Clinical utility of arterial spin labeling for preoperative grading of glioma

Abstract

There were obvious differences in biological behavior and prognosis between low- and high-grade gliomas, it is of great importance for clinicians to make a right judgement for preoperative grading. We conducted a comprehensive meta-analysis to evaluate the clinical utility of arterial spin labeling for preoperative grading. We searched the PubMed, Embase, China National Knowledge Infrastructure, and Weipu electronic databases for articles published through 10 November 2017 and used ‘arterial spin-labeling’ or ‘ASL perfusion, grading’ or ‘differentiation, glioma’ or ‘glial tumor, diagnostic test’ as the search terms. A manual search of relevant original and review articles was performed to identify additional studies. The meta-analysis included nine studies. No obvious heterogeneity was found in the data in a fixed-effect model. The pooled sensitivity and specificity were 90% (95% confidence interval (CI): 0.84–0.94) and 91% (95% CI: 0.83–0.96), respectively, and the pooled positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were 10.40 (95% CI: 2.21–20.77) and 0.11 (95% CI: 0.07–0.18). The diagnostic odds ratio (DOR) was 92.47 (95% CI: 39.61–215.92). The diagnostic score was 4.53 (95% CI: 3.68–5.38). The area under the curve (AUC) was 0.94 (95% CI: 0.91–0.96). Subgroup analyses did not change the pooled results. No publication bias was found (P=0.102). The normalized maximal tumor blood flow/normal white matter ratio obtained with the arterial spin labeling technique was relatively accurate for distinguishing high/low-grade glioma. As a non-invasive procedure with favorable repeatability, this index may be useful for clinical diagnostics.

Utility of Serum EB Virus Zta Antibody in the Diagnostic of Nasopharyngeal Carcinoma: Evidences From 2,126 Cases and 15,644 Controls

“…And the bivariate mixed effects model was used. We calculated the following parameters and their 95% confidence internals (CIs): sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnosis odds ratio (DOR), and summary receiver operating characteristics curve (AUC), An AUC of 1.0 represents the perfect discrimination ability (15)(16)(17). The heterogeneity within studies was examined using Q test and I 2 statistic.…”

Clinical utility of contrast‐enhanced ultrasonography in the diagnosis of benign and malignant small renal masses among Asian population

“…For all analysis the following parameters were calculated for assessing the diagnostic ability, including sensitivity, specificity, diagnostic odds ratio (DOR), negative likelihood ratio (NLR), positive likelihood ratio (PLR), area under the curve (AUC) with 95% confidence intervals (CIs). [15][16][17][18] We also conducted the subgroup analysis in study design (retrospective vs. perspective), lesion length (≤3 vs. ≤ 4), and sample size (<62 [sample size median] vs. >62). The sensitivity analysis was evaluated by four ways including goodness of fit, bivariate normality, influence analysis, and outlier detection.…”

“…For each study we extracted four folds data for analysis including TP, FP, FN, and TN. For all analysis the following parameters were calculated for assessing the diagnostic ability, including sensitivity, specificity, diagnostic odds ratio (DOR), negative likelihood ratio (NLR), positive likelihood ratio (PLR), area under the curve (AUC) with 95% confidence intervals (CIs) . We also conducted the subgroup analysis in study design (retrospective vs. perspective), lesion length (≤3 vs. ≤ 4), and sample size (<62 [sample size median] vs. >62).…”