IBIIS-AIMI Seminar: Imaging Analytics for Neuro-Oncology: Towards Computational Diagnostics - Spyridon Bakas, PhD

Abstract: 
Central nervous system (CNS) tumors come with vastly heterogeneous histologic, molecular, and radiographic landscapes, rendering their precise characterization challenging. The rapidly growing fields of biophysical modeling and radiomics have shown promise in better characterizing the molecular, spatial, and temporal heterogeneity of tumors. Integrative analysis of CNS tumors, including clinically acquired multi-parametric magnetic resonance imaging (mpMRI), assists in identifying macroscopic quantifiable tumor patterns of invasion and proliferation, potentially leading to improved (a) detection/segmentation of tumor subregions and (b) computer-aided diagnostic/prognostic/predictive modeling. This talk will touch upon example studies on this space, as well as an overview of the largest to-date real-world federated learning study to detect brain tumor boundaries.

About: 
Spyridon (Spyros) Bakas (Ph.D.) is a Tenure Track Assistant Professor at the Center for Biomedical Image Computing and Analytics (CBICA), with joint appointments between the Dept. of Pathology & Laboratory Medicine and the Dept. of Radiology, at the Perelman School of Medicine of the University of Pennsylvania (UPenn). His research interests focus on the development and application of advanced computational algorithms in oncological imaging, with the intention of improving the assessment, quantification, and diagnosis of cancer in the current clinical practice. He has published extensively on MR, contrast-enhanced ultrasound (CEUS), and digitized histopathology, imaging data. He is involved in radio-patho-genomic research, where correlations between quantitative imaging features and genomic information lead to highly accurate imaging biomarkers enabling treatment selection models customized on an individual patient basis. He is also involved in federated machine learning approaches towards facilitating expedited multi-institutional studies, while patient data are always retained within the acquiring institution. Dr. Bakas has received grant funding from the National Cancer Institute of the National Institutes of Health, the National Science Foundation, the Abramson Cancer Center, and the Translational Biomedical Imaging Center of the Institute for Translational Medicine and Therapeutics of UPenn. He has co-authored >70 peer-reviewed manuscripts and >60 medical conference abstracts. He is a board member of the MICCAI Society's Special Interest Group on Biomedical Image Analysis Challenges (SIG-BIAC) (2020-present), on the MICCAI Organizing Committee (2018, 2020-2021), and has served as the organizer and chair of numerous tutorials, workshops, and computational challenges at both technical and clinical scientific meetings, including the MICCAI, ISBI, RSNA, and SNO meetings.