Jansen JF, Lu Y, Gupta G, Lee NY, Stambuk HE, Mazaheri Y, Deasy JO, Shukla-Dave A. Texture analysis on parametric maps derived from dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer. World J Radiol 2016; 8(1): 90-97 [PMID: 26834947 DOI: 10.4329/wjr.v8.i1.90]
Corresponding Author of This Article
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
Research Domain of This Article
Radiology, Nuclear Medicine & Medical Imaging
Article-Type of This Article
Retrospective Study
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Jansen JF, Lu Y, Gupta G, Lee NY, Stambuk HE, Mazaheri Y, Deasy JO, Shukla-Dave A. Texture analysis on parametric maps derived from dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer. World J Radiol 2016; 8(1): 90-97 [PMID: 26834947 DOI: 10.4329/wjr.v8.i1.90]
World J Radiol. Jan 28, 2016; 8(1): 90-97 Published online Jan 28, 2016. doi: 10.4329/wjr.v8.i1.90
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.
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
Abstract
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.
