News | Clinical Decision Support | February 11, 2019

New Appropriate Use Criteria Outlined for Multimodality Imaging of Nonvalvular Heart Disease

Guidance document from 10 societies discusses assessment of cardiac structure and function

New Appropriate Use Criteria Outlined for Multimodality Imaging of Nonvalvular Heart Disease

February 11, 2019 — The American College of Cardiology (ACC), along with nine other cardiology professional societies, recently published a new guidance document for appropriate use criteria (AUC) for multimodality imaging in the assessment of cardiac structure and function in nonvalvular heart disease. The guidance was published online Jan. 7 in the Journal of the American College of Cardiology (JACC).  

This document is the second of two companion AUC documents. The first document addresses the evaluation and use of multimodality imaging in the diagnosis and management of valvular heart disease, whereas this document addresses this topic with regard to structural (nonvalvular) heart disease. While dealing with different subjects, the two documents do share a common structure and feature some clinical overlap. The goal of the companion AUC documents is to provide a comprehensive resource for multimodality imaging in the context of structural and valvular heart disease, encompassing multiple imaging modalities.

For more information: www.acc.org

 

Reference

1. Doherty J.U., Kort S., Mehran R., et al. ACC/AATS/AHA/ASE/ASNC/HRS/SCAI/SCCT/SCMR/STS 2019 Appropriate Use Criteria for Multimodality Imaging in the Assessment of Cardiac Structure and Function in Nonvalvular Heart Disease. Journal of the American College of Cardiology, Jan. 7, 2019. https://doi.org/10.1016/j.jacc.2018.10.038

Related Content

A high-fidelity 3-D tractography of the left ventricle heart muscle fibers of a mouse

Figure 1. A high-fidelity 3-D tractography of the left ventricle heart muscle fibers of a mouse from Amsterdam Ph.D. researcher Gustav Strijkers.

News | Cardiac Imaging | June 07, 2019
The Amsterdam University Medical Center has won MR Solutions’ Image of the Year 2019 award for the best molecular...
At #ACC.19, Siemens unveiled a version of its go.Top platform optimized for cardiovascular imaging. The newly packaged scanner can generate the data needed to do CT-based FFR (fractional flow reserve).

At #ACC.19, Siemens unveiled a version of its go.Top platform optimized for cardiovascular imaging. The newly packaged scanner can generate the data needed to do CT-based FFR (fractional flow reserve). Photo by Greg Freiherr

Feature | Cardiac Imaging | March 22, 2019 | By Greg Freiherr
Reflecting a trend toward the increased use of ...
SyncVision iFR Co-registration from Philips Healthcare maps iFR pressure readings onto angiogram.

SyncVision iFR Co-registration from Philips Healthcare maps iFR pressure readings onto angiogram. Results from an international study presented at #ACC19 show that pressure readings in coronary arteries may identify locations of stenoses remaining after cardiac cath interventions.

Feature | Cardiac Imaging | March 18, 2019 | By Greg Freiherr
As many as one in four patients who undergo cath lab interventions can benefit from a technology that identifies the
Jennifer N. A. Silva, M.D., a pediatric cardiologist at Washington University School of Medicine in Saint Louis, Mo., describes “mixed reality” at ACC19 Future Hub.

Jennifer N. A. Silva, M.D., a pediatric cardiologist at Washington University School of Medicine in Saint Louis, Mo., describes “mixed reality” at ACC19 Future Hub.

Feature | Cardiac Imaging | March 17, 2019 | By Greg Freiherr
Virtual reality (VR) and its less immersive kin, augmented reality (AR), are gaining traction in some medical applica
WVU cardiology chief Partho Sengupta, M.D., describes at ACC 2019 how artificial intelligence already helps cardiologists in echocardiography.

WVU cardiology chief Partho Sengupta, M.D., describes at ACC 2019 how artificial intelligence already helps cardiologists in echocardiography. Photo by Greg Freiherr

Feature | Cardiac Imaging | March 16, 2019 | By Greg Freiherr
Machine learning is already having an enormous impact on cardiology, automatically calculating measurements in echoca
Podcast | Cardiac Imaging | March 15, 2019
Debate About Coronary Testing Highlights ACC Session

Collage depicts broad applications in machine learning or deep learning (DL) that can be applied to advanced medical imaging technologies. Size of the liver and its fat fraction — 22 percent — (top middle in collage) can be quantified automatically using an algorithm developed by Dr. Albert Hsiao and his team at the University of California San Diego. This and other information that might be mined by DL algorithms from CT and MR images could help personalize patients’ treatment. Collage provided by Albert Hsiao

Feature | Cardiac Imaging | March 12, 2019 | By Greg Freiherr
Acquiring these data could change patient management
Podcast | Cardiac Imaging | March 12, 2019
How smart algorithms might reduce the burden of modern practice
Podcast | Cardiac Imaging | March 08, 2019
Why CT angiography cannot replace invasive angiography
Podcast | Cardiac Imaging | March 04, 2019
AI, Mobile Technologies Are Changing How We Think About Cardiac Disease
Overlay Init