Texture analysis on parametric maps derived from dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer

Jaap Jansen, Y. Lu, G. Gupta, N.Y. Lee, H.E. Stambuk, Y. Mazaheri, J.O. Deasy, A. Shukla-Dave

Research output: Contribution to journalArticleAcademicpeer-review

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 (K-trans) and volume fraction of the extravascular extracellular space (v(e)). Image texture analysis was then employed on maps of K-trans and v(e), generating two texture measures: Energy (E) and homogeneity.

RESULTS: No significant changes were found for the mean and standard deviation for K-trans and v(e) between pre- and intra-treatment (P > 0.09). Texture analysis revealed that the imaging biomarker E of v(e) 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.

Original languageEnglish
Pages (from-to)90-97
Number of pages8
JournalWorld Journal of Radiology
Volume8
Issue number1
DOIs
Publication statusPublished - 28 Jan 2016

Keywords

  • Tumor heterogeneity
  • Dynamic contrast-enhanced magnetic resonance imaging
  • Image texture analysis
  • Head and neck squamous cell carcinomas

Cite this