New AI Tool Measures Fat Around Heart and Determines the Risk of Diabetes

Jul 19, 2021- by CMI| Category : Medical Imaging1 min read
New AI Tool Measures Fat Around Heart and Determines the Risk of Diabetes

 

A new tool was invented by using artificial intelligence that could measure the accumulated fat around the heart and could determine the risk of diabetes in patients.

Researchers of the Queen Mary University of London developed a new AI tool that could quantify fat surrounding the heart to determine the risk of diabetes in an individual. Accumulation of fat especially around the heart could lead to various severe cardiovascular and metabolic diseases such as diabetes. The new AI tool is used to calculate the level of surrounding fat around heart from regular MRI images so that it could determine the diabetes risk and have required treatment on it.

A particular collection of fat tissues that are formed around the heart is known as pericardial adipose tissues (PAT). The risk of diabetes and coronary heart diseases are linked to the level of PAT formation around heart. High level of PAT increases the risk of diabetes in an individual. Computed tomography (CT) scan was usually used to measure PAT level. However, the accuracy level of CT scan was not definite as patients were exposed to ionizing radiations, which limits researcher’s ability to measure accurate levels of PAT. To overcome this limitation, the new AI tool was invented that could measure the accurate level of PAT by standard MRI scan of the heart.

The researchers demonstrated clinical potential of the new tool by conducting its trial over 40000 from UK. It was observed that the tool accurately measured the level of PAT and further evaluated the risk of diabetes of the patient. Mr. Steffen Petersen, a research supervisor, said that the tool is ready to be used in the clinical tests as it has accuracy in measuring PAT level and it also gives a link between PAT level and diseases risk in patient. The researchers claimed that the tool could also be used for further study to bring advancement in the technology to improve clinical utility.

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