Computed DWI MRI Results in Superior Capability for N-Stage Assessment of Non-Small Cell Lung Cancer Than That of Actual DWI, STIR Imaging, and FDG-PET/CT.

BACKGROUND: Computed diffusion-weighted imaging (cDWI) is a mathematical computation technique that generates DWIs for any b-value by using actual DWI (aDWI) data with at least two different b-values and may improve differentiation of metastatic from nonmetastatic lymph nodes. PURPOSE: To determine the appropriate b-value for cDWI to achieve a better diagnostic capability for lymph node staging (N-staging) in non-small cell lung cancer (NSCLC) patients compared to aDWI, short inversion time (TI) inversion recovery (STIR) imaging, or positron emission tomography with 2-[fluorine-18] fluoro-2-deoxy-d-glucose combined with computed tomography (FDG-PET/CT). STUDY TYPE: Prospective. SUBJECTS: A total of 245 (127 males and 118 females; mean age 72 years) consecutive histopathologically confirmed NSCLC patients. FIELD STRENGTH/SEQUENCE: A 3 T, half-Fourier single-shot turbo spin-echo sequence, electrocardiogram (ECG)-triggered STIR fast advanced spin-echo (FASE) sequence with black blood and STIR acquisition and DWI obtained by FASE with b-values of 0 and 1000 sec/mm2 . ASSESSMENT: From aDWIs with b-values of 0 and 1000 (aDWI1000 ) sec/mm2 , cDWI using 400 (cDWI400 ), 600 (cDWI600 ), 800 (cDWI800 ), and 2000 (cDWI2000 ) sec/mm2 were generated. Then, 114 metastatic and 114 nonmetastatic nodes (mediastinal and hilar lymph nodes) were selected and evaluated with a contrast ratio (CR) for each cDWI and aDWI, apparent diffusion coefficient (ADC), lymph node-to-muscle ratio (LMR) on STIR, and maximum standard uptake value (SUVmax ). STATISTICAL TESTS: Receiver operating characteristic curve (ROC) analysis, Youden index, and McNemar's test. RESULTS: Area under the curve (AUC) of CR600 was significantly larger than the CR400 , CR800 , CR2000 , aCR1000 , and SUVmax . Comparison of N-staging accuracy showed that CR600 was significantly higher than CR400 , CR2000 , ADC, aCR1000 , and SUVmax , although there were no significant differences with CR800 (P = 0.99) and LMR (P = 0.99). DATA CONCLUSION: cDWI with b-value at 600 sec/mm2 may have potential to improve N-staging accuracy as compared with aDWI, STIR, and PET/CT. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Comparison of lung CT number and airway dimension evaluation capabilities of ultra-high-resolution CT, using different scan modes and reconstruction methods including deep learning reconstruction, with those of multi-detector CT in a QIBA phantom study.

