With the earth’s warmest March on record in 175 years barely in the rearview mirror, a team of radiology experts says medical imaging must step up its sustainability efforts.
Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans.
Encouragingly, the MRI scans did not require the latest equipment advances and were conducted on a standard machine that is readily available at most hospitals—a 1.5 Tesla.
Unique to radiologists is that their workloads have not yet declined to the pre-pandemic levels seen in 2019 like other specialties have started to witness.
There are many known disparities in breast imaging that have been found in previous studies, but insight into diagnostic mammography processes is still lacking.
Preoperative MRI use increased substantially from 2003 to 2016—from 2.9% to 28.2% to be exact—but the modality remained underutilized in certain regions and among specific populations in the United States.
Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans.
"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday.
![Advanced artificial intelligence (AI) models can evaluate cardiovascular risk in routine chest CT scans without contrast, according to new research published in Nature Communications.[1] In fact, the authors noted, the AI approach may be more effective at identifying issues than relying on guidance from radiologists. Representative non-contrast CT slices for two patients (left), with super-imposed segmentations (right). One artificial intelligence (AI) model was used to segment a cardiac mask.](/sites/default/files/styles/stack_views/public/2024-04/screen_shot_2024-04-23_at_10.44.32_am.png.webp?itok=vXt3hxDo)
