Improving image quality, diagnosis with advanced viz
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| Bob Mitchell, Editor |
For example, researchers found that integrating MRI-based attenuation correction methods and lower extremity CT angiography (CTA) can improve diagnostic imaging quality and lead to better diagnosis.
In recent years, CTA applications have increased particularly in the trauma setting, with many multi-trauma patients requiring a variety of imaging studies, Bryan. R. Foster, MD, assistant professor of radiology at Oregon Health & Science University in Portland, Ore., and colleagues, said. Many hospitals have combined torso CT and extremity CTA into a single study with one contrast bolus. However, the image quality and diagnostic accuracy of the protocol have not been verified, the authors noted.
The researchers completed a retrospective study which assessed the image quality and clinical utility of a polytrauma protocol with integrated lower extremity CTA using a 64-slice CT system and single contrast bolus. The researchers discovered reported injuries in 15.5 percent of patients, with a total of 63 arterial injuries observed. The diagnoses included: occlusion, narrowing, active extravasation, pseudoaneurysm and occlusion with arteriovenous fistula. Seven of the patients underwent surgeries, and CTA-detected injuries were confirmed in six of the seven patients.
Another study focused on MRAC as one method used in atlas registration and pattern recognition (AT&PR), and a way of providing better PET quantification accuracy than a basic MR image segmentation approach, according to a study in the September issue of the Journal of Nuclear Medicine.
The MR image segmentation algorithm used a combination of image thresholds, Dixon fat-water segmentation and component analysis to detect the lungs. The AT&PR algorithm uses a database of previously aligned pairs of MRI/CT image volumes.
For each patient, these dual-modality images are registered to the patient MRI volume, and machine-learning techniques predict attenuation values on a continuous scale. The researchers said MRAC methods are compared via a quantitative analysis of AC PET images using volumes in normal organs and on lesions. They assumed the PET/CT values after CT-based AC to be the reference standard.
And, finally, a study published online in Radiology on Sept. 22 shows new bone suppression image processing software, used with a standard x-ray, can improve radiologists’ accuracy in detecting small lung cancers on chest films.
Feng Li, MD, PhD, of the department of radiology at the University of Chicago, and colleagues wanted to determine whether bone suppression imaging could improve radiologists’ performance in detecting small lung cancers.
The researchers observed an increase in accuracy using the new technique, and wrote that “while dual-energy subtraction radiography provides the highest accuracy, use of bone suppression software in combination with standard radiograph can improve detection of small nodular cancers compared with the use of standard radiographs alone.”
Ten observers, including six radiologists and four radiology residents, assessed images and rated their confidence in detecting the presence or absence of a lung cancer first by using standard imaging, then a bone suppression image and finally a DES image. The study included radiographs from 50 patients with a total of 55 confirmed primary nodular cancers and 30 patients without cancer. Receiver operating characteristic analysis was then used to evaluate the radiologists’ performance.
Let us know how your organization is leveraging advanced visualization to improve diagnosis imaging quality.
Bob Mitchell
CMIO, Editor
bmitchell@trimedmedia.com