SYDE Gard Student won the Best Student Paper Award at the 2020 Optical Society of America

Saturday, June 13, 2020

PhotoMedicine Labs student Saad Abbasi, supervised by Professor Parsin Haji Reza, won the Best Student Paper Award at the 2020 Optical Society of America (OSA) Biophotonics Congress for the paper titled “All-optical Reflection-mode Microscopic Histology of Unstained Human Tissues”. Held between April 20th and 23rd, OSA Biophotonics Conference gathers students and researchers working on all aspects of biomedical optics and represents the year’s best results.  Employing Photoacoustic Remote Sensing (PARS), this paper describes a method that can visualize microscopic tissue structure, similar to histopathology, without the requirement of contact or any staining prior to examination. Importantly, this method operates in reflection-mode which enables the assessment of thick unprocessed tissue, circumventing the laborious and time-consuming histopathological workflow.

Paper Summary:

Positive surgical margins are associated with an increased risk of recurrence in multiple types of cancer and routinely require patients to undergo follow-up surgery or adjuvant treatment. Some cancers, such as non-small cell lung carcinoma, are only treatable via surgery in early stages of the disease and the survivability rates drop considerably in cases where clear surgical margins are not achieved. The gold standard for margin assessment remains post-operative histopathological analysis. However, the preparation of histology slides is a laborious process which potentially take more than two weeks before a diagnosis can be presented, resulting in poorer patient outcomes and increasing the stress on the healthcare system. Although Intraoperative techniques such as frozen sectioning have improved patient outcomes, the quality of the slides is poorer than post-operative histopathological analysis which results in a high variability in diagnosis. Clearly, there is a need for a real-time intraoperative feedback tool that is able to visualize surgical margins directly on the patient’s body (in-situ)