Aiforia Workshop

Enabling Patient Care and Discovery by Embracing AI and Digital Pathology Description

Please join Aiforia to hear how pathologists and investigators from the Mayo Clinic, MGH/Harvard Medical School, Rutgers University, and Memorial Sloan Kettering Cancer Center are enabling patient care, translational research, and discovery by embracing artificial intelligence (AI) and digital pathology. Each has used Aiforia’s cloud-based digital pathology platform to develop AI models with the goal of advancing research and improving patient care. Speakers will share lessons learned as they developed, published, and applied the AI models to their clinical and research data sets.

The individual presentations will be followed by a panel discussion with the speakers.

Speakers:

Dr. Nilay Bakoglu, Memorial Sloan Kettering Cancer Center

Artificial Intelligence (AI)-Based Automated Determination of Histomorphological Features and Mitosis Detection in Multiple Organ Systems

AI and other neural networks have made great progress in capturing the detection of morphological diagnoses. In this study, we present our experiences in invasive area detection of breast and colon cancer, tissue elements detection in colon specimens, and atypical and typical mitosis detection in several organs. 344 H&E WSIs and WMIs of 228 cases were trained, tested, and validated in the AI platform (Aiforia Inc). The final AI models showed F1 score of 94.49% for Invasive carcinoma of the breast, 97.40%, and 97.68% for atypical and typical mitosis layers, and 98.02% for vessels and lymph nodes respectively. We aim to use exported data of AI models for defining prognostically significant findings in WSIs to apply on Whole Block imaging including whole-mount samples.

Dr. Alexandra Zuraw, Digital Pathology Place
Dr. Valentina Perosa, MGH/Harvard Medical School
Dr. Donming Sun and Dr. Colin Ziabakhsh, Rutgers University

Dr. Tom Westerling-Bui, Aiforia, CCO, Americas

Modern AI Pathology Platform solutions for Translational Research and Diagnostic Support

Transforming diagnostic pathology by leveraging digital pathology and AI requires a concerted effort by many stakeholders. A significant impact of AI in diagnostic support requires a broad application strategy across the spectrum of AP (and visual cue-based CP). We will discuss challenges, opportunities, and solutions by highlighting recent work with our various partners. Adoption of the Aiforia Clinical platform and the Create platform as a translational research product can drive AI models to the clinic at scale. Case studies presented include a model for assessing eosinophilic esophagitis developed with Dr. Moreira (Mayo Clinic) and QuantCRC, by Dr. Pai (Mayo Clinic), that provides a powerful AI adjunct to routine pathologic reporting of colorectal cancer and a prognostic model that can improve prediction of recurrence-free survival

You will learn how Mayo Clinic is leveraging the Aiforia platform to engage with their entire Pathology community to drive AI translation into the clinic. We show 2 case studies, one where Dr. Roger Moreira and colleagues have developed a model for the assessment of Eosinophilic esophagitis and one where Dr. Rish Pai and colleagues have developed QuantCRC, an AI model that provides a powerful adjunct to routine pathologic reporting of CRC and underlies a prognostic model improving prediction of recurrence-free survival.

Refreshments will be provided.

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