A crossbar array of magnetoresistive memory devices for in-memory computing.

Implementations of artificial neural networks that borrow analogue techniques could potentially offer low-power alternatives to fully digital approaches1-3. One notable example is in-memory computing based on crossbar arrays of non-volatile memories4-7 that execute, in an analogue manner, multiply-accumulate operations prevalent in artificial neural networks. Various non-volatile memories-including resistive memory8-13, phase-change memory14,15 and flash memory16-19-have been used for such approaches. However, it remains challenging to develop a crossbar array of spin-transfer-torque magnetoresistive random-access memory (MRAM)20-22,  despite the technology's practical advantages such as endurance and large-scale commercialization5. The difficulty stems from the low resistance of MRAM, which would result in large power consumption in a conventional crossbar array that uses current summation for analogue multiply-accumulate operations. Here we report a 64 × 64 crossbar array based on MRAM cells that overcomes the low-resistance issue with an architecture that uses resistance summation for analogue multiply-accumulate operations. The array is integrated with readout electronics in 28-nanometre complementary metal-oxide-semiconductor technology. Using this array, a two-layer perceptron is implemented to classify 10,000 Modified National Institute of Standards and Technology digits with an accuracy of 93.23 per cent (software baseline: 95.24 per cent). In an emulation of a deeper, eight-layer Visual Geometry Group-8 neural network with measured errors, the classification accuracy improves to 98.86 per cent (software baseline: 99.28 per cent). We also use the array to implement a single layer in a ten-layer neural network to realize face detection with an accuracy of 93.4 per cent.

Development and validation of an automatic classification algorithm for the diagnosis of Alzheimer's disease using a high-performance interpretable deep learning network.

OBJECTIVES: To develop and validate an automatic classification algorithm for diagnosing Alzheimer's disease (AD) or mild cognitive impairment (MCI). METHODS AND MATERIALS: This study evaluated a high-performance interpretable network algorithm (TabNet) and compared its performance with that of XGBoost, a widely used classifier. Brain segmentation was performed using a commercially approved software. TabNet and XGBoost were trained on the volumes or radiomics features of 102 segmented regions for classifying subjects into AD, MCI, or cognitively normal (CN) groups. The diagnostic performances of the two algorithms were compared using areas under the curves (AUCs). Additionally, 20 deep learning-based AD signature areas were investigated. RESULTS: Between December 2014 and March 2017, 161 AD, 153 MCI, and 306 CN cases were enrolled. Another 120 AD, 90 MCI, and 141 CN cases were included for the internal validation. Public datasets were used for external validation. TabNet with volume features had an AUC of 0.951 (95% confidence interval [CI], 0.947-0.955) for AD vs CN, which was similar to that of XGBoost (0.953 [95% CI, 0.951-0.955], p = 0.41). External validation revealed the similar performances of two classifiers using volume features (0.871 vs. 0.871, p = 0.86). Likewise, two algorithms showed similar performances with one another in classifying MCI. The addition of radiomics data did not improve the performance of TabNet. TabNet and XGBoost focused on the same 13/20 regions of interest, including the hippocampus, inferior lateral ventricle, and entorhinal cortex. CONCLUSIONS: TabNet shows high performance in AD classification and detailed interpretation of the selected regions. CLINICAL RELEVANCE STATEMENT: Using a high-performance interpretable deep learning network, the automatic classification algorithm assisted in accurate Alzheimer's disease detection using 3D T1-weighted brain MRI and detailed interpretation of the selected regions. KEY POINTS: • MR volumetry data revealed that TabNet had a high diagnostic performance in differentiating Alzheimer's disease (AD) from cognitive normal cases, which was comparable with that of XGBoost. • The addition of radiomics data to the volume data did not improve the diagnostic performance of TabNet. • Both TabNet and XGBoost selected the clinically meaningful regions of interest in AD, including the hippocampus, inferior lateral ventricle, and entorhinal cortex.

Risk estimation for idiopathic normal-pressure hydrocephalus: development and validation of a brain morphometry-based nomogram.

