Covering Disruptive Technology Powering Business in The Digital Age

Alibaba Group’s research institute DAMO Academy said it has come up with an early screening method powered by artificial intelligence (AI) technologies to detect pancreatic cancer with high accuracy, a significant breakthrough that made large-scale pancreatic cancer screening possible.

Its deep learning-based algorithm can detect pancreatic lesions hard to observe by human eyes in non-contrast CT scans, making it possible to enhance imaging-based screening for pancreatic cancer.

According to a recent journal from Nature Medicine, the model, trained on more than 3,200 image sets, achieved high performance on key diagnostic indicators. It achieved a specificity of 99.9%, suggesting that there is only one false-positive in every 1,000 tests and a sensitivity of 92.9%, outperforming human radiologists by 34.1% in sensitivity and 6.3% in specificity.

In collaboration with over ten world-leading medical institutions, researchers from DAMO Academy used the AI-based screening method to screen over 20,000 patients and detected 31 cases of pathological changes that were earlier missed by doctors. The model has been used over 500,000 times in hospital and medical checkup settings in China.

“Early detection of pancreatic cancer is hard to realise in conventional screening, which results in late detection and poor prognosis. The AI plus non-contrast CT technology holds the promise to be an effective and cost-efficient tool to achieve detection of pancreatic cancer in the early stages and make large-scale pancreatic cancer screening possible to prevent the loss of lives,” said Le Lu, Head of Alibaba’s Damo Academy’s Medical AI Team and Fellow at IEEE.

Extending the Survival Rate through Early Detection

The survival rate of pancreatic cancer is low compared to other cancers, partly because it is often found at later stages when treatment is hard. It is the seventh leading cause of cancer-related deaths worldwide, with an average five-year survival rate of around 5 to 10 percent.

Combined with non-contrast CT imaging, the early screening technology can help doctors with the early detection of pancreatic cancer, a challenging disease given its often unspecific symptoms. It can also be applied to large-scale screening efforts, for example, as part of the non-contrast CT offering in routine medical checkups or during visits to emergency departments.

The accuracy metrics of the algorithm are “superior to those of several acknowledged screening methods such as Pap smears for cervical cancer or mammography for breast cancer. This makes it tempting to call for integration of this specific method into large-scale screening efforts,” said Jörg Kleeff and Ulrich Ronellenfitsch from Martin-Luther-University Halle-Wittenberg, University Medical Center Halle (Saale) at Germany.

The professors also pointed out further thorough assessment is needed before it is ready to be rolled out into widespread practice.

For more details, please refer to this peer-reviewed article from DAMO Academy in collaboration with leading medical institutions published on Nature Medicine: https://www.nature.com/articles/s41591-023-02640-w.

(0)(0)