Cardiac Imaging

While cardiac ultrasound is the widely used imaging modality for heart assessments, computed tomography (CT), magnetic resonance imaging (MRI) and nuclear imaging are also used and are often complimentary, each offering specific details about the heart other modalities cannot. For this reason the clinical question being asked often determines the imaging test that will be used.

An example of an FDA cleared radiology AI algorithm to automatically take a cardiac CT scan and identify, contour and quantify soft plaque in the coronary arteries. The Cleerly software then generates an automated report with images, measurements and a risk assessment for the patient. This type of quantification is too time consuming and complex for human readers to bother with, but AI assisted reports like this may become a new normal over the next decade. Example from Cleerly Imaging at SCCT 2022.

Legal considerations for artificial intelligence in radiology and cardiology

There are now more than 520 FDA-cleared AI algorithms and the majority are for radiology and cardiology, raising the question of who is liable if the AI gets something wrong.

February 3, 2023
Example of a cardiovascular information system (CVIS) cath lab reporting module with a coronary tree model that will auto complete sections of the report based on how the cardiologist modifies the model. Image from the ScImage booth at ACC 2022. Photo by Dave Fornell

VIDEO: 4 key trends in cardiovascular information systems, according to Signify Reseach

Signify Research shares the latest big trends in cardiovascular IT systems, including the role of EMR cardiology modules vs. third-party CVIS, structured reporting, integration into enterprise imaging and inclusion of ambulatory surgical centers. 

February 1, 2023
#CTA #photoncountingCT #aortaCT

Photon counting cuts CTA contrast dosage 25%

Not only does the low-volume contrast protocol preserve supplies, it also protects patients who might be vulnerable to adverse reactions and/or side effects from contrast use. 

January 26, 2023
As artificial intelligence (AI) adoption expands in radiology, there is growing concern that AI algorithms needs to undergo quality assurance (QA) reviews. How to validate radiology AI? How can you validate medical imaging AI?

Cardiologists use video-based AI model to ID coronary artery disease

A team of specialists out of Cedars-Sinai developed the deep learning model using TTEs from nearly 3,000 patients.

January 26, 2023

Increased use of CCTA improves CAD outcomes without raising costs

Researchers examined data from nearly 2 million patients, sharing their full findings in JACC: Cardiovascular Imaging.

January 23, 2023
Blood pressure

‘Revolutionary’ new CT scans identify the most common cause of high blood pressure

Primary aldosteronism (PA) is one the single most common causes of hypertension, but identifying patients with PA—and knowing which ones may benefit from a surgical treatment—can be quite challenging.

January 17, 2023
subtraction coronary CT angiography

Subtraction boosts CCTA accuracy, even in the presence of extensive calcium

Researchers recently found results yielded via subtraction CCTA to be similar to those produced by ICA in assessing stenosis grading.

January 11, 2023
transesophageal echocardiography (TEE)

Simulations help 'accelerate the TEE learning curve' for cardiology trainees

Simulation-based training can help cardiology fellows improve their TTE abilities, even when instructors or equipment are in short supply. 

January 11, 2023

Around the web

Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.

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. 

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