Engineers from MIT in Cambridge, Massachusetts have developed a non-invasive MRI sensor no bigger than a penny that can detect and measure electrical activity or optical signals in the brain, according to a recent MIT news release. The research was published online Oct. 22 in Nature Biomedical Engineering.

When imaging brain tumors such as gliomas, machine learning may advance the use of imaging and augment clinical care for patients, according to a review published Oct. 17 in the American Journal of Roentgenology—specifically in tumor segmentation and MRI radiomics.

The color scale used to optimize image interpretation has a measurable diagnostic effect on the interpretation of computed tomography perfusion (CTP) exams and apparent diffusion coefficient (ADC) images, according to an Oct. 15 study published in Clinical Radiology.

MRIguidance, a spin-off company of the University Medical Center Utrecht in the Netherlands, is developing an advanced MRI software that can characterize both soft tissue and bone without the use of radiation, according to a company news release published Oct. 16.

“For those who are unfamiliar with the field of machine learning (ML), the emerging research can be daunting, with a wide variation in the terms used and the metrics presented,” wrote Guy S. Handelman, with Belfast City Hospital in Northern Ireland, U.K., in a recent AJR perspective.

In patients with liver cirrhosis, four-dimensional (4D) flow MRI can help indicate the risk of bleeding in gastroesophageal varices and reduce the need for invasive endoscopy procedures, wrote authors of an Oct. 16 Radiology study.

With the help of diffusion spectrum imaging, scientists from the University at Buffalo in New York are creating models to better understand how brain structure affects language-based performance tasks.

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