Canon Medical Systems’ Olea Medical to Expand U.S. Access to eyonis® LCS for AI-Powered Lung Cancer Screening
Median Technologies’ agreement will expand availability of the FDA-cleared detection and diagnostic-assessment technology to U.S. radiology providers and healthcare systems
SAN FRANCISCO, CA and SOPHIA ANTIPOLIS, France, Aug. 03, 2026 (GLOBE NEWSWIRE) -- Eyonis Inc., a Median Technologies company focused on applying artificial intelligence to the early detection and diagnosis of cancer, today announced that Median Technologies has entered into a strategic commercial agreement with Olea Medical, a Canon Medical Systems company, that will expand U.S. access to eyonis® LCS Lung Cancer Screening. The broader agreement also covers Europe and other markets that may be mutually agreed upon over time.
Canon Medical Systems is an established CT technology provider to U.S. hospitals and imaging centers, giving Olea Medical access to radiology organizations that are building and expanding lung cancer screening programs nationwide. Under the agreement, Olea Medical will support the commercialization of eyonis LCS—the first FDA-cleared AI-powered Software as a Medical Device (SaMD) to both detect pulmonary nodules and assess their likelihood of malignancy on low-dose CT—through its relationships with radiology providers and healthcare systems.
The first SaMD to combine detection with diagnosis
Lung cancer screening requires radiologists not only to detect pulmonary nodules, but also to determine which findings are most likely to represent cancer and require timely intervention. Although most screenings do not reveal lung cancer, indeterminate findings can lead to repeated imaging, prolonged surveillance, patient anxiety, and difficult decisions about whether to recommend an invasive procedure.
eyonis® LCS addresses both stages of that process, supporting the detection of suspicious pulmonary nodules and the assessment of their likelihood of malignancy from low-dose CT examinations. By bringing detection and diagnosis into a single lung cancer screening workflow for the first time, the technology addresses one of the most significant challenges in lung cancer care—helping clinicians identify cancer earlier with greater diagnostic confidence.
In the multireader, multicase clinical study[i] submitted as part of the FDA clearance process, radiologists using eyonis LCS achieved:
- sensitivity of 93.3%, compared with 80.3% without the technology
- specificity of 92.4%, compared with 76.4% without it
These gains corresponded to:
- 66% fewer false-negative interpretations
- 68% fewer false-positive interpretations
Overall, 75% of radiologists improved diagnostic performance when assisted by eyonis® LCS compared with manual reading alone. The study met all primary clinical and regulatory endpoints.
“Lung cancer screening can only save lives when radiologists and care teams have the capacity and confidence to act on what they find,” said Oran Muduroglu, President of Eyonis. “By combining detection and diagnostic assessment in one AI-powered SaMD, eyonis LCS is designed to help radiologists identify patients who need timely intervention while reducing the burden created by indeterminate findings. Canon Medical Systems and Olea Medical give us an important new channel for bringing that capability directly to healthcare providers.”
Supporting radiologists beyond nodule detection
Today’s standard approach to diagnosis calls for radiologists to balance the risk of immediate invasive biopsy against the possibility that disease could progress if patients with suspicious nodules wait several months to be re-screened. Unfortunately, the common “watchful waiting” period of three to six months means cancer may progress to a less treatable stage. Patients diagnosed with lung cancer at an early stage have a 20-year survival rate of 80 percent. The average five-year survival rate for all lung cancer patients is 18.6 percent because only 16 percent of lung cancers are diagnosed at an early stage. Distinguishing potentially malignant findings from benign nodules as early as possible is therefore central to effective screening.
eyonis LCS augments radiologist expertise with AI-powered detection and diagnostic insight, helping clinicians interpret screening examinations with greater confidence and consistency. Specifically designed and approved for the low-dose CT lung cancer screening pathway, eyonis LCS goes beyond detection-only solutions by providing additional diagnostic information about suspicious findings. eyonis LCS is also designed to integrate with existing imaging infrastructure, including hospital PACS environments, so results can be incorporated into established radiology workflows.
About Eyonis
Eyonis, a Median Technologies company, markets a suite of AI-powered Software as a Medical Device (SaMD) designed to improve the early detection and diagnosis of cancer. Its flagship product, eyonis® LCS, analyzes low-dose CT examinations to support both the detection of suspicious lung nodules and the assessment of their likelihood of malignancy within the lung cancer screening workflow. eyonis LCS received FDA clearance in the United States in February 2026 and CE marking in Europe in July 2026. To learn more, visit https://eyonis.ai.
About Median Technologies
Median Technologies provides AI-powered medical imaging solutions for cancer diagnosis, treatment and drug development. The company operates through two businesses: Eyonis, which develops AI-powered Software as a Medical Device for cancer detection and diagnosis, and iCRO, which provides imaging services for oncology clinical trials. Headquartered in France with operations in the United States and China, Median Technologies is listed on Euronext Growth Paris under the ticker ALMDT. To learn more, visit https://mediantechnologies.com/
About Olea Medical
Olea Medical, a Canon Group Company, is a medical imaging software company specializing in advanced, clinically validated solutions for radiology. Its portfolio includes quantitative image analysis, post-processing, and clinical decision support tools designed to assist healthcare professionals in diagnostic interpretation and workflow optimization across a broad range of clinical applications.
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[i] (Jonas DE, et al. JAMA. 9 mars 2021 ; 325(10):971-987)
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Todd Stein eyonis 5104170612 todd@toddsteincommunications.com
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