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

TNF-alpha is a master regulator of drug-specific T-cell activation.

The Journal of allergy and clinical immunology·2026
Same author

Predicting Recurrence Risk of Glioblastoma Based on Preoperative-Postoperative Longitudinal MRI: A Multicenter Study.

Bioengineering (Basel, Switzerland)·2026
Same author

Integrative genetic analysis reveals shared genetic architecture underlying coronary artery disease, CT-Defined coronary atherosclerosis, and cardiometabolic risk factors.

Functional & integrative genomics·2026
Same author

Sea Urchin-Like Platinum-Coated Gold Nanozymes-Based Ultra-Sensitive Colorimetric Detection and Mechanism Differentiation Platform for Dual-Marker Guided Genotoxicity Assessment.

Advanced healthcare materials·2026
Same author

Leveraging the Oryza telomere-to-telomere genome and wild-rice substitution lines for rice-quality improvement.

Current biology : CB·2026
Same author

Cardiac computed tomography-derived left atrial volume index as a predictor of major adverse cardiovascular events after transcatheter aortic valve replacement.

Quantitative imaging in medicine and surgery·2026

Related Experiment Video

Updated: Sep 24, 2025

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
10:26

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

Published on: May 19, 2023

2.1K

Improved interobserver agreement on nodule type and Lung-RADS classification of subsolid nodules using computer-aided

Jun Shu1, Didi Wen1, Ziliang Xu1

  • 1Department of Radiology, Xijing Hospital, Fourth Military Medical University, Changle West Road No. 127 Xi'an City 710032, Shaanxi Province, China.

European Journal of Radiology
|May 10, 2022
PubMed
Summary

A semi-automated tool significantly improved interobserver agreement for classifying subsolid nodules (SSNs) using Lung CT Screening Reporting and Data System (Lung-RADS). This computer-aided method enhances nodule assessment accuracy for lung cancer screening.

Keywords:
Cancer screeningInterobserver variationLung cancerMultidetector computed tomography

More Related Videos

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

1.6K
Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy
05:24

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy

Published on: January 10, 2025

518

Related Experiment Videos

Last Updated: Sep 24, 2025

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
10:26

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

Published on: May 19, 2023

2.1K
Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer
07:53

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

1.6K
Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy
05:24

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy

Published on: January 10, 2025

518

Area of Science:

  • Pulmonary Medicine
  • Radiology
  • Artificial Intelligence in Medical Imaging

Background:

  • Lung CT Screening Reporting and Data System (Lung-RADS) classification of subsolid nodules (SSNs) faces challenges due to inconsistent interobserver agreement in determining nodule type and size.
  • Accurate classification is crucial for effective lung cancer screening and patient management.

Purpose of the Study:

  • To evaluate the impact of a semi-automated computer-aided method on improving interobserver agreement for Lung-RADS classification of SSNs.
  • To assess the accuracy of the computer-aided tool in nodule characterization and size measurement.

Main Methods:

  • 156 SSNs from 121 patients undergoing lung cancer screening were analyzed.
  • Three radiologists independently classified nodules and measured sizes (total and solid components) manually and with a semi-automated tool.
  • Interobserver agreement was assessed using intraclass correlation coefficients (ICC) and Fleiss kappa statistics.

Main Results:

  • The semi-automated tool significantly increased interobserver agreement for nodule type (kappa 0.974 vs. 0.783) and Lung-RADS classification (kappa 0.958-0.952 vs. 0.652).
  • Semi-automated size measurements showed smaller bias and narrower limits of agreement compared to manual measurements.
  • The tool identified more invasive adenocarcinomas as higher-risk nodules (Lung-RADS 4B) compared to manual assessment.

Conclusions:

  • Semi-automated assessment enhances interobserver agreement in Lung-RADS classification for SSNs.
  • This computer-aided approach improves nodule characterization and may lead to more accurate risk stratification, particularly for invasive adenocarcinomas.