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©The Author(s) 2016. Published by Baishideng Publishing Group Inc. All rights reserved.
Texture analysis on parametric maps derived from dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer
Jacobus FA Jansen, Yonggang Lu, Gaorav Gupta, Nancy Y Lee, Hilda E Stambuk, Yousef Mazaheri, Joseph O Deasy, Amita Shukla-Dave
Jacobus FA Jansen, Department of Radiology, Maastricht University Medical Center, 6211 LK Maastricht, the Netherlands
Yonggang Lu, Yousef Mazaheri, Joseph O Deasy, Amita Shukla-Dave, Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, United States
Gaorav Gupta, Nancy Y Lee, Departments of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, United States
Hilda E Stambuk, Yousef Mazaheri, Amita Shukla-Dave, Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, United States
Supported by The National Cancer Institute/National Institutes of Health, No. 1 R01 CA115895.
Institutional review board statement: Nineteen patients were enrolled in the institutional review board (IRB) of the Memorial Sloan-Kettering Cancer Center, New York, NY protocol titled “Dynamic Contrast Enhanced MRI and Magnetic Resonance Spectroscopy of Head and Neck Tumors” (IRB No. 06-007).
Informed consent statement: All patients gave informed consent for their participation in the institutional review board-approved study. This study was also compliant with the Health Insurance Portability and Accountability Act.
Conflict-of-interest statement: All authors have no conflicts of interest with regard to this manuscript.
Data sharing statement: Upon formal request and with proper motivation, all original data in anonymized format is available from the corresponding author for local inspection, but cannot leave Memorial Sloan-Kettering Cancer Center.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Amita Shukla-Dave, PhD, Director Quantitative Imaging, Associate Attending Physicist, Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, United States.
davea@mskcc.org
Telephone: +1-212-6393184 Fax: +1-212-7173010
Received: June 29, 2015
Peer-review started: July 4, 2015
First decision: September 22, 2015
Revised: September 24, 2015
Accepted: November 23, 2015
Article in press: November 25, 2015
Published online: January 28, 2016
Processing time: 210 Days and 18.2 Hours
AIM: To investigate the merits of texture analysis on parametric maps derived from pharmacokinetic modeling with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as imaging biomarkers for the prediction of treatment response in patients with head and neck squamous cell carcinoma (HNSCC).
METHODS: In this retrospective study, 19 HNSCC patients underwent pre- and intra-treatment DCE-MRI scans at a 1.5T MRI scanner. All patients had chemo-radiation treatment. Pharmacokinetic modeling was performed on the acquired DCE-MRI images, generating maps of volume transfer rate (Ktrans) and volume fraction of the extravascular extracellular space (ve). Image texture analysis was then employed on maps of Ktrans and ve, generating two texture measures: Energy (E) and homogeneity.
RESULTS: No significant changes were found for the mean and standard deviation for Ktrans and ve between pre- and intra-treatment (P > 0.09). Texture analysis revealed that the imaging biomarker E of ve was significantly higher in intra-treatment scans, relative to pretreatment scans (P < 0.04).
CONCLUSION: Chemo-radiation treatment in HNSCC significantly reduces the heterogeneity of tumors.
Core tip: Head and neck squamous cell carcinoma (HNSCC) is a major form of cancer that still kills many cancer patients, and patients would certainly benefit with improved imaging methodology. The merits of texture analysis were investigated on parametric maps derived from pharmacokinetic modeling with dynamic contrast-enhanced magnetic resonance imaging as imaging biomarkers for the prediction of treatment response in patients with HNSCC, undergoing chemo-radiation treatment. Texture analysis revealed that the imaging biomarker energy of parameter ve was significantly higher in intra-treatment scans, relative to pretreatment scans. This indicates that chemo-radiation treatment in HNSCC significantly reduces the heterogeneity of tumors.
