New Studies Suggest That DiA's AI-based Software, LVivo EF, Is Accurate and Efficient in Assessing Ejection Fraction Values Compared to Cardiac MRI and Contrast Echocardiography

BEER-SHEVA, Israel, June 19, 2019 /PRNewswire/ -- DiA Imaging Analysis, the developers of artificial intelligence (AI) powered ultrasound analysis solutions, has announced today the presentation of two studies assessing the performance and accuracy of the company's LVivo EF AI-based solution that generates fully automated Left Ventricular (LV) Ejection Fraction (EF). EF is a main indicator in assessing the global function of the Left Ventricle. Presently, many readers quantify EF visually or trace endocardial borders that may not be well defined, yielding high variability among results. LVivo EF aims to substantially reduce this variability by generating objective, accurate and fast AI-based EF.

The studies were led by Martin Goldman MD, Solomon Bienstock MD, Rajeev Samtani MD, Steve Liao MD, Usman Baber MD, Dr. Arieh Greenbaum MD, Lori B. Croft MD and Eric Stern MD from Mount Sinai Hospital, New York.

The first study: "Validation of a Novel Artificial Intelligence Left Ventricular Ejection Fraction Quantification Software (LVivo EF by DIA) by Cardiac MRI" tested the accuracy of the LVivo EF tool on 76 patients by retrospectively running it on cardiac 4 chamber clips. The LVivo EF results were then compared to those obtained by MRI EF as a gold standard. The study indicated a strong correlation between cardiac MRI and LVivo EF (R2=0.89) and it suggests that LVivo EF may be used over a wide range of cardiac function, to evaluate EF in a fast and accurate manner.

"This study further validated DiA's AI-based tool, LVivo EF, against cardiac MRI EF, a recognized gold standard for the assessment of cardiac function. Based on the study's findings, LVivo EF has the potential to provide accurate and objective quantification of LV EF to support clinicians in the decision-making process, right at the patient's bedside, saving time and resources. This is specifically important in patients with low EF, where accuracy has clinical and therapeutic implications. Moreover, by providing the endocardial border overlay on the moving images, it also facilitates immediate confirmation of its accuracy by the reader," said Dr. Martin Goldman, Associate Director of the CV Institute, Director of the Fellowship Training Program and Director of Medical Education at the Icahn School of Medicine at Mount Sinai Hospital.

The successful validation of LVivo EF as compared to MRI EF, led the team to publish a second study that compared LVivo EF results to physician's evaluation of EF using transthoracic echocardiography (TTE), with and without contrast agents, entitled Fully Automated Echocardiographic Artificial Intelligence Software (LVivo EF by DiA) Could Replace Contrast Agents for Improving Accuracy of Left Ventricular Ejection Fraction Quantification. The results indicated that in non-contrast studies compared to cardiac MRI, LVivo EF was significantly better than physicians' assessments (R2=0.823 compared to R2=0.622), while for contrast studies, which are often used to improve LV EF analysis, LVivo EF on non-contrast images and physicians' quantification of contrast enhanced images were similar (R2=0.913 and R2=0.873).

"The excellent results of the studies demonstrate the accuracy of the LVivo EF tool as well as its clinical and economic value," said Hila Goldman-Aslan, DiA's Co-Founder and CEO. "The results fit DiA's vision of supporting clinicians' in decision-making processes by generating automatic, objective and accurate AI-Based solutions. We thank Dr. Goldman's team for these fascinating studies."

Both studies will be presented by Solomon Bienstock MD, Icahn School of Medicine at Mount Sinai at the ASE 2019, 30th Annual Scientific Session (Portland, USA), June 24th, Exhibit Hall C, P-099, 11:45-13:15.

DiA invites interested parties to learn more about how AI could make ultrasound analysis accessible to all and ultimately improve patient care. They will be presenting at ASE 2019 in booth #115. To contact DiA's team, visit DiA's website: www.dia-analysis.com or email at: [email protected]

About DiA Imaging Analysis

DiA Imaging Analysis makes ultrasound analysis accessible to all by using its advanced AI-based technology which assists clinicians, at all experience levels, analyze ultrasound images - objectively and accurately. The technology is based on advanced pattern recognition, deep learning and machine learning algorithms which imitate the way the human eye detects borders and identifies motion. DiA's automated tools deliver fast and accurate clinical indications to support the decision-making process, ultimately improving patient care. The company was founded by Dr. Noah Liel-Cohen, Hila Goldman Aslan (CEO), Michal Yaacobi (CTO), and Arnon Toussia-Cohen (CCO). For more information on DiA Imaging Analysis please visit www.dia-analysis.com

Contacts

Edith Schlanger
DiA Imaging Analysis [email protected]
+972-522802021

SOURCE DIA Imaging Analysis

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