Tumor Growth Monitoring
Tumor Growth Monitoring - Related Videos
07:55
The Influence of Liver Resection on Intrahepatic Tumor Growth
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Cited by 6 •
2016
A high incidence of tumor recurrence after resection of liver metastases remains an unsolved problem. The illustrated mouse model may be useful to investigate the reasons for such recurrences. It combines a liver resection model with intrahepatic tumor cell injection for the first time.
08:11
Measuring Growth and Gene Expression Dynamics of Tumor-Targeted S. Typhimurium Bacteria
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Cited by 22 •
2013
The goal of these experiments is to generate quantitative time-course data on the growth and gene expression dynamics of attenuated S. typhimurium bacterial colonies growing inside tumors. This video covers tumor cell preparation and implantation, bacteria preparation and injection, whole-animal luminescence imaging, tumor excision, and bacterial colony counting.
09:14
An In Vitro System to Study Tumor Dormancy and the Switch to Metastatic Growth
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Cited by 39 •
2011
A modified 3-D in vitro system is presented in which growth characteristics of several tumor cell lines in reconstituted basement membrane correlate with the dormant or proliferative behavior of the tumor cells at a metastatic secondary site in vivo.
11:09
Establishing Intracranial Brain Tumor Xenografts With Subsequent Analysis of Tumor Growth and Response to Therapy using Bioluminescence Imaging
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Cited by 104 •
2010
Luciferase-modified human brain tumor xenografts can be established intracranially in athymic mice, with subsequent monitoring of tumor growth and response to therapy using bioluminescence imaging. In combination with survival analysis, bioluminescence monitoring is an essential research tool for pre-clinical testing of therapies being considered for treating brain tumors.
10:35
An Orthotopic Model of Serous Ovarian Cancer in Immunocompetent Mice for in vivo Tumor Imaging and Monitoring of Tumor Immune Responses
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Cited by 18 •
2010
To study in vivo tumor growth and tumor microenvironment, we used a syngeneic and orthotopic mouse model of ovarian cancer in immunocompetent animals. We transduced a mouse tumor cell line (MOV1) with Katushka fluorescent protein (MOV1KAT) and here we show its orthotopic implantation in ovary and in vivo imaging.
FAQs
Repeated measurements create a longitudinal record rather than a single snapshot. By comparing tumor size, volume, cellular activity, or biomarkers at defined intervals, researchers can quantify change and relate that trajectory to disease progression or treatment response. This time-based comparison also helps separate a temporary treatment-related change from a sustained pattern, improving interpretation of experimental results.
Size alone may not capture what is happening biologically inside a tumor. Pairing physical or imaging-based measurements with cellular activity and biomarker data provides complementary evidence about changes in tumor biology. This broader view can make treatment assessments more informative, particularly when a change in measured size could reflect either altered tumor status or a treatment-related process such as inflammation.
Distinguishing progression from inflammation requires interpreting several indicators across time instead of relying on one measurement. A tumor may change in apparent size while cellular activity or biomarker patterns provide additional context. Comparing these measures at repeated, defined intervals allows researchers to identify whether the observed change is more consistent with ongoing tumor biology or a treatment-related alteration.
Reliable monitoring depends on collecting comparable measurements at defined intervals and recording the same relevant indicators across observations. Consistent assessment of size, volume, cellular activity, or biomarkers supports quantitative comparison rather than impression-based judgment. In biology research, this standardization improves reproducibility, making results easier to interpret across experimental groups and more useful for evaluating therapies.
A workflow may include repeated imaging, physical measurements, biomarker analysis, and cell-based assays. These approaches contribute different types of information, including tumor size, volume, cellular activity, and other indicators of change. Combining results across defined intervals produces a quantitative picture of tumor behavior and helps researchers relate observable changes to disease progression or treatment response.
During therapy studies, repeated measurements provide a basis for comparing tumor changes before and after treatment. Researchers can use these data to evaluate treatment response and examine whether the tumor continues to change over time. The resulting quantitative analysis supports comparison among experimental conditions and contributes to the development of more effective diagnostic and therapeutic strategies.
Patterns collected over time can reveal that a treatment response is not permanent or that tumor-associated changes reappear. Monitoring therefore helps researchers identify treatment resistance and recurrence as distinct outcomes to investigate, rather than treating every observation as a simple size measurement. These findings can guide further study of tumor biology and the performance of experimental therapies.
It connects observable tumor change with broader questions about disease progression, treatment response, and tumor biology. By integrating size or volume with cellular activity and biomarker information, researchers obtain evidence that supports quantitative analysis rather than relying on a single endpoint. This makes monitoring useful for reproducible cancer research and for developing diagnostic and therapeutic strategies.