Abstract Details

Title Validation of FLAIR Hyperintensities Segmentation With Icobrain Dm 5.16

Topic Aging, Dementia, and Behavioral Neurology

Presentation(s) P4 - Poster Session 4 (5:00 PM-6:00 PM)

Poster/Presentation
Number 3-008

Objective Develop a robust automated deep learning-based method for assessment of hyperintensities on T2 FLAIR images.

Background

Cerebrovascular lesions often occur in Alzheimer’s Disease (AD) and may be an important modifier of AD progression. Automated MRI volumetry plays an important role in assessing the presence and extent of vascular lesions. icobrain dm is an established regulatory-cleared brain MRI quantification tool used in clinics worldwide to evaluate neurological markers pertaining to dementia care.

Design/Methods icobrain dm segments brain tissues and substructures on T1-weighted images and hyperintensities on fluid attenuated inversion recovery (FLAIR) images. Recent versions of icobrain dm employ fully-deep-learning-based segmentation models, trained on a variety of brain scans over the whole lifespan2. Reproducibility of icobrain dm 5.16 was assessed in test-retest studies acquired in four MRI scanners (GE 3T, Siemens 3T, Philips 3T and Philips 1.5T) from 5 patients in different stages of the AD continuum (aged 69.0 ± 10.5) and 5 controls (aged 52.2 ± 17.6)3.

Results All controls had less than 3ml FLAIR hyperintensity volumes, while the AD patients had volumes ranging from 4ml to 21ml. Overall, the absolute test-retest error was 0.04 ± 0.06 ml (mean±std; 0.02ml median, 0.08ml p90) for same-scanner comparisons (n=40) and 0.17 ± 0.18 ml (mean±std; 0.09ml median, 0.45ml p90) for inter-scanner comparisons (n=240).

Conclusions

icobrain dm 5.16 produces robust and reproducible segmentations of vascular lesions in the elderly population. These findings underscore the value of icobrain dm for early and accurate disease detection and monitoring to help optimize patient monitoring and care.

Authors/Disclosures
Annemie Ribbens PRESENTER	Annemie Ribbens has received personal compensation for serving as an employee of icometrix. Annemie Ribbens has stock in icometrix. Annemie Ribbens has received intellectual property interests from a discovery or technology relating to health care.
Wim Van Hecke, PhD (University Hospital Brussels)	Dr. Van Hecke has received personal compensation for serving as an employee of icometrix.
Diana Sima	Diana Sima has received personal compensation for serving as an employee of icometrix.
Arno Liseune (icometrix)	No disclosure on file
Ricardo Magalhaes (Icometrix)	Ricardo Magalhaes has received personal compensation for serving as an employee of icometrix.
Thanh Vân Phan (icometrix)	No disclosure on file
Simon Van Eyndhoven (icometrix)	Simon Van Eyndhoven has received personal compensation for serving as an employee of icometrix.
Arne Brys, MS	Dr. Brys has received personal compensation for serving as an employee of icometrix.
Rafay Khan (icometrix)	Rafay Khan has received personal compensation for serving as an employee of icometrix.
Melissa Wittens (Vrije Universiteit Brussel / University of Antwerp)	No disclosure on file
Gert-Jan Allemeersch, MD	Dr. Allemeersch has nothing to disclose.
Tim Vanderhasselt, MD	Dr. Vanderhasselt has nothing to disclose.
Ann Vanbinst (UZ Brussel)	No disclosure on file
Johan de Mey (UZ Brussel)	No disclosure on file
Sebastiaan Engelborghs, MD, PhD (University of Antwerp, Biomedical Sciences)	No disclosure on file
Dirk Smeets	Dirk Smeets has received personal compensation in the range of $100,000-$499,999 for serving as a Consultant for icometrix. Dirk Smeets has stock in icometrix.

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