Collaborative research by Deep Bio and Dr. Lotan research team at Johns Hopkins Medicine was revealed at AUA 2023
SEOUL, SOUTH KOREA (PRWEB) MAY 11, 2023 - Deep Bio, a pioneer in medical AI for digital pathology and cancer diagnostics support software, announced that Dr. Lotan from Johns Hopkins Medicine presented their collaborative research which utilized the deep learning-based algorithm for prostate cancer diagnosis support at a podium session in the American Urological Association (AUA) annual meeting 2023.
This joint research compared human pathologists and an AI algorithm in grading prostate biopsy specimens to predict biochemical recurrence after radical prostatectomy. Gleason score is one of the key elements to grade prostate cancer and can lead to different clinical decisions. For example, even though 3+4 and 4+3 Gleason scores are identical Gleason score 7s, each has a different prognosis. Gleason 3+4 requires more than active surveillance but tends to fare much better in prognosis than Gleason 4+3.
The study reassessed the diagnoses of 284 patients initially diagnosed as Gleason grade group 2 (Gleason score 3+4) and underwent radical prostatectomy at Johns Hopkins Medicine from 2000 to 2014. This cohort is one of the most challenging cohorts to diagnose since many cases diagnosed 3+4 before could be downgraded to 3+3 or upgraded to 4+3. Johns Hopkins Medicine also has up to 14 years of follow-up data on the patients (an average of 4 years of follow-up) and approximately 16% of the patients went through recurrence of prostate cancer. As the ISUP guidelines have changed in those periods, all of these biopsies were re-graded by two expert genitourinary pathologists and a third expert genitourinary pathologist served as a tiebreak for discrepant reads. To compare human pathologists and AI algorithms, Deep Bio’s AI-based prostate cancer diagnosis support software DeepDx® Prostate analyzed all the biopsies to provide Gleason grades as well.
The results showed poor agreements between the two pathologists, generating a kappa of 0.17 while grading between the consensus pathology read and the AI algorithm generated a slightly higher kappa of 0.33. Importantly, however, the study suggested that the algorithm can act as a tool that stratifies patients for subsequent biochemical recurrence after radical prostatectomy. This risk stratification has the potential to prevent a lot of unnecessary surgeries and aid in choosing between treatment modalities.
“It is a meaningful milestone for Deep Bio to conduct a joint research with Johns Hopkins Medicine, one of the top global universities, and the findings are remarkable for prostate cancer diagnosis using AI,” said Sun-Woo Kim, CEO of Deep Bio. “As precise diagnosis and personalization have become the crucial factors in deciding medical decisions for medical professionals, we will focus on bringing innovative deep learning technologies that can unlock new insights in cancer diagnosis and treatment” added he.
Deep Bio continues to focus on not only AI diagnostics but also R&D and presenting the results in various international conferences and events. The company also continues to build its presence in the global market through collaboration with overseas digital pathology solution providers in the US, Europe, and India.
About Deep Bio
Deep Bio Inc. is an AI healthcare company with in-house expertise in deep learning and cancer pathology. Our vision is to radically improve efficiency and accuracy of pathologic cancer diagnosis and prognosis, by equipping pathologists with deep learning-based IVD SaMDs (In Vitro Diagnostics Software as a Medical Device), for optimal cancer treatment decisions. To learn more, visit http://www.deepbio.co.kr. DeepDx® Prostate is a clinically-validated AI for prostate core needle biopsy tissue image analysis. Whole-slide images (WSIs) of H&E-stained biopsy tissue specimens are analyzed for prostate cancer, Gleason scores and grade groups. Extensively tested at 4 US CLIA labs (700k+ cores between 2019 and 2021), DeepDx® Prostate can alleviate the shortage of pathologists and the resultant increase in workload, while reducing diagnostic subjectivity and variability. To learn more, visit http://www.deepbio.co.kr