Post by Dr. René Hosch

🚨 New publication from SHIP — and this one is truly special! 🚨 I’m very happy, and honestly proud of our team, to finally share the news that our latest paper ("Leveraging Sarcopenia index by automated CT body composition analysis for pan cancer prognostic stratification ") has been published in #NPJDigitalMedicine. It's a project that's been with us for quite some time and represents a true team effort. Publication 🧾: https://lnkd.in/e2hp4SbC As many of you will know, our group comes from radiology (Radiologie Universitätsmedizin Essen), and segmentation models and body composition analysis have always formed a key part of our research. We believe in using AI to extract hidden, clinically relevant features from routine imaging and turn everyday data into valuable insights for patient care. In this study, we analysed baseline CT scans of oncology patients and derived a volumetric, image-based sarcopenia index (SI), which is the ratio of muscle to bone volume. Our results demonstrate that this image-based marker significantly correlates with the overall survival and has a prognostic value, highlighting the potential of AI-based imaging biomarkers in precision oncology. This project embodies our long-term vision of using AI models to capture the full informational potential of medical imaging and make it clinically actionable. 🌟 Special thanks: 1) Katarzyna Borys: Huge congratulations on your persistence and scientific rigour! 2) Felix Nensa: Thank you for your guidance and support throughout. 3) Prof. Martin Schuler: for your invaluable oncological insights and knowledge throughout the whole process. 4) Our collaborators in Brussels: Riccardo De Angelis, Nicolas Coquelet, Kevin B., and Maria Antonietta Bali, for providing the external validation cohort and for their fantastic collaboration. 5) And, of course, thank you to all the co-authors and contributors for their expertise and dedication. 🤝 If you are interested in our BCA algorithm or datasets, then please take a look at the following: BOA: https://lnkd.in/eiqJ5HSw SAROS: https://lnkd.in/ePHMVSJ3 Felix Nensa Prof. Dr. Johannes Haubold Anton S. Quinsten, M.Sc. Julia van Holt Michael Forsting Lale Umutlu Jens Kleesiek IKIM - Institut für Künstliche Intelligenz in der Medizin Universitätsmedizin Essen Dr Anke Diehl Nicolas Coquelet Sara Schramm, Prof. Dr. med. Judith Kohnke Giulia Baldini Lennard Kroll Viktor Grünwald Arzu Oezcelik Eugen Malamutmann Prof. Dr. med. Benedikt Schaarschmidt Ken Herrmann Christoph M. Friedrich Boris Hadaschik Julius Keyl Kamyar Arzideh Eva Hartmann Dirk Schadendorf Rainer Kimmig Sebastian Bauer Prof. Dr. Jens Siveke Justin Woolley #AIinMedicine #Radiology #Oncology #BodyComposition #Sarcopenia #ImagingBiomarkers #PrecisionMedicine #MedicalAI #Research #IKIM #SHIP