We are proud to announce that PANCAIM is organising the first ever large-scale study comparing radiologists and AI for pancreatic cancer detection: PANORAMA – Pancreatic Cancer Diagnosis – Radiologists Meet AI!
In the context of the PANCAIM project, Radboud UMC is organising the first ever large-scale, international, multi-reader, multi-case study assessing and comparing radiologists and AI for pancreatic cancer diagnosis. With over 1500 patients involved, this cutting-edge, multi-center study is poised to redefine early pancreatic cancer detection!
PANORAMA consists of two sub-studies:
- AI study: An annotated data consisting of retrospective, multicenter, cancer-enriched routine upper-abdominal CECT scans which represents clinical reality by including diagnostic and prediagnostic PDAC scans as well as non-PDAC patients. AI development teams use this dataset to develop AI models, and submit their trained algorithms (in Docker containers) for evaluation. All algorithms will be ranked, based on their performance on a hidden testing cohort of 400 unseen scans.
- Reader study: The reader study will include around 400 cases from multiple institutions that will be read by a panel of 40+ international readers with varying levels of expertise.
In the end, PANORAMA aims to benchmark state-of-the-art AI algorithms developed in the grand challenge, against abdominal radiologists participating in the reader study to evaluate the clinical viability of modern pancreas-AI solutions at PDAC detection and diagnosis in CECT.
If you are an abdominal radiologist handling contrast CT scans in your routine clinical practice, we would like to invite you to participate in the study! PANORAMA offers both international impact – we’re hosting the first-ever international study where radiologists and AI algorithms from across the globe will be assessed in a standardized, bias-free environment – and multi-disciplinary excellence: PANORAMA’s design is forged in collaboration with a scientific advisory board comprising 13 international experts in radiology, histopathology, surgery, and AI and even patient representatives).
To learn more, check out the dedicated website at https://panorama.grand-challenge.org/reader-study/
If you are interested to join the PANORAMA reader study and be part of this journey to push the boundaries of early pancreatic cancer detection, please sign up using this form: https://docs.google.com/forms/d/e/1FAIpQLSfO246IT-kUQ4eLIDYD1AmuLT3NAx8TohzyiZfHK1rMOlrl2Q/viewform
Organising Team: Natália Alves, Megan Schuurmans, Henkjan Huisman, John J. Hermans