Polar maps of the coronary arteries that provide information regarding morphology and patency in a single image could potentially speed up diagnosis. But the technology still has some bugs in it, according to German researchers.
Polar maps of the coronary arteries that provide information regarding morphology and patency in a single image could potentially speed up diagnosis. But the technology still has some bugs in it, according to German researchers.
A polar map of a landmass resembles a penny that's been squashed by a train: The distance north and south is shorter compared with the longitudinally stretched east and west. A world map with this configuration is able to depict its entire contents on one side, although the representation becomes a bit unrealistic at the edges.
Polar maps of the coronary arteries suffer from the same spatial distortion.
"The problem is that the near vessels are displayed bigger than the farther vessels, particularly around the pole areas and the sides," said lead investigator Dr. Felix Schoth.
As the technique improves, however, it will allow for faster diagnosis, as curved multiplanar reformatted or volume-rendered images of the coronaries are time-consuming to produce, he said.
Schoth and colleagues from Aachen University Hospital in Germany performed a standard CT angiography exam on 10 subjects, using a 16-slice scanner (120 kVp, 550 mAs). Image reconstruction was performed at 60% of the R-R interval.
A newly developed algorithm provides a maximum intensity projection of the myocardium, including the coronary arteries, in 3D polar coordinates. The aortic valve acts as the North Pole.
The images are then "unfolded" into two dimensions as planar projection polar maps. Visibility of the coronary arteries was rated on a scale from 0 (not visible) to 3 (good visibility). Visibility was good proximally, fair medially, and poor distally.
The ratings were as follows:
LAD proximal 2.4, medial 2.2, distal 1.4;
RCA proximal 2.1, medial 1.9, distal 1.3; and
RCX proximal 2.4, medial 1.8, distal 1.3.
Stents and coronary calcifications were displayed accurately, but the ventricles had poor contrast, Schoth said.
A 64-slice scanner would not improve the distortion, which originates from the planar projection; further perfection of the algorithm and data acquisition will accomplish that. But since the temporal and spatial resolution are much better with a 64-slice scanner, smaller vessels would be visible and artifacts would further be reduced, Schoth said.
What is the Best Use of AI in CT Lung Cancer Screening?
April 18th 2025In comparison to radiologist assessment, the use of AI to pre-screen patients with low-dose CT lung cancer screening provided a 12 percent reduction in mean interpretation time with a slight increase in specificity and a slight decrease in the recall rate, according to new research.
The Reading Room: Racial and Ethnic Minorities, Cancer Screenings, and COVID-19
November 3rd 2020In this podcast episode, Dr. Shalom Kalnicki, from Montefiore and Albert Einstein College of Medicine, discusses the disparities minority patients face with cancer screenings and what can be done to increase access during the pandemic.
Can CT-Based AI Radiomics Enhance Prediction of Recurrence-Free Survival for Non-Metastatic ccRCC?
April 14th 2025In comparison to a model based on clinicopathological risk factors, a CT radiomics-based machine learning model offered greater than a 10 percent higher AUC for predicting five-year recurrence-free survival in patients with non-metastatic clear cell renal cell carcinoma (ccRCC).
Could Lymph Node Distribution Patterns on CT Improve Staging for Colon Cancer?
April 11th 2025For patients with microsatellite instability-high colon cancer, distribution-based clinical lymph node staging (dCN) with computed tomography (CT) offered nearly double the accuracy rate of clinical lymph node staging in a recent study.