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We aimed to evaluate the pooled incidence of central vein sign on T2*-weighted images from patients with multiple sclerosis (MS), and to determine the diagnostic performance of this central vein sign for differentiating MS from other white matter lesions and provide an optimal cut-off value. A computerized systematic search of the literature in PUBMED and EMBASE was conducted up to December 14, 2018. Original articles investigating central vein sign on T2*-weighted images of patients with MS were selected. The pooled incidence was obtained using random-effects model. The pooled sensitivity and specificity were obtained using a bivariate random-effects model. An optimal cut-off value for the proportion of lesions with a central vein sign was calculated from those studies providing individual patient data. Twenty-one eligible articles covering 501 patients with MS were included. The pooled incidence of central vein sign at the level of individual lesion in patients with MS was 74% (95% CI, 65–82%). The pooled sensitivity and pooled specificity for the diagnostic performance of the central vein sign were 98% (95% CI, 92–100%) and 97% (95% CI, 91–99%), respectively. The area under the HSROC curve was 1.00 (95% CI, 0.99–1.00). The optimal cut-off value for the proportion of lesions with a central vein sign was found to be 45%. Although various T2*-weighted images have been used across studies, the current evidence supports the use of the central vein sign on T2*-weighted images to differentiate MS from other white matter lesions. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the pooled diagnostic yield of MR myelography in patients with newly diagnosed spontaneous intracranial hypotension (SIH). Methods: A literature search of the MEDLINE/PubMed and Embase databases was conducted until July 25, 2021, including studies with the following inclusion criteria: (a) population: patients with newly diagnosed SIH; (b) diagnostic modality: MR myelography or MR myelography with intrathecal gadolinium for evaluation of CSF leakage; (c) outcomes: diagnostic yield of MR myelography or MR myelography with intrathecal gadolinium. The risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. DerSimonian–Laird random-effects modeling was used to calculate the pooled estimates. Subgroup analysis regarding epidural fluid collection and meta-regression were additionally performed. Results: Fifteen studies with 643 patients were included. Eight studies used MR myelography with intrathecal gadolinium, and 11 used MR myelography. The overall quality of the included studies was moderate. The pooled diagnostic yield of MR myelography was 86% (95% CI, 80–91%) and that of MR myelography with intrathecal gadolinium was 83% (95% CI, 51–96%). There was no significant difference in pooled diagnostic yield between MR myelography and MR myelography with intrathecal gadolinium (p = 0.512). In subgroup analysis, the pooled diagnostic yield of the epidural fluid collection was 91% (95% CI, 84–94%). In meta-regression, the diagnostic yield was unaffected regardless of consecutive enrollment, magnet strength, or 2D/3D. Conclusions: MR myelography had a high diagnostic yield in patients with SIH. MR myelography is non-invasive and not inferior to MR myelography with intrathecal gadolinium. Key Points: • The pooled diagnostic yield of MR myelography was 86% (95% CI, 80–91%) in patients with spontaneous intracranial hypotension. • There was no significant difference in pooled diagnostic yield between MR myelography and MR myelography with intrathecal gadolinium. • MR myelography is non-invasive and not inferior to MR myelography with intrathecal gadolinium. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the diagnostic performance of hippocampal volumetry for Alzheimer's disease (AD) or mild cognitive impairment (MCI). Methods: The MEDLINE and Embase databases were searched for articles that evaluated the diagnostic performance of hippocampal volumetry in differentiating AD or MCI from normal controls, published up to March 6, 2022. The quality of the articles was evaluated by the QUADAS-2 tool. A bivariate random-effects model was used to pool sensitivity, specificity, and area under the curve. Sensitivity analysis and meta-regression were conducted to explain study heterogeneity. The diagnostic performance of entorhinal cortex volumetry was also pooled. Results: Thirty-three articles (5157 patients) were included. The pooled sensitivity and specificity for AD were 82% (95% confidence interval [CI], 77–86%) and 87% (95% CI, 82–91%), whereas those for MCI were 60% (95% CI, 51–69%) and 75% (95% CI, 67–81%), respectively. No difference in the diagnostic performance was observed between automatic and manual segmentation (p = 0.11). MMSE scores, study design, and the reference standard being used were associated with study heterogeneity (p < 0.01). Subgroup analysis demonstrated a higher diagnostic performance of entorhinal cortex volumetry for both AD (pooled sensitivity: 88% vs. 79%, specificity: 92% vs. 89%, p = 0.07) and MCI (pooled sensitivity: 71% vs. 55%, specificity: 83% vs. 68%, p = 0.06). Conclusions: Our meta-analysis demonstrated good diagnostic performance of hippocampal volumetry for AD or MCI. Entorhinal cortex volumetry might have superior diagnostic performance to hippocampal volumetry. However, due to a small number of studies, the diagnostic performance of entorhinal cortex volumetry is yet to be determined. Key Points: • The pooled sensitivity and specificity of hippocampal volumetry for Alzheimer's disease were 82% and 87%, whereas those for mild cognitive impairment were 60% and 75%, respectively. • No significant difference in the diagnostic performance was observed between automatic and manual segmentation. • Subgroup analysis demonstrated superior diagnostic performance of entorhinal cortex volumetry for AD (pooled sensitivity: 88%, specificity: 92%) and MCI (pooled sensitivity: 71%, specificity: 83%). [ABSTRACT FROM AUTHOR]

