AI-Based Image Analysis Module to Aid Cancer Detection in Bronchoscopic Lung Biopsies

Bronchoscopy guidelines generally advocate for the use of rapid on-site evaluation (ROSE) during lung biopsies to determine lung cancer, but this requires a cytologist or a highly trained cytotechnician to be physically present, limiting its availability at many centers due to resource constraints. Now, a novel system promising fast, in-room, accurate identification of tissue that is suspicious for cancer can fill in the gaps by extending the benefits of ROSE to the proceduralist when the service is not available due to staff limitations.

Invenio Imaging (Santa Clara, CA, USA) has completed enrolment for a pivotal trial in collaboration with Johnson & Johnson (New Brunswick, NJ, USA) aimed at gaining FDA approval for its AI-powered software that identifies lung cancer. The trial, named the ON-SITE study, is being conducted at two university centers in Texas and North Carolina. It seeks to develop and validate an AI-based image analysis module for Invenio’s NIO Laser Imaging System, which enhances lung imaging by accelerating the creation and analysis of digital images. The NIO system enables more operational flexibility by allowing hospital staff to quickly image fresh tissue biopsies in settings where such capabilities were previously unavailable. The system simplifies sample preparation, as it requires no staining or sectioning and can be managed by existing operating room personnel.

“AI aiding healthcare may seem utopic, but the future is coming,” said Gustavo Cumbo-Nacheli, principal investigator for the ON-SITE study. “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 to benefit profile, and personalized treatments.”

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