OBJECTIVES: To develop and validate a nomogram based on MRI features for predicting iNPH. METHODS: Patients aged ≥ 60 years (clinically diagnosed with iNPH, Parkinson's disease, or Alzheimer's disease or healthy controls) who underwent MRI including three-dimensional T1-weighted volumetric MRI were retrospectively identified from two tertiary referral hospitals (one hospital for derivation set and the other for validation set). Clinical and imaging features for iNPH were assessed. Deep learning-based brain segmentation software was used for 3D volumetry. A prediction model was developed using logistic regression and transformed into a nomogram. The performance of the nomogram was assessed with respect to discrimination and calibration abilities. The nomogram was internally and externally validated. RESULTS: A total of 452 patients (mean age ± SD, 73.2 ± 6.5 years; 200 men) were evaluated as the derivation set. One hundred eleven and 341 patients were categorized into the iNPH and non-iNPH groups, respectively. In multivariable analysis, high-convexity tightness (odds ratio [OR], 35.1; 95% CI: 4.5, 275.5), callosal angle < 90° (OR, 12.5; 95% CI: 3.1, 50.0), and normalized lateral ventricle volume (OR, 4.2; 95% CI: 2.7, 6.7) were associated with iNPH. The nomogram combining these three variables showed an area under the curve of 0.995 (95% CI: 0.991, 0.999) in the study sample, 0.994 (95% CI: 0.990, 0.998) in the internal validation sample, and 0.969 (95% CI: 0.940, 0.997) in the external validation sample. CONCLUSION: A brain morphometry-based nomogram including high-convexity tightness, callosal angle < 90°, and normalized lateral ventricle volume can help accurately estimate the probability of iNPH. KEY POINTS: • The nomogram with MRI findings (high-convexity tightness, callosal angle, and normalized lateral ventricle volume) helped in predicting the probability of idiopathic normal-pressure hydrocephalus. • The nomogram may facilitate the prediction of idiopathic normal-pressure hydrocephalus and consequently avoid unnecessary invasive procedures such as the cerebrospinal fluid tap test, drainage test, and cerebrospinal fluid shunt surgery.

Diagnostic performance of T2* gradient echo, susceptibility-weighted imaging, and quantitative susceptibility mapping for patients with multiple system atrophy-parkinsonian type: a systematic review and meta-analysis.

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%).

Diagnostic yield of MR myelography in patients with newly diagnosed spontaneous intracranial hypotension: a systematic review and meta-analysis.

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.

Diagnostic performance of hippocampal volumetry in Alzheimer's disease or mild cognitive impairment: a meta-analysis.

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%).

Prognostic value of diffusion-weighted imaging in patients with newly diagnosed sporadic Creutzfeldt-Jakob disease.

OBJECTIVES: To evaluate clinico-radiologic markers that predict poor overall survival (OS) in sporadic Creutzfeldt-Jakob disease (sCJD) and to develop a prognostic model. MATERIALS AND METHODS: Patients with newly diagnosed sCJD were included who underwent diffusion-weighted imaging (DWI) from February 2000 to July 2020. The impact of 9 clinico-radiologic features on OS was analyzed using univariable and multivariable Cox proportional hazards regression model. The DWI prognostic score model was generated. The weighted kappa was calculated for interobserver agreement. RESULTS: Sixty patients (mean age ± SD, 61.0 ± 9.7 years, 32 women) were included. Univariable analysis showed positive associations between poor OS and patient age (p = 0.003), extent of involved cortical lobes (p = 0.11), involvement of caudate nucleus (p = 0.07), and putamen (p = 0.04). Multivariable analysis demonstrated two independent prognostic factors: age ≥ 60 (HR 2.65, 95% CI, 1.41-4.98), and diffusion restriction in caudate nucleus and putamen (HR 2.24, 95% CI, 1.15-4.37). Based on these features, the DWI prognostic score model was generated: low-risk (0-1 point), intermediate-risk (2-3 points), and high-risk (4-5 points) groups. Median OS in high-risk group was 1.7 months, which was significantly shorter than those in the intermediate-risk (14.2 months) and low-risk (26.5 months) groups (p < 0.001). Interobserver agreements were excellent (κ = 0.91-0.92). CONCLUSIONS: Our study demonstrated that age and diffusion restriction in caudate nucleus and putamen were the independent prognostic factors of poor overall survival in sporadic Creutzfeldt-Jakob disease. Our DWI prognostic score model may be useful in clinical settings for disease stratification. KEY POINTS: • Age ≥ 60, and diffusion restriction in caudate nucleus and putamen were the independent prognostic factors of poor overall survival in sCJD. • Based on our DWI prognostic score model, median overall survival in high-risk group was 1.7 months, which was significantly shorter than those in the intermediate-risk group (14.2 months) and low-risk group (26.5 months) (p < 0.001). • The proposed DWI prognostic score model may be useful in clinical settings for disease stratification.

