PT  - JOURNAL ARTICLE
AU  - J.F.A. Jansen
AU  - H.E. Stambuk
AU  - J.A. Koutcher
AU  - A. Shukla-Dave
TI  - Non-Gaussian Analysis of Diffusion-Weighted MR Imaging in Head and Neck Squamous Cell Carcinoma: A Feasibility Study
AID  - 10.3174/ajnr.A1919
DP  - 2010 Apr 01
TA  - American Journal of Neuroradiology
PG  - 741--748
VI  - 31
IP  - 4
4099  - http://www.ajnr.org/content/31/4/741.short
4100  - http://www.ajnr.org/content/31/4/741.full
SO  - Am. J. Neuroradiol.2010 Apr 01; 31
AB  - BACKGROUND AND PURPOSE: Water in biological structures often displays non-Gaussian diffusion behavior. The objective of this study was to test the feasibility of non-Gaussian fitting by using the kurtosis model of the signal intensity decay curves obtained from DWI by using an extended range of b-values in studies of phantoms and HNSCC. MATERIALS AND METHODS: Seventeen patients with HNSCC underwent DWI by using 6 b-factors (0, 50–1500 s/mm2) at 1.5T. Monoexponential (yielding ADCmono) and non-Gaussian kurtosis (yielding apparent diffusion coefficient Dapp and apparent kurtosis coefficient Kapp) fits were performed on a voxel-by-voxel basis in selected regions of interest (primary tumors, metastatic lymph nodes, and spinal cord). DWI studies were also performed on phantoms containing either water or homogenized asparagus. To determine whether the kurtosis model provided a significantly better fit than did the monoexponential model, an F test was performed. Spearman correlation coefficients were calculated to assess correlations between Kapp and Dapp. RESULTS: The kurtosis model fit the experimental data points significantly better than did the monoexponential model (P < .05). Dapp was approximately twice the value of ADCmono (eg, in neck nodal metastases Dapp was 1.54 and ADCmono was 0.84). Kapp showed a weak Spearman correlation with Dapp in a homogenized asparagus phantom and for 44% of tumor lesions. CONCLUSIONS: The use of kurtosis modeling to fit DWI data acquired by using an extended b-value range in HNSCC is feasible and yields a significantly better fit of the data than does monoexponential modeling. It also provides an additional parameter, Kapp, potentially with added value. ADCapparent diffusion coefficientBOTbase of tongueDWIdiffusion-weighted imagingGd-DTPAgadolinium-diethylene-triamine pentaacetic acidHNhead and neckHNSCChead and neck squamous cell carcinomaNPCnasopharyngeal cancerROIregion of interestSCCsquamous cell carcinomaSNRsignal intensity-to-noise ratio