Multicenter retrospective study finds combining radiologist assessment with DeepHealth’s Prostate AI could reduce biopsies by 18.9% while identifying men with clinically significant prostate cancer with 98.4% sensitivity
SOMERVILLE, Mass., Oct. 08, 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 new findings published in European Radiology supporting that AI applications within DeepHealth’s Prostate MR Solution1 could help clinicians decide more confidently which men may need a prostate biopsy, particularly when MRI findings are uncertain.2
Prostate cancer is the second most commonly diagnosed cancer among men worldwide, with an estimated 1.55 million new cases in 2024.3 MRI helps clinicians assess whether prostate cancer may be present, but some findings remain uncertain.4 A biopsy involves collecting small tissue samples to check for cancer and, if found, assess its grade. While biopsies are essential for diagnosis, they are invasive and can sometimes find no cancer or only low-grade disease that may not need treatment.4,5 Reducing unnecessary biopsies can spare some men related risks and help focus care on those most likely to benefit.
The international, multicenter study retrospectively analyzed prostate MRI exams performed between 2014 and 2025 in Germany, the Netherlands and the United States. The study included 787 men already undergoing clinical evaluation for suspected prostate cancer, of whom 380 had clinically significant disease. Scans were acquired on equipment from five different manufacturers, supporting the vendor-neutral performance of DeepHealth’s AI across diverse imaging environments. The study found that an approach combining radiologists’ MRI assessments with AI risk classification could have avoided 149 biopsies (18.9%) in this biopsied population, while still maintaining 98.4% sensitivity of identifying clinically significant prostate cancer.2
DeepHealth’s Prostate MR Solution integrates automated lesion detection and risk classification, intelligent gland segmentation with PSA density calculation and PI-RADS-compliant reporting into one seamless platform. The solution integrates with more than 11 fusion biopsy systems to eliminate manual data transfer and support radiologists at every critical decision point.
“These findings show how AI applications within our Prostate MR Solution can support clinicians at one of the most consequential decision points in prostate care,” said Niccolò Stefani, M.D., Business and Product Leader, Clinical AI, DeepHealth. “Our aim is to help care teams make more informed decisions about the next step for each patient. As part of our broader clinical AI portfolio, our Prostate MR Solution is designed to bring additional insight into the clinical workflow, with clinical judgment at the center.”
“When an MRI finding is uncertain, deciding whether to recommend a biopsy can be difficult,” said Francesco Giganti, M.D., Professor of Radiology at University College London and senior author of the study. “Our findings suggest that AI could provide another piece of evidence to help clinicians make that decision. The opportunity is to use DeepHealth’s Prostate MR Solution to better identify which men may benefit from a biopsy, with the final medical decision remaining with the clinical team.”
The Prostate MR Solution is part of DeepHealth’s broader Radiology AI Suite, which brings together clinical AI, intelligent workflow and performance analytics capabilities across breast, neurological, thoracic, musculoskeletal, thyroid, prostate, abdominal and pelvic imaging. By connecting these capabilities on a single platform, DeepHealth can help imaging organizations bring AI into everyday care and support clinicians across the imaging workflow, strengthening diagnostic confidence and operational efficiency.
Read the study in European Radiology.
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 empowering 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 and future product offerings and capabilities. 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
- DeepHealth Prostate MRI Solution is CE Mark Class IIb (EU MDR). FDA 510(k) cleared (US). DeepHealth Prostate MR Solution comprises multiple applications including DeepHealth Prostate AI and DeepHealth Viewer. DeepHealth Viewer is manufactured by eRAD, Inc. and distributed by DeepHealth, Inc.
- Guenzel K, Poirot MG, van Loon A, et al. Multicentre evaluation of artificial intelligence risk classification for detection of clinically significant prostate cancer on biparametric MRI. European Radiology. 2026.
- International Agency for Research on Cancer. Global Cancer Observatory: Prostate cancer fact sheet. GLOBOCAN 2024.
- European Association of Urology. EAU Guidelines on Prostate Cancer. 2026. Chapter 5: Diagnostic Evaluation. Available at: https://uroweb.org/guidelines/prostate-cancer/chapter/diagnostic-evaluation. Accessed September 29, 2026.
- American Cancer Society. Tests for Prostate Cancer. Available at: https://www.cancer.org/cancer/types/prostate-cancer/detection-diagnosis-staging/how-diagnosed.html. Accessed September 29, 2026.
