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Objectives: To investigate the diagnostic performance of T2*-weighted gradient echo (GRE) imaging, susceptibility-weighted imaging (SWI), or quantitative susceptibility mapping (QSM) in differentiating multiple system atrophy–parkinsonian type (MSA-P) from Parkinson's disease (PD). Methods: A systematic literature search through the MEDLINE and EMBASE databases was performed, starting on September 8, 2020, to identify studies evaluating the diagnostic performance of putaminal hypointensity on T2* GRE or SWI and phase shift on QSM in differentiating MSA-P from PD. The pooled sensitivity and specificity were obtained using hierarchical logistic regression modeling and hierarchical summary receiver operating characteristic (HSROC) modeling. The pooled diagnostic yields of T2* GRE, SWI, or QSM among MSA-P patients were calculated using the DerSimonian–Laird random-effects model. Results: Twelve original articles with 985 patients were finally included. SWI was performed in seven studies, T2* GRE was performed in three studies, and QSM was performed in two studies. The pooled sensitivity and specificity were 0.65 (95% CI 0.51–0.78) and 0.90 (95% CI 0.83–0.95), respectively. The area under the HSROC curve was 0.87 (95% CI 0.84–0.90). The Higgins I2 statistic calculations revealed considerable heterogeneity in terms of both sensitivity (I2 = 72.12%) and specificity (I2 = 70.38%). The coupled forest plot revealed the threshold effect. For the nine studies in which area under the curve (AUC) was obtainable, the AUC ranged from 0.68 to 0.947, with a median of 0.819. The pooled diagnostic yield of T2* GRE, SWI, or QSM was 66% (95% CI 51–78%). Conclusions: Putaminal hypointensity on T2* GRE or SWI and phase shift on QSM might be a promising diagnostic tool in differentiating MSA-P from PD. Further large multicenter prospective study is warranted. Key Points: • Three different index tests, definitions of positive image findings, thresholds, the way how to draw ROIs, reference standard, and MRI parameters could affect the heterogeneity of the study. • The pooled sensitivity and specificity were 0.65 (95% CI 0.51–0.78) and 0.90 (95% CI 0.83–0.95), respectively. • The pooled diagnostic yield of T2* GRE, SWI, or QSM was 66% (95% CI 51–78%). [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]

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: To evaluate the real-world diagnostic performance of high-resolution susceptibility-weighted imaging (HR-SWI) and investigate whether the reader's predictions can be used to find cases where HR-SWI finding and final clinical diagnosis matched. Methods: This retrospective study enrolled patients with suspected Parkinsonism (n = 48) or volunteers with other intracranial pathologies (n = 31) who underwent brain magnetic resonance imaging (MRI) including HR-SWI, which was used to evaluate nigrosome 1 (NG1). All patients with suspected Parkinsonism underwent N-3-fluoropropyl-2-carbomethoxy-3-4-iodophenyl nortropane (FP-CIT) positron emission tomography and a clinical diagnosis was made by a neurologist. The HR-SWI data were qualitatively analyzed by two independent reviewers. A consensus reading was performed and a diagnostic confidence score was assigned. According to final clinical diagnosis, diagnostic sensitivity, specificity, and accuracy were calculated. Receiver operating characteristic (ROC) curve analysis was used to examine whether the diagnostic confidence score could be used to identify HR-SWI finding—final clinical diagnosis matched cases. Results: Of the 48 patients with suspected Parkinsonism, 31 were diagnosed with idiopathic Parkinson's disease, and three with multiple system atrophy. The remaining 14 patients were included in the disease control group. Of the 31 volunteers, 10 subjects were excluded due to possibility of nigrostriatal degeneration and finally 21 subjects were enrolled as controls with non-Parkinsonism pathology (non-PD control). After consensus reading, 25 subjects were classified as true positive and 28 as true negative, according to HR-SWI findings. The calculated diagnostic sensitivity, specificity, and accuracy were 73.5%, 80.0%, and 76.8%, respectively. With using diagnostic concordance score, the area under the ROC curve for the detection of concordance case was 0.83 (95% CI: 0.72–0.91, p < 0.05). Conclusion: The diagnostic performance of NG1 detection using HR-SWI with 3T MRI was within acceptable range. Using the reader's diagnostic confidence could be helpful to find cases which HR-SWI finding and final clinical conclusion match. So HR-SWI may be of added value in the evaluation of suspected Parkinsonism. [ABSTRACT FROM AUTHOR]

