SBIR Phase II: An automated digital pathology lab for rapid on-site processing and imaging of tissue biopsies

Award ID: 2039417

The broader impact/ commercial potential of this Small Business Innovation Research (SBIR) Phase II project supports digital pathology. For the past century, pathology has been performed on microscopically thin sections of tissues that are stained and mounted onto glass microscope slides for analysis by a pathologist. This process is labor-intensive, costly, and the turnaround time is typically one week. For the vast majority of biopsy procedures, the diagnostic result is not obtained for days or even weeks after the procedure. Current bedside pathology techniques for rapid diagnosis and quality assurance of biopsy samples are slow, inaccurate, destructive to the tissue, and require the presence of multiple trained personnel, which prevent them from being widely used. Recent technological advances allow digitizing of the physical microscope slides and enable a fully digital pathology workflow. However, to date no system can take a fresh tissue sample through the entire long, laborious processing lifecycle prior to imaging. This project will develop a tissue processing and imaging platform to enable fast, automated processing from the fresh sample to the digital image within minutes of tissue removal. This will provide better care and patient outcomes and enables new opportunities to provide care in clinical settings with more limited pathology resources. This Small Business Innovation Research Phase II project continues development of an integrated technology platform that automates the entire process of tissue processing and digital imaging, obviating the need for trained personnel to be on-site. This project will support the development of new strategies to automate the acquisition of high-quality microscopic images from samples with widely varying surface topographies, while simultaneously improving both speed and image quality to meet clinical needs. The new technologies will support parallel, hands-free automated sample processing to increase throughput for analysis of multiple samples in a single session. The project will culminate in verification and clinical validation of the integrated system. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Henry Ahn