DeepHealth Receives FDA Clearance for AI-Powered Breast Ultrasound

SOMERVILLE, Mass., July 30, 2026 (GLOBE NEWSWIRE) -- DeepHealth, Inc., a global leader in AI-powered health informatics and a wholly owned subsidiary of RadNet, Inc. (NASDAQ: RDNT), today announced FDA 510(k) clearance for DeepHealth Breast Ultrasound,¹ an AI-powered solution that brings greater standardization, clinical accuracy and efficiency to breast ultrasound imaging. DeepHealth Breast Ultrasound automates lesion detection, characterization and reporting, streamlining sonographer and radiologist workflows in one intelligent experience. Together with its AI-powered mammography solutions, the expanded DeepHealth breast platform is the most comprehensive in the industry.

In addition to a multi-reader multi-case study involving 16 U.S. board-certified radiologists at select imaging centers and hospitals,² RadNet has validated the effectiveness of DeepHealth Breast Ultrasound in live clinical settings under regulated research protocols. Now with FDA clearance, DeepHealth Breast Ultrasound is commercially available for sale to customers in the United States who can pursue reimbursement under an existing Category III CPT code for quantitative ultrasound tissue characterization.³ By the end of this year, the solution will be implemented across RadNet’s network of centers, with an estimated more than 700,000 breast ultrasound studies annually that may be eligible 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, improving 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 designed to support more efficient 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 greater than 98% accuracy in localizing breast lesions and improved sensitivity for breast cancer detection by 8%²
• Automated lesion characterization – Analyzes images acquired by the sonographer to assist the interpreting physician in generating and characterizing the lesion shape, orientation, margin, echo pattern and posterior features, in line with ACR BI-RADS, reducing radiologist interpretation time by 37%²
• Automated reporting – Generates a comprehensive radiology report of the key findings and impressions, helping radiologists move more efficiently 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 findings in a standardized format, reducing manual documentation for sonographers with the aim of reducing 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 platform⁵ — a modular, interoperable AI-powered portfolio addressing real-world clinical needs across breast cancer screening and diagnostic pathways — includes applications for cancer detection in both mammography and ultrasound, density assessment, breast arterial calcification assessment, image-based breast cancer risk prediction⁶ and mammography quality analytics, with viewing and reporting tools for improved operational efficiency.

About DeepHealth
DeepHealth is a wholly owned subsidiary of RadNet, Inc. (NASDAQ: RDNT) and serves as the umbrella brand for RadNet’s Digital Health segment. DeepHealth provides AI-powered health informatics with the aim of epowering breakthroughs in care through imaging. DeepHealth leverages advanced AI for operational efficiency and improved clinical outcomes in breast, chest, musculoskeletal, neuro, prostate and thyroid health. At the heart of DeepHealth’s portfolio is a cloud-native operating system – DeepHealth OS – that unifies data across the clinical and operational workflow. Thousands of imaging centers and radiology departments around the world use DeepHealth solutions to enable earlier, more reliable and more efficient disease detection, including in large-scale cancer screening programs. DeepHealth’s human-centered, intuitive technology aims to push the boundaries of what’s possible in healthcare. Learn more at deephealth.com. 

About RadNet, Inc. 
RadNet, Inc. is a leading national provider of freestanding, fixed-site diagnostic imaging services in the United States based on the number of locations and annual imaging revenue. RadNet has a network of owned and/or operated outpatient imaging centers. RadNet’s imaging center markets include Arizona, California, Delaware, Florida, Idaho, Indiana, Maryland, New Jersey, New York, Texas and Virginia. In addition, RadNet provides radiology information technology and artificial intelligence solutions marketed under the DeepHealth brand, teleradiology professional services and other related products and services to customers in the diagnostic imaging industry globally. Together with contracted radiologists, and inclusive of full-time and per diem employees and technologists, RadNet has over 12,000 team members. Learn more at radnet.com. 

Forward Looking Statements
This communication contains certain “forward-looking statements” within the meaning of the safe harbour provisions of the U.S. Private Securities Litigation Reform Act of 1995, Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. Forward-looking statements can be identified by words such as: “anticipate,” “believe,” “could,” “estimate,” “expect,” “forecast,” “intend,” “may,” “outlook,” “plan,” “potential,” “possible,” “predict,” “project,” “seek,” “should,” “target,” “will” or “would,” the negative of these words, and similar references to future periods. Examples of forward-looking statements include statements regarding our technology’s ability to stage-shift disease through proactive, timely intervention and discussions regarding our product features. Actual results could differ materially from those currently anticipated due to a number of risks and uncertainties, many of which are beyond RadNet’s control.

