ability to engage in multi-centre imaging research projects

For NIF they include

  • Improved data quality
  • Improved international reputation
  • The ability to run multi-centre trials

The transition plan post-funding includes: maintenance of existing services for 10 years; the integration of additional instruments; creation of a project web portal; planned new national and international service deployments; refinements and improvements; and CoreTrustSeal certification.

Project documents have been archived in the NIF Customer Relationship Management (CRM) system (accessible by NIF staff). Project software is hosted on GitHub and is freely available for download here: https://github.com/NIF-au/TDR. For further information please contact either the national Project Manager or NIF.

Project Manager and UWA lead: Andrew Mehnert (NIF Informatics Fellow, Centre for Microscopy, Characterisation and Analysis).
NIF lead – Graham Galloway (Chief Executive Officer, NIF)
UQ lead – Andrew Janke (NIF Informatics Fellow, Centre for Advanced Imaging)
UNSW lead – Marco Gruwel (Senior Research Associate, Mark Wainwright Analytical Centre)
Monash lead – Wojtek Goscinski (Associate Director, Monash eResearch Centre)
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