Health system spends nearly $7M on AI to boost prostate MRI performance

A large healthcare system is spending nearly $7 million (USD) as it aims to bolster MRI use and improve the detection of prostate cancer. 

The United Kingdom’s National Health Service announced the investments on Wednesday as part of a total pot of nearly $20 million spread across seven different projects. 

Of that figure, over $3 million will go to Lucida Medical, a U.K. company that provides AI for improving early detection of prostate cancer via MRI. Another $3.5 million will go to Spain-headquartered Quibim, which also aids in prostate cancer assessment.

“This NHS rollout is a major milestone in our mission to improve cancer diagnostics through AI,” Ángel Alberich-Bayarri, PhD, CEO of Quibim, said in a July 9 announcement from the company. “By empowering radiologists with AI, we can help ensure more men are diagnosed earlier, when their chances of survival are highest,” he added later. 

NHS will evaluate the use of QP-Prostate, software that helps rads to automatically identify cancer. This project will explore whether the product can increase the number of diagnoses and proportion of cases found at an early stage. Quibim said its flagship software will be rolled out across seven hospitals in England, with the project lasting two years. It noted that prostate cancer is the most common form of the disease among men in the U.K., with over 52,000 new cases and 12,000 deaths annually. Despite advances in imaging, only about 50% of all instances are diagnosed early when treatment is most effective. NHS is aiming to boost this number to 75% by 2028. 

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Altogether, the experiment will involve about 3,000 patients across a geographically diverse group of hospitals. Quality metrics assessed will include increases in prostate cancer diagnoses and early detection, cost effectiveness and long-term impact on NHS resources, the role of AI in reducing diagnostic disparities, and public perceptions around AI. 

Meanwhile, the Lucida Medical project also aims to boost early detection and diagnostic efficiency. It involves the use of AI-based software called Pi (Prostate Intelligence), which automatically analyzes MRIs for cancer. Lucida said the NHS will use its software across up to 15 hospitals. The health system aims to diagnose patients within 28 days of primary care doc referrals, a challenge given radiology staffing constraints and the complexity of interpreting prostate MRIs. 

Integrating Pi could save up to 21 days per patient, initial estimates indicate. This will be piloted at Leeds Teaching Hospitals to enable men requiring a biopsy to receive one on the same or next day following an MRI, “significantly reducing wait times.” The technology also may enable more men to avoid biopsies altogether, the company noted. This could increase the detection of early-stage cancers by between 4% to 8%, potentially representing up to 4,480 additional cases per year. 

“This technology will support our radiologists across greater Manchester to diagnose prostate cancer sooner allowing us to identify men who need treatment most urgently,” Dr. Rhidian Bramley, clinical lead for diagnostics at Greater Manchester Cancer Alliance and a consultant radiologist, said in the announcement from Lucida Medical. 

The work was commissioned and funded by the NHS Cancer Program with the support of the Small Business Research Initiative. Other projects in the initiative will focus on concerns such as screening for high-risk Hodgkin lymphoma and increasing the uptake of national screening programs using an “automated patient engagement platform.” You can read more about the NHS AI investments here.

Radiology Business Marty Stempniak

Marty Stempniak has covered healthcare since 2012, with his byline appearing in the American Hospital Association's member magazine, Modern Healthcare and McKnight's. Prior to that, he wrote about village government and local business for his hometown newspaper in Oak Park, Illinois. He won a Peter Lisagor and Gold EXCEL awards in 2017 for his coverage of the opioid epidemic. 

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