Skip to main content

Main menu

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • JNM Supplement
    • SNMMI Annual Meeting Abstracts
    • Continuing Education
    • JNM Podcasts
  • Subscriptions
    • Subscribers
    • Institutional and Non-member
    • Rates
    • Journal Claims
    • Corporate & Special Sales
  • Authors
    • Submit to JNM
    • Information for Authors
    • Assignment of Copyright
    • AQARA requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • SNMMI
    • JNM
    • JNMT
    • SNMMI Journals
    • SNMMI

User menu

  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
Journal of Nuclear Medicine
  • SNMMI
    • JNM
    • JNMT
    • SNMMI Journals
    • SNMMI
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Journal of Nuclear Medicine

Advanced Search

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • JNM Supplement
    • SNMMI Annual Meeting Abstracts
    • Continuing Education
    • JNM Podcasts
  • Subscriptions
    • Subscribers
    • Institutional and Non-member
    • Rates
    • Journal Claims
    • Corporate & Special Sales
  • Authors
    • Submit to JNM
    • Information for Authors
    • Assignment of Copyright
    • AQARA requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • View or Listen to JNM Podcast
  • Visit JNM on Facebook
  • Join JNM on LinkedIn
  • Follow JNM on Twitter
  • Subscribe to our RSS feeds
Research ArticleClinical Investigations

Tumor Texture Analysis in 18F-FDG PET: Relationships Between Texture Parameters, Histogram Indices, Standardized Uptake Values, Metabolic Volumes, and Total Lesion Glycolysis

Fanny Orlhac, Michaël Soussan, Jacques-Antoine Maisonobe, Camilo A. Garcia, Bruno Vanderlinden and Irène Buvat
Journal of Nuclear Medicine March 2014, 55 (3) 414-422; DOI: https://doi.org/10.2967/jnumed.113.129858
Fanny Orlhac
1Imaging and Modeling in Neurobiology and Cancerology, Paris 11 University, Orsay, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michaël Soussan
1Imaging and Modeling in Neurobiology and Cancerology, Paris 11 University, Orsay, France
2Paris 13 University, Sorbonne Paris Cité, Bobigny, France
3AP-HP, Department of Nuclear Medicine, Avicenne University Hospital, Bobigny, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jacques-Antoine Maisonobe
1Imaging and Modeling in Neurobiology and Cancerology, Paris 11 University, Orsay, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Camilo A. Garcia
4Department of Nuclear Medicine, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium; and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Bruno Vanderlinden
4Department of Nuclear Medicine, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium; and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Irène Buvat
1Imaging and Modeling in Neurobiology and Cancerology, Paris 11 University, Orsay, France
5CEA-SHFJ, Orsay, France
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • PDF
Loading

Data supplements

  • Supplemental Data

    Files in this Data Supplement:

    • Supplemental Data
PreviousNext
Back to top

In this issue

Journal of Nuclear Medicine: 55 (3)
Journal of Nuclear Medicine
Vol. 55, Issue 3
March 1, 2014
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Journal of Nuclear Medicine.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Tumor Texture Analysis in 18F-FDG PET: Relationships Between Texture Parameters, Histogram Indices, Standardized Uptake Values, Metabolic Volumes, and Total Lesion Glycolysis
(Your Name) has sent you a message from Journal of Nuclear Medicine
(Your Name) thought you would like to see the Journal of Nuclear Medicine web site.
Citation Tools
Tumor Texture Analysis in 18F-FDG PET: Relationships Between Texture Parameters, Histogram Indices, Standardized Uptake Values, Metabolic Volumes, and Total Lesion Glycolysis
Fanny Orlhac, Michaël Soussan, Jacques-Antoine Maisonobe, Camilo A. Garcia, Bruno Vanderlinden, Irène Buvat
Journal of Nuclear Medicine Mar 2014, 55 (3) 414-422; DOI: 10.2967/jnumed.113.129858

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Tumor Texture Analysis in 18F-FDG PET: Relationships Between Texture Parameters, Histogram Indices, Standardized Uptake Values, Metabolic Volumes, and Total Lesion Glycolysis
Fanny Orlhac, Michaël Soussan, Jacques-Antoine Maisonobe, Camilo A. Garcia, Bruno Vanderlinden, Irène Buvat
Journal of Nuclear Medicine Mar 2014, 55 (3) 414-422; DOI: 10.2967/jnumed.113.129858
Twitter logo Facebook logo LinkedIn logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Bookmark this article

Jump to section

  • Article
    • Abstract
    • MATERIALS AND METHODS
    • RESULTS
    • DISCUSSION
    • CONCLUSION
    • DISCLOSURE
    • Footnotes
    • REFERENCES
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • PDF

Related Articles

  • This Month in JNM
  • PubMed
  • Google Scholar

Cited By...

