A recent study highlights that artificial intelligence (AI) can streamline the use of data from lung scans to improve the ability to predict the risk of death from lung cancer, cardiovascular disease and other conditions.
The US Preventive Services Task Force currently recommends annual lung screening with low-dose chest tomography for people aged 50 to 80 who are at increased risk for lung cancer, including smokers with a long history.
In addition to images of the lungs, the scans provide information about other structures in this region of the body.
“The main purpose of CT imaging is to detect nodules suspected of lung cancer, but there is much richer anatomical information, including body composition data,” explained Kaiwen Xu, a doctoral candidate in the Department of Informatics at Vanderbilt University.
Previously, the team developed and launched an artificial intelligence algorithm capable of automatically reading measurements related to body composition from CT scans used for lung screening. These measurements include the percentage of body fat, bone and muscle.
Abnormal body composition, such as obesity and loss of muscle mass, correlates with chronic diseases, including heart disease, and has been linked to risk and prognosis for conditions such as cardiovascular disease and chronic obstructive pulmonary disease (COPD). In lung cancer treatment, these measurements have been shown to have a significant impact on patients’ survival and quality of life.
In the current study, the team examined the added value of AI to body composition measurements using CT scans in a population of more than 20,000 people from a national screening study. The results showed that integrating these measurements led to improved predictions of the risk of death from lung cancer, heart disease and overall mortality.
This AI approach may extend the utility of low-dose CT scans beyond the early detection of lung cancer. This can help identify people at high risk early, allowing interventions such as lifestyle changes or physical fitness at an early stage.
In particular, measures of fat present in muscle were strong predictors of mortality, which aligns with previous research. The bottom line is that imaging technology can provide detailed information about a diverse range of conditions, not just the lungs. This more frequent integration into clinical care could be essential for early identification and management of health risks.
Source: 360medical.ro
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2023-08-07 19:44:05
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