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BrightHeart gains FDA Clearance for real-time AI analysis tool in fetal heart screenings

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Key Takeaways

  • BrightHeart's AI platform, now FDA-cleared, enhances real-time fetal ultrasound exams by detecting congenital heart defects (CHDs) with a cart-side tablet.
  • The technology addresses the challenge of undiagnosed CHDs, improving diagnostic accuracy and streamlining clinical workflows during prenatal care.
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BrightHeart's FDA-cleared AI platform enhances fetal heart screenings, improving detection of congenital heart defects during ultrasounds with real-time analysis.

AI analysis for fetal heart screening available: ©Jirsak - stock.adobe.com

AI analysis for fetal heart screening available: ©Jirsak - stock.adobe.com

BrightHeart, a Paris-based artificial intelligence company for obstetrics and pediatric cardiology, announced it has received FDA 510(k) clearance for an updated version of its BrightHeart platform. The new approval allows clinicians to access the company’s AI-driven analysis in real time using a cart-side tablet during fetal ultrasound exams.

The technology aims to address a persistent clinical challenge: detecting congenital heart defects (CHDs) in utero. CHDs are the most common type of birth defect, but up to 70% go undiagnosed during standard prenatal ultrasounds, according to the company.

BrightHeart’s AI platform flags potential structural abnormalities in the fetal heart, helping to alert clinicians to possible CHDs during routine exams. The company says the real-time tablet integration streamlines workflows and improves the accuracy of screenings.

“Our product expansion builds upon the success of our initial pilot experience, bringing real-time feedback directly to the clinicians to streamline the workflow and enhance accuracy,” said Cécile Dupont, CEO of BrightHeart and partner at Sofinnova Partners. “We were thrilled to achieve clearance through our first Special 510(k) submission within just a few months.”

Clinicians involved in the pilot program have praised the tablet’s real-time capabilities. Jennifer Lam-Rachlin, a maternal-fetal medicine specialist at Mount Sinai Hospital in New York, said the device helps improve both efficiency and confidence during exams.

“Heart defects are so hard to detect, and so devastating if missed,” added Sara Garmel, perinatologist and founding partner at Michigan Perinatal Associates. “By surfacing the alerts directly during the scan, BrightHeart helps bring greater structure and efficiency to fetal heart exams to support earlier and more accurate detection.”

With several FDA clearances now in hand, BrightHeart is preparing for a limited market release to deploy the platform in select clinics. The company is encouraging collaboration from clinicians, researchers, and industry partners to further expand access to AI-supported prenatal care.

BrightHeart is part of Sofinnova MD Start, the medical device accelerator from Sofinnova Partners. Its software leverages AI to analyze fetal heart ultrasounds and assist health care providers in evaluating complex cardiac structures.

How AI is making a difference in prenatal care

Advances in artificial intelligence are rapidly transforming health care by improving diagnostic accuracy, enhancing clinical workflows, and expanding access to expert-level care. In fields like obstetrics and pediatric cardiology—where early detection of abnormalities can be critical—AI tools are proving especially valuable, according to experts.

This type of technology supports clinicians rather than replacing them. It provides decision support during exams, offers standardized analysis, and helps reduce the cognitive burden of interpreting complex scans. That, in turn, can lead to faster diagnoses and more timely interventions—especially in busy or resource-limited settings where access to pediatric cardiology specialists may be limited.

Moreover, integrating AI directly into the exam workflow—through tools like a cart-side tablet—can enhance efficiency by allowing real-time feedback without disrupting clinical routines. These capabilities are increasingly important as health care systems look to improve outcomes while managing costs and workforce shortages.

The adoption of AI in prenatal imaging is part of a broader trend across medicine. Similar technologies are being used to detect cancers on radiological images, identify early signs of neurological disorders, and predict patient deterioration in hospitals. While challenges around data privacy, regulation, and clinician trust remain, AI is clearly becoming a key ally in the move toward more precise, accessible, and scalable health care, according to experts.

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