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

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 DCEMRI 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.