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

AI-augmented thyroid scintigraphy for robust classification of disease.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2026
Same author

Detection of Valve Vegetations in Native and Prosthetic Valves using Echocardiographic Radiomics and Deep Learning on Transesophageal Echocardiography Images.

Journal of biomedical physics & engineering·2026
Same author

Design and geometry optimization of a dual-panel prostate dedicated PET scanner.

Physics in medicine and biology·2026
Same author

Enhancing pulmonary embolism diagnosis: a squeeze-and-attention U-Net for precise detection and segmentation in CT angiography.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2026
Same author

Imaging tumor microenvironment: clinical experience with 68Ga-FAPI PET/CT across multiple cancer types.

The quarterly journal of nuclear medicine and molecular imaging : official publication of the Italian Association of Nuclear Medicine (AIMN) [and] the International Association of Radiopharmacology (IAR), [and] Section of the Society of...·2026
Same author

NeuroMix-DL: Improving imaging quality of a fast multiparametric MRI protocol using deep learning.

European journal of radiology·2026

Related Experiment Video

Updated: Dec 23, 2025

Use of a Multi-compartment Dynamic Single Enzyme Phantom for Studies of Hyperpolarized Magnetic Resonance Agents
08:59

Use of a Multi-compartment Dynamic Single Enzyme Phantom for Studies of Hyperpolarized Magnetic Resonance Agents

Published on: April 15, 2016

7.1K

Cardiac SPECT radiomic features repeatability and reproducibility: A multi-scanner phantom study.

Mohammad Edalat-Javid1, Isaac Shiri2, Ghasem Hajianfar3

  • 1Department of Energy Engineering and Physics, Amir Kabir University of Technology, Tehran, Iran.

Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology
|April 26, 2020
PubMed
Summary
This summary is machine-generated.

Cardiac SPECT radiomic features show variable robustness against imaging setting changes. Only specific texture features like IDMN and IDN demonstrated high reproducibility, suggesting careful selection for clinical studies.

Keywords:
SPECT/CTcardiovascular imagingradiomicsrepeatabilityreproducibility

More Related Videos

Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement
06:33

Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement

Published on: July 29, 2013

11.6K
Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
07:21

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

Published on: February 12, 2011

14.7K

Related Experiment Videos

Last Updated: Dec 23, 2025

Use of a Multi-compartment Dynamic Single Enzyme Phantom for Studies of Hyperpolarized Magnetic Resonance Agents
08:59

Use of a Multi-compartment Dynamic Single Enzyme Phantom for Studies of Hyperpolarized Magnetic Resonance Agents

Published on: April 15, 2016

7.1K
Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement
06:33

Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement

Published on: July 29, 2013

11.6K
Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking
07:21

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

Published on: February 12, 2011

14.7K

Area of Science:

  • Medical Imaging
  • Radiomics
  • Nuclear Medicine

Background:

  • Radiomic features in cardiac Single-Photon Emission Computed Tomography (SPECT) imaging are increasingly utilized.
  • Assessing the robustness of these features is crucial for reliable clinical application.

Purpose of the Study:

  • To evaluate the impact of varying imaging acquisition and reconstruction parameters on the robustness of cardiac SPECT radiomic features.
  • To identify radiomic features that maintain high reproducibility across different SPECT imaging settings.

Main Methods:

  • Four SPECT/SPECT-CT cameras imaged a cardiac phantom with 99mTc.
  • Acquisition and reconstruction parameters (views, matrix size, AC, algorithm, iterations, subsets, filters) were systematically varied.
  • Eighty-seven radiomic features were extracted and their reproducibility assessed using the coefficient of variation (COV).

Main Results:

  • Only Inverse Difference Moment Normalized (IDMN), Inverse Difference Normalized (IDN), Run Percentage (RP), Zone Entropy (ZE), and Dependence Entropy (DE) features showed high reproducibility (COV ≤ 5%).
  • Large Area Low Gray Level Emphasis (LALGLE), Small Area Low Gray Level Emphasis (SALGLE), Low Gray Level Zone Emphasis (LGLZE), and Small Dependence Low Gray Level Emphasis (SDLGLE) features exhibited low reproducibility (COV > 20%).
  • Matrix size significantly impacted feature variability, with 82.8% of features showing COV > 20% upon modification.

Conclusions:

  • Cardiac SPECT radiomic feature reproducibility is feature-dependent and influenced by imaging protocols.
  • Specific texture features demonstrate potential for robust clinical application.
  • Further validation of reproducible features in clinical settings is warranted.