Lung Imaging
Lung Imaging - Related Videos
05:55
Whole Lung Agarose Inflation: A Method of Preparing Lungs for Ex vivo Live Imaging
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2023
This video describes a method of preparing lungs for ex vivo live imaging to study interactions between cancer cells and stromal cells, using agarose for inflation. In the sample protocol, agarose inflation procedure is described before observing live cellular interactions.
11:26
Real-time X-ray Imaging of Lung Fluid Volumes in Neonatal Mouse Lung
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Cited by 1 •
2016
We present a protocol to assess the rate of alveolar fluid clearance or pulmonary edema in neonatal mouse lung using X-ray imaging technology.
11:19
Ex vivo Live Imaging of Lung Metastasis and Their Microenvironment
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Cited by 6 •
2016
We describe a relatively simple method for ex vivo live imaging of the tumor cell-stroma interactions within lung metastasis, utilizing fluorescent reporters in mice. Using spinning-disk confocal microscopy, this technique enables visualization of live cells for at least 4 hr and could be adapted to study other inflammatory lung conditions.
07:19
Long-term High-Resolution Intravital Microscopy in the Lung with a Vacuum Stabilized Imaging Window
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Cited by 32 •
2016
This protocol describes the use of multiphoton microscopy to perform long-term high-resolution, single cell imaging of the intact lung in real time using a vacuum stabilized imaging window.
02:42
Imaging Bacterial Localization and Host Interaction in Human Lung Tissue
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2026
Source: Mills, B., et al., Optical Screening of Novel Bacteria-specific Probes on Ex Vivo Human Lung Tissue by Confocal Laser Endomicroscopy. J. Vis. Exp. (2017)This video demonstrates real-time imaging of fluorescently labeled Staphylococcus aureus in suspension and lung tissue using fibered confocal fluorescence microscopy.
FAQs
Each modality emphasizes a different biological or physical property. CT distinguishes tissues through differences in X-ray attenuation, MRI uses magnetic behavior, and PET detects radiotracer uptake. Consequently, imaging can provide complementary information about lung structure, tissue characteristics, and tumor-associated metabolic activity, helping researchers characterize disease more comprehensively than relying on a single image type.
Contrast agents increase the distinction between tissues or highlight blood flow, making selected structures easier to differentiate on images. This added contrast can support more precise interpretation of tumor location and surrounding tissue relationships. In research studies, improved visualization may strengthen assessments of tumor characteristics, treatment planning, and changes observed during follow-up imaging.
Quantitative analysis converts image features into measurable information, including tumor size, metabolic changes, and heterogeneity. Heterogeneity describes variation within a tumor rather than treating it as uniform. Tracking these measurements can reveal patterns that visual inspection may miss, supporting biomarker development and more consistent evaluation of disease behavior or treatment response.
Selection depends on the information the study needs, such as structural visualization, tumor characterization, staging, treatment planning, or response assessment. Chest radiography, CT, MRI, and PET can therefore serve different or complementary purposes. Combining findings across methods allows investigators to relate anatomy, tissue or blood-flow distinctions, and radiotracer uptake to the research question.
Imaging helps investigators locate pulmonary tumors and characterize their extent, supplying information needed for staging. Those findings can then inform treatment planning by showing where disease is situated and how it relates to surrounding structures. In cancer research, this role also helps standardize how participants are evaluated before treatment and how disease status is documented.
Repeated imaging can document whether tumors change in size, metabolism, or internal heterogeneity over the course of a study. These outcomes support treatment-response assessment and may reveal patterns useful for developing imaging biomarkers. By linking measurable image changes with study endpoints, investigators can improve clinical study design and evaluate disease progression more systematically.