Leveraging artificial intelligence (AI) algorithms, the qXR-CTR reportedly provides automated cardiothoracic ratios (CTRs) through assessment of plain chest radiographs.
The Food and Drug Administration (FDA) has granted 510(k) clearance for qXR-CTR, a deep learning-enabled algorithm that may offer more enhanced detection of cardiomegaly via automated cardiothoracic ratio (CTR) measurement on plain chest X-rays.
The qXR-CTR algorithm, which can be utilized in inpatient and outpatient settings, enables more precise measurement of the ratio between the maximum transverse diameter of the heart to the maximum inner transverse diameter of the thoracic cavity, according to Qure.ai, the developer of qXR-CTR.
The company indicated that automation of the CTR measurement via X-rays may bolster the accuracy of cardiomegaly diagnosis and possibly facilitate earlier detection of heart failure.
"Integrating AI into cardiac diagnostics has long shown immense promise, and Qure.ai’s latest advancement with qXR-CTR is a testament to how much of that potential is now being realized. Early detection of heart failure is a challenge, but with tools like these, we are narrowing the gap. The combination of identifying increased cardiothoracic ratio and pleural effusion, in particular, is a significant stride,” noted Tariq Ahmad, M.D., M.P.H., the Chief or the Heart Failure Program and an associate professor of medicine (cardiovascular medicine) at the Yale School of Medicine in New Haven, Ct.
Qure.ai said qXR-CTR represents the 12th 510(k) clearance for the company with previous clearances including pleural effusion and pneumothorax detection on chest X-rays, and qER Quant for quantification of critical abnormalities on head computed tomography (CT) scans.