OBJECTIVE: Ultra-high-resolution CT (UHR-CT), which can be applied normal resolution (NR), high-resolution (HR), and super-high-resolution (SHR) modes, has become available as in conjunction with multi-detector CT (MDCT). Moreover, deep learning reconstruction (DLR) method, as well as filtered back projection (FBP), hybrid-type iterative reconstruction (IR), and model-based IR methods, has been clinically used. The purpose of this study was to directly compare lung CT number and airway dimension evaluation capabilities of UHR-CT using different scan modes with those of MDCT with different reconstruction methods as investigated in a lung density and airway phantom design recommended by QIBA. MATERIALS AND METHODS: Lung CT number, inner diameter (ID), inner area (IA), and wall thickness (WT) were measured, and mean differences between measured CT number, ID, IA, WT, and standard reference were compared by means of Tukey's HSD test between all UHR-CT data and MDCT reconstructed with FBP as 1.0-mm section thickness. RESULTS: For each reconstruction method, mean differences in lung CT numbers and all airway parameters on 0.5-mm and 1-mm section thickness CTs obtained with SHR and HR modes showed significant differences with those obtained with the NR mode on UHR-CT and MDCT (p < 0.05). Moreover, the mean differences on all UHR-CTs obtained with SHR, HR, or NR modes were significantly different from those of 1.0-mm section thickness MDCTs reconstructed with FBP (p < 0.05). CONCLUSION: Scan modes and reconstruction methods used for UHR-CT were found to significantly affect lung CT number and airway dimension evaluations as did reconstruction methods used for MDCT. KEY POINTS: • Scan and reconstruction methods used for UHR-CT showed significantly higher CT numbers and smaller airway dimension evaluations as did those for MDCT in a QIBA phantom study (p < 0.05). • Mean differences in lung CT number for 0.25-mm, 0.5-mm, and 1.0-mm section thickness CT images obtained with SHR and HR modes were significantly larger than those for CT images at 1.0-mm section thickness obtained with MDCT and reconstructed with FBP (p < 0.05). • Mean differences in inner diameter (ID), inner area (IA), and wall thickness (WT) measured with SHR and HR modes on 0.5- and 1.0-mm section thickness CT images were significantly smaller than those obtained with NR mode on UHR-CT and MDCT (p < 0.05).

A Bayesian estimation method for cerebral blood flow measurement by area-detector CT perfusion imaging.

PURPOSE: Bayesian estimation with advanced noise reduction (BEANR) in CT perfusion (CTP) could deliver more reliable cerebral blood flow (CBF) measurements than the commonly used reformulated singular value decomposition (rSVD). We compared the efficacy of CBF measurement by CTP using BEANR and rSVD, evaluating both relative to N-isopropyl-p-[(123) I]- iodoamphetamine (123I-IMP) single-photon emission computed tomography (SPECT) as a reference standard, in patients with cerebrovascular disease. METHODS: Thirty-one patients with suspected cerebrovascular disease underwent both CTP on a 320 detector-row CT system and SPECT. We applied rSVD and BEANR in the ischemic and contralateral regions to create CBF maps and calculate CBF ratios from the ischemic side to the healthy contralateral side (CBF index). The analysis involved comparing the CBF index between CTP methods and SPECT using Pearson's correlation and limits of agreement determined with Bland-Altman analyses, before comparing the mean difference in the CBF index between each CTP method and SPECT using the Wilcoxon matched pairs signed-rank test. RESULTS: The CBF indices of BEANR and 123I-IMP SPECT were significantly and positively correlated (r = 0.55, p < 0.0001), but there was no significant correlation between the rSVD method and SPECT (r = 0.15, p > 0.05). BEANR produced smaller limits of agreement for CBF than rSVD. The mean difference in the CBF index between BEANR and SPECT differed significantly from that between rSVD and SPECT (p < 0.001). CONCLUSIONS: BEANR has a better potential utility for CBF measurement in CTP than rSVD compared to SPECT in patients with cerebrovascular disease.

Three-Dimensional Gradient-Echo-Based Amide Proton Transfer-Weighted Imaging of Brain Tumors: Comparison With Two-Dimensional Spin-Echo-Based Amide Proton Transfer-Weighted Imaging.

