ONDRI validates MRI distortion correction protocol for multi-site research

Close only counts in horseshoes and hand grenades.

This phrase, coined by Frank Robinson, highlights a reality; that is, that most things that demand measurement require accuracy. Close is not good enough.

This notion is particularly true for an intricate matter such as brain imaging, be it utilizing magnetic resonance imaging (MRI) or other technologies.

When examining images of the brain and its components, millimetres – and even partial millimetres – can make a big difference to observations and potential implications. Yet distortion is expected when utilizing MRI technology.

In fact, manufacturers provide their own programs which are installed with the scanner, to correct for known distortions.

Imaging for multi-site studies

Image distortion becomes an even more pertinent issue when conducting a study at multiple sites. Images must be comparable from site to site, for the study observations to be optimal.

Distortions that arise from imperfect magnetic fields created by the scanner – fields that are used in the production of images – can vary in different directions; they can also change for different scanners depending on the scanner hardware that is used.

These distortions require correction over and above that provided by the manufacturers, to produce the highest quality multi-site study data.

ONDRI is among the first

As published¹ recently by Nuwan D. Nanayakkara et al, ONDRI’s Foundational Study successfully adopted a geometric distortion correction protocol² that was developed more than ten years ago by Vladimir S. Fonov et al, at the Montreal Neurological Institute at McGill University in Montreal.

ONDRI researchers were among the first to adopt this protocol in a large multi-site study, and they showed that it indeed worked as hypothesized.

How do you correct distortion in a multi-site study?

One way to ensure uniformity across sites is by measuring the exact same object at the different labs. If the detailed specifications of the object are known, then the differences between these known measurements and those produced at each lab can be programmed into site specific algorithms. Once these are developed and applied at each site, measurements are comparable across sites.

Lego^®, which is manufactured to an accuracy of 2 micrometers (or 2/1,000th of a millimetre) per piece, allows the type of accuracy that is needed for this application. The protocol adopted by ONDRI involved using “phantom” models made from Lego – made to the exact same specifications – at each lab. These models were scanned monthly, and correction algorithms were applied based on variations from the known model specifications.

Participants helped ensure success

Once the site-specific correction algorithms were developed, two volunteer ONDRI study participants traveled to all ten sites, within a two-month period, and were scanned using the MRI technology. The correction algorithms were applied, which proved that across sites, this protocol worked to improve the uniformity of measurements.

Research demands higher levels of exactitude

It is important to understand that MRI technologies, which are used widely in clinical practice, work very well as designed. Once these scanners are installed and calibrated, the images produced are highly effective at helping clinicians diagnose and track many brain diseases.

The requirements of clinical research, especially research into biomarkers of disease at early stages, are different than those of clinical practice. The scale of the measurements and relevant changes therein is smaller; therefore the type of correction protocol adopted by ONDRI can improve measurements made in multi-site research studies.

“In this study, we are able to achieve very high accuracy in our MRI measures across sites, after diligently applying the phantom model protocol”, said Nanayakkara. “We believe that greater accuracy in these measurements, particularly in small samples, can ultimately help clinicians identify changes in brain morphology more easily, which can allow for improvements in early diagnosis of disease,” he continued.

Delivering tools for improvements in early diagnosis of neurodegenerative and cerebrovascular diseases, which can ultimately affect disease trajectory – this is one of the primary aims of ONDRI’s research.