Leveraging Label-Free Digital Imaging to Enable Rapid On-Site Evaluation (ROSE) During Thyroid Biopsy Procedures

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Project Summary/Abstract Pathware is developing Bioptic™, an imaging platform to analyze biopsy samples at the point-of-care. The system will rapidly digitize unstained biopsy samples and utilize computer-aided detection/diagnostics to enable quick and efficient evaluations by pathologists. Typical barriers to point-of-care diagnostics are overcome by combining novel computational microscopy with AI (Artificial Intelligence) algorithms to direct on-site or remote pathologists to regions of clinical interest. This proposed research's broad, long-term objective is to enable real- time diagnostics of pathology samples at the point-of-care. Thyroid nodules have a high incidence rate, and assessment via fine-needle aspiration (FNA) biopsy is often an integral step in the diagnostic pipeline. The biopsy samples are frequently inadequate for diagnosis resulting in repeat biopsies or unnecessary surgical resections. Rapid On-Site Evaluation (ROSE) for sample adequacy is ideal for patient care, because it mitigates the risk of inadequate samples by verifying diagnostic quality at the point-of-care. Despite the high incidence of inadequate biopsies, ROSE is performed in less than 25% of thyroid biopsy procedures due to financial and operational barriers, including pathologist availability. The current alternatives to ROSE (telepathology, robotic microscopy, and live-streaming microscopy) are plagued by barriers to adoption due to the requirement of staining samples, technical challenges, and regulatory limitations. AI- assisted ROSE has the potential to overcome these barriers and provide a superior standard-of-care. The immediate goals of the proposed project are to 1) demonstrate non-destructive imaging of unstained thyroid cytology smears with a novel microscopy modality and 2) train AI algorithms on the acquired images for future development of computer-aided detection algorithms for ROSE adequacy assessments.