A prospective multi-centre study of susceptibility map-weighted MRI for the diagnosis of neurodegenerative parkinsonism.

OBJECTIVES: This study aimed to compare susceptibility map-weighted imaging (SMwI) using various MRI machines (three vendors) with N-3-fluoropropyl-2-ß-carbomethoxy-3-ß-(4-iodophe nyl)nortropane (18F-FP-CIT) PET in the diagnosis of neurodegenerative parkinsonism in a multi-centre setting. METHODS: We prospectively recruited 257 subjects, including 157 patients with neurodegenerative parkinsonism, 54 patients with non-neurodegenerative parkinsonism, and 46 healthy subjects from 10 hospitals between November 2019 and October 2020. All participants underwent both SMwI and 18F-FP-CIT PET. SMwI was interpreted by two independent reviewers for the presence or absence of abnormalities in nigrosome 1, and discrepancies were resolved by consensus. 18F-FP-CIT PET was used as the reference standard. Inter-observer agreement was tested using Cohen's kappa coefficient. McNemar's test was used to test the agreement between the interpretations of SMwI and 18F-FP-CIT PET per participant and substantia nigra (SN). RESULTS: The inter-observer agreement was 0.924 and 0.942 per SN and participant, respectively. The diagnostic sensitivity of SMwI was 97.9% and 99.4% per SN and participant, respectively; its specificity was 95.9% and 95.2%, respectively, and its accuracy was 97.1% and 97.7%, respectively. There was no significant difference between the results of SMwI and 18F-FP-CIT PET (p > 0.05, for both SN and participant). CONCLUSIONS: This study demonstrated that the high diagnostic performance of SMwI was maintained in a multi-centre setting with various MRI scanners, suggesting the generalisability of SMwI for determining nigrostriatal degeneration in patients with parkinsonism. KEY POINTS: • Susceptibility map-weighted imaging helps clinicians to predict nigrostriatal degeneration. • The protocol for susceptibility map-weighted imaging can be standardised across MRI vendors. • Susceptibility map-weighted imaging showed diagnostic performance comparable to that of dopamine transporter PET in a multi-centre setting with various MRI scanners.

Impact of Brain MRI on the Diagnosis of Infective Endocarditis and Treatment Decisions: Systematic Review and Meta-Analysis.

BACKGROUND. Despite increasing use of brain MRI to evaluate patients with suspected infective endocarditis, the clinical impact of brain MRI in this setting has not yet been systematically reviewed. OBJECTIVE. The purpose of this study was to evaluate the frequency of brain MRI findings in patients with suspected or confirmed infective endocarditis and to determine the impact of such findings on clinical decisions. EVIDENCE ACQUISITION. A systematic search of the PubMed, Embase, and Cochrane databases was performed from January 1, 1990, to December 31, 2020, to identify original research investigations of brain MRI in patients with suspected or confirmed infective endocarditis. Study quality was assessed with QUADAS-2. Study endpoints included the frequency of brain MRI findings and the frequency of diagnostic modifications, modification of therapeutic plan, and modification of valve surgery plan resulting from MRI findings. Frequencies were pooled by means of the inverse variance method. Subgroup analysis was performed. EVIDENCE SYNTHESIS. A total of 21 studies with 2133 patients were included. Overall study quality was considered moderate. In terms of brain MRI findings, the pooled frequency of acute ischemic lesions was 61.9% (95% CI, 50.7-71.9%); of cerebral microbleeds, 52.9% (95% CI, 41.6-63.9%); hemorrhagic lesions, 24.7% (95% CI, 15.1-37.9%); abscess or meningitis, 9.5% (95% CI, 5.6-15.6%); and intracranial mycotic aneurysm, 6.2% (95% CI, 4.0-9.4%). Subgroup analysis after exclusion of three studies in which neurologic findings were the indication for all brain MRI examinations yielded similar frequencies of these findings. Six studies included results on the impact of brain MRI findings on clinical decisions. The frequencies of diagnostic modifications in two studies were 5.4% and 32.1%. The pooled frequency of therapeutic plan modification in six studies was 12.8% (95% CI, 6.5-23.7%) and of surgical plan modification in five studies was 14.2% (95% CI, 8.2-23.4%). CONCLUSION. In patients with suspected or confirmed infective endocarditis, brain MRI examinations commonly show relevant abnormalities that affect diagnostic and therapeutic clinical decisions. CLINICAL IMPACT. The findings support a potential role for screening brain MRI in the evaluation of patients with suspected or confirmed infective endocarditis, regardless of the presence or absence of neurologic symptoms.