Objectives: A combination of T2/FLAIR mismatch sign and advanced imaging parameters may improve the determination of molecular subtypes of diffuse lower-grade glioma. We assessed the diagnostic value of adding the apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) to the T2/FLAIR mismatch sign for differentiation of the IDH mutation or 1p/19q codeletion.Materials and Methods: Preoperative conventional, diffusion-weighted, and dynamic susceptibility contrast imaging were performed on 110 patients with diffuse lower-grade gliomas. The study population was classified into three groups using molecular subtype, namely IDH mutation and 1p/19q codeletion (IDHmut-Codel), IDH wild type (IDHwt) and IDH mutation and no 1p/19q codeletion (IDHmut-Noncodel). T2/FLAIR mismatch sign and the histogram parameters of apparent diffusion coefficient (ADC) and normalised cerebral blood volume (nCBV) values were assessed. A multivariate logistic regression model was constructed to distinguish IDHmut-Noncodel from IDHmut-Codel and IDHwt and from IDHwt, and the performance was compared with that of single parameters using the area under the receiver operating characteristics curve (AUC).Results: Positive visual T2/FLAIR mismatch sign and higher nCBV skewness were significant variables to distinguish IDHmut-Noncodel from the other two groups (AUC, 0.88; 95% CI, 0.81-0.96). A lower ADC10 was a significant variable for distinguishing IDHmut-Noncodel from the IDHwt group (AUC, 0.75; 95% CI, 0.62-0.89). Adding ADC or CBV histogram parameters to T2/FLAIR mismatch sign improved performance in distinguishing IDHmut-Noncodel from the other two groups (AUC 0.882 vs. AUC 0.810) or from IDHwt (AUC 0.923 vs. AUC 0.868).Conclusions: The combination of the T2/FLAIR mismatch sign with ADC or CBV histogram parameters can improve the identification of IDHmut-Noncodel diffuse lower-grade gliomas, which can be easily applied in clinical practice.Key Points: • The combination of the T2/FLAIR mismatch sign with the ADC or CBV histogram parameters can improve the identification of IDHmut-Noncodel diffuse lower-grade gliomas. • The multivariable model showed a significantly better performance for distinguishing the IDHmut-Noncodel group from other diffuse lower-grade gliomas than the T2/FLAIR mismatch sign alone or any single parameter. • The IDHmut-Noncodel type was associated with intermediate treatment outcomes; therefore, the identification of IDHmut-Noncodel diffuse lower-grade gliomas could be helpful for determining the clinical approach. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study was to determine whether diffusion and perfusion imaging parameters demonstrate different diagnostic values for predicting pseudoprogression between glioblastoma subgroups stratified by O6-mythylguanine-DNA methyltransferase (MGMT) promoter methylation status.Methods: We enrolled seventy-five glioblastoma patients that had presented with enlarged contrast-enhanced lesions on magnetic resonance imaging (MRI) one month after completing concurrent chemoradiotherapy and undergoing MGMT promoter methylation testing. The imaging parameters included 10 or 90 % histogram cutoffs of apparent diffusion coefficient (ADC10), normalized cerebral blood volume (nCBV90), and initial area under the time signal-intensity curve (IAUC90). The results of the areas under the receiver operating characteristic curve (AUCs) with cross-validation were compared between MGMT methylation and unmethylation groups.Results: MR imaging parameters demonstrated a trend toward higher accuracy in the MGMT promoter methylation group than in the unmethylation group (cross-validated AUCs = 0.70-0.95 and 0.56-0.87, respectively). The combination of MGMT methylation status with imaging parameters improved the AUCs from 0.70 to 0.75-0.90 for both readers in comparison with MGMT methylation status alone. The probability of pseudoprogression was highest (95.7 %) when nCBV90 was below 4.02 in the MGMT promoter methylation group.Conclusions: MR imaging