Reproducibility and usefulness of quantitative apparent diffusion coefficient measurements for predicting program death-ligand 1 expression in nasopharyngeal carcinoma.

BACKGROUND: Accurate assessment of programmed death-ligand 1 (PD-L1) expression status in nasopharyngeal carcinoma (NPC) before immunotherapy is crucial. We aimed to explore the reproducibility and usefulness of the quantitative apparent diffusion coefficient (ADC) measurements for predicting PD-L1expression status in NPC. METHODS: We retrospectively recruited 134 NPC patients who underwent MRI scans and PD-L1 detection. A PD-L1 combined positive score (CPS) ≥ 20 was identified as high expression status. Patients were divide into two cohorts based on the MRI scanning devices, including a 1.5-T MRI cohort (n = 85, 44 PD-L1 high expression) and a 3.0-T MRI cohort (n = 49, 24 PD-L1 high expression). The mean ADC (ADCmean), minimum ADC (ADCmin) and maximal ADC (ADCmax) values were independently measured by two observers. The ADC measurement reproducibility was assessed by interclass correlation coefficients (ICC). The correlations between ADC parameters and CPS were analyzed by spearman's correlation coefficient (r), and the performance for PD-L1expression status prediction was assessed by the area under receiver operating characteristic curve (AUC). RESULTS: The measurement reproducibility of ADCmean, ADCmin and ADCmax was good in the 1.5-T MRI cohort (ICC: 0.843-0.930) and 3.0-T MRI cohort (ICC: 0.929-0.960). The ADCmean, ADCmin, and ADCmax tended to inversely correlate with the CPS (r:-0.37 - -0.52 in the 1.5-T MRI cohort, and - 0.52 - -0.60 in the 3.0-T MRI cohort; P all < 0.01). The ADCmean, ADCmin and ADCmax yielded the AUC of 0.756 (95% CI: 0.651, 0.861), 0.689 (95% CI: 0.576, 0.802), and 0.733 (95%CI: 0.626, 0.839) in the 1.5-T MRI cohort and 0.820 (95%CI: 0.703, 0.937), 0.755 (95% CI: 0.616, 0.894), and 0.760 (95%CI: 0.627, 0.893) in the 3.0-T MRI cohort for predicting PD-L1 high expression status, respectively. CONCLUSION: ADC measurements may act as a reproducible and feasible method to predict PD-L1 expression status in NPC.

Wine Authentication Using Integration Assay of MIR, NIR, E-tongue, HS-SPME-GC-MS, and Multivariate Analyses: A Case Study for a Typical Cabernet Sauvignon Wine.

Background: Cabernet Sauvignon wine enjoys large market in China, and its adulteration has become a well-known problem and challenge. Objective: This study aims to evaluate the capabilities of multiple techniques, including headspace-solid-phase microextraction-GC-MS (HS-SPME-GC-MS), electronic tongue (E-tongue) spectroscopy, mid-infrared (MIR) spectroscopy, and near-infrared (NIR) spectroscopy, to differentiate this popular imported wine in China. Methods: MIR spectroscopy, NIR spectroscopy, E-tongue spectroscopy, and HS-SPME-GC-MS were used. Multivariate analysis techniques were applied to further explore the instrumental determination data for the wine discrimination. Results: Joint use of MIR and NIR with Grey relational analysis (GRA), E-tongue with principal component analysis (PCA) and hierarchical cluster analysis, and HS-SPME-GC-MS with PCA allowed unanimous differentiation of the wines. Conclusions: The approach described herein offers both ecologically friendly and multiperspective mutual corroboration techniques for Cabernet Sauvignon wine discrimination. The integrative methodology could be used as a reference for wine authentication. Highlights: GRA was first applied to discriminate the wine samples. Mutual corroboration was verified by multivariate statistics combined with MIR, NIR, E-tongue, and SPME-GC/MS. Integrated techniques pointed to a unanimous authentication of the wine samples.