We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App


ATTENTION: Due to the COVID-19 PANDEMIC, many events are being rescheduled for a later date, converted into virtual venues, or altogether cancelled. Please check with the event organizer or website prior to planning for any forthcoming event.

CT Lung Imaging Combined with Machine Learning Predicts Further COPD Care

By MedImaging International staff writers
Posted on 24 Jun 2022
Print article
Image: Quantitative CT lung imaging and ML improves prediction of ED visits and hospitalizations in COPD (Photo courtesy of Pexels)
Image: Quantitative CT lung imaging and ML improves prediction of ED visits and hospitalizations in COPD (Photo courtesy of Pexels)

Healthcare utilization in chronic obstructive pulmonary disease (COPD) patients is a growing concern. Patients with COPD are more likely to utilize healthcare services, have higher rates of hospitalizations and hospital readmissions, and higher rates of mortality. Hence, predicting increased risk of future healthcare utilization in COPD patients is important for improving patient management. Now, a new study has found that healthcare utilization could potentially be predicted in mild COPD patients using computed tomography (CT) lung imaging and machine learning.

The study by researchers at the Toronto Metropolitan University (Toronto, ON, Canada) aimed to determine the importance of CT lung imaging measurements relative to other demographic and clinical measurements for predicting future health services use with machine learning in COPD. In the retrospective study, the researchers evaluated lung function measurements and chest CT images of 527 COPD participants from 2010 to 2017. Up to two follow-up visits (1.5- and 3-year follow-up) were performed and participants were asked for details related to healthcare utilization. Healthcare utilization was defined as any COPD hospitalization or emergency room visit due to respiratory problems in the 12 months prior to the follow-up visits.

The researchers found that out of the 527 COPD participants evaluated, 179 (35%) used healthcare services at follow-up. There were no significant differences between the participants with or without healthcare utilization at follow-up for age, sex, BMI or pack-years. The accuracy for predicting subsequent healthcare utilization was 80% when all measurements were considered, 76% for CT measurements alone and 65% for demographic and lung function measurements alone. Based on these findings, the researchers concluded that a combination of CT lung imaging and conventional measurements leads to greater prediction accuracy of subsequent health services use than conventional measurements alone, and may provide needed prognostic information for patients suffering from COPD.

Related Links:
Toronto Metropolitan University 

Print article



view channel
Image: The Definium 656 HD is the company’s most advanced fixed X-ray system yet (Photo courtesy of GE Healthcare)

Next-Gen X-Ray System Brings ‘Personal Assistant’ to Radiology Departments

X-ray imaging often provides the entry point to diagnostic imaging - accounting for 60% of all imaging studies conducted. As a result, X-ray technologists, radiologists and radiology administrators are... Read more


view channel
Image: The new device can better measure blood flow and oxygenation in the placenta (Photo courtesy of University of Pennsylvania)

Novel Method Combines Optical Measurements with Ultrasound for Monitoring ‘Engine’ of Pregnancy

The placenta, considered as the “engine” of pregnancy, is an organ that plays a crucial role in delivering nutrients and oxygen to the fetus. Placental dysfunction can lead to complications such as fetal... Read more

Imaging IT

view channel

Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology

The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read more
Copyright © 2000-2022 Globetech Media. All rights reserved.