AUTHOR=Song Chengru , Cheng Peng , Cheng Jingliang , Zhang Yong , Xie Shanshan 

TITLE=Value of Apparent Diffusion Coefficient Histogram Analysis in the Differential Diagnosis of Nasopharyngeal Lymphoma and Nasopharyngeal Carcinoma Based on Readout-Segmented Diffusion-Weighted Imaging

JOURNAL=Frontiers in Oncology

VOLUME=11

YEAR=2021

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.632796

DOI=10.3389/fonc.2021.632796

ISSN=2234-943X

ABSTRACT=<sec><title>Background</title><p>This study aims to explore the utility of whole-lesion apparent diffusion coefficient (ADC) histogram analysis for differentiating nasopharyngeal lymphoma (NPL) from nasopharyngeal carcinoma (NPC) following readout-segmented echo-planar diffusion-weighted imaging (RESOLVE sequence).</p></sec><sec><title>Methods</title><p>Thirty-eight patients with NPL and 62 patients with NPC, who received routine head-and-neck MRI and RESOLVE (b-value: 0 and 1,000 s/mm<sup>2</sup>) examinations, were retrospectively evaluated as derivation cohort (February 2015 to August 2018); another 23 patients were analyzed as validation cohort (September 2018 to December 2019). The RESOLVE data were obtained from the MAGNETOM Skyra 3T MR system (Siemens Healthcare, Erlangen, Germany). Fifteen parameters derived from the whole-lesion histogram analysis (ADC<sub>mean</sub>, variance, skewness, kurtosis, ADC<sub>1</sub>, ADC<sub>10</sub>, ADC<sub>20</sub>, ADC<sub>30</sub>, ADC<sub>40</sub>, ADC<sub>50</sub>, ADC<sub>60</sub>, ADC<sub>70</sub>, ADC<sub>80</sub>, ADC<sub>90</sub>, and ADC<sub>99</sub>) were calculated for each patient. Then, statistical analyses were performed between the two groups to determine the statistical significance of each histogram parameter. A receiver operating characteristic curve (ROC) analysis was conducted to assess the diagnostic performance of each histogram parameter for distinguishing NPL from NPC and further tested in the validation cohort; calibration of the selected parameter was tested with Hosmer–Lemeshow test.</p></sec><sec><title>Results</title><p>NPL exhibited significantly lower ADC<sub>mean</sub>, variance, ADC<sub>1</sub>, ADC<sub>10</sub>, ADC<sub>20</sub>, ADC<sub>30</sub>, ADC<sub>40</sub>, ADC<sub>50</sub>, ADC<sub>60</sub>, ADC<sub>70</sub>, ADC<sub>80</sub>, ADC<sub>90</sub> and ADC<sub>99</sub>, when compared to NPC (all, <italic>P</italic> &lt; 0.05), while no significant differences were found on skewness and kurtosis. Furthermore, ADC<sub>99</sub> revealed the highest diagnostic efficiency, followed by ADC<sub>10</sub> and ADC<sub>20</sub>. Optimal diagnostic performance (AUC = 0.790, sensitivity = 91.9%, and specificity = 63.2%) could be achieved when setting ADC<sub>99</sub> = 1,485.0 × 10<sup>−6</sup> mm<sup>2</sup>/s as the threshold value. The predictive performance was maintained in the validation cohort (AUC = 0.817, sensitivity = 94.6%, and specificity = 56.2%)</p></sec><sec><title>Conclusion</title><p>Whole-lesion ADC histograms based on RESOLVE are effective in differentiating NPC from NPL.</p></sec>