Pancreatic cancer is the deadliest form of cancer worldwide, mainly because the disease is often discovered late. Symptoms associated with these tumors are often nonspecific, so patients and doctors do not immediately suspect cancer. Moreover, these tumors are difficult to detect in the early stages on abdominal CT scans. Once the diagnosis is made, curative treatment is usually no longer possible. Only ten percent of patients survive beyond five years.
Reliable benchmark
AI researcher Henkjan Huisman and radiologist John Hermans explored ways to improve diagnostics using AI. They created a reliable benchmark: a confidential dataset of scans from nearly 400 patients from Western countries, assessed by a large group of international experts. They then invited developers worldwide to submit AI models capable of detecting pancreatic cancer. More than 250 models were submitted, ranked, and compared to experts.
The researchers tested these models on the confidential dataset and found that the best AI models detected pancreatic cancer more accurately than the average radiologist. For example, the AI system produced 38% fewer false positives compared to the group of radiologists. AI made the correct assessment in 92% of scans, versus 88% for the radiologists.
These results show that AI can at least support radiologists in their work and, in the long run, help reduce their workload. The developed AI still needs validation and is not yet available for patients in clinical practice. But these are important developments, emphasizes lead researcher Henkjan Huisman: "Precisely because we have developed a reliable benchmark, we know that the AI systems outperforming clinicians are truly effective."
Potential for earlier diagnosis
The best AI model may also offer opportunities for earlier diagnosis. Radiologist John Hermans explains: "In the study, we see initial indications that this AI model could really help achieve faster diagnosis and, therefore, potentially faster treatment. This is a small ray of hope, something we urgently need for this type of cancer."
However, Hermans stresses that it is still too early to use AI directly for early diagnostics: "We must avoid false positives for this disease, given the unnecessary strain on healthcare and, especially, the anxiety such suspicions cause for patients." Therefore, the researchers are now training better AI models on other, broader abdominal scans. For this, Hermans, Huisman, and colleagues received a grant from the Hanarth Fund (link: Funding for AI in detecting pancreatic cancer and pathology - Hanarth Fund supports two projects at Radboudumc - Radboudumc ).
About the publication
This research was published in Lancet Oncology: Artificial intelligence and radiologists in pancreatic cancer detection using standard of care CT (PANORAMA): an international, paired, non-inferiority, confirmatory, observational study. Natalia Alves, Megan Schuurmans, Dawid Rutkowski, Anindo Saha, Pierpaolo Vendittelli [...], Sebastiaan van Koeverden, Deniece M. Riviere, Wulphert Venderink [...], Geert Litjens, John Hermans, Henkjan Huisman, on behalf of the PANORAMA consortium. DOI: 10.5281/zenodo.10599559.
https://www.sciencedirect.com/science/article/pii/S1470204525005674?dgcid=coauthor
This study was funded by the European Union's Horizon Europe program.
