Cutting-Edge AI Innovation for Precise Lung Cancer Detection

Cancer – a massive health concern among society:

Cancer, a global disease, has been causing the death of approximately 10 million lives annually, according to the World Health Organisation report. Nonetheless, cancer is curable when detected early and treated right. Hence, experts have been innovating a learning-machine-based model for cancer identification purposes with greater performance in analyzing and tracking cancer patients.

Lung cancer

The respiratory medicine consultant at Royal Marsden and team leader at the Institute of Cancer Research stressed the crucial need for urgent initiatives to accelerate lung cancer detection, highlighting its significance as a prime example.

According to the National Institutes of Health, Lung cancer is one of the most deadly desease globally with the account of 1.8 million deaths across the world. Lung cancer, a major contributor to cancer mortality, underscores the need for faster detection, as over 60% of lung cancer cases in England are diagnosed at late stages. Initiatives like this radionics model offer hope for identifying high-risk patients early, thereby increasing the chances of survival for those diagnosed with lung cancer.

According to Dr. Richard Lee, “People diagnosed with lung cancer at the earliest stage are much more likely to survive for five years, when compared with those whose cancer is caught late.”

“This means it is a priority we find ways to speed up the detection of the disease, and this study – which is the first to develop a radiomics model specifically focused on large lung nodules – could one day support clinicians in identifying high-risk patients.”

Artificial intelligence – a better methodology for disease identification:

The AI system, crafted by experts affiliated with the Royal Marsden NHS Foundation Trust, the Institute of Cancer Research in London, and Imperial College London, exhibits the capacity to ascertain the malignancy of anomalous growths identified within CT scans.

This innovative algorithm surpasses current methods in both efficiency and accuracy, as verified by a study published in the Lancet's eBioMedicine journal. The research team envisions that this AI technology could enhance early detection and improve the success of cancer treatment by identifying high-risk patients and expediting intervention.

Dr Benjamin Hunter, a clinical oncology registrar at the Royal Marsden and a clinical research fellow at Imperial, states “In the future, we hope it will improve early detection and potentially make cancer treatment more successful by highlighting high-risk patients and fast-tracking them to earlier intervention.”

The development process involved using CT scans of around 500 patients with large lung nodules to create an AI algorithm using radionics, a technique capable of extracting vital information from medical images not easily identifiable to the human eye.

The AI model demonstrated its effectiveness by achieving an impressive area under the curve (AUC) score of 0.87 in identifying the risk of cancer in each nodule, outperforming existing diagnostic tests such as the Brock score (0.67) and the Herder score (0.83).

“According to these initial results, our model appears to identify cancerous large lung nodules accurately,” Hunter said. “Next, we plan to test the technology on patients with large lung nodules in clinic to see if it can accurately predict their risk of lung cancer.”

Further studies are planned to test the technology on patients with large lung nodules, with the AI model expected to assist doctors in making faster decisions about patients with growths currently considered medium-risk. When combined with existing diagnostic tools, it successfully identified high-risk patients in this group, suggesting early intervention for 82% of nodules later confirmed as cancerous.

While the Libra study, supported by various organizations, is still in its early stages, it holds the potential to accelerate cancer detection and streamline the analysis of CT scans. Researchers aspire to push boundaries by leveraging innovative AI technology to expedite disease detection.

“Through this work, we hope to push boundaries to speed up the detection of the disease using innovative technologies such as AI,” said the Libra study’s chief investigator, Dr Richard Lee.

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