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

Computed Tomography01:10

Computed Tomography

7.6K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
7.6K
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

893
DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
893

You might also read

Related Articles

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

Sort by
Same author

Regional disparities in access to epinephrine auto-injectors for children and adults in Italy.

European annals of allergy and clinical immunology·2026
Same author

PD-L1 overexpression induces STAT signaling and promotes the secretion of pro-angiogenic cytokines in non-small cell lung cancer (NSCLC).

Lung cancer (Amsterdam, Netherlands)·2023
Same author

Resistance to osimertinib in advanced EGFR-mutated NSCLC: a prospective study of molecular genotyping on tissue and liquid biopsies.

British journal of cancer·2023
Same author

Consensus clustering methodology to improve molecular stratification of non-small cell lung cancer.

Scientific reports·2023
Same author

Defining hereditary alpha-tryptasemia as a risk/modifying factor for anaphylaxis: are we there yet?

European annals of allergy and clinical immunology·2023
Same author

A study of persistent symptoms and pulmonary function at 3 months post moderate or severe COVID-19 in Angola.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease·2023

Related Experiment Video

Updated: May 1, 2026

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer
11:31

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer

Published on: May 20, 2016

10.3K

Computed tomography-histologic correlations in lung cancer.

I Ariozzi, I Paladini, L Gnetti

    Pathologica
    |April 16, 2014
    PubMed
    Summary

    Accurate lung cancer diagnosis, especially early-stage adenocarcinoma, is challenging due to varied CT imaging features. A multidisciplinary approach improves differential diagnosis and radiologic-pathologic interpretation accuracy.

    More Related Videos

    Utilizing 18F-FDG PET/CT Imaging and Quantitative Histology to Measure Dynamic Changes in the Glucose Metabolism in Mouse Models of Lung Cancer
    06:51

    Utilizing 18F-FDG PET/CT Imaging and Quantitative Histology to Measure Dynamic Changes in the Glucose Metabolism in Mouse Models of Lung Cancer

    Published on: July 21, 2018

    19.0K
    Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
    08:05

    Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

    Published on: December 19, 2020

    13.4K

    Related Experiment Videos

    Last Updated: May 1, 2026

    Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer
    11:31

    Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer

    Published on: May 20, 2016

    10.3K
    Utilizing 18F-FDG PET/CT Imaging and Quantitative Histology to Measure Dynamic Changes in the Glucose Metabolism in Mouse Models of Lung Cancer
    06:51

    Utilizing 18F-FDG PET/CT Imaging and Quantitative Histology to Measure Dynamic Changes in the Glucose Metabolism in Mouse Models of Lung Cancer

    Published on: July 21, 2018

    19.0K
    Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
    08:05

    Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

    Published on: December 19, 2020

    13.4K

    Area of Science:

    • Oncology
    • Radiology
    • Pathology

    Background:

    • Multidisciplinary evaluation is crucial for managing lung cancer patients.
    • Accurate diagnosis of early-stage lung cancer presents a significant challenge in computed tomography (CT) imaging.
    • Adenocarcinoma, the most common lung cancer subtype, exhibits diverse radiological features, complicating diagnosis.

    Purpose of the Study:

    • To review common challenges in lung cancer diagnosis.
    • To highlight issues in paired radiological-histologic interpretation of CT findings.
    • To emphasize the role of a multidisciplinary approach in improving diagnostic accuracy.

    Main Methods:

    • Literature review focusing on CT imaging findings in lung cancer.
    • Analysis of diagnostic agreement between radiologists and clinicians.
    • Discussion of the impact of lung cancer classification on diagnosis.

    Main Results:

    • Early-stage lung cancer detection on CT has lower accuracy due to non-specific radiological features.
    • The 2011 lung cancer classification may have influenced diagnostic agreement.
    • Varied radiological presentations of adenocarcinoma contribute to diagnostic difficulties.

    Conclusions:

    • A multidisciplinary approach enhances the differential diagnosis of ambiguous radiological findings in lung cancer.
    • Addressing challenges in radiological-histologic interpretation is key to improving lung cancer diagnosis.
    • Improving diagnostic accuracy for lung cancer, particularly adenocarcinoma, requires collaborative efforts.