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

Imaging Studies II: Positron Emission Tomography and Scintigraphy01:25

Imaging Studies II: Positron Emission Tomography and Scintigraphy

853
Positron Emission Tomography (PET) is a medical imaging technique that provides crucial insights into the body's physiological functions at a molecular level. It is an indispensable resource for diagnosing, staging, and monitoring various illnesses, notably cancer, neurological disorders, and cardiovascular conditions.
Fundamental Principles of PET
853

You might also read

Related Articles

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

Sort by
Same author

Macrophage-secreted brain-derived neurotrophic factor promotes tumor growth in triple-negative breast cancer by inducing axonogenesis.

Cell death and differentiation·2026
Same author

Role of apparent diffusion coefficient (ADC) and MRI-derived parameters in identifying p53-abnormal subtypes of endometrial cancer.

European journal of radiology open·2026
Same author

Beyond the tumor: recurrence-prone radiomics for prognostication in negative PSMA PET/CT scans of prostate cancer.

Biomedical physics & engineering express·2026
Same author

Pituitary Home Hypothesis: A Spatial Perspective on Glandular Function.

World neurosurgery·2026
Same author

Nociceptor neurons suppress antitumor immunity in breast cancer.

Research square·2026
Same author

Assessing ascorbic and salicylic acid-induced drought tolerance in marjoram (Origanum vulgare L.) using the MGIDI index.

BMC plant biology·2026

Related Experiment Video

Updated: May 2, 2026

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer
03:55

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer

Published on: June 9, 2023

469

ELTIRADS framework for thyroid nodule classification integrating elastography, TIRADS, and radiomics with

Erfan Barzegar-Golmoghani1, Mobin Mohebi1,2, Zahra Gohari3

  • 1Department of Biomedical Engineering, Tarbiat Modares University, Tehran, Iran.

Scientific Reports
|March 14, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces ELTIRADS, a new AI approach combining ultrasound, elastography, and radiomics for accurate malignant thyroid nodule detection. It significantly improves diagnostic performance over traditional methods.

Keywords:
ElastographyHierarchical clusteringInterpretable machine learningNodule classificationRadiomics

More Related Videos

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.7K
Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
05:41

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis

Published on: February 9, 2024

514

Related Experiment Videos

Last Updated: May 2, 2026

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer
03:55

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer

Published on: June 9, 2023

469
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.7K
Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
05:41

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis

Published on: February 9, 2024

514

Area of Science:

  • Oncology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Early detection of malignant thyroid nodules is vital for effective treatment.
  • Traditional diagnostic methods for thyroid nodules suffer from expert variability and limited advanced imaging integration.

Purpose of the Study:

  • To investigate a novel multimodal approach (ELTIRADS) for enhanced thyroid nodule malignancy detection.
  • To integrate traditional methods with advanced machine learning and imaging techniques.

Main Methods:

  • A prospective cohort study of 181 patients with 181 thyroid nodules.
  • Data included patient demographics, ultrasound elastography, and radiomic features.
  • A Support Vector Machine (SVM) classifier was trained using ELTIRADS, incorporating Thyroid Imaging Reporting and Data System (TIRADS) scores, elastography, and radiomic features.

Main Results:

  • The ELTIRADS SVM model achieved high diagnostic accuracy (0.92), sensitivity (0.89), specificity (0.94), precision (0.89), and F1 score (0.89).
  • Interpretable machine learning techniques like SHAP and PDP were used for enhanced understanding of model predictions.

Conclusions:

  • The multimodal ELTIRADS approach shows significant promise for improving the accuracy of malignant thyroid nodule detection.
  • This advancement contributes to personalized and precision medicine in thyroid cancer diagnosis and research.