Xiaoyang Lu1, Weilin Xu1, Yuyu Wei1, Tao Li1, Liansheng Gao1, Xiongjie Fu1, Yuan Yao1, Lin Wang2. 1. Department of Neurosurgery, Second Affiliated Hospital, Zhejiang University School of Medicine, NO.88 Jiefang Rd, Zhejiang, 310009, Hangzhou, China. 2. Department of Neurosurgery, Second Affiliated Hospital, Zhejiang University School of Medicine, NO.88 Jiefang Rd, Zhejiang, 310009, Hangzhou, China. dr_wang@zju.edu.cn.
Abstract
OBJECTIVE: The purpose of this meta-analysis was to evaluate the diagnostic performance of diffusion-weighted imaging (DWI) for differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM). MATERIALS AND METHODS: A thorough search of the databases including PubMed, EMBASE, and Cochrane Library was carried out and the data acquired were up to November 1, 2017. The quality of the studies involved was evaluated using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies, revised version). Multiple analytic values including sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the summary receiver operating characteristic (SROC) curve were calculated and pooled for the statistical analysis. The subgroup analysis was also performed to explore the heterogeneity. RESULTS: Eight retrospective studies (461 patients with 461 lesions) were included. The pooled SEN, SPE, PLR, NLR, and DOR with 95% confidence interval (CI) were 0.82 [95% CI 0.70-0.90], 0.84 [95% CI 0.75-0.90], 4.96 [95% CI 3.20-7.69], 0.22 [95% CI 0.13-0.37], and 22.85 [95% CI 10.42-50.11], respectively. The area under the curve (AUC) given by SROC curve was 0.90 [95% CI 0.87-0.92]. The subgroup analysis indicated the slice thickness of the images (> 3 mm versus ≤ 3 mm) was a significant factor affecting the heterogeneity. No existence of significant publication bias was confirmed with Deeks' test. CONCLUSIONS: DWI showed moderate diagnostic performance for differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM). Moreover, it is of clinical significance using DWI combined with conventional MRI to differentiate PCNSL from GBM.
OBJECTIVE: The purpose of this meta-analysis was to evaluate the diagnostic performance of diffusion-weighted imaging (DWI) for differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM). MATERIALS AND METHODS: A thorough search of the databases including PubMed, EMBASE, and Cochrane Library was carried out and the data acquired were up to November 1, 2017. The quality of the studies involved was evaluated using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies, revised version). Multiple analytic values including sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the summary receiver operating characteristic (SROC) curve were calculated and pooled for the statistical analysis. The subgroup analysis was also performed to explore the heterogeneity. RESULTS: Eight retrospective studies (461 patients with 461 lesions) were included. The pooled SEN, SPE, PLR, NLR, and DOR with 95% confidence interval (CI) were 0.82 [95% CI 0.70-0.90], 0.84 [95% CI 0.75-0.90], 4.96 [95% CI 3.20-7.69], 0.22 [95% CI 0.13-0.37], and 22.85 [95% CI 10.42-50.11], respectively. The area under the curve (AUC) given by SROC curve was 0.90 [95% CI 0.87-0.92]. The subgroup analysis indicated the slice thickness of the images (> 3 mm versus ≤ 3 mm) was a significant factor affecting the heterogeneity. No existence of significant publication bias was confirmed with Deeks' test. CONCLUSIONS: DWI showed moderate diagnostic performance for differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM). Moreover, it is of clinical significance using DWI combined with conventional MRI to differentiate PCNSL from GBM.
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Authors: Patrick Y Wen; Michael Weller; Eudocia Quant Lee; Brian M Alexander; Jill S Barnholtz-Sloan; Floris P Barthel; Tracy T Batchelor; Ranjit S Bindra; Susan M Chang; E Antonio Chiocca; Timothy F Cloughesy; John F DeGroot; Evanthia Galanis; Mark R Gilbert; Monika E Hegi; Craig Horbinski; Raymond Y Huang; Andrew B Lassman; Emilie Le Rhun; Michael Lim; Minesh P Mehta; Ingo K Mellinghoff; Giuseppe Minniti; David Nathanson; Michael Platten; Matthias Preusser; Patrick Roth; Marc Sanson; David Schiff; Susan C Short; Martin J B Taphoorn; Joerg-Christian Tonn; Jonathan Tsang; Roel G W Verhaak; Andreas von Deimling; Wolfgang Wick; Gelareh Zadeh; David A Reardon; Kenneth D Aldape; Martin J van den Bent Journal: Neuro Oncol Date: 2020-08-17 Impact factor: 12.300