Have a look at what was trending last month in radiology: Learn about real time data improving the stroke patient pathway, AI-powered fight against lung cancer, a novel MRI technique verifying brain changes in Long COVID patients, and other radiology trends.
📖 Author: Katrin Lewandowski | OpenRad team
Radiology trend: Real time data as game changer in stroke patient pathway
According to digitalhealth.net, a unified live stroke registry empowers clinicians to proactively navigate the entire patient journey. The essential role of clinicians in capturing and sharing real-time data is foundational to the digital transformation of the British NHS.
The article says: “Real time databases give real time access to information; the visibility this provides across the pathway, from the stroke nurse assessing the patient in A&E to the consultant on the ward, and on to GPs, therapists and supplementary services in the wider stroke community is empowering.”
Lung cancer: Milestone met in AI-powered fight against it
Building Better Healthcare states that a global initiative founded by various stakeholders during the World Economic Forum’s Annual Meeting in 2022 managed to figure out how to digitally identify lung cancer risk before symptoms even show.
AI screening for lung cancer risk plays a vital role here: Artificial intelligence is used in chest X-ray analysis to detect high-risk nodules. These nodules can be indicative of lung cancer.
New MRI technique verifies lasting brain changes in Long COVID patients
As written by itn Imaging Technology News, the novel MRI technique called diffusion microstructure imaging (DMI) is able to give us detailed information about brain tissues.
With the DMI technique, physicians also managed to verify that patients who have Long COVID show specific patterns of brain changes. These differ from the ones observed in individuals that have fully recovered from the disease.
Mammography: Deep learning for classification of microcalcifications
The last but not least November radiology trend is an AI model designed to localise and characterise microcalcifications on mammograms. It has been published on the portal SpringerOpen.
Detecting breast cancer early is vital, and while mammography is a key screening tool, the demand for these services often exceeds the available radiologist capacity. Artificial intelligence however offers support in assessing microcalcifications on mammograms.
A team of three expert radiologists has created and evaluated an AI model that localises and characterises the above described microcalcifications.
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📷 Photo credits: daniela-mueller.com