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).
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.
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).
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.
From the *Department of Radiology, Xuzhou Central Hospital; and
†Department of Radiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou; and
‡Department of Radiology, The First Affiliated Hospital of Soochow University, Soochow, China.
Received for publication March 16, 2018; accepted October 25, 2018.
Address correspondence to: Li Geng, MS, Department of Radiology, Affiliated Hospital of Xuzhou Medical College, No. 199, Jiefang South Road, Quanshan District, Xuzhou 22100, China (e-mail: email@example.com).
The authors declare no conflict of interest.
R.Z. designed the study, analyzed the data, and wrote the paper. L.G. and X.W. searched and reviewed the literature. D.X. extracted data from papers.