Artificial intelligence for disease diagnosis and risk prediction in nuclear cardiology
RJH Miller, C Huang, JX Liang, PJ Slomka - Journal of Nuclear Cardiology, 2022 - Elsevier
Artificial intelligence (AI) techniques have emerged as a highly efficient approach to
accurately and rapidly interpret diagnostic imaging and may play a vital role in nuclear …
accurately and rapidly interpret diagnostic imaging and may play a vital role in nuclear …
Quality metrics for single-photon emission computed tomography myocardial perfusion imaging: an ASNC information statement
FG Hage, AJ Einstein, K Ananthasubramaniam… - Journal of Nuclear …, 2023 - Elsevier
The central mission of the American Society of Nuclear Cardiology (ASNC) is to improve
cardiovascular outcomes through image-guided patient management. The most commonly …
cardiovascular outcomes through image-guided patient management. The most commonly …
[HTML][HTML] Visually estimated coronary artery calcium score improves SPECT-MPI risk stratification
C Trpkov, A Savtchenko, Z Liang, P Feng… - IJC Heart & …, 2021 - Elsevier
Aims Computed tomographic attenuation correction (CTAC) scans for single photon
emission computed tomography myocardial perfusion imaging (SPECT-MPI) may reveal …
emission computed tomography myocardial perfusion imaging (SPECT-MPI) may reveal …
AI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging
Epicardial adipose tissue (EAT) volume and attenuation are associated with cardiovascular
risk, but manual annotation is time-consuming. We evaluated whether automated deep …
risk, but manual annotation is time-consuming. We evaluated whether automated deep …
Clinical phenotypes among patients with normal cardiac perfusion using unsupervised learning: a retrospective observational study
Background Myocardial perfusion imaging (MPI) is one of the most common cardiac scans
and is used for diagnosis of coronary artery disease and assessment of cardiovascular risk …
and is used for diagnosis of coronary artery disease and assessment of cardiovascular risk …
Unsupervised learning to characterize patients with known coronary artery disease undergoing myocardial perfusion imaging
Purpose Patients with known coronary artery disease (CAD) comprise a heterogenous
population with varied clinical and imaging characteristics. Unsupervised machine learning …
population with varied clinical and imaging characteristics. Unsupervised machine learning …
Prognostic value of phase analysis for predicting adverse cardiac events beyond conventional single-photon emission computed tomography variables: results from …
K Kuronuma, RJH Miller, Y Otaki… - Circulation …, 2021 - Am Heart Assoc
Background: Phase analysis of single-photon emission computed tomography myocardial
perfusion imaging provides dyssynchrony information which correlates well with …
perfusion imaging provides dyssynchrony information which correlates well with …
Direct risk assessment from myocardial perfusion imaging using explainable deep learning
Background Myocardial perfusion imaging (MPI) is frequently used to provide risk
stratification, but methods to improve the accuracy of these predictions are needed …
stratification, but methods to improve the accuracy of these predictions are needed …
The Updated Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT 2.0)
The Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE
SPECT) has been expanded to include more patients and CT attenuation correction …
SPECT) has been expanded to include more patients and CT attenuation correction …
The application of artificial intelligence in nuclear cardiology
A decade of unprecedented progress in artificial intelligence (AI) has demonstrated a lot of
interest in medical imaging research including nuclear cardiology. AI has a potential to …
interest in medical imaging research including nuclear cardiology. AI has a potential to …