The First Australian Multi-Centre Study of Dementia using Ultra-High Field MRI

Australia is at the forefront of dementia research with world leading studies such as the Australian Imaging and Lifestyle study of Ageing (AIBL) led by a consortium of Australia’s leading Dementia centres, and the recently started Prospective Study of Ageing (PISA) led by the QIMR Berghofer.

The installation of the first human ultra-high field MRI scanner in the southern hemisphere at the Centre for Advance Imaging, the Qld node of the National Imaging Facility, in 2014 opened up a new era of imaging research. The Siemens 7T whole-body MRI scanner brought Australia to the forefront of ultra-high field research enabling examination of the human brain with an unprecedented level of detail.

Subsequently, a second 7T scanner was installed at the Melbourne Brain Centre providing a unique opportunity for a national multi-centre collaboration in ultra-high field MRI and the capability to explore new imaging biomarkers for diagnosis of neurodegenerative disease. A major project is underway, led by the Brisbane-based CSIRO eHealth Research Centre, co-funded by the CRC for Mental Health and in collaboration with the QIMR Berghofer, University of Melbourne and Florey Institute for Neuroscience with the broad aim of characterising new bioimaging biomarkers of neurodegeneration in the aging population. A suite of MRI methods is being applied at both sites on large cohorts of healthy aging subjects and patients diagnosed with fronto-temporal dementia. The scanning part of the project has been successfully completed with superb image quality obtained using state of the art sequences. A significant effort is now underway to analyse this valuable data which may contain a wealth of diagnostic information not otherwise available.


This story was contributed by The University of Queensland

Feature image: (Left) 3D MP2RAGE 0.9mm isotropic showing exceptional tissue contrast, (centre) example of a Quantitative Susceptibility Mapping (QSM), a mechanism for useful chemical identification and quantification of specific biomarkers, and (right) T2W TSE using coronal accquisition for hippocampus subfield examination. 

Wildlife Matters


A restrained alligator inside a CT scanner with veterinarians and researchers looking on

Dr Tim Kuchel and zoo veterinarian Dr David McLelland talking about George’s exam

The Large Animal Research and Imaging Facility had an unusual visitor. George the Alligator from the Adelaide Zoo came by for a temporal mandibular joint and dental check-up, courtesy of our 16 slice Phillips CT scanner.

A CT scan showing 3D structure of an alligator head

A CT scan of George, revealing bone structure

It had been recognised over the past two years that George did not open his mouth wide or quickly, and instead took food gently and played with it before swallowing it slowly in a most unlikely Alligator way. The differential diagnosis most likely was temporomandibular joint (TMJ) pathology which may have been able to be diagnosed/described by a CT scan. George was physically restrained, and his mouth secured (the muscles to open the mouth are quite weak, fortunately) and his 180kg body carried by 6 staff and placed into the NIF funded 16 slice CT scanner. Then the Alligator was scanned prone in a 16-slice Philips CT scanner using a 3D protocol (KV/mA: 120/350; field of view: 350 mm; matrix: 256×256; thickness/overlap: 1 mm/0.5 mm). The CT protocol was designed to give good high-resolution data, optimal contrast and good signal-to-noise ratios. Unfortunately, whilst good quality images were taken of the TMJ and adjoining tissue, no obvious abnormality was detected. Normally treatment with a non-steroidal anti-inflammatory drug (NSAIDs) would be employed to help with a diagnosis and potential efficacious treatment, it has been decided that the downside of the use of NSAIDs in a slow metabolising reptile was not outweighed by the clinical difficulty the ‘jaw opening problem’. George is not losing weight, is an old Alligator, so careful observation of his wellbeing will be undertaken over the next 6 months to ensure that his welfare is not adversely affected.

Two alligators resting on the ground

George, on the left, next to his girlfriend, after coming home from LARIF

This story was contributed by LARIF and the Adelaide Zoo

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” (

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 (, 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 (, 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 ( 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 ( platform.

Software developed to support the implementation of the repository services includes: Docker ( 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 ( 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 –
  • 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: 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)

New diagnostic strategies to determine cardiovascular risk

Despite significant advances in diagnostic and therapeutic technologies, cardiovascular disease (CVD) remains the global leading cause of death, accounting for 17.3 million deaths per year, and is expected to grow to more than 23.6 million by 2030. Currently, the prevention of MI and stroke is limited due to the lack of sensitive imaging methods. Those available usually involve invasive procedures such as coronary angiograms, which are potentially associated with complications, including death caused by MI or bleeding. Hence, there is a great need for new diagnostic strategies to determine whether the individual patient is at risk of MI or stroke, which then would allow for effective and early preventative treatment and improved clinical outcome.