Thin-Slice Pituitary MRI with Deep Learning-based Reconstruction: Diagnostic Performance in a Postoperative Setting.

Background Achieving high-spatial-resolution pituitary MRI is challenging because of the trade-off between image noise and spatial resolution. Deep learning-based MRI reconstruction enables image denoising with sharp edges and reduced artifacts, which improves the image quality of thin-slice MRI. Purpose To assess the diagnostic performance of 1-mm slice thickness MRI with deep learning-based reconstruction (DLR) (hereafter, 1-mm MRI+DLR) compared with 3-mm slice thickness MRI (hereafter, 3-mm MRI) for identifying residual tumor and cavernous sinus invasion in the evaluation of postoperative pituitary adenoma. Materials and Methods This single-institution retrospective study included 65 patients (mean age ± standard deviation, 54 years ± 10; 26 women) who underwent a combined imaging protocol including 3-mm MRI and 1-mm MRI+DLR for postoperative evaluation of pituitary adenoma between August and October 2019. Reference standards for correct diagnosis were established by using all available imaging resources, clinical histories, laboratory findings, surgical records, and pathology reports. The diagnostic performances of 3-mm MRI, 1-mm slice thickness MRI without DLR (hereafter, 1-mm MRI), and 1-mm MRI+DLR for identifying residual tumor and cavernous sinus invasion were evaluated by two readers and compared between the protocols. Results The performance of 1-mm MRI+DLR in the identification of residual tumor was comparable to that of 3-mm MRI (area under the receiver operating characteristic curve [AUC], 0.89-0.92 vs 0.85-0.89, respectively; P ≥ .09). In the identification of cavernous sinus invasion, the diagnostic performance of 1-mm MRI+DLR was higher than that of 3-mm MRI (AUC, 0.95-0.98 vs 0.83-0.87, respectively; P ≤ .02). Conventional 1-mm MRI (AUC, 0.82-0.83) showed comparable diagnostic performance to 3-mm MRI (AUC, 0.83-0.87) (P ≥ .38). With 1-mm MRI+DLR, residual tumor was diagnosed in 20 patients and cavernous sinus invasion was diagnosed in 14 patients, in whom these diagnoses were not made with 3-mm MRI. Conclusion In the postoperative evaluation of pituitary adenoma, 1-mm slice thickness MRI with deep learning-based reconstruction showed higher diagnostic performance than 3-mm slice thickness MRI in the identification of cavernous sinus invasion and comparable diagnostic performance to 3-mm slice thickness MRI in the identification of residual tumor. © RSNA, 2020 Online supplemental material is available for this article.

Diagnostic performance of the medial temporal lobe atrophy scale in patients with Alzheimer's disease: a systematic review and meta-analysis.

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.

Diagnostic performance of loss of nigral hyperintensity on susceptibility-weighted imaging in parkinsonism: an updated meta-analysis.

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%.

Diagnostic performance and interobserver agreement of the callosal angle and Evans' index in idiopathic normal pressure hydrocephalus: a systematic review and meta-analysis.

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.

Diagnostic value of diffusion-weighted brain magnetic resonance imaging in patients with sporadic Creutzfeldt-Jakob disease: a systematic review and meta-analysis.

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%).

High-Throughput NOx Removal by Two-Stage Plasma Honeycomb Monolith Catalyst.

A two-stage plasma catalyst system for high-throughput NOx removal was investigated. Herein, the plasma stage involved the large-volume plasma discharge of humidified gas and was carried out in a sandwich-type honeycomb monolith reactor consisting of a commercial honeycomb catalyst (50 mm high; 93 mm in diameter) located between two parallel perforated disks that formed the electrodes. The results demonstrated that, in the plasma stage, the reduction of NOx did not occur at room temperature; instead, NO was only oxidized to NO2 and n-heptane to oxygenated hydrocarbons. The oxidation of NO and n-heptane in the honeycomb plasma discharge state was largely affected by the humidity of the feed gas. Furthermore, the oxidation of NO to NO2 occurs preferably to that of n-heptane with a tendency of the NO oxidation to decrease with increasing feed gas humidity. The reason is that the generation of O3 decreases as the amount of water vapor in the feed gas increases. Compared to the catalyst alone, the two-stage plasma catalyst system increased NOx removal by 29% at a temperature of 200 °C and an energy density of 25 J/L.

