Second Opinion® BLE

Pearl Inc.'s Second Opinion® BLE is an automated radiological image processing software that employs machine learning to accurately identify and display bone level measurements in dental radiographs. This device serves as a crucial aid for dental professionals, enhancing the review of bitewing and periapical images by providing a validated, concurrent reading of interproximal bone levels, thereby improving diagnostic support.

Pearl Inc. has developed Second Opinion® BLE, a radiological automated image processing software designed to assist dental health professionals. Its primary purpose is to identify and display precise bone level measurements from bitewing and periapical radiographs, serving as a concurrent and second reader for permanent teeth in patients aged 12 years or older. The device leverages an Application Programming Interface (API), Machine Learning Modules, and a Client User Interface to facilitate its operation, thereby aiding clinicians in their review of bone levels without serving as the sole diagnostic tool.Following a comprehensive review, Second Opinion® BLE was deemed substantially equivalent to existing legally marketed devices. Both non-clinical and clinical studies rigorously evaluated its performance, confirming its software characteristics and demonstrating its safety and effectiveness for its intended application. The clinical trials specifically highlighted the system's strong precision and recall in measuring interproximal bone levels across both bitewing and periapical images, successfully meeting all pre-specified acceptance criteria and concluding that the device raises no new safety or effectiveness concerns, thus enabling its market clearance.

AI Regulatory Concerns

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• Q1. What specific machine learning algorithms or architectures are employed within Second Opinion® BLE, and how do they handle variability in image quality or patient anatomy?; Beyond precision and recall, what other performance metrics were evaluated in clinical studies, particularly regarding diagnostic accuracy or reduction in diagnostic discrepancies?; How does the system's performance compare in patients with existing bone loss conditions versus those with healthy bone levels, and are there any limitations in specific pathological cases?; What is the process for integrating Second Opinion® BLE with existing dental practice management software or imaging systems, and what are the API capabilities for data export or integration with AI-driven treatment planning?; Are there plans for future iterations of Second Opinion® BLE to expand its capabilities to detect other dental pathologies or to measure bone levels around implants?