Risk of Cardiovascular Disease Computed Through Chest CT

First Posted: May 27, 2014 06:02 PM EDT
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Computed tomography (CT) scans are imaging procedures that use special x-ray technology to create a series of detailed pictures (or scans) of areas inside the body. Researchers determined that chest CTs can help determine a patient's heart health.

The worldwide prevalence of cardiovascular disease is overwhelming. As a result, doctors, researchers, medical experts, and health officials work tirelessly to treat heart-related ailments and also search for ways to prevent and/or detect them as early as possible. Researchers from the University Medical Center Utrecht in the Netherlands are contributing to that cause.

Chest CTs routinely provide radiologists with findings that are unrelated to the CT indication (known as incidental findings), but there exists no guidance on how to gauge these findings in their daily practice. The researchers sought to find a way to assess the incidental findings and use them to help predict one's risk of cardiovascular disease.

The researchers' study, "Incidental Imaging Findings from Routine Chest CT Used to Identify Subjects at High Risk of Future Cardiovascular Events," was published in the journal Radiology. The analysis featured follow-up data from 10,410 patients who underwent a diagnostic chest CT for non-cardiovascular conditions. The researchers developed a prediction model that incorporated age, gender, CT indication, left anterior descending coronary artery calcifications, mitral valve calcifications, descending aorta calcifications, and cardiac diameter.

"Extensive literature has clearly documented the uncertainty of prediction models based on conventional risk factors," said Dr. Pushpa M. Jairam, of the University Medical Center Utrecht, in this EurekAlert! news release. "With this study, we address to some extent, the need for a shift in cardiovascular risk assessment from conventional risk factors to direct measures of subclinical atherosclerosis."

The factors included in the prediction model are believed to have to potential to improve diagnosis and treatment for patients in question. The overall goal of the findings was for patients to potentially have the ability to receive timely preventive cardiovascular risk management.

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