OBJECTIVE: Although amide proton transfer-weighted (APTw) imaging is reported by 2-dimensional (2D) spin-echo-based sequencing, 3-dimensional (3D) APTw imaging can be obtained by gradient-echo-based sequencing. The purpose of this study was to compare the efficacy of APTw imaging between 2D and 3D imaging in patients with various brain tumors. METHODS: A total of 49 patients who had undergone 53 examinations [5 low-grade gliomas (LGG), 16 high-grade gliomas (HGG), 6 malignant lymphomas, 4 metastases, and 22 meningiomas] underwent APTw imaging using 2D and 3D sequences. The magnetization transfer ratio asymmetry (MTR asym ) was assessed by means of region of interest measurements. Pearson correlation was performed to determine the relationship between MTR asym for the 2 methods, and Student's t test to compare MTR asym for LGG and HGG. The diagnostic accuracy to differentiate HGG from LGG of the 2 methods was compared by means of the McNemar test. RESULTS: Three-dimensional APTw imaging showed a significant correlation with 2D APTw imaging ( r = 0.79, P < 0.0001). The limits of agreement between the 2 methods were -0.021 ± 1.42%. The MTR asym of HGG (2D: 1.97 ± 0.96, 3D: 2.11 ± 0.95) was significantly higher than those of LGG (2D: 0.46 ± 0.89%, P < 0.01; 3D: 0.15 ± 1.09%, P < 0.001). The diagnostic performance of the 2 methods to differentiate HGG from LGG was not significantly different ( P = 1). CONCLUSIONS: The potential capability of 3D APTw imaging is equal to or greater than that of 2D APTw imaging and is considered at least as valuable in patients with brain tumors.

Deep Learning Reconstruction of Diffusion-weighted MRI Improves Image Quality for Prostatic Imaging.

Background Deep learning reconstruction (DLR) may improve image quality. However, its impact on diffusion-weighted imaging (DWI) of the prostate has yet to be assessed. Purpose To determine whether DLR can improve image quality of diffusion-weighted MRI at b values ranging from 1000 sec/mm2 to 5000 sec/mm2 in patients with prostate cancer. Materials and Methods In this retrospective study, images of the prostate obtained at DWI with a b value of 0 sec/mm2, DWI with a b value of 1000 sec/mm2 (DWI1000), DWI with a b value of 3000 sec/mm2 (DWI3000), and DWI with a b value of 5000 sec/mm2 (DWI5000) from consecutive patients with biopsy-proven cancer from January to June 2020 were reconstructed with and without DLR. Image quality was assessed using signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) from region-of-interest analysis and qualitatively assessed using a five-point visual scoring system (1 [very poor] to 5 [excellent]) for each high-b-value DWI sequence with and without DLR. The SNR, CNR, and visual score for DWI with and without DLR were compared with the paired t test and the Wilcoxon signed rank test with Bonferroni correction, respectively. Apparent diffusion coefficients (ADCs) from DWI with and without DLR were also compared with the paired t test with Bonferroni correction. Results A total of 60 patients (mean age, 67 years; age range, 49-79 years) were analyzed. DWI with DLR showed significantly higher SNRs and CNRs than DWI without DLR (P < .001); for example, with DWI1000 the mean SNR was 38.7 ± 0.6 versus 17.8 ± 0.6, respectively (P < .001), and the mean CNR was 18.4 ± 5.6 versus 7.4 ± 5.6, respectively (P < .001). DWI with DLR also demonstrated higher qualitative image quality than DWI without DLR (mean score: 4.8 ± 0.4 vs 4.0 ± 0.7, respectively, with DWI1000 [P = .001], 3.8 ± 0.7 vs 3.0 ± 0.8 with DWI3000 [P = .002], and 3.1 ± 0.8 vs 2.0 ± 0.9 with DWI5000 [P < .001]). ADCs derived with and without DLR did not differ substantially (P > .99). Conclusion Deep learning reconstruction improves the image quality of diffusion-weighted MRI scans of prostate cancer with no impact on apparent diffusion coefficient quantitation with a 3.0-T MRI system. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Efficacy of Ultrashort Echo Time Pulmonary MRI for Lung Nodule Detection and Lung-RADS Classification.

