Liver:
The first nonalcoholic steatohepatitis (NASH) treatment in North America is set to boost demand for MR liver imaging to monitor treatment effectiveness, with similar expectations for Europe. Multiparametric AI tools, like Quibim's new offering launched in Europe in early 2024, enhance the quantified assessment of liver fat and iron. However, in Asia Pacific, despite increasing attention to liver disease and high Non-alcoholic fatty liver disease (NAFLD) prevalence, liver imaging volumes remain low due to limited funding and investment in new AI tools. Notably, there are currently no National Medical Products Administration (NMPA) approvals for liver AI tools in China.
Cardiology:
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MR's potential in cardiac functional assessment for cardiovascular disease is growing, supported by increased investment in AI for faster cardiovascular magnetic resonance (CMR) image interpretation, which is traditionally labour-intensive for radiologists. Recent studies highlight AI's role in assessing pulmonary arterial hypertension and enhancing contrast CMR for diagnosis and screening. Challenges to wider CMR screening adoption include slow reimbursement processes, limited MR access in many markets, and less investment in CMR AI compared to CT, where Heartflow and Cleerly lead the segment.
Rising adoption of AI-enhanced workflows
Despite billions of USD invested in AI image analysis software vendors, leading MR equipment OEMs are also heavily investing in AI to enhance MR hardware. This AI-driven image enhancement has become crucial for differentiating products and sustaining demand for new generations of MR equipment.
The rapid adoption of AI-based image acquisition and reconstruction technology, especially in new 1.5T systems, has led some industry experts to predict declining demand for 3T systems. Many believe AI-enhanced 1.5T systems will become the standard for most scans, except in advanced research or specialist centres.
The market for AI-based MR tools is projected to reach nearly $350 million by 2027. However, MR is still a smaller market compared to high-volume screening applications like stroke, cardiac FFR-CT, lung screening, and mammography.
Nevertheless, substantial research funding into neurodegenerative conditions and increased MR availability could make AI most impactful in speeding up and improving MR scan readings. Startups are gaining attention from cardiac MR, liver assessment, abbreviated MR for breast cancer diagnosis, and other conditions, which are targeting less competitive segments as leading AI markets mature and consolidate.
