8 trends in radiology technology to watch in 2023

Example of artificial intelligence generated measurements to quantify the size of a lung cancer nodule during a followup CT scan to see if the lesion is regressing with treatment. This type of automation can aid radiologists by doing the tedious, time consuming work. Photo by Dave Fornell
Example of artificial intelligence generated measurements to quantify the size of a lung cancer nodule during a followup CT scan to see if the lesion is regressing with treatment. This type of automation can aid radiologists by doing the tedious, time consuming work. Photo by Dave Fornell

Here is a list of some key trends in radiology technology from our editors based on our coverage of the radiology market.

Deep learning helps experts take advantage of 'rare' chance to study deadly tumor progression

#glioblastoma multiforme #GBM #braintumor

Segmentation results of the three spatial axes for the initial and final time images of each patient. Image courtesy of the Journal of Theoretical Biology.

Researchers from the University of Waterloo and the University of Toronto are collaborating to better understand how glioblastoma multiforme (GBM) advances when it is not treated.

New research discourages use of advanced vascular imaging in trauma patients

cerebrovascular injury #traumaimaging #vascularimaging #vascularinjury

These severe injuries would raise a strong suspicion of an adjacent vascular injury. Thin white arrows demonstrate a dissection flap in the left vertebral artery. Image courtesy of Clinical Radiology.

Experts argue that the overall incidence of blunt cerebrovascular injury is very low and that symptomatic vascular injuries in these cases are even lower.