DeepHealth Receives FDA Clearance for AI-Powered Breast Ultrasound

DeepHealth, Inc., a worldwide leader in AI-driven health informatics and an exclusively owned subsidiary of RadNet, Inc., announced FDA 510(k) clearance for DeepHealth Breast Ultrasound, an AI-driven solution that brings greater standardization, scientific accuracy, and effectiveness to breast ultrasound imaging. DeepHealth Breast Ultrasound mechanizes lesion identification, characterization, and reporting, rationalizing sonographer and radiologist workflows in one intelligent experience. Composed with its AI-driven mammography services, the expanded DeepHealth breast platform is significantly more comprehensive in the industry.

In addition to a multi-reader, multi-case research study including 16 U.S. board-certified radiologists at select imaging centers and hospitals, RadNet has authenticated the efficiency of DeepHealth Breast Ultrasound in live healthcare settings under regulated research protocols. Recently, with FDA clearance, DeepHealth Breast Ultrasound is commercially available for sale to consumers in the United States who can pursue reimbursement under an existing Category III CPT code for quantitative ultrasound tissue characterization. By the end of this year, the services will be implemented in RadNet’s network of centers, with a projected more than 700,000 breast ultrasound studies yearly that may be qualified for reimbursement.

“Breast ultrasound is an essential component of the breast care pathway, with approximately 40% of women undergoing the exam at some point in their lives.4 It is a highly complex, operator-dependent examination, which can lead to significant variability in image acquisition, interpretation and reporting,” said Dr. Jason McKellop, Medical Director of Women's Imaging for RadNet California. “With DeepHealth's breast ultrasound solution, we can achieve greater standardization of workflows, improve consistency while saving time for patients, sonographers and radiologists. By streamlining the examination process, we can help reduce exam times, enhance efficiency and ultimately improve patient outcomes.”

DeepHealth Breast Ultrasound is intended to support more effective and standardized ultrasound workflows through:

• Automated lesion detection - Assists the interpreting physician to localize the presence or absence of suspicious soft-tissue lesions in standard ultrasound breast images, with demonstrated superior to 98% in localizing breast lesions and improved sensitivity for breast cancer identification by 8%
• Automated lesion characterization - Analyzes images developed by the sonographer to assist the interpreting doctors in generating and characterizing the lesion orientation, shape, margin, echo pattern, and posterior characteristics, in line with ACR BI-RADS, lowering radiologist interpretation time by 37%.
• Automated reporting - Generates a comprehensive radiology report of the significant findings and impressions, supporting radiologists to shift more effectively from image review to final report while retaining control of the final assessment.
• Expedited sonographer workflow - Automatically extracts and organizes lesion measurements, characteristics, and other relevant results in a standardized format, lowering physical documentation for sonographers to lower overall exam time.

“No single imaging pathway addresses every woman’s needs. With the addition of Breast Ultrasound, we are proud to support women across a broader range of screening and diagnostic pathways, including those with dense breasts and others who may require supplemental imaging. Bringing together AI-powered capabilities across mammography and ultrasound helps clinicians respond to different imaging needs and deliver more comprehensive, personalized breast care,” said Niccolò Stefani, M.D., Business and Product Leader, Clinical AI at DeepHealth.

DeepHealth’s breast imaging platform is a modular, interoperable AI-driven collection addressing real-world healthcare requirements in the breast cancer screening and diagnostic pathways, including applications for cancer identification in both mammography and ultrasound, density assessment, breast arterial calcification assessment, image-driven breast cancer challenges prediction and mammography quality analytics, with viewing and reporting devices for enhanced operational effectiveness.

According to Towards Healthcare, the teleradiology market is projected to experience significant growth, with estimates suggesting the market size will increase from USD 11.61 billion in 2026 to approximately USD 38.43 billion by 2035. Expected to maintain a CAGR of 14.23% from 2026 to 2035. Teleradiology enhances consumer care by allowing radiologists to supply their expertise without necessarily being at the same location as the patient. This is particularly essential when radiologist subspecialists such as MRI radiologists, pediatric radiologists, and neuro-radiologists are in demand, because these specialists are few in number and generally located in metropolitan cities.

About DeepHealth

DeepHealth is a wholly owned subsidiary of RadNet, Inc. and serves as the umbrella brand for RadNet’s Digital Health section. DeepHealth offers AI-driven health informatics to allow breakthroughs in care via imaging. DeepHealth leverages progressive AI for operational effectiveness and improved clinical results in breast, chest, neuro, musculoskeletal, prostate and thyroid health. At the heart of DeepHealth’s portfolio is a cloud-native operating technology, DeepHealth OS, which unifies data in the healthcare and operational workflow. Thousands of imaging centers and radiology departments around the world use DeepHealth services to allow earlier, more dependable and more effective disease detection, including in large-scale cancer screening programs. DeepHealth’s human-centered, intuitive technology aims to push the boundaries of possible in medical care.

About RadNet, Inc.

RadNet, Inc. is an important national supplier of freestanding, fixed-site diagnostic imaging solutions in the United States based on the number of locations and yearly imaging revenue. RadNet has a network of owned and operated outpatient imaging centers. RadNet’s imaging center markets involve Arizona, California, Delaware, Florida, Idaho, Indiana, Maryland, New Jersey, New York, Texas and Virginia. In addition, RadNet offers radiology information technology and artificial intelligence services marketed under the DeepHealth brand, teleradiology professional solutions and other related products and solutions to consumers in the diagnostic imaging industry worldwide. Together with contracted radiologists and a comprehensive team of full-time and per diem employees and scientists, RadNet has over 12,000 team members.

A recent report by Towards Healthcare highlights that the teleradiology market is growing. Teleradiology offers a lucrative opportunity for radiologists because of its ability to increase their professional horizons and income streams. By providing remote interpretation of healthcare images, radiologists reach a wider patient base, growing their caseload and opportunity. The flexibility to work from any location enables them to optimize their schedules and attain a better work-life balance. Radiologists leverage their specialized skills and knowledge to offer expert insights in various cases, aligning themselves as sought-after professionals. Furthermore, the capability to offer emergency coverage around the clock leads to higher compensation opportunities.