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AI shows pancreatic cancer promise



Pancreatic cancer

An artificial intelligence (AI) tool developed by researchers in Taiwan is highly effective at detecting pancreatic cancer on CT, according to a new study.

Pancreatic cancer is the 10th most common cancer in the UK, with around 10,500 new cases diagnosed every day.

CT is the most commonly-used method for detecting tumours in the pancreas but misses around the 40 per cent of tumours under two centimetres in size.

There is an urgent need to find an effective tool to help radiologists detect tumours before it’s too late.

Researchers in Taiwan have been studying a computer-aided detection (CAD) tool that uses deep learning to detect these tumours.

Previous research demonstrated that the tool could accurately distinguish pancreatic cancer from noncancerous pancreas.

However, that study relied on radiologists manually identifying the pancreas using labour-intensive segmentation imaging.

In the new study, the AI tool successfully identified the pancreas automatically without the need for manual observation.

An internal test set analysed images of 546 patients with pancreatic cancer and 733 control participants.

The tool achieved 90 per cent sensitivity and 96 per cent specificity in the internal test set.

The researchers then validated their findings with a set of 1,473 individual CT exams from institutions throughout Taiwan.

The tool achieved 90 per cent sensitivity and 93 per cent specificity in distinguishing pancreatic cancer from the controls within that set.

Meanwhile, sensitivity for detecting pancreatic cancers less than 2 centimetres was 75 per cent.

Study senior author Weichung Wang, Ph.D., professor at National Taiwan University and director of the university’s MeDA Lab, said:

“The performance of the deep learning tool seemed on par with that of radiologists.

“Specifically, in this study, the sensitivity of the deep learning computer-aided detection tool for pancreatic cancer was comparable with that of radiologists in a tertiary referral centre regardless of tumour size and stage.”

Co-senior author, Wei-Chi Liao, M.D., Ph.D., from National Taiwan University and National Taiwan University Hospital, added:

“The CAD tool may serve as a supplement for radiologists to enhance the detection of pancreatic cancer.”

The researchers plan to conduct further studies where they hope to analyse the tool’s performance on more diverse populations.

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