AI nearly twice as good as biopsy at assessing rare cancer

Key Takeaways:

– AI could be twice as accurate as biopsies at assessing the aggressiveness of rare types of cancer, potentially saving lives.
– The study focused on retroperitoneal sarcoma, a rare form of soft tissue sarcoma.
– Diagnosis of retroperitoneal sarcoma is currently slow and difficult due to its rarity and complex surgery involved.
– The researchers used CT scans of patients to develop and train an AI algorithm.
– The AI algorithm accurately assessed tumor aggressiveness 82% of the time, compared to biopsies at 44% accuracy.
– The AI model was also able to predict the type of sarcoma in 84% of cases, compared to radiologists at 65% accuracy.
– The method could improve diagnosis speed, help clinicians manage the disease, and identify high-risk and low-risk patients for appropriate treatment.
– The researchers believe the AI model could be useful for other cancer types as well.
– The study demonstrates the potential of AI in healthcare to solve challenges and improve patient outcomes.

The Next Web:

AI could be nearly twice as accurate as biopsies at assessing the aggressiveness of some rare types of cancer, a new study suggests. According to researchers this could save the lives of thousands of patients.

A research team from the Royal Marsden NHS Foundation Trust and the Institute for Cancer Research (ICR) focused on retroperitoneal sarcoma — a form of soft tissue sarcoma that develops in the back of the abdomen.

“There is an urgent need to improve the diagnosis and treatment of patients with retroperitoneal sarcoma, who currently have poor outcomes,” said Dr Amani Arthur, first author of the study.

“The disease is very rare — clinicians may only see one or two cases in their career — which means diagnosis can be slow. This type of sarcoma is also difficult to treat as it can grow to large sizes and, due to the tumour’s location in the abdomen, involve complex surgery.”

To develop and train an AI algorithm, the researchers used CT scans of 170 patients suffering from the two most common types of retroperitoneal sarcoma: leiomyosarcoma and liposarcoma. Then, they tested the algorithm on a set of 89 patients across Europe and the US.

The technology accurately assessed the aggressiveness of the tumours 82% of the time, while biopsies were correct in only 44% of the cases. The AI model was also able to predict the type of 84% of the sarcomas tested, compared to radiologists who could diagnose 65% of the cases.