MR News & Stories

From 2.5 weeks to 2 days: MRI patient access transformed.

Magnetic resonance imaging (MRI) is the gold standard of imaging diagnostics in many medical fields. But it is still far from always being readily available – even where it would be the best option. Technological progress is rapid. The next generation MRI could look very different. 

Magnetic resonance imaging (MRI) has been part of routine medical practice for years. The big tubes produce fascinating images. No wonder that MRI is seen as the crowning glory of diagnostics. But how exactly does it work? What’s so special about it? We answer twelve questions to give a better idea.

The development of magnetic resonance imaging (MRI) is an exciting story of innovation spanning four decades – if not several centuries – and two Nobel prizes. But the fact that MRI scanners are now used in patient care all over the world is also thanks to industrial research and development.

A large, bearded character, pediatric radiologist and amateur rock musician Professor Erich Sorantin from Graz stands up for equal rights of children in imaging – also in MRI. In terms of technology, he relies on precision equipment from Siemens Healthineers.

With an upgrade of your MR scanner to BioMatrix Technology, you can better master the challenges facing MRI today. Learn firsthand how easy the upgrade from the 3T MRI MAGNETOM Skyra to the MAGNETOM Vida Fit is.

Ineffective utilization affects patient wait-times, revenue, as well as referral and patient satisfaction. We are moving the needle in MRI productivity to increase patient volumes and overcome economic pressure.

Our new column “Point of View” picks up trends and developments in healthcare. In this first edition, Greg Freiherr comments on the advent of AI in the medical world – and how he learned to embrace it.

In recent years, the link between tumor therapies and cardiac disease has gained substantial attention. With improving survival rates of patients with various malignancies, potential detrimental effects on cardiac function and outcome including increased morbidity and mortality has become the center of such investigations.

The developments in computational hardware and algorithms, in particular the advent of methods suitable for training complex neural networks (Deep Learning), have opened up new possibilities for machine learning [1] and automation in many applications. MRI, postprocessing and interpretation, in fact radiology in general, are no exception.

MRF¹ uses quantitative information to generate a more precise understanding of a patient’s condition. Based on reliable, absolute numbers, MRF data could increase objective comparisons in follow-up studies. Ultimately, aided by AI, quantitative measurements could lead to more personalized treatments.