BIH Lecture | Jens Rittscher "Advancing Cell-Based Medicine Through Computational Tissue Imaging"

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The online talk is part of the Lecture Series "Frontiers in Translational Medicine - Scientific and Structural Challenges" on key questions of translation in medicine.

BIH Lecture

“Advancing Cell-Based Medicine Through Computational Tissue Imaging”

The convergence of advances in imaging technologies and AI at the microscopic level will transform how we diagnose and treat disease. Cellular pathology plays a critical role in translating these advancements into the clinical setting. This talk will highlight research efforts that were enabled through cross disciplinary interactions between clinical scientists, physicists, biologists, and engineers to address unmet needs.

Enabled by recent advances in expansion microscopy we demonstrated the possibility of imaging mitochondria at the ultrastructure level at scale. Using deep learning we developed a robust methodology for the quantitative analysis of these complex images and illustrate how such an analysis can provide biological insights. In Berlin, this work will be extended through a collaboration with Dr.Philipp Mergenthaler to investigate mitochondrial diseases.

In the context of myeloproliferative neoplasms (MPN), a group of rare disorders of the bone marrow, we demonstrate that quantitative image analysis can improve the accuracy of diagnosis. The terminology used with the current classification scheme for MPN remains subjective, qualitative, and variably reproducible. In contrast to novel technologies for the detection of genetic aberrations in blood cancers, haematopathologists still summarise highly complicated tissue features as text-based reports. Our results demonstrate that a more quantitative approach allows defining disease subtypes and quantifying response to disease-modifying treatments. The talk will illustrate how spatial transcriptomics provides new avenues for identifying morphological features.

Finally, our recent efforts to advance pathology through 3D imaging will be highlighted. Overcoming the limitations of analysing thin tissue sections could accelerate the discovery of novel histology-based biomarkers and improve our ability for early detection. The talk will illustrate how advances in imaging, AI, and sample processing will be combined to develop a provide a tissue-based platform for research and discovery.

About the Speaker

Jens Rittscher is Professor of Engineering Science at the University of Oxford with his appointment held jointly between the Institute of Biomedical Engineering and the Nuffield Department of Medicine. He is a group leader at the Big Data Institute and is affiliated with the Ludwig Institute of Cancer Research and the Wellcome Centre as an adjunct member. Previously, he was a senior research scientist and manager at GE Global Research (Niskyauna, NY, USA).

His research interests lie in enabling biomedical imaging through the development of new algorithms and novel computational platforms, with a current focus to improve mechanistic understanding of cancer and patient care through quantitative analysis of image data. He is a co-director of the Oxford EPSRC Centre for Doctoral Training in Health Data Science.

Presently, he serves on the executive committee of the Medical Image Analysis and the editorial board of Biological Imaging. In 2019 he co-founded the Oxford University Spinout company Ground Truth Labs. He holds a Stiftung Charité Visiting Fellowship and is a member of the BIH Scientific Advisory Board.