Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks.

PHOTO GALLERY: Medical imaging technology at RSNA 2024
Take a virtual tour around the Radiological Society of North America (RSNA) meeting to see the sights and new technologies displayed across the vast exhibit hall floors.
Cardiology, radiology specialists debate CCTA’s rise as a go-to imaging modality for CAD
CCTA is being utilized more and more for the diagnosis and management of suspected coronary artery disease. An international group of specialists shared their perspective on this ongoing trend.
Can large language models break language barriers in radiology reports?
With the growing demand for virtual care and an increasingly mobile population, the need to improve communication with non-English-speaking patients is immense.
Most patients want to know if AI is involved in their care
“With this signal about the public’s preference for notification, the question for health systems and policymakers is not whether to notify patients but when and how.”
New algorithm is twice as accurate at predicting stroke timing compared to the standard of care
Determining stroke onset is critical for management, as there is a small window of time for initiating treatment that can inhibit damage.

High false-positive diagnoses tolerated with CT colonography

Patients and health care professionals are willing to tolerate high rates of false-positive diagnoses with CT colonography in exchange for diagnosis of extracolonic malignancy, according to a study published online May 22 by Radiology. 

May 29, 2014

C-RADS results could serve as benchmark for CT colonography screening

Results from the CT Colonography Reporting and Data Systems (C-RADS) could establish baseline values for CT colonography (CTC) screening, according to a study published in the June American Journal of Roentgenology. 

May 28, 2014

Could multiparametric MRI be meaningful for bladder cancer?

Multiparametic MRI may be beneficial for the detection, staging and follow-up of bladder cancer, according to an article published in the June issue of the American Journal of Roentgenology.

May 28, 2014

Rethinking tumor response: Is RECIST categorization accurate?

Volumetric analysis of breast cancer liver metastasis using CT may provide a more accurate reflection of locoregional treatment response than Response Evaluation Criteria in Solid Tumors (RECIST) categorization, according to a study published online May 13 in Academic Radiology.

May 28, 2014

Iterative model reconstruction improves image quality, reduces dose in cCTA

Knowledge-based iterative model reconstruction (IMR) reduces intravascular noise on coronary computed tomography angiography (cCTA) by 86 to 88 percent and betters image quality at radiation exposure levels 80 percent below standard technique, according to a study published in the June issue of Academic Radiology.

May 15, 2014

Questions about CAD

Computer-aided detection (CAD) seems like an obvious next step in the evolution of image interpretation. Automation is taking root in so many fields, and radiology is no exception. A tool that can help spot lesions or other areas of interest would be incredibly valuable, even if the technology can’t replace a highly trained professional (and it’s not likely that most people would be comfortable turning over image interpretation to a machine, anyway).

May 7, 2014

Lung volume estimation feasible with automatic segmentation of chest CT

Automatic lung segmentation of routine chest CT scans allows for a technically stable estimation of lung volume, though work remains to reduce variation, according to a study published in the May issue of Radiology.

April 30, 2014

CAD helps catch coronary artery stenosis, but what about false positives?

Use of a computer-assisted detection (CAD) algorithm to identify coronary artery stenosis on coronary CT angiography resulted in relatively high sensitivity and negative predictive value in a recent study from South Korea.

April 28, 2014

Around the web

Cardiovascular Business

Cardiology practices pay $17.7M to settle fraud allegations brought on by whistleblowers

A total of 16 cardiology practices from 12 states settled with the DOJ to resolve allegations they overbilled Medicare for imaging agents used to diagnose cardiovascular disease.

Cardiovascular Business

Cardiology, radiology specialists debate CCTA’s rise as a go-to imaging modality for CAD

CCTA is being utilized more and more for the diagnosis and management of suspected coronary artery disease. An international group of specialists shared their perspective on this ongoing trend.

Cardiovascular Business

New AI program delivers rapid, accurate echo video assessments

The new technology shows early potential to make a significant impact on imaging workflows and patient care.