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Objective: To evaluate the diagnostic yield and performance of DWI in patients with sporadic CJD (sCJD). Methods: A systematic literature search of the MEDLINE and EMBASE databases was performed, since their inception up to July 28, 2020. Pooled diagnostic yield of diffusion-weighted imaging was calculated using DerSimonian-Laird random-effects model. Pooled diagnostic performance of DWI (sensitivity, specificity, and area under the curve) in diagnosing sCJD among patients with rapidly progressive dementia was calculated using a bivariate random-effects model. Subgroup analysis and meta-regression were performed. Results: Fifteen original articles with a total of 1144 patients with sCJD were included. The pooled diagnostic yield was 91% (95% confidence interval [CI], 86 to 94%); summary sensitivity, 91% (95% CI, 84 to 95%); and specificity, 97% (95% CI, 94 to 99%). The area under the hierarchical summary receiver operating characteristic curve was 0.99 (95% CI, 0.97–0.99). Simultaneous involvement of the neocortex and striatum was the most common finding, and the neocortex was the most common site to be involved on DWI followed by striatum, thalamus, and cerebellum. Subgroup analysis and meta-regression demonstrated significant heterogeneity among the studies associated with the reference standards used for diagnosis of sCJD. Conclusions: DWI showed excellent diagnostic value in diagnosis of sporadic Creutzfeldt-Jakob disease among patients with rapidly progressive dementia. Simultaneous involvement of the neocortex and striatum was the most common finding, and the neocortex was the most common site to be involved on diffusion-weighted imaging followed by striatum, thalamus, and cerebellum. Key Points: • The pooled diagnostic yield of diffusion-weighted imaging in sporadic Creutzfeldt-Jakob disease was 91%. • The diagnostic performance of diffusion-weighted imaging for predicting sporadic Creutzfeldt-Jakob disease among patients with rapidly progressive dementia was excellent, with pooled sensitivity, 91%, and specificity, 97%. • Simultaneous involvement in the neocortex and striatum was most commonly seen on diffusion-weighted imaging (60%), followed by the neocortex without striatum (30%), thalamus (21%), cerebellum (8%), and striatum without neocortex (7%). [ABSTRACT FROM AUTHOR]

Objective: To evaluate the diagnostic performance and interobserver agreement of the callosal angle and Evans' index in idiopathic normal pressure hydrocephalus (iNPH). Methods: A systematic search of MEDLINE and EMBASE was performed to find studies assessing the diagnostic performance or interobserver agreement of the callosal angle and Evans' index in iNPH. Pooled sensitivity and specificity of the two radiologic indices were calculated. The area under the curve (AUC) was obtained based on a hierarchical summary receiver operating characteristic curve. The diagnostic performances of both radiologic indices were compared in subgroup analysis. To evaluate interobserver agreement, the pooled correlation coefficient was calculated. Results: Ten original articles (874 patients) were included. The pooled sensitivity and specificity of the callosal angle in the diagnosis of iNPH were 91% (95% CI, 86–94%) and 93% (95% CI, 89–96%), respectively. The pooled sensitivity and specificity of Evans' index were 96% (95% CI, 47–100%) and 83% (95% CI, 77–88%), respectively. Subgroup analysis demonstrated a significant higher specificity of the callosal angle than that of Evans' index (p < 0.01). The AUC of the callosal angle and Evans' index were 0.97 (95% CI, 0.95–0.98) and 0.87 (95% CI, 0.84–0.90), respectively. The pooled correlation coefficients for the callosal angle and Evans' index were 0.92 (95% CI, 0.82–0.96) and 0.92 (95% CI, 0.83–0.97), respectively. Conclusions: Our meta-analysis demonstrated a high performance of the callosal angle in the diagnosis of iNPH. Evans' index showed reasonable diagnostic performance with high sensitivity but low specificity. Interobserver agreements were excellent in both radiologic indices. Key Points: • Callosal angle showed high diagnostic performance in idiopathic normal pressure hydrocephalus. • Evans' index showed reasonable diagnostic performance with high sensitivity but low specificity. • Interobserver agreements were excellent in both callosal angle and Evans' index. [ABSTRACT FROM AUTHOR]

Purpose: Grading of brain gliomas is of clinical importance, and noninvasive molecular imaging may help differentiate low- and high-grade gliomas. We aimed to evaluate the diagnostic performance of amide proton transfer-weighted (APTw) MRI for differentiating low- and high-grade gliomas on 3-T scanners. Methods: A systematic literature search of Ovid-MEDLINE and EMBASE was performed up to March 28, 2018. Original articles evaluating the diagnostic performance of APTw MRI for differentiating low- and high-grade gliomas were selected. The pooled sensitivity and specificity were calculated using a bivariate random-effects model. A coupled forest plot and a hierarchical summary receiver operating characteristic curve were obtained. Heterogeneity was investigated using Higgins inconsistency index (I2) test. Meta-regression was performed. Results: Ten original articles with a total of 353 patients were included. High-grade gliomas showed significantly higher APT signal intensity than low-grade gliomas. The pooled sensitivity and specificity for the diagnostic performance of APTw MRI for differentiating low-grade and high-grade gliomas were 88% (95% CI, 77–94%) and 91% (95% CI, 82–96%), respectively. Higgins I2 statistic demonstrated heterogeneity in the sensitivity (I2 = 68.17%), whereas no heterogeneity was noted in the specificity (I2 = 44.84%). In meta-regression, RF saturation power was associated with study heterogeneity. Correlation coefficients between APT signal intensity and Ki-67 cellular proliferation index ranged from 0.430 to 0.597, indicating moderate correlation. All studies showed excellent interobserver agreement. Conclusions: Although heterogeneous protocols were used, APTw MRI demonstrated excellent diagnostic performance for differentiating low- and high-grade gliomas. APTw MRI could be a reliable technique for glioma grading in clinical practice. [ABSTRACT FROM AUTHOR]

Objectives: Differentiation of glioma from brain metastasis is clinically crucial because it affects the clinical outcome of patients and alters patient management. Here, we present a systematic review and meta-analysis of the currently available data on perfusion magnetic resonance imaging (MRI) for differentiating glioma from brain metastasis, assessing MRI protocols and parameters.Methods: A computerised search of Ovid-MEDLINE and EMBASE databases was performed up to 3 October 2017, to find studies on the diagnostic performance of perfusion MRI for differentiating glioma from brain metastasis. Pooled summary estimates of sensitivity and specificity were obtained using hierarchical logistic regression modelling. We conducted meta-regression and subgroup analyses to explain the effects of the study heterogeneity.Results: Eighteen studies with 900 patients were included. The pooled sensitivity and specificity were 90% (95% CI, 84-94%) and 91% (95% CI, 84-95%), respectively. The area under the hierarchical summary receiver operating characteristic curve was 0.96 (95% CI, 0.94-0.98). The meta-regression showed that the percentage of glioma in the study population and the study design were significant factors affecting study heterogeneity. In a subgroup analysis including patients with glioblastoma only, the pooled sensitivity was 92% (95% CI, 84-97%) and the pooled specificity was 94% (95% CI, 85-98%).Conclusions: Although various perfusion MRI techniques were used, the current evidence supports the use of perfusion MRI to differentiate glioma from brain metastasis. In particular, perfusion MRI showed excellent diagnostic performance for differentiating glioblastoma from brain metastasis.Key Points: • Perfusion MRI shows high diagnostic performance for differentiating glioma from brain metastasis. • The pooled sensitivity was 90% and pooled specificity was 91%. • Peritumoral rCBV derived from DSC is a relatively well-validated. [ABSTRACT FROM AUTHOR]