QMENTA’s AI Platform Selected for the CAVS-MS Multiple Sclerosis
Biomarker Study Funded By the National Institute of Health

The QMENTA platform streamlines data synthesis and analysis, reducing the potential for errors while saving time and lowering costs.

 

BOSTON, Mass., November 9, 2020  QMENTA, a leading innovator in cloud-based AI solutions for medical imaging, announced that its AI-driven platform was selected for Phase II of the multi-center CAVS-MS study funded by the National Institute of Health (NIH). The study is designed to determine if a proposed new biomarker, called the central vein sign (CVS), can reliably improve the diagnosis of Multiple Sclerosis (MS) in people suspected of having the disease. The QMENTA platform, used previously in Phase I of this research program, combines multiple AI and other software tools into an integrated system that accelerates the synthesis of complex medical data such as brain imaging scans and associated clinical data.

“Up to 20% of MS diagnoses turn out to be inaccurate. With this multi-center study, we hope to reduce that number by evaluating if this new biomarker can improve diagnostic accuracy,” said Daniel Ontaneda, MD, PhD, a principal investigator for the trial. “In Phase I of the study, QMENTA’s platform proved to be the ideal tool for aggregating and standardizing data from multiple sites, ultimately speeding the CVS validation.”

The QMENTA software platform will be used across all sites to coordinate information from 400 individuals in the study population.

“QMENTA is dedicated to working with world-class institutions to accelerate breakthroughs in the fight against brain diseases,” said Robert Bancroft, CEO. “Our work on the CAVS-MS study is designed to significantly simplify the synthesis and analysis of the study’s complex data set, thereby freeing the researchers to focus more of their expertise on discovery and insights instead of data administration and logistics.”

The AI-driven QMENTA platform will deliver quantitative data analysis using a cloud-based workflow for evaluating the central vein sign for MS diagnosis. The all-in-one platform enables each site to securely and privately contribute data, which is then sorted and automatically assessed to confirm adherence with the predetermined protocol, thus helping to reduce preventable errors and delays. The images are then analyzed using a deep-learning model for automated white matter lesion segmentation to improve the efficacy and reproducibility of the current lesion detection methods. The algorithm was developed by QMENTA’s scientific experts specifically for this study and integrated into the platform to update the CAVS-MS workflow.

About QMENTA

Headquartered in Boston, Mass. with a research and development center in Barcelona, Spain, QMENTA develops AI-enabled, cloud-based neuroimaging technology that empowers researchers and physicians to study, understand, diagnose, and treat brain disease with certainty and speed. The company’s platform is used in studies and trials throughout the world. For more information, visit QMENTA.com.