Forward-looking statements are neither historical facts nor assurances of future performance. Instead, they are based only on management’s current beliefs, expectations and assumptions regarding the future of RadNet’s business, future plans and strategies, projections, anticipated events and trends, the economy and other future conditions. Because forward-looking statements relate to the future, they are subject to inherent uncertainties, risks and changes in circumstances that are difficult to predict and many of which are outside of RadNet’s control. RadNet’s actual results and financial condition may differ materially from those indicated in the forward-looking statements as a result of various factors. Neither RadNet, nor any of its directors, executive officers, or advisors, provide any representation, assurance or guarantee that the occurrence of the events expressed or implied in any forward-looking statements will actually occur, or if any of them do occur, what impact they will have on the business, results of operations or financial condition of RadNet. Should any risks and uncertainties develop into actual events, these developments could have a material adverse effect on RadNet’s business and the ability to realize the expected benefits of the technology. Risks and uncertainties that could cause results to differ from expectations include, but are not limited to: (1) the ability to recognize the anticipated benefits of the technology, and (2) the risk of legislative, regulatory, economic, competitive, and technological changes, and other risks and uncertainties described in the “Risk Factors,” “Management’s Discussion and Analysis,” and other sections of our filings with the Securities and Exchange Commission, including our most recent Annual Report on Form 10-K and Quarterly Reports on Form 10-Q. The foregoing review of important factors should not be construed as exhaustive and should be read in conjunction with the other cautionary statements that are included elsewhere. Additional information concerning risks, uncertainties and assumptions can be found in RadNet’s filings with the Securities and Exchange Commission (the “SEC”), including the risk factors discussed in RadNet’s most recent Annual Report on Form 10-K, as updated by its Quarterly Reports on Form 10-Q and future filings with the SEC.

Forward-looking statements included herein are made only as of the date hereof and, except as required by applicable law, RadNet does not undertake any obligation to update any forward-looking statements, or any other information in this communication, as a result of new information, future developments or otherwise, or to correct any inaccuracies or omissions in them which become apparent. All forward-looking statements in this communication are qualified in their entirety by this cautionary statement.

DeepHealth Media Contact
Andra Axente
Director of Communications
+31614440971
[email protected]

RadNet Media Contacts 
Jane Mazur 
Senior Vice President, Corporate Communications 
+1 585-355-5978 
[email protected]

Mark Stolper
Executive Vice President and Chief Financial Officer
+1 310-445-2800

References

1. Deephealth Breast Ultrasound is the commercial name for the See-Mode Augmented Reporting Tool, Breast (SMART-B) device, cleared by the FDA under 510(k) K260303. The clearance is held by See-Mode Technologies Pty Ltd, a DeepHealth company, which manufactures the device; it is distributed in the United States by DeepHealth, Inc.
2. Data on file. Based on data from MRMC study submitted to FDA for 510(k) clearance K260303.
3. Reimbursement depends on payer policy.
4. Based on change of regulations and gold-standard approach in breast cancer screening. U.S. Food and Drug Administration. Mammography Quality Standards Act and Regulation Amendments: Small Entity Compliance Guide—Guidance for Industry and Food and Drug Administration Staff. Issued August 26, 2024, https://www.fda.gov/media/181152/download.
   U.S. Food and Drug Administration. Understanding Breast Density. FDA Office of Women’s Health. https://www.fda.gov/consumers/womens-health-topics/understanding-breast-density
5. DeepHealth breast solutions comprise multiple applications, including Mammo Dx, Breast Density, Safeguard Review, Risk Assessment, BAC Assessment, Mammography Insight, Breast Ultrasound and workflow tools including DeepHealth Viewer. DeepHealth Viewer is manufactured by eRAD, Inc. and distributed by DeepHealth, Inc. Mammography Insights is manufactured by Aquila, Inc. and distributed by DeepHealth, Inc.
6. Not cleared for use in the U.S. Capability available in Europe.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/b8473709-04f0-4b5c-b856-bab20d7d6c80

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