The market for AI-based applications for medical imaging is predicted to be worth $1.5 billion by 2024

AI-based clinical applications for medical imaging to be worth $1.5 billion in 2024

September 24, 2020
by John R. Fischer, Senior Reporter
The world market for AI-based clinical applications used in medical imaging is predicted to hit a value of nearly $1.5 billion by 2024.

The expected boost is set to occur in the face of slower-than-expected growth around these products and the repercussions of the COVID-19 pandemic, according to a report by Signify Research.

"Startups have been highly focused on algorithm development, but have not truly addressed the challenges of workflow integration and route to market as effectively," Sanjay M. Parekh, Ph.D., senior analyst at Signify Research, told HCB News. "A recent market push from the incumbents, through a build-and-partner strategy, has increased their presence in this market. Some imaging IT vendors have focused more on developing native algorithm developments to push AI into the clinical workflow, whereas other have partnered with AI developers. The incumbents have also offered startups a route to market/a means to better integrate their solutions through AI imaging platforms and AI marketplaces. Given their foothold, incumbents have the advantage of a large customer base, which they can tap in to, pushing AI solutions to their customers."

"There are frequent product launches, and the availability of regulatory approved products is accelerating,” said Dr. Sanjay Parekh, senior analyst at Signify Research, in a statement. "Since 2018, almost 60 AI-based clinical applications for medical imaging have received U.S. FDA approval, while a similar number of solutions have received CE Mark approval."

The market comprises software solutions for automated detection, including triage, as well as quantification and classification of radiology findings. Barriers to their adoption and use include the use of AI in clinical practice, a lack of clinical validation, the challenges of workflow integration, and limited reimbursement. These issues have hindered growth more so than industry experts expected, with the COVID-19 pandemic further exacerbating the situation.

Market growth, however, is projected to accelerate as the pandemic subsides and customer confidence in AI-based clinical solutions increases, leading to a peak annual growth rate of 44% predicted for 2022. Signify Research forecasts that the AI in the medical imaging market is set to reach $1.5 billion in 2024, a CAGR of 33% between 2020 and 2024.

Driving this growth will be the cardiology imaging AI clinical segment, followed by pulmonology, and neurology clinical segments, which, along with breast, account for 86% of these AI-based clinical applications in the world market. The four clinical segments are projected to still account for more than 75% of the market in 2024, with AI applications for clinical segments such as prostate and liver imaging gaining a bigger stake in the market.

"Barriers to market adoption include the utility of AI in clinical practice, a lack of clinical validation, the challenges of workflow integration, and limited reimbursement," said Parekh. "However, many of these barriers are increasingly being addressed, as there has been a rapid increase in the number of AI solutions receiving regulatory approval; AI imaging platforms are addressing the challenges of workflow integration and orchestration; and the potential of reimbursement for AI is on the horizon."

"From enhanced productivity and increased diagnostic accuracy, to more personalized treatment planning and improved clinical outcomes, AI will play a key role in enabling radiologists to meet the demands of their workload," said Parekh. "The increasing volume of diagnostic imaging procedures, exacerbated by the current backlog of imaging exams due to national lockdowns, coupled with the shortage of radiologists in many countries, will undoubtedly further increase the need for AI in radiology."

A number of AI applications are attracting attention and showing great potential for changing practices within medical imaging. For example, NYU Langone and Facebook have garnered much interest through a joint project in which they illustrate how AI can be used with less data to generate MR scans at a faster pace without compromising image quality and diagnostic accuracy.

“This study is an important step toward clinical acceptance and utilization of AI-accelerated MR scans because it demonstrates for the first time that AI-generated images are essentially indistinguishable in appearance from standard clinical MR exams, and are interchangeable in regard to diagnostic accuracy,” said Michael P. Recht, professor of radiology at NYU Langone and lead study author, in a statement following the publication of a study showing evidence of the benefits associated with the project.