Tumor Tissue Imaging
Tumor Tissue Imaging - Related Videos
11:12
Tissue Engineering of a Human 3D in vitro Tumor Test System
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Cited by 34 •
2013
Methods to create human 3D tumor tissues as test systems are described. These technologies are based on a decellularized Biological Vascularized Scaffold (BioVaSc), primary human cells and a tumor cell line, which can be cultured under static as well as under dynamic conditions in a flow bioreactor.
02:07
Imaging Tumor Cell Migration in Glioblastoma Tissue Using Time-Lapse Scanning Confocal Microscopy
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2025
Source: Parker, J. J., et al. A Human Glioblastoma Organotypic Slice Culture Model for Study of Tumor Cell Migration and Patient-specific Effects of Anti-Invasive Drugs. J. Vis. Exp. (2017)This video showcases the imaging of glioblastoma tissue slices expressing green fluorescent protein (GFP) via confocal microscopy. High-resolution images are captured at consistent intervals to track tumor cell movement and direction.
02:31
FFPE Tumor Tissue Macrodissection: A Technique to Obtain Specific Tumorous Tissue from Unstained Specimens
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2023
This video describes a method for the manual macrodissection of cancer tissue from unstained tissue specimens to obtain a specific cancer tissue. The tissue section can be processed further to obtain DNA for genome-wide studies on gastrointestinal cancers.
14:04
Viral Nanoparticles for In vivo Tumor Imaging
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Cited by 45 •
2012
Plant viral nanoparticles (VNPs) are promising platforms for applications in biomedicine. Here, we describe the procedures for plant VNP propagation, purification, characterization, and bioconjugation. Finally, we show the application of VNPs for tumor homing and imaging using a mouse xenograft model and fluorescence imaging.
09:18
Multianimal Magnetic Resonance Imaging for Tumor Measurements in Pancreatic Cancer Mouse Models
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2026
This protocol uses a multichamber bed for parallel magnetic resonance imaging (MRI) of up to four animals to detect pancreatic adenocarcinoma tumors in genetically engineered mouse models. This multianimal MRI protocol is fast and cost-effective for detecting and measuring tumors, facilitating animal selection for preclinical studies and longitudinal monitoring of tumor growth.
FAQs
Tumor tissue imaging uses differences in light absorption, fluorescence, magnetic properties, or radiotracer accumulation to distinguish tissue features. These signals do not all represent the same biology: some emphasize architecture or cellular features, whereas others reveal molecular signals or tracer distribution. Selecting the contrast mechanism therefore affects which tumor characteristics become visible and how findings are interpreted.
Image processing converts raw signals into maps that link visual patterns with anatomical and biological features. This step helps organize information from tissue structure, cellular characteristics, and molecular signals rather than leaving the findings as uninterpreted intensity differences. The resulting maps can support consistent characterization of tumors and provide a basis for comparing features relevant to invasion, vascularization, or treatment resistance.
Multiplex imaging can examine multiple signals within the same tissue context, while three-dimensional imaging adds spatial information across tumor volume. Together, these approaches may connect cellular or molecular patterns with architecture more completely than a single signal or limited view. Their value for precision oncology lies in strengthening quantitative pathology and linking spatial features to biologic behavior.
Reading tumor images requires attention to which biological feature generates the signal. Architecture and cellular features describe organization, while molecular signals or radiotracer accumulation can indicate different aspects of tumor biology. This distinction matters because an image may show structural abnormality without directly representing every molecular process, so interpretation should remain tied to the modality and signal being measured.
Within medicine, these images can contribute at several stages: detecting a tumor, classifying it, guiding a biopsy, planning treatment, and assessing therapeutic response. Imaging methods may therefore serve different purposes depending on the clinical question. Their usefulness comes from relating visible tissue features or signals to a specific decision, rather than treating every image as interchangeable.
For biopsy guidance, imaging supplies spatial information about tumor tissue that can help direct sampling, while treatment planning uses the depicted tumor characteristics to inform how therapy is organized. These applications show why images are valuable beyond detection: they connect visualization with an action in the clinical workflow, although the relevant information depends on the modality and image features available.
During follow-up, changes in tumor imaging signals or tissue appearance can be examined for evidence of therapeutic response. Interpretation depends on the biological or anatomical feature represented by the modality, because different contrasts emphasize different signals. This makes imaging useful for tracking response while also supporting research into why some tumors show treatment resistance.
Research applications extend beyond individual tumor detection. Investigators can use images to relate tissue structure to invasion, vascularization, and treatment resistance, then apply quantitative pathology to measure those relationships. Multiplex and three-dimensional approaches may add complementary spatial and molecular information, helping researchers study tumor biology and potentially strengthen precision oncology.