{"id":41097,"date":"2026-07-31T11:32:21","date_gmt":"2026-07-31T11:32:21","guid":{"rendered":"https:\/\/g-medtech.com\/news\/?p=41097"},"modified":"2026-07-31T11:42:10","modified_gmt":"2026-07-31T11:42:10","slug":"deephealth-receives-fda-clearance-for-ai-powered-breast-ultrasound-solution","status":"publish","type":"post","link":"https:\/\/g-medtech.com\/news\/deephealth-receives-fda-clearance-for-ai-powered-breast-ultrasound-solution\/","title":{"rendered":"DeepHealth Receives FDA Clearance for AI-Powered Breast Ultrasound Solution"},"content":{"rendered":"\n

DeepHealth<\/a>, a global leader in AI-powered health informatics and a wholly owned subsidiary of RadNet, has announced FDA 510(k) clearance for DeepHealth Breast Ultrasound, an AI-powered solution designed to bring greater standardization, clinical accuracy, and efficiency to breast ultrasound imaging. The solution automates lesion detection, characterization, and reporting, streamlining sonographer and radiologist workflows. Together with its AI-powered mammography solutions, the expanded DeepHealth breast platform is positioned as the most comprehensive in the industry.<\/p>\n\n\n\n

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. It is a highly complex, operator-dependent examination that can lead to significant variability in image acquisition, interpretation, and reporting. DeepHealth Breast Ultrasound is designed to support more efficient and standardized workflows through automated lesion detection, which assists interpreting physicians in localizing suspicious soft-tissue lesions with greater than 98% accuracy and improves sensitivity for breast cancer detection by 8%; automated lesion characterization aligned with ACR BI-RADS, reducing radiologist interpretation time by 37%; automated reporting that generates comprehensive radiology reports; and expedited sonographer workflow that reduces manual documentation.<\/p>\n\n\n\n

Now with FDA clearance, the solution 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. 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. The clearance follows a multi-reader, multi-case study involving 16 U.S. board-certified radiologists at select imaging centers and hospitals, as well as validation in live clinical settings under regulated research protocols.<\/p>\n\n\n\n

DeepHealth’s breast imaging platform \u2014 a modular, interoperable AI-powered portfolio addressing real-world clinical needs across breast cancer screening and diagnostic pathways \u2014 includes applications for cancer detection in both mammography and ultrasound, density assessment, breast arterial calcification assessment, image-based breast cancer risk prediction, and mammography quality analytics, with viewing and reporting tools for improved operational efficiency.<\/p>\n\n\n\n

Dr. Jason McKellop, Medical Director of Women’s Imaging for RadNet California, said 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. McKellop noted that it is a highly complex, operator-dependent examination that can lead to significant variability in image acquisition, interpretation, and reporting. McKellop added that with DeepHealth’s breast ultrasound solution, greater standardization of workflows can be achieved, improving consistency while saving time for patients, sonographers, and radiologists, and that by streamlining the examination process, exam times can be reduced, efficiency enhanced, and ultimately patient outcomes improved.<\/p>\n\n\n\n

Niccol\u00f2 Stefani, M.D., Business and Product Leader for Clinical AI at DeepHealth, said no single imaging pathway addresses every woman’s needs, and with the addition of breast ultrasound, the company is 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. Stefani added that bringing together AI-powered capabilities across mammography and ultrasound helps clinicians respond to different imaging needs and deliver more comprehensive, personalized breast care.<\/p>\n","protected":false},"excerpt":{"rendered":"

DeepHealth has received FDA 510(k) clearance for its AI-powered breast ultrasound solution, which automates lesion detection, characterization, and reporting to improve standardization, accuracy, and efficiency in breast imaging.<\/p>\n","protected":false},"author":2,"featured_media":41098,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"colormag_page_layout":"default_layout","footnotes":""},"categories":[7,676,25],"tags":[626,687,655],"class_list":["post-41097","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-americas","category-imaging-diagnostics","category-products-technologies","tag-ai","tag-fda","tag-ultrasound"],"_links":{"self":[{"href":"https:\/\/g-medtech.com\/news\/wp-json\/wp\/v2\/posts\/41097","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/g-medtech.com\/news\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/g-medtech.com\/news\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/g-medtech.com\/news\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/g-medtech.com\/news\/wp-json\/wp\/v2\/comments?post=41097"}],"version-history":[{"count":3,"href":"https:\/\/g-medtech.com\/news\/wp-json\/wp\/v2\/posts\/41097\/revisions"}],"predecessor-version":[{"id":41101,"href":"https:\/\/g-medtech.com\/news\/wp-json\/wp\/v2\/posts\/41097\/revisions\/41101"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/g-medtech.com\/news\/wp-json\/wp\/v2\/media\/41098"}],"wp:attachment":[{"href":"https:\/\/g-medtech.com\/news\/wp-json\/wp\/v2\/media?parent=41097"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/g-medtech.com\/news\/wp-json\/wp\/v2\/categories?post=41097"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/g-medtech.com\/news\/wp-json\/wp\/v2\/tags?post=41097"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}