Histogram analysis of apparent diffusion coefficient maps in the prognosis of patients with locally advanced head and neck squamous cell carcinoma: Comparison of different region of interest selection methods

Abstract

ObjectiveTo investigate the influence of different region of interest (ROI) selection methods on the histogram analysis of apparent diffusion coefficient (ADC) maps and to compare their performance in predicting overall survival (OS) in patients with locally advanced head and neck squamous cell carcinoma (HNSCC). MethodsA total of 73 patients with locally advanced HNSCC who underwent pretreatment diffusion-weighted magnetic resonance imaging were included. Based on the largest slice ROI (ROILS) and whole tumor ROI (ROIWT), ADC histogram parameters including mean ADC (ADCmean); median ADC (ADCmedian); 10th, 25th, 75th, and 90th percentiles of ADC values (ADC10, ADC25, ADC75, and ADC90); kurtosis; and skewness were obtained. Intraclass correlation coefficients (ICCs) and Bland–Altman plots were used to evaluate measurement reproducibility. The association of ADC histogram parameters and clinicopathological factors with OS was analyzed using log-rank tests and Cox regression. ResultsThe measurements of ADC histogram parameters based on ROIWT showed better reproducibility than ROILS (ICCs for ROIWT: 0.772–0.961; ICCs for ROILS: 0.511–0.851). The higher ADC values (ADCmean, ADCmedian, ADC10, and ADC25 based on both ROIs; ADC75 based on ROILS) and lower kurtosis based on ROILS were significantly associated with worse OS of patients with locally advanced HNSCC (all P < 0.05). In the multivariate Cox analysis, ADC10 measured with ROIWT (P = 0.019, hazard ratio = 2.63, 95% confidence interval 1.17–5.90) was an independent prognostic factor after adjusting for clinicopathological factors. ConclusionsROI selection methods could influence ADC histogram analysis. ADC10 based on ROIWT had the best independent prognostic value for patients with locally advanced HNSCC.