Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Radiological Investigation III: Pulmonary Angiogram and PET Scan

Radiological Investigation III: Pulmonary Angiogram and PET Scan

Radiological investigations are paramount in the diagnosis and management of various pulmonary diseases. Two essential investigations are the Pulmonary Angiogram and the Positron Emission Tomography (PET) Scan.
Pulmonary Angiogram
A Pulmonary Angiogram is an invasive procedure involving injecting a contrast medium through a catheter threaded into the pulmonary artery or the right side of the heart to visualize the pulmonary vasculature. Computed Tomography (CT) scans have mainly replaced this...

Radiological Investigation II: MRI and Ventilation Perfusion Scan

Radiological Investigation II: MRI and Ventilation Perfusion Scan

Description
Magnetic Resonance Imaging (MRI) and Ventilation Perfusion Scans are two radiological investigations that offer detailed diagnostic images of the body, particularly lung structures.
MRI
MRI uses magnetic fields and radiofrequency signals to distinguish between normal and abnormal tissues. This technology provides a more detailed diagnostic image than CT scans, enabling it to characterize pulmonary nodules, stage bronchogenic carcinoma, and evaluate inflammatory activity in...

Radiological Investigation I: X-ray and CT

Radiological Investigation I: X-ray and CT

Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and...

You might also read

Related Articles

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

Sort by

Same author

Decumbic acid derivatives from soil fungus <i>Lasiodiplodia</i> sp. BG1083.

Natural product research·2026

Same author

CT-Guided Anchored Needle Versus Hook-Wire Localization for Pulmonary Nodules: A Meta-Analysis.

Journal of computer assisted tomography·2025

Same author

Stent with radioactive seeds placement for obstructive hilar cholangiocarcinoma: comparison between unilateral and bilateral placement.

Wideochirurgia i inne techniki maloinwazyjne = Videosurgery and other miniinvasive techniques·2025

Same author

Liu Wei Di Huang Decoction Alleviates Renal Fibrosis by Inhibiting Endothelial Mesenchymal Transitions via Upregulating Sirt1 Expression and Inhibiting the Wnt/β-Catenin Signaling Pathway.

Drug design, development and therapy·2025

Same author

Resting-state EEG alterations and cognitive impairment in atrial fibrillation: insights into neural biomarkers and functional connectivity.

Frontiers in neurology·2025

Same author

Frailty: An Important Determinant Influencing Glycaemic Control in Elderly Chinese Patients Diagnosed With Type 2 Diabetes.

Clinical and experimental pharmacology & physiology·2025

Search research articles

Related Experiment Video

Updated: May 25, 2025

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

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

Published on: May 19, 2023

CT radiomics based model for differentiating malignant and benign small (≤20mm) solid pulmonary nodules.

Jing-Xi Sun¹, Xuan-Xuan Zhou¹, Yan-Jin Yu¹

¹Department of Radiology, Xuzhou Central Hospital, Xuzhou, China.

Frontiers in Oncology

|February 28, 2025

Summary

A new CT radiomics model accurately differentiates benign and malignant small pulmonary nodules (SPNs). This tool aids in diagnosing SPNs, improving patient management and reducing unnecessary procedures.

Keywords:

CT prediction pulmonary nodule radiomics small

More Related Videos

$Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy$

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy

Published on: January 10, 2025

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

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

Published on: October 13, 2023

Related Experiment Videos

Last Updated: May 25, 2025

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

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

Published on: May 19, 2023

$Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy$

Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy

Published on: January 10, 2025

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

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

Published on: October 13, 2023

Area of Science:

Radiology
Medical Imaging
Oncology

Background:

Limited models exist for evaluating small (≤ 20 mm) solid pulmonary nodules (SPNs) using computed tomography (CT) radiomics.
Accurate differentiation of benign and malignant SPNs is crucial for patient management.

Purpose of the Study:

To develop and validate a CT radiomics-based model for distinguishing benign from malignant small SPNs.

Main Methods:

A cohort of 210 patients with small SPNs was randomly divided into training (168) and testing (42) groups.
CT images were analyzed to extract radiomics features.
A radiomics scoring model was developed using logistic regression and validated in the testing cohort.

Main Results:

A model incorporating 9 CT radiomics features, lobulation, spiculation, and diameter demonstrated high diagnostic accuracy.
The CT radiomics-based model achieved an area under the curve (AUC) of 0.957 (training) and 0.943 (testing).
Significant predictors included lobulation (P < 0.001), spiculation (P < 0.001), and diameter (P < 0.001).

Conclusions:

The developed CT radiomics-based model provides valuable diagnostic accuracy for differentiating benign and malignant small SPNs.
This model can potentially improve the diagnostic process for small pulmonary nodules.