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An artificial intelligence (AI) model has been created by scientists, doctors and researchers which can identify cancer accurately, marking a developmental stage which can speed up the diagnosis of the disease and fast-track treatment.

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Cancer has become a leading cause of fatalities throughout the world, resulting in around 10 million deaths every year, which is one in six patients, according to the World Health Organization.

However, in many cases, cancer can be cured and lives can be saved if it is detected early and swift treatment is provided to patients.

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Experts from Royal Marsden NHS foundation trust along with Imperial College London and the Institute of Cancer Research, London, designed the AI tool which can identify if abnormal growths seen on a person's CT scans are cancerous.

As per the study, the performance of the algorithm has been more efficient and effective compared to the current methods. The research's findings were published in the eBioMedicine journal of the Lancet.

“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,” stated Dr Benjamin Hunter, a clinical research fellow at Imperial and a clinical oncology registrar who works at the Royal Marsden.

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The research team used CT scans of around 500 patients who had large lung nodules to create an AI algorithm with the use of radiomics. Through the technique, vital information can be extracted from medical images that the human eye fails to easily spot.

A measure, known as area under the curve (AUC), was used in the study to test the model's effectiveness at predicting cancer.

If a model gets an AUC of 1 it will be considered, with 0.5 indicating that it is randomly guessing. The results of the study showed that the risk of cancer in each nodule can be identified by the AI model with an AUC of 0.87.

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

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

Speaking about lung cancer which is considered the biggest reason for cancer mortality, Lee stated, “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.”

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