Feasibility study of reduced field of view diffusion-weighted magnetic resonance imaging in head and neck tumors

Abstract

Background Reduced field of view (rFOV) imaging may be used to improve the quality of diffusion-weighted imaging (DWI) in the head and neck (HN) region. Purpose To evaluate the feasibility of rFOV-DWI in patients affected by HN tumors, through a comparison with conventional full FOV (fFOV) DWI. Material and Methods Twenty-two patients with histologically-proven malignant or benign tumors of the head and neck were included in a retrospective study. All patients underwent pre-treatment magnetic resonance imaging (MRI) studies including rFOV-DWI and fFOV-DWI. The apparent diffusion coefficient (ADC) value distributions inside tumor and muscle were derived and the mean, standard deviation (SD), and kurtosis were calculated. Image distortion was quantitatively and qualitatively evaluated, as well as the capability of lesion identification. The Wilcoxon test was used to compare all variables. Agreements between the ADC estimations were assessed by Bland-Altman plots. Results Image distortion and lesion identification scores were both higher for rFOV-DWI compared to fFOV-DWI. A reduction in ADC values with rFOV-DWI emerged for both lesion and muscle, with a mean percentage difference in ADC of 6.2% in the lesions and 24.9% in the muscle. The difference in SD of ADC was statistically significant in the lesions, indicating a higher ADC homogeneity for rFOV DWI ( P = 0.005). Conclusion The application of rFOV DWI in patients affected by HN tumors is feasible and promising, based on both qualitative and quantitative analyses. This technique has potential for improving the diagnostic accuracy of fFOV-DWI for the study of specific tumoral areas.

Comparison of reduced field‐of‐view diffusion‐weighted imaging (DWI) and conventional DWI techniques in the assessment of rectal carcinoma at 3.0T: Image quality and histological T staging

“…However, Lu et al 33 discovered that the mean ADC values of thyroid glands based on the rFOV DWI sequence were significantly reduced compared with the values calculated based on the fFOV DWI sequence. Vidiri et al 34 also reported that the mean ADC values of head and neck tumors were significantly different between DWI sequences. The reasons for the above ADC measurement disparities potentially include different physiologies of the investigated organs and the characteristic features of the rFOV DWI sequence in terms of artifact reduction, excellent fat saturation, and high resolution.…”

“…SNR was significantly higher in rFOV DWI than in fFOV DWI (44. 17 6 11.01 vs. 34.76 6 13.30, P < 0.001). The subjective IQ parameters of rFOV DWI sequence were rated superior to those of fFOV DWI sequence by both readers (P < 0.001).…”

Differentiation of olfactory neuroblastomas from nasal squamous cell carcinomas using MR diffusion kurtosis imaging and dynamic contrast‐enhanced MRI

“…DKI is a novel technique with a non‐Gaussian diffusion‐weighted model, which can more accurately describe the complicated water diffusivity in living tissues and provide additional information on tissue heterogeneity, cellularity, and vascularity beyond diffusion‐weighted imaging (DWI). Previous studies have applied this promising technique to investigate tumors in the head and neck as well as to predict tumor responses to treatment, revealing that DKI holds the potential to be used as a biomarker for tumor characterization and as a predictor of treatment outcomes . In addition, Jiang et al found that the kurtosis (K) value of DKI demonstrated significantly higher accuracy compared with the apparent diffusion coefficient (ADC) value for differentiating benign from malignant sinonasal lesions, suggesting that DKI may be helpful for differentiating ONBs from SCCs.…”

“…Previous studies have applied this promising technique to investigate tumors in the head and neck as well as to predict tumor responses to treatment, revealing that DKI holds the potential to be used as a biomarker for tumor characterization and as a predictor of treatment outcomes. [12][13][14] In addition, Jiang et al 15 found that the kurtosis (K) value of DKI demonstrated significantly higher accuracy compared with the apparent diffusion coefficient (ADC) value for differentiating benign from malignant sinonasal lesions, suggesting that DKI may be helpful for differentiating ONBs from SCCs. By providing noninvasive morphologic and functional information of the tumor microvasculature, quantitative DCE-MRI can be useful for discriminating malignancies from benign lesions and monitoring treatment response in the head and neck.…”

Response Evaluation in Head and Neck Oncology: Definition and Prediction

“…Current developments in MRI technique (e.g., diffusion-weighted imaging [DWI]) for the first time permit the evaluation of tumor biology [21] . Faster imaging procedures of even higher quality are possible with technical innovations (e.g., the reduced field-of-view technique) [61] . These developments will play an important role, especially in the differentiation between posttherapeutic scarring, residual tumor, and early recurrent disease [2] .…”