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Invenio Imaging announces first patients enrolled in US pivotal study of AI-based image analysis module for lung cancer

Press releases may be edited for formatting or style | August 13, 2024 Rad Oncology
SANTA CLARA, Calif., Aug. 9, 2024 /PRNewswire/ -- Invenio Imaging, a leader in intraoperative fresh tissue imaging and artificial intelligence (AI), announced today the enrollment of the first patients in a US pivotal study of its AI-based image analysis module for lung cancer. The ON-SITE study, a multicenter study in bronchoscopy combining Stimulated Raman Histology with Artificial Intelligence for rapid lung cancer detection, is in collaboration with Johnson & Johnson Enterprise Innovation Inc. and will be conducted at multiple centers including The University of Texas MD Anderson Cancer Center, Corewell Health, Memorial Sloan Kettering Cancer Center, and University of North Carolina at Chapel Hill.

Lung cancer is the leading cause of cancer-related deaths in the United States. This has led to the institution of large-scale screening programs for high-risk patients, which results in an estimated 3.1 million new primary lung nodules identified each year. Despite major sector investment in minimally-invasive biopsy technology, obtaining adequate tissue for biomarker and treatment determination remains a challenge. For this reason, bronchoscopy guidelines recommend rapid-on-site tissue evaluation (ROSE) for lung biopsies.

Invenio aims to develop the first FDA-cleared AI to identify cell/tissue morphology suspicious for cancer in lung biopsies

"ROSE requires that a cytologist or highly trained cytotechnician be physically present in the procedure room, and thus it is not available at many centers performing lung biopsy due to resource limitations," said Jason Akulian, MD, Director of Interventional Pulmonlogy at UNC, "we are excited by the NIO's potential to extend the benefits of ROSE to the proceduralist when the service is not available."

The NIO® Laser Imaging System allows rapid imaging of fresh tissue biopsies in the treatment room. Sample preparation does not require staining or sectioning and can be performed by the existing OR-staff. NIO® Slides are also designed to allow retrieval of the sample for downstream analysis. NIO® images are natively digital and can be shared in near real-time. The ON-SITE study aims to develop and validate an AI-based image analysis module for the NIO® Laser Imaging System that is intended to assist physicians in the detection of cancer in bronchoscopic lung biopsies in situations where ROSE is not available for the sample type.

"Artificial intelligence aiding healthcare may seem utopic, but the future is coming. While still investigational, the promise of fast, in-room, accurate identification of tissue that is suspicious for cancer has the potential to ultimately lead to improved outcomes, a beneficial cost/benefit profile, and personalized treatments," said Gustavo Cumbo-Nacheli, MD, pulmonologist at Corewell Health and one of the site PIs for the ON-SITE study.

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