Skip to main content

Main menu

  • Home
  • Current Issue
  • Archive
  • Info for
    • Authors
    • Subscribers
    • Advertisers
    • Editorial Board
  • Other Publications
    • In Vivo
    • Cancer Genomics & Proteomics
    • Cancer Diagnosis & Prognosis
  • More
    • IIAR
    • Conferences
    • 2008 Nobel Laureates
  • About Us
    • General Policy
    • Contact
  • Other Publications
    • Anticancer Research
    • In Vivo
    • Cancer Genomics & Proteomics

User menu

  • Register
  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
Anticancer Research
  • Other Publications
    • Anticancer Research
    • In Vivo
    • Cancer Genomics & Proteomics
  • Register
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Anticancer Research

Advanced Search

  • Home
  • Current Issue
  • Archive
  • Info for
    • Authors
    • Subscribers
    • Advertisers
    • Editorial Board
  • Other Publications
    • In Vivo
    • Cancer Genomics & Proteomics
    • Cancer Diagnosis & Prognosis
  • More
    • IIAR
    • Conferences
    • 2008 Nobel Laureates
  • About Us
    • General Policy
    • Contact
  • Visit us on Facebook
  • Follow us on Linkedin
Research ArticleClinical Studies

Classification Model to Estimate MIB-1 (Ki 67) Proliferation Index in NSCLC Patients Evaluated With 18F-FDG-PET/CT

BARBARA PALUMBO, ROSANNA CAPOZZI, FRANCESCO BIANCONI, MARIO LUCA FRAVOLINI, SILVIA CASCIANELLI, SALVATORE GERARDO MESSINA, GUIDO BELLEZZA, ANGELO SIDONI, FRANCESCO PUMA and MARK RAGUSA
Anticancer Research June 2020, 40 (6) 3355-3360; DOI: https://doi.org/10.21873/anticanres.14318
BARBARA PALUMBO
1Section of Nuclear Medicine and Health Physics, Department of Surgical and Biomedical Sciences, Università degli Studi di Perugia, Perugia, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
ROSANNA CAPOZZI
2Section of Thoracic Surgery, Università degli Studi di Perugia, Azienda Ospedaliera “S. Maria della Misericordia”, Perugia, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
FRANCESCO BIANCONI
3Department of Engineering, Università degli Studi di Perugia, Perugia, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: bianco@ieee.org
MARIO LUCA FRAVOLINI
3Department of Engineering, Università degli Studi di Perugia, Perugia, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
SILVIA CASCIANELLI
3Department of Engineering, Università degli Studi di Perugia, Perugia, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
SALVATORE GERARDO MESSINA
4Nuclear Medicine Division, Azienda Ospedaliera di Perugia, Perugia, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
GUIDO BELLEZZA
5Section of Anatomic Pathology and Histology, Department of Experimental Medicine, Università degli Studi di Perugia, Perugia, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
ANGELO SIDONI
5Section of Anatomic Pathology and Histology, Department of Experimental Medicine, Università degli Studi di Perugia, Perugia, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
FRANCESCO PUMA
2Section of Thoracic Surgery, Università degli Studi di Perugia, Azienda Ospedaliera “S. Maria della Misericordia”, Perugia, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
MARK RAGUSA
6Thoracic Surgery Unit, Azienda Ospedaliera “S. Maria”, Terni, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Abstract

Background/Aim: Proliferation biomarkers such as MIB-1 are strong predictors of clinical outcome and response to therapy in patients with non-small-cell lung cancer, but they require histological examination. In this work, we present a classification model to predict MIB-1 expression based on clinical parameters from positron emission tomography. Patients and Methods: We retrospectively evaluated 78 patients with histology-proven non-small-cell lung cancer (NSCLC) who underwent 18F-FDG-PET/CT for clinical examination. We stratified the population into a low and high proliferation group using MIB-1=25% as cut-off value. We built a predictive model based on binary classification trees to estimate the group label from the maximum standardized uptake value (SUVmax) and lesion diameter. Results: The proposed model showed ability to predict the correct proliferation group with overall accuracy >82% (78% and 86% for the low- and high-proliferation group, respectively). Conclusion: Our results indicate that radiotracer activity evaluated via SUVmax and lesion diameter are correlated with tumour proliferation index MIB-1.

  • 18F-FDG PET/CT
  • non-small-cell lung cancer
  • MIB-1
  • artificial intelligence
  • Received April 16, 2020.
  • Revision received April 30, 2020.
  • Accepted May 4, 2020.
  • Copyright© 2020, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved
View Full Text

This article requires a subscription to view the full text. If you have a subscription you may use the login form below to view the article. Access to this article can also be purchased.

Log in using your username and password

Forgot your user name or password?

Purchase access

You may purchase access to this article. This will require you to create an account if you don't already have one.

patientACCESS

patientACCESS - Patients desiring access to articles
PreviousNext
Back to top

In this issue

Anticancer Research: 40 (6)
Anticancer Research
Vol. 40, Issue 6
June 2020
  • Table of Contents
  • Table of Contents (PDF)
  • Index by author
  • Back Matter (PDF)
  • Ed Board (PDF)
  • Front Matter (PDF)
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 Anticancer Research.

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.
Classification Model to Estimate MIB-1 (Ki 67) Proliferation Index in NSCLC Patients Evaluated With 18F-FDG-PET/CT
(Your Name) has sent you a message from Anticancer Research
(Your Name) thought you would like to see the Anticancer Research web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
4 + 1 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.
Citation Tools
Classification Model to Estimate MIB-1 (Ki 67) Proliferation Index in NSCLC Patients Evaluated With 18F-FDG-PET/CT
BARBARA PALUMBO, ROSANNA CAPOZZI, FRANCESCO BIANCONI, MARIO LUCA FRAVOLINI, SILVIA CASCIANELLI, SALVATORE GERARDO MESSINA, GUIDO BELLEZZA, ANGELO SIDONI, FRANCESCO PUMA, MARK RAGUSA
Anticancer Research Jun 2020, 40 (6) 3355-3360; DOI: 10.21873/anticanres.14318

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Reprints and Permissions
Share
Classification Model to Estimate MIB-1 (Ki 67) Proliferation Index in NSCLC Patients Evaluated With 18F-FDG-PET/CT
BARBARA PALUMBO, ROSANNA CAPOZZI, FRANCESCO BIANCONI, MARIO LUCA FRAVOLINI, SILVIA CASCIANELLI, SALVATORE GERARDO MESSINA, GUIDO BELLEZZA, ANGELO SIDONI, FRANCESCO PUMA, MARK RAGUSA
Anticancer Research Jun 2020, 40 (6) 3355-3360; DOI: 10.21873/anticanres.14318
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Patients and Methods
    • Results
    • Discussion
    • Acknowledgements
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • No citing articles found.
  • Google Scholar

More in this TOC Section

  • Retrospective Study of Radiotherapy Impact on the Outcome of Material-assisted Implant-based Subpectoral Breast Reconstruction
  • Carbon-ion Radiotherapy for Oligometastatic Colorectal Cancer in the Liver or Lung
  • Treatment Volume, Dose Prescription and Delivery Techniques for Dose-intensification in Rectal Cancer: A National Survey
Show more Clinical Studies

Similar Articles

Keywords

  • 18F-FDG PET/CT
  • non-small-cell lung cancer
  • MIB-1
  • Artificial intelligence
Anticancer Research

© 2021 Anticancer Research

Powered by HighWire