Background Pulmonary MRI with ultrashort echo time (UTE) has been compared with chest CT for nodule detection and classification. However, direct comparisons of these methods' capabilities for Lung CT Screening Reporting and Data System (Lung-RADS) evaluation remain lacking. Purpose To compare the capabilities of pulmonary MRI with UTE with those of standard- or low-dose thin-section CT for Lung-RADS classification. Materials and Methods In this prospective study, standard- and low-dose chest CT (270 mA and 60 mA, respectively) and MRI with UTE were used to examine consecutive participants enrolled between January 2017 and December 2020 who met American College of Radiology Appropriateness Criteria for lung cancer screening with low-dose CT. Probability of nodule presence was assessed for all methods with a five-point visual scoring system by two board-certified radiologists. All nodules were then evaluated in terms of their Lung-RADS classification using each method. To compare nodule detection capability of the three methods, consensus for performances was rated by using jackknife free-response receiver operating characteristic analysis, and sensitivity was compared by means of the McNemar test. In addition, weighted κ statistics were used to determine the agreement between Lung-RADS classification obtained with each method and the reference standard generated from standard-dose CT evaluated by two radiologists who were not included in the image analysis session. Results A total of 205 participants (mean age: 64 years ± 7 [standard deviation], 106 men) with 1073 nodules were enrolled. Figure of merit (FOM) (P < .001) had significant differences among three modalities (standard-dose CT: FOM = 0.91, low-dose CT: FOM = 0.89, pulmonary MRI with UTE: FOM = 0.94), with no evidence of false-positive findings in participants with all modalities (P > .05). Agreements for Lung-RADS classification between all modalities and the reference standard were almost perfect (standard-dose CT: κ = 0.82, P < .001; low-dose CT: κ = 0.82, P < .001; pulmonary MRI with UTE: κ = 0.82, P < .001). Conclusion In a lung cancer screening population, ultrashort echo time pulmonary MRI was comparable to standard- or low-dose CT for Lung CT Screening Reporting and Data System classification. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Wielpütz in this issue.

Comparison of utility of deep learning reconstruction on 3D MRCPs obtained with three different k-space data acquisitions in patients with IPMN.

OBJECTIVE: To compare the utility of deep learning reconstruction (DLR) for improving acquisition time, image quality, and intraductal papillary mucinous neoplasm (IPMN) evaluation for 3D MRCP obtained with parallel imaging (PI), multiple k-space data acquisition for each repetition time (TR) technique (Fast 3D mode multiple: Fast 3Dm) and compressed sensing (CS) with PI. MATERIALS AND METHODS: A total of 32 IPMN patients who had undergone 3D MRCPs obtained with PI, Fast 3Dm, and CS with PI and reconstructed with and without DLR were retrospectively included in this study. Acquisition time, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) obtained with all protocols were compared using Tukey's HSD test. Results of endoscopic ultrasound, ERCP, surgery, or pathological examination were determined as standard reference, and distribution classifications were compared among all 3D MRCP protocols by McNemar's test. RESULTS: Acquisition times of Fast 3Dm and CS with PI with and without DLR were significantly shorter than those of PI with and without DLR (p < 0.05). Each MRCP sequence with DLR showed significantly higher SNRs and CNRs than those without DLR (p < 0.05). IPMN distribution accuracy of PI with and without DLR and Fast 3Dm with DLR was significantly higher than that of Fast 3Dm without DLR and CS with PI without DLR (p < 0.05). CONCLUSION: DLR is useful for improving image quality and IPMN evaluation capability on 3D MRCP obtained with PI, Fast 3Dm, or CS with PI. Moreover, Fast 3Dm and CS with PI may play as substitution to PI for MRCP in patients with IPMN. KEY POINTS: • Mean examination times of multiple k-space data acquisitions for each TR and compressed sensing with parallel imaging were significantly shorter than that of parallel imaging (p < 0.0001). • When comparing image quality of 3D MRCPs with and without deep learning reconstruction, deep learning reconstruction significantly improved signal-to-noise ratio and contrast-to-noise ratio (p < 0.05). • IPMN distribution accuracies of parallel imaging with and without deep learning reconstruction (with vs. without: 88.0% vs. 88.0%) and multiple k-space data acquisitions for each TR with deep learning reconstruction (86.0%) were significantly higher than those of others (p < 0.05).

