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 hp
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




CT Scans Better Detecting Abnormalities in Patients with Influenza A Virus H1N1

By MedImaging International staff writers
Posted on 10 Nov 2009
Print article
Computed tomography (CT) scans are better than conventional X-ray radiography in showing the extent of disease in patients with the influenza A virus H1N1, according to recent research.

The study was published online October 21, 2009, in the American Journal of Roentgenology (AJR). The study group consisted of seven patients with the H1N1 virus. All seven patients received chest X-rays and three patients had CT scans. "All patients with CT abnormalities showed abnormal findings on the corresponding chest X-rays,” said Amr M. Ajlan, M.D., from the McGill University Health Center (Montreal, QC, Canada), and lead author of the study.

"However, the extent of involvement was more diffuse and the distribution of disease was better characterized on CT,” said Dr. Ajlan. "The strength of our study is that all CT scans performed showed a similar distribution of abnormalities, which might help physicians prospectively diagnose H1N1 using medical imaging. Most cases of H1N1 are mild and self-limited; however, high-risk patients are more likely to have severe complications. Our study suggests that CT is superior to standard chest X-rays and should be the imaging modality of choice in high-risk patients.”

Related Links:
McGill University Health Center




Wall Fixtures
MRI SERIES
New
HF Stationary X-Ray Machine
TR20G
Radiation Therapy Treatment Software Application
Elekta ONE
Portable Color Doppler Ultrasound System
S5000

Print article

Channels

Ultrasound

view channel
Image: Ultrasound detection of vascular changes post-RT corresponds to shifts in the immune microenvironment (Photo courtesy of Theranostics, DOI:10.7150/thno.97759)

Ultrasound Imaging Non-Invasively Tracks Tumor Response to Radiation and Immunotherapy

While immunotherapy holds promise in the fight against triple-negative breast cancer, many patients fail to respond to current treatments. A major challenge has been predicting and monitoring how individual... Read more

Nuclear Medicine

view channel
Image: [18F]3F4AP in a human subject after mild incomplete spinal cord injury (Photo courtesy of The Journal of Nuclear Medicine, DOI:10.2967/jnumed.124.268242)

Novel PET Technique Visualizes Spinal Cord Injuries to Predict Recovery

Each year, around 18,000 individuals in the United States experience spinal cord injuries, leading to severe mobility loss that often results in a lifelong battle to regain independence and improve quality of life.... Read more

General/Advanced Imaging

view channel
Image: This image presents heatmaps highlighting the areas LILAC focuses on when making predictions (Photo courtesy of Dr. Heejong Kim/Weill Cornell Medicine)

AI System Detects Subtle Changes in Series of Medical Images Over Time

Traditional approaches for analyzing longitudinal image datasets typically require significant customization and extensive pre-processing. For instance, in studies of the brain, researchers often begin... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.