While MRI is the imaging technique of choice for assessing a range of cancers, including prostate cancer, in the UK alone, the number of radiologists is predicted to reach 40% by 2027, indicating the need for a streamlined, simplified and accurate means of cancer diagnosis, Med Tech reports.

A clinical study shows that radiologists can miss 12% of significant prostate cancer cases using MRI. The data, presented at the European Society of Urogenital Radiology (ESUR) in September 2023, shows that Pi could help reduce undetected cancers by up to 6% while reducing avoidable biopsies by up to 43%.

According to Med Tech, with the help of artificial intelligence, Pi analyzes MRIs and is fully integrated into the radiologist’s workflow, targeting key issues related to variability, radiologist timing and diagnostic accuracy in prostate cancer. Specifically, Pi is designed to be used by radiologists to evaluate and report prostate MRI studies by automatically creating 3D segmentations, volumes and risk scores. Its results can be used to save radiologists time and to support biopsy and treatment decisions.

“We desperately need to cut waiting times, detect cancer early, and provide patients and clinicians with all the information needed to for optimum treatment. With this CE mark, the results of our investment in AI and clinical research over the last four years can now be used by doctors to provide the best possible diagnosis for men with suspected prostate cancer”, explained co-founder and chief medical officer Professor Evis Sala, chair of radiology at the Università Cattolica del Sacro Cuore and director of the Advanced Radiology Centre at the Policlinico Universitario A. Gemelli, IRCCS.

Lucida Medical will demonstrate Pi at the Radiological Society of North America (RSNA) 2023 Annual Meeting.

What is Pi?
Prostate Intelligence (Pi) is an AI and machine learning based software system designed to help radiologists detect and report the presence of prostate cancer lesions from MR scans (MRI).

How does the technique work?

It spots hidden patterns in the data and learns who is most at risk. The algorithm is suggested to have the power of helping reduce the number of people who may have been falsely diagnosed with dementia.

Data from people who have attended a network of 30 National Alzheimer’s Coordinating Centre memory clinics in the US, was analyzed by the study’s researchers. At the beginning of the study, the attendees didn’t have dementia even though they have had problems with their memory or some other brain functions.

The study started in 2005 and finished in 2015. For that period of time one in ten attendees was diagnosed with dementia within two years after they visited the memory clinic.

So, what did the research find?

According to the study, the machine learning model is able to predict these new dementia cases with up to 92 per cent accuracy. Also, it is even more accurate than two existing alternative research methods.

According to Professor David Llewellyn, who is  from the University of Exeter, they were now able to teach computers to accurately predict who will go on to develop dementia within two years.

Also, he added:

“We’re also excited to learn that our machine learning approach was able to identify patients who may have been misdiagnosed. This has the potential to reduce the guesswork in clinical practice and significantly improve the diagnostic pathway, helping families access the support they need as swiftly and as accurately as possible.”

Dr Janice Ranson, who also worked on the project, commented:

“We know that dementia is a highly feared condition. Embedding machine learning in memory clinics could help ensure diagnosis is far more accurate, reducing the unnecessary distress that a wrong diagnosis could cause.”

Machine learning was found to work effectively, using patient information which is routinely available in clinics such as memory and brain function, performance on cognitive tests and specific lifestyle factors.

Now the team has a new plan which includes conducting follow-up studies in order to evaluate the practical use of the method in clinics, as well as to assess whether it can be rolled out to improve dementia diagnosis, treatment and care.

The head of research at Alzheimer’s Research UK, Dr Rosa Sancho shared:

“Artificial intelligence has huge potential for improving early detection of the diseases that cause dementia and could revolutionise the diagnosis process for people concerned about themselves or a loved one showing symptoms. This technique is a significant improvement over existing alternative approaches and could give doctors a basis for recommending lifestyle changes and identifying people who might benefit from support or in-depth assessments.”

Besides, two years ago, VR was found to help people who are suffering from dementia recall past memories and tackle behavioral issues in 2019.