Objective: To evaluate the diagnostic performance and reliability of the medial temporal lobe atrophy (MTA) scale in patients with Alzheimer's disease. Methods: A systematic literature search of MEDLINE and EMBASE databases was performed to select studies that evaluated the diagnostic performance or reliability of MTA scale, published up to January 21, 2021. Pooled estimates of sensitivity and specificity were calculated using a bivariate random-effects model. Pooled correlation coefficients for intra- and interobserver agreements were calculated using the random-effects model based on Fisher's Z transformation of correlations. Meta-regression was performed to explain the study heterogeneity. Subgroup analysis was performed to compare the diagnostic performance of the MTA scale and hippocampal volumetry. Results: Twenty-one original articles were included. The pooled sensitivity and specificity of the MTA scale in differentiating Alzheimer's disease from healthy control were 74% (95% CI, 68–79%) and 88% (95% CI, 83–91%), respectively. The area under the curve of the MTA scale was 0.88 (95% CI, 0.84–0.90). Meta-regression demonstrated that the difference in the method of rating the MTA scale was significantly associated with study heterogeneity (p = 0.04). No significant difference was observed in five studies regarding the diagnostic performance between MTA scale and hippocampal volumetry (p = 0.40). The pooled correlation coefficients for intra- and interobserver agreements were 0.85 (95% CI, 0.69–0.93) and 0.83 (95% CI, 0.66–0.92), respectively. Conclusions: Our meta-analysis demonstrated a good diagnostic performance and reliability of the MTA scale in Alzheimer's disease. Key Points: • The pooled sensitivity and specificity of the MTA scale in differentiating Alzheimer's disease from healthy control were 74% and 88%, respectively. • There was no significant difference in the diagnostic performance between MTA scale and hippocampal volumetry. • The reliability of MTA scale was excellent based on the pooled correlation coefficient for intra- and interobserver agreements. [ABSTRACT FROM AUTHOR]

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]

Objectives: To evaluate diagnostic performance of loss of nigral hyperintensity on SWI in differentiating idiopathic Parkinson's disease (IPD) or primary parkinsonism (including IPD and Parkinson-plus syndrome) from healthy/disease controls. Methods: MEDLINE/PubMed and EMBASE databases were searched to identify original articles investigating the diagnostic performance of loss of nigral hyperintensity for differentiating IPD or primary parkinsonism from healthy/disease control, up to April 3, 2020. Pooled sensitivity and specificity were calculated using a bivariate random-effects model. The proportion of nondiagnostic scan, inter- and intrareader agreement, and the proportion of concordance between clinical laterality and imaging asymmetry were also pooled. Results: Nineteen articles covering 2125 patients (1097 with primary parkinsonism, 1028 healthy/disease controls) were included. For discrimination between IPD and healthy/disease controls, pooled sensitivity and specificity were 0.96 (95% CI, 0.91–0.98) and 0.95 (95% CI, 0.92–0.97). For discrimination between primary parkinsonism and healthy/disease controls, pooled sensitivity and specificity were 0.87 (95% CI, 0.75–0.94) and 0.93 (95% CI, 0.85–0.97). The pooled proportion of non-diagnostic scans on random-effects modeling was 4.2% (95% CI, 2.5–6.9%). The inter- and intrareader agreements were almost perfect, with the pooled coefficients being 0.84 (95% CI, 0.78–0.89) and 0.96 (95% CI, 0.89–0.99), respectively. The pooled proportion of concordant cases was 69.3% (95% CI, 58.4–78.4%). Conclusions: Loss of nigral hyperintensity on SWI can differentiate IPD or primary parkinsonism from a healthy/disease control group with high accuracy. However, the proportion of non-diagnostic scans is not negligible and must be taken into account. Key Points: • For discrimination between idiopathic Parkinson's disease and healthy/disease controls, pooled sensitivity and specificity of loss of nigral hyperintensity were 0.96 and 0.95. • For discrimination between primary parkinsonism and healthy/disease controls, pooled sensitivity and specificity of loss of nigral hyperintensity were 0.87 and 0.93. • The pooled proportion of non-diagnostic scans on random-effects modeling was 4.2%. [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]

Progressive supranuclear palsy (PSP) and Parkinson's disease (PD) are difficult to differentiate especially in the early stages. We aimed to investigate the diagnostic performance of the magnetic resonance parkinsonism index (MRPI) in differentiating PSP from PD. A systematic literature search of PubMed-MEDLINE and EMBASE was performed to identify original articles evaluating the diagnostic performance of the MRPI in differentiating PSP from PD published up to 20 February 2021. The pooled sensitivity, specificity, and 95% CI were calculated using the bivariate random-effects model. The area under the curve (AUC) was calculated using a hierarchical summary receiver operating characteristic (HSROC) model. Meta-regression was performed to explain the effects of heterogeneity. A total of 14 original articles involving 484 PSP patients and 1243 PD patients were included. In all studies, T1-weighted images were used to calculate the MRPI. Among the 14 studies, nine studies used 3D T1-weighted images. The pooled sensitivity and specificity for the diagnostic performance of the MRPI in differentiating PSP from PD were 96% (95% CI, 87–99%) and 98% (95% CI, 91–100%), respectively. The area under the HSROC curve was 0.99 (95% CI, 0.98–1.00). Heterogeneity was present (sensitivity: I2 = 97.29%; specificity: I2 = 98.82%). Meta-regression showed the association of the magnet field strength with heterogeneity. Studies using 3 T MRI showed significantly higher sensitivity (100%) and specificity (100%) than those of studies using 1.5 T MRI (sensitivity of 98% and specificity of 97%) (p < 0.01). Thus, the MRPI could accurately differentiate PSP from PD and support the implementation of appropriate management strategies for patients with PSP. [ABSTRACT FROM AUTHOR]