This project is a multicentre collaboration led by the University of Queensland (UQ), Australian Institute for Bioengineering and Nanotechnology (AIBN), including the Queensland nodes of the National Imaging Facility and Australian National Fabrication Facility, Monash University, Baker IDI Heart and Diabetes Institute and the SooChow University. Together this project developed novel molecular imaging nanoparticles to enhance for MRI detection of activated platelets which is associated with unstable vulnerable atherosclerotic plaques.


A complete description of the project, including the particles and imaging methods, is available via the a publication in Biomaterials journal.


The uncovered toxins in Fang Blenny fish venom could pave the way for new medications

The UQ Node of the National Imaging facility has recently helped a scientific breakthrough in the field of venom research. The 3D image of a fang blenny reef fish was produced at the Centre for Advanced Imaging using the Siemens micro CT scanner. It was part of an international study led by Professor Bryan Fry from UQ school of Biological sciences involving,  Leiden University in Netherlands, Liverpool School of Tropical Medicine in UK, Monash University and the University of Queensland in Australia. The study was recently published in Current Biology. 

The team of scientists confirm that one group of fang blenny have venom glands that contain enkephalins, an opioid hormone that works by targeting the same molecules as synthetic opioid painkillers. According to Fry, the venoms of these species may serve as a novel source of painkillers. Currently prescribed opioids have led to an epidemic of addiction, so doctors and scientists are keen to find alternatives.

You can find more about this discovery through the following online articles by New Scientists, BBC, Science, National Public Radio (NPR), New York Times, and more!

Discover Magazine

The Atlantic

Science Magazine

New Scientist




New York Times


Collaborators: Liverpool School of Tropical Medicine, UK; Leiden University, The Netherlands; The University of Queensland, Australia; Monash University, Australia; University of Karachi, Pakistan; Leiden University Medical Centre, The Netherlands; Bangor University, UK; Anglia Ruskin University, UK

Bringing extinct Australia fauna back to life

What do long extinct pig-footed bandicoots, anatomical education and 3D printing have in common? Justin Adams and Paul McMenamin of the Centre for Human Anatomy Education at the Monash Department of Anatomy and Developmental Biology are using imaging data generated by the Monash NIF node fellows and the radiography team at Monash Biomedical Imaging. Their work developing highly detailed tissue models of human anatomy and long extinct Australian fauna is bring the dead back to life.

Neurosurgical training using simulators is now becoming more commonplace. High resolution CT and MRI data of cadaver hands, and biomechanical data available on the different tissues of the hand are being utilized to maximize anatomical and biomechanical accuracy in the development of a hand surgery simulator. These types of 3D datasets and rendering methods are being used to help develop the next generation of surgical assist robots by developing methods for generating precise tissue maps from clinical imaging data. Justin, Paul and his team including PhD student Raf Ratinam use the small bore Inveon CT and extended structural scans on the Skyra 3T MRI to generate high resolution images of iodine preserved human tissue specimens.

The CT and MR images are then reconstructed and “stitched” together to generate the tissue maps, enable further segmentation, 3D rendering and visualisation highlighting to allow students to visualise the tissue morphology during surgical training and anatomy classes. The datasets are then 3D printed using multiple materials to mimic tissue densities and generate highly realistic physical models of hand anatomy for surgical practice and training.

The researchers have also used the techniques with patient clinical CT scans to 3D print fractured bones to produce 3D models that allow surgeons to visualise the fracture and locate fastening points that speeds up the actual surgery. Patients could even collect a souvenir of their bone fracture or break, which would make an interesting trophy in the pool room cupboard at home!



Justin Adams

Paul McMenamin

Raf Ratinam

Michael de Veer

Tara Sepehrizadeh

Gang Zheng

National network of trusted data repositories establish standard for the future

Imaging equipment such as MRI, PET and CT scanners are capable of producing vast amounts of valuable research data. In order to maximise research outcomes, data must be stored securely, have its quality verified, and should be accessible to the wider research community.

