Tumor Size Quantification
Tumor Size Quantification - Related Videos
11:38
An Innovative Method for Exosome Quantification and Size Measurement
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Cited by 102 •
2015
A method for isolation of exosomes from whole blood and further analysis by nanoparticle tracking using a semi-automatic instrument is presented in this article. The presented technology provides an extremely sensitive method for visualizing and analyzing particles in liquid suspension.
10:44
Production of Large Numbers of Size-controlled Tumor Spheroids Using Microwell Plates
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Cited by 36 •
2013
We introduce a protocol for the generation of large numbers (thousands to hundreds of thousands) of uniform size- and composition-controlled tumor spheroids, using commercially available microwell plates.
12:01
Quantification and Size-profiling of Extracellular Vesicles Using Tunable Resistive Pulse Sensing
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Cited by 99 •
2014
Extracellular vesicles play important roles in physiological and pathological processes, including coagulation, immune responses, and cancer or as potential therapeutic agents in drug delivery or regenerative medicine. This protocol presents methods for the quantification and size characterization of isolated and non-isolated extracellular vesicles in various fluids using tunable resistive pulse sensing.
10:31
The Drosophila Imaginal Disc Tumor Model: Visualization and Quantification of Gene Expression and Tumor Invasiveness Using Genetic Mosaics
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Cited by 11 •
2016
This protocol demonstrates how to generate fluorescently marked, genetically defined clonal tumors in the Drosophila eye/antennal imaginal discs (EAD). It describes how to dissect the EAD and brain from the third instar larvae and how to process them to visualize and quantify gene expression changes and tumor invasiveness.
16:59
Computer-assisted Large-scale Visualization and Quantification of Pancreatic Islet Mass, Size Distribution and Architecture
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Cited by 14 •
2011
Novel computer-assisted methods of large-scale procurement and analysis of immunohistochemically stained pancreatic specimens are described: (1) Virtual Slice capture of the entire section; (2) Mass analysis of large-scale data; (3) Reconstruction of 2D Virtual Slices; (4) 3D islet mapping; and (5) Mathematical analysis.
FAQs
The measured boundary determines which tissue is included in the result. A boundary placed differently can alter reported dimensions, area, or volume even when the underlying tumor has not changed. For that reason, physical, imaging-based, and digital workflows depend on consistent boundary identification to make repeated measurements and group comparisons meaningful.
Geometric formulas translate measured dimensions into an estimated volume, whereas segmentation-based analysis uses a delineated tumor boundary to calculate volume from image data. These approaches therefore rely on different intermediate information: selected dimensions in one case and the mapped region in the other. Recognizing this distinction helps investigators interpret results according to how the measurement was generated.
Standardization makes measurements comparable across treatment groups and across time. Without a consistent approach, apparent differences may reflect the measurement process rather than tumor dynamics. In cancer research, this matters when investigators classify a tumor as growing, regressing, or stable and when they use size changes to evaluate therapeutic response.
A practical workflow begins by choosing physical calipers, medical or laboratory imaging, or digital image analysis for the available tumor representation. Investigators then identify the tumor boundaries, record dimensions or area when appropriate, and apply a geometric formula or segmentation-based volume calculation. Repeating the same measurement approach over time supports reliable tracking of change.
Tumor Size Quantification helps investigators compare treatment groups by converting tumor observations into measurements that can be followed over time. The resulting trajectories can indicate growth, regression, or stable disease, providing an outcome measure for therapeutic studies. Its value depends on consistent acquisition and interpretation, because treatment conclusions are tied to the measured change.
Within cancer research, size measurements can be paired with biological investigations to examine how tumor dynamics relate to underlying mechanisms. They can also help connect experimental findings with clinical outcomes. This makes the measurement useful beyond a single endpoint: it supports evaluation of experimental models and interpretation of how disease burden changes during a study.