By Dr. Osama Abdullah
Multiple sclerosis (MS) is a chronic condition of the central nervous system, marked by unpredictable progression and highly individual patient trajectories. Its diagnosis and ongoing monitoring rely heavily on MRI imaging to detect lesions and assess changes in brain volume over time. Yet even in advanced healthcare systems, this process remains time-consuming, often subjective, and heavily dependent on access to specialist expertise. This challenge is especially pressing in the UAE, where MS prevalence is estimated to be nearly double the global average, and the demand for personalized, timely neurological care continues to rise.
The LAMINATE study was developed to address this critical gap. A collaboration between NYU Abu Dhabi’s Center for Brain and Health, Cleveland Clinic Abu Dhabi, and Yas Clinic, the project aims to create a streamlined and standardized approach for assessing MS progression through MRI. At its core, LAMINATE delivers an automated tool that detects, segments, and compares brain lesions and atrophy across multiple time points, helping clinicians make earlier and more informed treatment decisions.
The primary objective is to improve the accuracy and consistency of MS monitoring while easing the diagnostic burden on clinical teams. By automating the comparison of MRI scans taken at different times – a task that typically requires painstaking, side-by-side review by a radiologist – LAMINATE helps uncover subtle changes that might otherwise go unnoticed. These include new or enlarging lesions, early signs of brain atrophy, and emerging imaging biomarkers such as the central vein sign (CVS), which has gained recognition for its potential to differentiate MS from other conditions.
The foundation of the research is a carefully curated dataset of over 150 MS patient scans, collected and manually labelled in partnership with Cleveland Clinic Abu Dhabi and Yas Clinic. These scans reflect a broad spectrum of real-world imaging variables – spanning different machines, field strengths, and scanning protocols – making the tool highly adaptable to diverse hospital environments. The system also includes a physician-facing interface, LesionView, which enables users to review lesion clusters, validate segmentation results, and generate customized reports directly from the hospital’s imaging platform.
From a methodological standpoint, the study prioritizes clinical relevance. The team developed site-specific workflows, applied longitudinal image registration to align serial scans, and incorporated CVS detection in anticipation of updates to the 2024 McDonald Criteria for MS diagnosis. The system is already in active use at Cleveland Clinic Abu Dhabi, with rollout underway at Yas Clinic and plans to extend deployment to additional hospitals in the region.
LAMINATE builds upon international best practices and the latest advances in medical imaging research. The project aligns with recommendations from the MAGNIMS-CMSC-NAIMS consortium, which advocates for longitudinal MRI assessments using 3D FLAIR imaging – an approach that is central to the LAMINATE pipeline. At the same time, it extends the capabilities of earlier segmentation tools by adapting them to local clinical contexts and data. Rather than simply replicating global innovations, the project brings a regionally tailored solution to the UAE’s healthcare ecosystem.
Looking ahead, the future of MS care will be increasingly precise, data-driven, and accessible. But precision must be matched with practicality – solutions that integrate seamlessly into everyday clinical workflows, where time is limited and resources vary. This is the vision behind LAMINATE: to reduce the time from scan to diagnosis, boost clinician confidence, and improve patients’ chances for timely intervention.
Crucially, this progress has been made possible through the support of the National MS Society UAE. Funding from the Society has enabled the project to move beyond academic proof-of-concept into clinical deployment, facilitating model development, validation, and hospital integration. As LAMINATE enters its next phase – expanding access, completing system integration, and developing regional training programs – continued support will be essential. This is not only a research project; it is a tangible opportunity to improve MS care throughout the Middle East.
While currently optimized for MS, the platform’s design is adaptable to other neurological and systemic conditions that require longitudinal imaging. These include neurodegenerative conditions such as Alzheimer’s and other dementias, where subtle patterns of atrophy can guide treatment; stroke recovery, where lesion changes can shape rehabilitation strategies; and oncology, where tumor evolution and treatment response must be closely tracked. By offering a scalable, clinically integrated solution for image-based condition monitoring, LAMINATE demonstrates how research and innovation can come together to reshape healthcare delivery, starting with MS, and reaching far beyond.
About the Author
Dr. Osama Abdullah is an MRI physicist and researcher based in Abu Dhabi. He is a co-investigator on the LAMINATE study and the second runner-up of the Innovation Award at Abu Dhabi Global Healthcare Week 2025. His work focuses on developing advanced imaging tools for neurological and neurodegenerative conditions, with a particular emphasis on clinical translation and regional impact.