Advanced imaging parameters improve the prediction of diffuse lower-grade gliomas subtype, IDH mutant with no 1p19q codeletion: added value to the T2/FLAIR mismatch sign.

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.

Repeatability of amide proton transfer-weighted signals in the brain according to clinical condition and anatomical location.

OBJECTIVES: To investigate whether clinical condition, imaging session, and locations affect repeatability of amide proton transfer-weighted (APTw) magnetic resonance imaging (MRI) in the brain. MATERIALS AND METHODS: Three APTw MRI data sets were acquired, involving two intrasession scans and one intersession scan for 19 healthy, 15 glioma, and 12 acute stroke adult participants (mean age 53.8, 54.6, and 68.5, respectively) on a 3T MR scanner. The mean APTw signals from five locations in healthy brain (supratentorial and infratentorial locations) and from entire tumor and stroke lesions (supratentorial location) were calculated. The within-subject coefficient of variation (wCV) and intraclass correlation coefficient (ICC) were calculated for each clinical conditions, image sessions, and anatomic locations. Differences in APTw signals between sessions were analyzed using repeated-measures analysis of variance. RESULTS: The ICC and wCV were 0.96 (95% confidence interval [CI], 0.91-0.99) and 16.1 (12.6-21.3) in glioma, 0.93 (0.82-0.98) and 15.0 (11.4-20.6) in stroke, and 0.84 (0.72-0.91) and 34.0 (28.7-41.0) in healthy brain. There were no significant differences in APTw signal between three sessions, irrespective of disease condition and location. The ICC and wCV were 0.85 (0.68-0.94) and 27.4 (21.8-35.6) in supratentorial, and 0.44 (- 0.18 to 0.76) and 32.7 (25.9 to 42.9) in infratentorial locations. There were significant differences in APTw signal between supra- (mean, 0.49%; 95% CI, 0.38-0.61) and infratentorial locations (1.09%, 0.98-1.20; p < 0.001). CONCLUSION: The repeatability of APTw signal was excellent in supratentorial locations, while it was poor in infratentorial locations due to severe B0 inhomogeneity and susceptibility which affects MTR asymmetry. KEY POINTS: • In supratentorial locations, APTw MRI showed excellent intrasession and intersession repeatability in brains of healthy controls and patients with glioma, as well as in stroke-affected regions. • APTw MRI showed excellent repeatability in supratentorial locations, but poor repeatability in infratentorial locations. • Considering poor repeatability in the infratentorial locations, the use of APTw MRI in longitudinal assessment in infratentorial locations is not indicated.

Cerebellar Hemangioblastoma: Diagnostic Yield of Contrast-Enhanced Abdominal CT and Whole-Spine MRI as Initial Screening Imaging.

OBJECTIVE. The existing literature lacks research into the benefits of initial screening imaging for patients with cerebellar hemangioblastoma. We aimed to evaluate the diagnostic yield of initial screening imaging using abdominal CT and whole-spine MRI in patients with cerebellar hemangioblastoma. MATERIALS AND METHODS. This retrospective study included 117 consecutive patients with histopathologically confirmed, newly diagnosed cerebellar hemangioblastomas at a single tertiary hospital between January 2006 and October 2018. Patients underwent contrast-enhanced abdominal CT, whole-spine MRI, or both to detect abdominal and spinal lesions of von Hippel-Lindau disease. Diagnostic yields and false referral rates for initial screening imaging were determined. RESULTS. After exclusion of six patients who forewent any initial imaging, 111 patients were included (53 men [mean age ± SD, 51 ± 13 years] and 58 women [mean age, 43 ± 16 years]). The diagnostic yield of abdominal CT was 3.8% (4 of 105; 95% CI, 1.1-9.3%), whereas the false referral rate was 1.0% (1 of 105; 95% CI, 0.0-5.2%). For whole-spine MRI, the corresponding values were 5.6% (4 of 71; 95% CI, 1.6-13.8%) and 2.8% (2 of 71; 95% CI, 0.3-9.8%), respectively. The respective diagnostic yields in patients with a single cerebellar hemangioblastoma were both 0% (0 of 98 and 66, respectively). CONCLUSION. For patients with a single cerebellar hemangioblastoma, screening examinations with abdominal CT and whole-spine MRI are unnecessary before the results of genetic testing are available.

Primary Central Nervous System Lymphoma: Diagnostic Yield of Whole-Body CT and FDG PET/CT for Initial Systemic Imaging.

