Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Quantitative single photon emission computed tomography/computed tomography of Tc-99m-pyrophosphate scans: metrics for short-term risk stratification in transthyretin cardiac amyloidosis.

Nuclear medicine communications·2026
Same author

Radiation Dose in Coronary Artery Disease Diagnostic Imaging-Reply.

JAMA·2026
Same author

Transient Ischemic Dilation with <sup>18</sup>F-flurpiridaz PET: Establishing Thresholds for a Novel Radiotracer.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology·2026
Same author

Prevalence and burden of coronary artery disease in young adults undergoing clinically indicated coronary CT angiography.

Open heart·2026
Same author

Automated AI-Based Aortic Measurements From Attenuation Correction CT as an Adjunctive Cardiovascular Risk Biomarker: An International Multicenter Study.

Circulation. Cardiovascular imaging·2026
Same author

Machine Learning Multiorgan Analysis of Coronary CT Angiography Body Composition, Myocardial Infarction, and Mortality in the SCOT-HEART Trial.

Radiology·2026

Related Experiment Video

Updated: Sep 15, 2025

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals
11:09

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals

Published on: December 16, 2022

3.9K

AI-Derived Splenic Response in Cardiac PET Predicts Mortality: A Multi-Site Study.

Naga L Dharmavaram1, Giselle Ramirez1, Aakash Shanbhag1,2

  • 1Departments of Medicine (Division of Artificial Intelligence in Medicine), Imaging, Cardiology, and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA.

Medrxiv : the Preprint Server for Health Sciences
|July 16, 2025
PubMed
Summary

Artificial intelligence-derived splenic ratio (SR) indicates inadequate stress during myocardial perfusion imaging (MPI). Elevated SR independently predicts major adverse cardiovascular events, aiding risk stratification in 82Rb PET MPI.

Keywords:
Artificial IntelligenceMyocardial perfusion imagingNuclear CardiologySplenic Switch-off

More Related Videos

MRI and PET in Mouse Models of Myocardial Infarction
10:46

MRI and PET in Mouse Models of Myocardial Infarction

Published on: December 19, 2013

11.9K
PET Imaging of Neuroinflammation Using [11C]DPA-713 in a Mouse Model of Ischemic Stroke
12:01

PET Imaging of Neuroinflammation Using [11C]DPA-713 in a Mouse Model of Ischemic Stroke

Published on: June 14, 2018

12.9K

Related Experiment Videos

Last Updated: Sep 15, 2025

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals
11:09

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals

Published on: December 16, 2022

3.9K
MRI and PET in Mouse Models of Myocardial Infarction
10:46

MRI and PET in Mouse Models of Myocardial Infarction

Published on: December 19, 2013

11.9K
PET Imaging of Neuroinflammation Using [11C]DPA-713 in a Mouse Model of Ischemic Stroke
12:01

PET Imaging of Neuroinflammation Using [11C]DPA-713 in a Mouse Model of Ischemic Stroke

Published on: June 14, 2018

12.9K

Area of Science:

  • Cardiology
  • Radiology
  • Medical Imaging

Background:

  • Inadequate pharmacologic stress during myocardial perfusion imaging (MPI) can compromise diagnostic accuracy.
  • The splenic ratio (SR) is an emerging imaging biomarker for assessing stress adequacy in MPI.
  • Artificial intelligence (AI) offers automated calculation of SR.

Purpose of the Study:

  • To assess the prognostic capability of AI-derived SR in a large multicenter cohort undergoing regadenoson stress testing with 82Rb PET.
  • To determine if AI-derived SR predicts major adverse cardiovascular events (MACE).

Main Methods:

  • Retrospective analysis of 10,913 patients from the REFINE PET registry with clinically indicated MPI.
  • Automated calculation of SR (stress vs. rest splenic uptake ratio).
  • Survival analysis using Kaplan-Meier and Cox models, adjusting for covariates including myocardial flow reserve (MFR).

Main Results:

  • Patients with high SR (≥90th percentile) showed an increased risk of MACE (HR 1.18).
  • This association persisted even in patients with preserved MFR (≥2) (HR 1.44).
  • AI-derived SR demonstrated independent association with adverse cardiovascular outcomes.

Conclusions:

  • Elevated AI-derived SR is an independent predictor of adverse cardiovascular outcomes.
  • SR serves as a novel, automated imaging biomarker for risk stratification in 82Rb PET MPI.
  • These findings highlight the importance of stress adequacy in MPI interpretation.