Can Trace-Weighted Images Be Used to Estimate Diffusional Kurtosis Imaging–Derived Indices of Non-Gaussian Water Diffusion in Head and Neck Cancer?

C Tessa,M Mascalchi,C Marzi,M Giannelli,S Diciotti

doi:10.3174/ajnr.a6167

Abstract

We read with great interest the appealing article by Tu et al,[1][1] aimed at assessing the role of histogram-based descriptors of the non-Gaussian diffusional kurtosis imaging (DKI) model[2][2] in treatment-response prediction of nasopharyngeal carcinoma. They found that histogram-based analysis of

Highlights

We read with great interest the appealing article by Tu et al,[1] aimed at assessing the role of histogram-based descriptors of the non-Gaussian diffusional kurtosis imaging (DKI) model[2] in treatment-response prediction of nasopharyngeal carcinoma
While a rigorous application of DKI would require the use of at least 15 diffusionweighting directions and 2 non-null b-values,[2] this simplification allows reducing the scan time, which is a pivotal issue in numerous extracranial applications of diffusion MR imaging
A recent in vivo study has demonstrated that the fit of the DKI model to trace-weighted images (TWIs) can introduce bias and error in the estimation of K and D of head and neck cancer, which can be non-negligible for single lesions.[4]

Summary

Introduction

We read with great interest the appealing article by Tu et al,[1] aimed at assessing the role of histogram-based descriptors of the non-Gaussian diffusional kurtosis imaging (DKI) model[2] in treatment-response prediction of nasopharyngeal carcinoma.

Results

Conclusion