Qure.ai announces FDA clearance for its AI-driven chest x-ray solution

This also marks the 6th FDA clearance for Qure’s chest X-ray based solutions

Qure.ai has announced its 13^th FDA clearance for their AI-enabled solutions. Qure’s chest X-ray based qXR-LN uses Artificial Intelligence (AI) to identify and localise lung nodules.

This also marks the 6^th FDA clearance for Qure’s chest X-ray based solutions.

qXR for Lung Nodule (qXR – LN) is computer-aided detection software designed to identify and highlight regions indicative of suspected pulmonary nodules ranging from 6 to 30 mm in size. Tailored for use in the incidental adult population, this innovative device is a game-changer in diagnostic technology. It can also serve as a crucial second reader for physicians, assisting in the review of frontal (AP/PA) chest radiographs of adults acquired on digital radiographic systems.

Prashant Warier, Co-Founder & CEO, Qure.ai, stated, “With this latest addition to our large series of recent FDA clearances, we are steadfast in our unwavering commitment to the US healthcare space. Having already effectively deployed and implemented this solution globally, this clearance marks yet another ground-breaking leap in our pioneering efforts to combat lung cancer. Our heightened emphasis on the North American marketplace solidifies our commitment to making a meaningful impact in the fight against this deadly disease and underscores our dedication to advancing healthcare through innovation, providing a transformative solution enhancing the early detection of cancer and ultimately improving patient outcomes.”

Qure conducted two studies to establish the safety and efficacy of its lung nodule device. In the initial pivotal study, Qure demonstrated standalone performance that met predefined success criteria, achieving an Area Under the Curve (AUC) of 94 per cent for nodule detection. The study involved qXR-LN and included chest X-ray scans collected from 8 states and 40 individual sites across the United States. The device’s performance was assessed against the ground truth determined by five American board-certified Radiologists. These Radiologists interpreted Chest X-rays alongside corresponding CT scans and reports, with the ground truth based on nodules visible on the Chest X-ray.

In the second pivotal study, a landmark clinical evaluation of qXR-LN was conducted through a multi-reader, multi-case clinical validation study. The performance of various readers, including radiologists, pulmonologists, and emergency room physicians, showed improvement. The qXR-LN algorithm demonstrated a statistically significant and clinically meaningful enhancement in pulmonary nodule detection across all reader groups. Notably, in the multi-reader, multi-case study, the use of qXR-LN resulted in some emergency room physicians and pulmonologists approaching or surpassing the baseline (unaided)performance of radiologists.

Lung nodule detection on plain film is crucial for the early identification of malignancy risk, enabling timely interventions and improving patient outcomes. Accurate detection aids in treatment planning, disease progression monitoring, and the reduction of false positives and negatives, contributing to cost-efficient and optimal healthcare.