Rui Long Zong, Li Geng1, Xiaohong Wang2, Daohai Xie2. 1. Department of Radiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou. 2. Department of Radiology, The First Affiliated Hospital of Soochow University, Soochow, China.
Abstract
OBJECTIVES: The aim of this study was to evaluate the diagnostic value of apparent diffusion coefficient (ADC) for the World Health Organization grade of pancreatic neuroendocrine tumors (pNETs). METHODS: The MEDLINE, Google Scholar, PubMed, and Embase databases were searched to identify relevant original articles investigating the ADC value in predicting the grade of pNETs. The pooled sensitivity (SE), specificity (SP), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated by using random effects models. Subgroup analysis was performed to discover heterogeneity effects. RESULTS: Nine studies with 386 patients met our inclusion criteria. For identifying G1 from G2/3, the pooled SE, SP, PLR, NLR, and area under the curve of the summary receiver operating characteristic curve were 0.84 (95% confidence interval [95% CI], 0.73-0.91), 0.87 (95% CI, 0.72-0.94), 6.3 (95% CI, 2.7-14.6), 0.19 (95% CI, 0.10-0.34), and 0.91 (95% CI, 0.89-0.94), respectively. The summary estimates for ADC in distinguishing G3 from G1/2 were as follows: SE, 0.93 (95% CI, 0.66-0.99); SP, 0.92 (95% CI, 0.86-0.95); PLR, 11.1 (95% CI, 6.6-18.6); NLR, 0.08 (95% CI, 0.01-0.45); and area under the curve, 0.92 (95% CI, 0.85-0.96). CONCLUSIONS: Diffusion-weighted imaging is a reliable tool for predicting the grade of pNETs, especially for G3. Moreover, the combination of 3.0-T device and higher b value can slightly help improve SE and SP.
OBJECTIVES: The aim of this study was to evaluate the diagnostic value of apparent diffusion coefficient (ADC) for the World Health Organization grade of pancreatic neuroendocrine tumors (pNETs). METHODS: The MEDLINE, Google Scholar, PubMed, and Embase databases were searched to identify relevant original articles investigating the ADC value in predicting the grade of pNETs. The pooled sensitivity (SE), specificity (SP), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated by using random effects models. Subgroup analysis was performed to discover heterogeneity effects. RESULTS: Nine studies with 386 patients met our inclusion criteria. For identifying G1 from G2/3, the pooled SE, SP, PLR, NLR, and area under the curve of the summary receiver operating characteristic curve were 0.84 (95% confidence interval [95% CI], 0.73-0.91), 0.87 (95% CI, 0.72-0.94), 6.3 (95% CI, 2.7-14.6), 0.19 (95% CI, 0.10-0.34), and 0.91 (95% CI, 0.89-0.94), respectively. The summary estimates for ADC in distinguishing G3 from G1/2 were as follows: SE, 0.93 (95% CI, 0.66-0.99); SP, 0.92 (95% CI, 0.86-0.95); PLR, 11.1 (95% CI, 6.6-18.6); NLR, 0.08 (95% CI, 0.01-0.45); and area under the curve, 0.92 (95% CI, 0.85-0.96). CONCLUSIONS: Diffusion-weighted imaging is a reliable tool for predicting the grade of pNETs, especially for G3. Moreover, the combination of 3.0-T device and higher b value can slightly help improve SE and SP.
Authors: Wouter Mebis; Annemiek Snoeckx; Bob Corthouts; Haroun El Addouli; Simon Nicolay; Astrid Van Hoyweghen; Maarten Spinhoven; Bart Op de Beeck Journal: J Belg Soc Radiol Date: 2020-01-30 Impact factor: 1.894