Heart failure is often a difficult condition to diagnose correctly because its symptoms can be quite vague. Now, a novel chest X-ray algorithm can screen for telltale signs of heart failure, such as an enlarged cardiothoracic ratio (CTR) and fluid in the lungs, along with other indicators visible on X-rays. This development represents a significant leap forward in the fields of medical imaging and heart care, offering a new method for early detection of heart failure via automated analysis of chest X-rays.

The qXR-CTR artificial intelligence (AI)-enabled chest X-ray solution from Qure.ai Technologies (New York, NY, USA) is an AI-powered solution designed to assist doctors in both hospital and clinic settings by automating the measurement of the CTR on chest X-rays. Specifically, it calculates the ratio of the maximum transverse diameter of the heart to the maximum inner transverse diameter of the thoracic cavity, providing the most accurate indicator of cardiomegaly on plain film. By employing advanced AI algorithms, the technology offers quick and accurate results, saving valuable time for healthcare professionals and enhancing the reliability of diagnoses.

Qure.ai has now received FDA clearance for measuring the CTR utilizing qXR-CTR, marking the company's 12th FDA-cleared algorithm. Qure.ai’s previous FDA-cleared findings include endotracheal tube location, tracheostomy tube location, pneumothorax, and pleural effusion identification for CXR; qER for intracranial hemorrhage detection on head CT scans, and qER Quant for quantifying serious abnormalities on head CT scans.

"We are delighted to receive FDA clearance for qXR-CTR,” said Prashant Warier, Co-Founder and CEO at Qure.ai. “This cutting-edge algorithm enhances the accuracy and efficiency of CTR assessment and empowers healthcare professionals with a valuable tool to diagnose and monitor risk of heart failure. This achievement reaches an industry record for the greatest number of FDA-cleared findings on CXR scans, demonstrating Qure.ai's commitment to advancing better patient outcomes through AI-driven solutions."

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