parameters could be stronger predictors of pseudoprogression in glioblastoma patients with the methylated MGMT promoter than in patients with the unmethylated MGMT promoter.Key Points: • The glioblastoma subgroup was stratified according to MGMT promoter methylation status. • Diagnostic values of diffusion and perfusion parameters for predicting pseudoprogression were compared. • Imaging parameters showed higher diagnostic accuracy in the MGMT promoter methylation group. • Imaging parameters were independent to MGMT promoter methylation status for predicting pseudoprogression. • Imaging biomarkers might demonstrate different diagnostic values according to MGMT promoter methylation. [ABSTRACT FROM AUTHOR]

Objectives: To determine the added value of amide proton transfer (APT) imaging to conventional and perfusion MRI for differentiating tumour progression (TP) from the treatment-related effect (TE) in patients with post-treatment glioblastomas.Methods: Sixty-five consecutive patients with enlarging contrast-enhancing lesions following concurrent chemoradiotherapy were assessed using contrast-enhanced T1-weighted MRI (CE-T1WI), 90th percentile histogram parameters of normalized cerebral blood volume (nCBV90) and APT asymmetry value (APT90). Diagnostic performance was determined using the area under the receiver operating characteristic curve (AUC) and cross validations.Results: There were statistically significant differences in the mean APT90 between the TP and the TE groups (3.87-4.01 % vs. 1.38-1.41 %; P < .001). Compared with CE-T1WI alone, the addition of APT90 to CE-T1WI significantly improved cross-validated AUC from 0.58-0.74 to 0.89-0.91 for differentiating TP from TE. The combination of CE-T1WI, nCBV90 and APT90 resulted in greater diagnostic accuracy for differentiating TP from TE than the combination of CE-T1WI and nCBV90 (cross-validated AUC, 0.95-0.97 vs. 0.84-0.91). The inter-reader agreement between the expert and trainee was excellent for the measurements of APT90 (intraclass correlation coefficient, 0.94).Conclusion: Adding APT imaging to conventional and perfusion MRI improves the diagnostic performance for differentiating TP from TE.Key Points: • APT imaging could provide a reliable distinction between TP and TE • Adding APT imaging to CE-T1WI improved the diagnostic accuracy versus CE-T1WI alone • Multimodal imaging using CE-T1WI, perfusion and APT imaging led to accurate diagnosis • The inter-reader agreement of APT histogram parameters was excellent. [ABSTRACT FROM AUTHOR]

Objectives: To determine the diagnostic superiority of parametric response mapping of apparent diffusion coefficient (ADCPR) for predicting glioblastoma treatment response, compared to single time point measurement.Methods: Fifty post-treatment glioblastoma patients were enrolled. ADCPR was calculated from serial apparent diffusion coefficient (ADC) maps acquired before and at the time of first detection of an enlarged contrast-enhancing lesion on voxel-by-voxel basis. The percentage-decrease in ADCPR and tenth percentile histogram cutoff value of ADC (ADC10) were compared at subsequent 3-month and 1-year follow-ups.Results: The percentage-decrease in ADCPR was significantly higher in the progression group (mean = 33.2-38.3 %) than in the stable-response group (mean = 9.7 %) at 3 months follow-up (corrected p < 0.001 for both readers). ADCPR significantly improved area under the receiver operating characteristic curve from 0.67 to 0.88 (corrected p = 0.037) and from 0.70 to 0.92 (corrected p = 0.020) for both readers, respectively, compared to ADC10 at 3-month follow-up, but did not significantly improve at 1-year follow-up. The inter-reader agreement was higher for ADCPR than ADC10 (intraclass correlation coefficient, 0.93 versus 0.86).Conclusion: Voxel-based ADCPR appears to be a superior imaging biomarker than ADC, particularly for predicting early tumour progression in patients with glioblastoma.Key Points: • Treatment response pattern of glioblastoma was evaluated using voxel-based ADCPR and ADC10. • Voxel-based ADCPR was more accurate in predicting treatment response pattern than ADC10. • Inter-reader agreement was higher in ADCPR calculation than in ADC10 calculation. • Voxel-based ADCPR can be a predictor of early treatment response pattern for glioblastoma. [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]