Addressing the needs of expanded screening
One of the key aims of Europe’s Beating Cancer Plan is to ensure that 90% of the EU population who qualify for breast, cervical, or colorectal cancer screening are offered it by 2025, resulting in increased imaging volumes for screening and the precision diagnosis and personalized treatment of detected cases. AI is widely regarded as a powerful tool that could help radiologists cope with the workload. By combining AI with deep clinical knowledge, Philips is already creating AI-enabled solutions that integrate into and accelerate clinical workflows and provide clinicians with greater clarity at every moment of cancer care. Philips MRCAT (MR for Calculating Attenuation) Brain imaging software, for example, uses trained AI models to capture information needed to accurately and efficiently generate a patient’s radiotherapy plan in a single fast MR exam, without the need for a time and resource consuming CT scan and subsequent CT-MR image co-registration. In an ongoing partnership with Leiden University Medical Center (Leiden, The Netherlands) that recently benefited from EUR 2 million funding from the Dutch Research Council (NWO), Philips is developing innovative new AI solutions to further speed up and improve MR examinations, the aim being to reduce scan times from tens of minutes to less than five minutes and reconstructing detailed MR images despite patient or internal organ movement.
By automating and accelerating routine imaging tasks, Philips’ AI-based solutions aim to simplify workflows and logistics, leaving more time for clinicians to focus on their patients’ needs. At the same time, AI-enabled image reconstruction, quantitative analysis, and data integration tools allow oncologists to make better-informed decisions in diagnosis, therapy planning, treatment, and follow-up to provide patients with more precise and personalized cancer care.