The U.S. Food and Drug Administration (FDA) has cleared Philips’ SmartHeart AI to provide clinicians with a tool to streamline cardiac magnetic resonance (MR) workflows.
MR of the heart is considered one of the most technically demanding applications of imaging techniques compared to other organs, and synchronized cardiac and respiratory gating or breath-hold techniques are required to overcome motion artifacts that impede diagnostic evaluation of cardiac MR scans.
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Trained on over 1,200 MR datasets, SmartHeart AI is designed to automate 14 standard and advanced cardiac views in under 30 seconds. According to Philips, this provision reduces operator variability, improves workflow consistency, and reduces the need for manual readjustments when performing cardiac MR.
Meanwhile, Philips claimed that SmartHeart can reduce the number of breath holds required by patients in basic views by up to 75%, thereby increasing patient comfort during cardiac MR evaluation.
With SmartHeart’s FDA clearance, this workflow tool supports the orchestration of additional AI tools within Philips’ extensive cardiac MR suite. CINE FreeBreathing is designed to improve diagnostic imaging without the need for breath-holding, thereby increasing comfort during cardiac MR in patients who cannot hold their breath or have irregular heart rhythms. Cardiac motion correction can be applied to correct both the heart and the respiratory system and is intended to result in a more definitive diagnosis. CardiacQuant Perfusion, on the other hand, provides a non-invasive quantitative assessment of myocardial perfusion, supporting a more objective diagnosis of subtle perfusion defects.
Ioannis Panagiotelis, MR Business Lead at Philips, said: “By integrating SmartHeart directly into the planning workflow, Philips is fundamentally redefining how CMR is performed, transforming it from a highly technical and time-consuming procedure to a streamlined, intelligent and scalable solution.”
Applications of AI are having a significant impact in the medical field, especially in streamlining image processing workflows to improve diagnostic accuracy and reduce the time doctors spend on MRI and related imaging protocols. According to a GlobalData report, the combined AI market across healthcare will be valued at $11.9 billion in 2024 and is expected to reach $57.4 billion in 2029.