Background Updated guidelines for suspected primary central nervous system lymphoma (PCNSL) are lacking. Purpose To investigate the diagnostic yield of initial systemic imaging in patients suspected of having PCNSL by using contrast material-enhanced chest and abdominopelvic CT and/or whole-body fluorine 18 fluorodeoxyglucose (FDG) PET/CT. Materials and Methods This retrospective study included 304 patients examined at a single tertiary hospital between January 1998 and October 2018. Consecutive adults (age >18 years) who were confirmed to have newly diagnosed PCNSL on the basis of findings at stereotactic brain biopsy were recruited. All patients were examined with contrast-enhanced chest and abdominopelvic CT and/or whole-body FDG PET/CT before initiation of PCNSL treatment. The diagnostic yield of CT and PET/CT was determined before therapy and at the time of recurrence in the brain. A χ2 test was performed to compare the diagnostic yield according to study date in order to assess for possible changes in technology during the study period. Results A total of 304 patients (180 men with a mean age [±standard deviation] of 58 years ± 13 and 124 women with a mean age of 59 years ± 13) were included. The diagnostic yield of CT and PET/CT for initial staging was 2% (six of 304 patients; 95% confidence interval [CI]: 0.7%, 4.3%), and these tests yielded false-positive findings in 13 of the 304 patients (4%; 95% CI: 2.3%, 7.2%). Diagnostic yield did not differ between patients evaluated before 2009 and those evaluated in 2009 and later (P = .82). The diagnostic yield of systemic imaging at recurrence was 1.5% (one of 68 patients; 95% CI: 0.0%, 7.9%), and these tests yielded false-positive findings in four of those 68 patients (6%; 95% CI: 1.6%, 14.4%). Conclusion Contrast-enhanced chest and abdominopelvic CT and/or whole-body fluorine 18 fluorodeoxyglucose PET/CT for initial staging, as well as for recurrence of suspected primary central nervous system lymphoma, had a low diagnostic yield. © RSNA, 2019 See also the editorial by Jara in this issue.

False-Positive Measurement at 2-Hydroxyglutarate MR Spectroscopy in Isocitrate Dehydrogenase Wild-Type Glioblastoma: A Multifactorial Analysis.

Background Isocitrate dehydrogenase (IDH) mutation has become one of the most important prognostic biomarkers in glioma management. Measurement of 2-hydroxyglutarate (2HG) with MR spectroscopy has shown high pooled sensitivity, although false-positive results with MR spectroscopy have been reported. Purpose To investigate factors associated with false-positive 2HG measurements at MR spectroscopy in patients with IDH wild-type glioblastoma. Materials and Methods This retrospective study was approved by the institutional review board, and informed consent was waived. Consecutive patients with histopathologically confirmed pre- and posttreatment glioblastoma were evaluated between December 2017 and August 2018. Spectroscopy parameters, including 2HG measurements, were obtained with single-voxel point-resolved spectroscopy, and apparent diffusion coefficient (ADC) values were calculated. Necrosis was graded according to the proportion of necrosis within a volume of interest. Poisson regression analyses were performed to determine factors related to false-positive 2HG measurements. Results A total of 82 patients were included (mean age, 55 years ± 12 [standard deviation]; 40 men). The 2HG measurement showed a false-positive rate of 21% (17 of 82; 95% CI: 13%, 31%) in patients with IDH wild-type glioblastoma. Multivariable analysis revealed that necrosis (prevalence ratio [PR], 3.9; 95% CI: 1.6, 9.4; P = .01) and ADC value (PR, 0.1 × 10-3 mm2/sec; 95% CI: [0.0, 0.7] × 10-3 mm2/sec; P = .02) were associated with a greater false-positive rate for the 2HG measurement. Necrosis of more than 20% was associated with a higher rate of false-positive 2HG measurements (50%) than was necrosis of 20% or less (15%, P = .01). The 2HG false-positive rate was higher in patients with pretreatment glioblastoma (46%) than in those with posttreatment glioblastoma (14%, P < .01). Among 17 patients with false-positive findings, 15 (88%; 95% CI: 64%, 99%) had a lactate concentration of 2.0 mmol/L or higher, and 14 (82%, 95% CI: 57%, 96%) had a lactate concentration of 3.0 mmol/L or higher. Conclusion Necrosis and apparent diffusion coefficient were associated with false-positive measurements of 2-hydroxyglutarate at MR spectroscopy in patients with isocitrate dehydrogenase wild-type glioblastoma. © RSNA, 2019 Online supplemental material is available for this article.