Informatics fellows from around Australia have combined their expertise to build a series of Trusted Data Repositories (TDR’s) to provide researchers with a secure location to store, share and curate their data.

This national project, Delivering durable, reliable, high-quality image data, jointly funded by the Australian National Data Service (ANDS) and Research Data Services (RDS), guarantees the storage of data for at least 10 years for use in future research.

Led by the National Imaging Facility (NIF), the project brought together researchers and informatics specialists from UQ’s Centre for Advanced Imaging (CAI), Monash Biomedical Imaging (MBI), Monash eResearch Centre, the University of Western Australia, RCC (Research Computing Centre, UQ) and the University of NSW. Together, the team has established best practices for TDR’s to store imaging data nationally, through the NIF network.

To read the full article, please click on the following link:

Imaging Data, a Treasured Asset

Micro-CT imaging data collected at CAI by National Imaging Facility (NIF) Fellow, Dr Karine Mardon, has been transformed into an interactive display as part of the 200 treasures exhibition at the Australian Museum’s newly restored Long Gallery (now Westpac Gallery).

The data has been reconstructed to create a multimedia, interactive exhibit where visitors can see a 3D model of the internal structures several specimen.

The Westpac Gallery 200 Treasures will be a permanent installation and featured 100 invaluable treasures from the Australian Museum collection, and the stories of 100 people who have had a profound influence on Australian history.

The gallery has a rich history, as the first gallery in Australias first museum. The 19th century theatre has been extensively restored over the past two years to preserve and adapt the space. While respecting the historical signifcance of the gallery, it has embracing a modern spirit reflecting the museum’s current and future collections.

The Museum has been experimenting with CT to view internal structures of a specimens without the need for dissection.

Micro-CT data collected at the Centre for Advanced Imaging on the Inveon PET-CT, funded as part of the National Imaging Facility (NIF) by Dr Karine Mardon. Multimedia display in the Westpac Long Gallery developed by the interactive design company Holly. All images are copyright of the Australian Museum.

For more information on this study, please click on the following link:

PhysIO – An open-source toolbox to model physiological noise in fMRI

In a collaborative project led by Lars Kasper from the Translational Neuromodeling Unit (TNU) and the Institute for Biomedical Engineering at the University of Zurich and ETH Zurich together with National Imaging Facility (NIF) Fellow Steffen Bollmann from the Centre for Advanced Imaging (CAI), The University of Queensland node, a new open source toolbox for improving fMRI data analysis has been developed.

The physIO simplifies the workflow of incorporating physiological noise correction in fMRI analyses by providing robust pre-processing, fully automated modelling and a user-friendly performance assessment for group studies. All of this is tightly integrated in the open source toolbox SPM, the most widely used software for analysing fMRI data.

The project was started by Lars Kasper to access physiological data, i.e. breathing and heartrate from a Philips MRI scanner. Soon, he extended the toolbox to perform analysis of the physiological data and implemented various noise modelling methods. Steffen Bollmann joined the project in 2013 when he wanted to apply the algorithms to data collected during his PhD on a GE MRI scanner. The toolbox was not compatible with the GE data format and Steffen contributed routines for reading in data from this vendor and developed an algorithm for detecting ECG peaks more robustly. This was required due to poor data quality at times, as Steffen worked with children with Attention Deficit Hyperactivity Disorder (ADHD), who had a hard time lying still in the MRI scanner.

“New features for the toolbox were often developed on weekends when we met and discussed problems and possible solutions. The toolbox and our understanding of the problems we had solved grew during this time and we had more and more people testing it on their data and reporting problems they faced. Now, more than five years after the first lines of code, we have read-in routines for all major MRI vendors and a large repertoire of noise correction methods has been tested and implemented”, Steffen said.

Encouraged by its successful application in several studies including hundreds of volunteers, the team hopes that this open source toolbox will find useful application in future neuroimaging studies of health and disease, particularly in areas strongly affected by physiological noise such as the brainstem.

To download the toolbox, refer to and for more information, contact Dr. Steffen Bollmann (


Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Switzerland
Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Switzerland
Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
Wellcome Trust Centre for Neuroimaging, University College London, London, UK
Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, UK
Department of Psychiatry and Psychotherapy, Campus Mitte, Charité Universitätsmedizin, Berlin, Germany
Department of Neurology, Schulthess Clinic, Zurich, Switzerland
Max Planck Institute for Metabolism Research, Cologne, Germany

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