Invenio Imaging's AI-Based Image Analysis Module Enrolls First Patients in Pivotal Lung Cancer Study
核心洞察
Invenio Imaging (搜索) initiated a pivotal US study (ON-SITE) to evaluate its AI-based image analysis module for rapid lung cancer (搜索) detection during bronchoscopy.
The study combines Stimulated Raman Histology with AI, aiming to assist physicians in detecting cancer in lung biopsies where rapid-on-site tissue evaluation (ROSE) is unavailable.
The ON-SITE study is being conducted at multiple centers, including The University of Texas MD Anderson Cancer Center and Memorial Sloan Kettering Cancer Center.
Invenio Imaging (搜索) has announced the enrollment of the first patients in its US pivotal study, ON-SITE, which assesses an AI-based image analysis module for lung cancer (搜索) detection. This multicenter study, conducted in collaboration with Johnson & Johnson Enterprise Innovation Inc. (搜索), integrates Stimulated Raman Histology with Artificial Intelligence to expedite lung cancer detection during bronchoscopy.
The ON-SITE study is being carried out at prominent centers such as The University of Texas MD Anderson Cancer Center, Corewell Health, Memorial Sloan Kettering Cancer Center, and the University of North Carolina at Chapel Hill. The primary goal is to validate an AI-based image analysis module for the NIO Laser Imaging System, assisting physicians in identifying cancer in bronchoscopic lung biopsies, particularly when rapid-on-site tissue evaluation (ROSE) is not accessible.
Addressing Lung Cancer Diagnosis Challenges
Lung cancer (搜索) remains the leading cause of cancer-related deaths in the United States, prompting large-scale screening programs that identify approximately 3.1 million new primary lung nodules annually. Despite investments in minimally invasive biopsy technology, obtaining adequate tissue for biomarker and treatment determination remains a significant challenge. Current bronchoscopy guidelines recommend ROSE for lung biopsies to address this issue.
According to Dr. Jason Akulian, Director of Interventional Pulmonology at UNC, "ROSE requires a cytologist or highly trained cytotechnician to be physically present, making it unavailable at many centers due to resource limitations. The NIO's potential to extend the benefits of ROSE to the proceduralist is exciting."
NIO Laser Imaging System and AI Integration
The NIO Laser Imaging System enables rapid imaging of fresh tissue biopsies directly in the treatment room, eliminating the need for staining or sectioning. The system is designed to allow retrieval of the sample for downstream analysis. The digital NIO images can be shared in near real-time. The ON-SITE study focuses on developing and validating an AI module to assist physicians in detecting cancer in bronchoscopic lung biopsies when ROSE is unavailable.
Dr. Gustavo Cumbo-Nacheli, a pulmonologist at Corewell Health and a site PI for the ON-SITE study, stated, "Artificial intelligence aiding healthcare may seem utopic, but the future is coming... 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."
Invenio Imaging's Perspective
"Enrolling the first patient in the ON-SITE study is an important milestone for Invenio, as we aim to develop the first FDA-cleared AI to identify cell/tissue morphology suspicious for cancer in lung biopsies," said Dr. Jay Trautman, co-founder and CEO of Invenio Imaging (搜索). "Near real-time image analysis on the NIO Laser Imaging System completes the end-to-end solution for streamlined intraoperative histology."