  • ROBI: a Robust and Optimized Biomarker Identifier to increase the likelihood of discovering relevant radiomic features
  • Promising Candidate Prognostic Biomarkers in [18F]FDG PET Images: Evaluation in Independent Cohorts of Non-Small Cell Lung Cancer Patients
  • An 18F-FDG PET/CT and Mean Lung Dose Model to Predict Early Radiation Pneumonitis in Stage III Non-Small Cell Lung Cancer Patients Treated with Chemoradiation and Immunotherapy
  • Effects of Tracer Uptake Time in Non-Small Cell Lung Cancer 18F-FDG PET Radiomics
  • Quantitative Radiomics Features in Diffuse Large B-Cell Lymphoma: Does Segmentation Method Matter?
  • Additional value of volumetric and texture analysis on FDG PET assessment in paediatric Hodgkin lymphoma: an Italian multicentric study protocol
  • Texture Feature Comparison Between Step-and-Shoot and Continuous-Bed-Motion 18F-FDG PET
  • Radiomics Analysis of Clinical Myocardial Perfusion Stress SPECT Images to Identify Coronary Artery Calcification
  • Radiomics Features of 18F-fluorodeoxyglucose Positron-Emission Tomography as a Novel Prognostic Signature in Colorectal Cancer
  • The Dark Side of Radiomics: On the Paramount Importance of Publishing Negative Results
  • Metabolic Biomarker-Based BRAFV600 Mutation Association and Prediction in Melanoma
  • Pretreatment 18F-FDG Uptake Heterogeneity Predicts Treatment Outcome of First-Line Chemotherapy in Patients with Metastatic Triple-Negative Breast Cancer
  • A Postreconstruction Harmonization Method for Multicenter Radiomic Studies in PET
  • Computational Radiomics System to Decode the Radiographic Phenotype
  • Understanding Changes in Tumor Texture Indices in PET: A Comparison Between Visual Assessment and Index Values in Simulated and Patient Data
  • Multiscale Texture Analysis: From 18F-FDG PET Images to Histologic Images
  • Pretreatment 18F-FDG PET Textural Features in Locally Advanced Non-Small Cell Lung Cancer: Secondary Analysis of ACRIN 6668/RTOG 0235
  • 18F-FDG PET/CT of Non-Small Cell Lung Carcinoma Under Neoadjuvant Chemotherapy: Background-Based Adaptive-Volume Metrics Outperform TLG and MTV in Predicting Histopathologic Response
  • Primary tumour standardised uptake value is prognostic in nonsmall cell lung cancer: a multivariate pooled analysis of individual data
  • Impact of Image Reconstruction Settings on Texture Features in 18F-FDG PET
  • Tumor Texture Analysis in PET: Where Do We Stand?
  • 18F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi-Cancer Site Patient Cohort
  • Google Scholar

More in this TOC Section

  • Cardiac Presynaptic Sympathetic Nervous Function Evaluated by Cardiac PET in Patients with Chronotropic Incompetence Without Heart Failure
  • Validation and Evaluation of a Vendor-Provided Head Motion Correction Algorithm on the uMI Panorama PET/CT System
  • An Investigation of Lesion Detection Accuracy for Artificial Intelligence–Based Denoising of Low-Dose 64Cu-DOTATATE PET Imaging in Patients with Neuroendocrine Neoplasms
Show more Clinical Investigations

Similar Articles

Keywords

  • PET
  • tumor
  • Texture
  • standardized uptake value
  • metabolic volume
  • total lesion glycolysis
SNMMI

© 2025 SNMMI

Powered by HighWire