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

You might also read

Related Articles

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

Sort by
Same author

Discovery of a Potent Small Molecule Antagonist of GRPR for the Treatment of Pruritus.

Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents·2026
Same author

Bridging preclinical and clinical fluorescence-guided surgery with advanced cancer vision goggles.

Npj imaging·2026
Same author

Interleukin-34-Induced Arg1+ Macrophages Play a Key Role in Breast Cancer Brain Metastasis.

Cancer research communications·2026
Same author

Near infrared fluorophore specific for annexin A2 identifies peripheral nerve injury in a rodent transection model.

Frontiers in cell and developmental biology·2026
Same author

CDK4/6 inhibitor ribociclib and doxorubicin combination treatment inhibits breast cancer bone metastasis and enhances T-cell targeted therapy.

Journal of bone oncology·2026
Same author

Tailoring Avidity through Morphology: Structure-Avidity Relationship in CD38-Binding Nanofiber Radiotracers.

ACS applied bio materials·2026

Related Experiment Video

Updated: Mar 20, 2026

Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers
12:24

Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers

Published on: July 17, 2012

12.9K

Gradient-Based Algorithm for Determining Tumor Volumes in Small Animals Using Planar Fluorescence Imaging Platform.

Jessica P Miller1, Christopher Egbulefu2, Julie L Prior2

  • 1Department of Radiology, Washington University School of Medicine, St. Louis, Missouri; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri.

Tomography (Ann Arbor, Mich.)
|May 21, 2016
PubMed
Summary

A new planar view tumor volume algorithm (PV-TVA) accurately estimates tumor volume from fluorescence images in cancer research. This method improves upon caliper-based measurements, offering a more precise tool for analyzing therapeutic effects in vivo.

Keywords:
cancerfluorescencenear infraredoptical imagingtumor volume

More Related Videos

In Vivo Optical Imaging of Brain Tumors and Arthritis Using Fluorescent SapC-DOPS Nanovesicles
09:04

In Vivo Optical Imaging of Brain Tumors and Arthritis Using Fluorescent SapC-DOPS Nanovesicles

Published on: May 2, 2014

11.9K
Radionuclide-fluorescence Reporter Gene Imaging to Track Tumor Progression in Rodent Tumor Models
10:04

Radionuclide-fluorescence Reporter Gene Imaging to Track Tumor Progression in Rodent Tumor Models

Published on: March 13, 2018

12.7K

Related Experiment Videos

Last Updated: Mar 20, 2026

Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers
12:24

Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers

Published on: July 17, 2012

12.9K
In Vivo Optical Imaging of Brain Tumors and Arthritis Using Fluorescent SapC-DOPS Nanovesicles
09:04

In Vivo Optical Imaging of Brain Tumors and Arthritis Using Fluorescent SapC-DOPS Nanovesicles

Published on: May 2, 2014

11.9K
Radionuclide-fluorescence Reporter Gene Imaging to Track Tumor Progression in Rodent Tumor Models
10:04

Radionuclide-fluorescence Reporter Gene Imaging to Track Tumor Progression in Rodent Tumor Models

Published on: March 13, 2018

12.7K

Area of Science:

  • Biomedical Imaging
  • Cancer Research
  • Optical Imaging

Background:

  • Planar fluorescence imaging is common in biological research for its simplicity and high-throughput capabilities.
  • Accurate tumor volume determination is crucial in cancer research using small animal models, but current methods using planar fluorescence images are often inaccurate.
  • Existing alternatives like physical or tomographic methods are either error-prone or too time-consuming for routine laboratory use.

Purpose of the Study:

  • To develop and validate a novel algorithm for accurate tumor volume estimation from planar fluorescence images.
  • To improve the accuracy of in vivo tumor volume assessment in cancer research compared to existing methods.
  • To provide a rapid, user-friendly, and archive-friendly tool for diverse cancer imaging applications.

Main Methods:

  • A custom-developed planar view tumor volume algorithm (PV-TVA) was created utilizing a priori knowledge of tumor xenograft models and a tumor-targeting near-infrared probe.
  • The algorithm processes near-infrared fluorescence images to enhance imaging depth within tissues.
  • Results were benchmarked against actual tumor volumes determined by water volume displacement and compared with caliper-based measurements and bioluminescence imaging.

Main Results:

  • The PV-TVA method demonstrated a significantly lower average deviation from actual tumor volume (9%) compared to the caliper-based method (18%).
  • PV-TVA showed a 10% average deviation from actual volume, outperforming bioluminescence imaging (36% deviation).
  • The algorithm offers improved accuracy, rapid data analysis, and ease of image archiving for subsequent analysis.

Conclusions:

  • The developed PV-TVA offers a more accurate and efficient method for estimating tumor volume from planar fluorescence images in cancer research.
  • This approach overcomes limitations of traditional methods, providing reliable data for evaluating cancer therapeutics in vivo.
  • The PV-TVA method holds potential for broad application in various cancer imaging studies due to its accuracy and ease of use.