Small Cell Lung Cancer Staging: Prospective Comparison of Conventional Staging Tests, FDG PET/CT, Whole-Body MRI, and Coregistered FDG PET/MRI.

BACKGROUND. Whole-body MRI and FDG PET/MRI have shown encouraging results for staging of thoracic malignancy but are poorly studied for staging of small cell lung cancer (SCLC). OBJECTIVE. The purpose of our study was to compare the performance of conventional staging tests, FDG PET/CT, whole-body MRI, and FDG PET/MRI for staging of SCLC. METHODS. This prospective study included 98 patients (64 men, 34 women; median age, 74 years) with SCLC who underwent conventional staging tests (brain MRI; neck, chest, and abdominopelvic CT; and bone scintigraphy), FDG PET/CT, and whole-body MRI within 2 weeks before treatment; coregistered FDG PET/MRI was generated. Two nuclear medicine physicians independently reviewed conventional tests and FDG PET/CT examinations in separate sessions, and two chest radiologists independently reviewed whole-body MRI and FDG PET/MRI examinations in separate sessions. Readers assessed T, N, and M categories; TNM stage; and Veterans Administration Lung Cancer Study Group (VALSG) stage. Reader pairs subsequently reached consensus. Stages determined clinically during tumor board sessions served as the reference standard. RESULTS. Accuracy for T category was higher (p < .05) for whole-body MRI (94.9%) and FDG PET/MRI (94.9%) than for FDG PET/CT (85.7%). Accuracy for N category was higher (p < .05) for whole-body MRI (84.7%), FDG PET/MRI (83.7%), and FDG PET/CT (81.6%) than for conventional staging tests (75.5%). Accuracy for M category was higher (p < .05) for whole-body MRI (94.9%), FDG PET/MRI (94.9%), and FDG PET/CT (94.9%) than for conventional staging tests (84.7%). Accuracy for TNM stage was higher (p < .05) for whole-body MRI (88.8%) and FDG PET/MRI (86.7%) than for FDG PET/CT (77.6%) and conventional staging tests (72.4%). Accuracy for VALSG stage was higher (p < .05) for whole-body MRI (95.9%), FDG PET/MRI (95.9%), and FDG PET/CT (98.0%) than for conventional staging tests (82.7%). Interobserver agreement, expressed as kappa coefficients, ranged from 0.81 to 0.94 across imaging tests and staging endpoints. CONCLUSION. FDG PET/CT, whole-body MRI, and coregistered FDG PET/MRI outperformed conventional tests for various staging endpoints in patients with SCLC. Whole-body MRI and FDG PET/MRI outperformed FDG PET/CT for T category and thus TNM stage, indicating the utility of MRI for assessing extent of local invasion in SCLC. CLINICAL IMPACT. Incorporation of either MRI approach may improve initial staging evaluation in SCLC.

Machine learning for lung texture analysis on thin-section CT: Capability for assessments of disease severity and therapeutic effect for connective tissue disease patients in comparison with expert panel evaluations.

BACKGROUND: The need for quantitative assessment of interstitial lung involvement on thin-section computed tomography (CT) has arisen in interstitial lung diseases including connective tissue disease (CTD). PURPOSE: To evaluate the capability of machine learning (ML)-based CT texture analysis for disease severity and treatment response assessments in comparison with qualitatively assessed thin-section CT for patients with CTD. MATERIAL AND METHODS: A total of 149 patients with CTD-related ILD (CTD-ILD) underwent initial and follow-up CT scans (total 364 paired serial CT examinations), pulmonary function tests, and serum KL-6 level tests. Based on all follow-up examination results, all paired serial CT examinations were assessed as "Stable" (n = 188), "Worse" (n = 98) and "Improved" (n = 78). Next, quantitative index changes were determined by software, and qualitative disease severity scores were assessed by consensus of two radiologists. To evaluate differences in each quantitative index as well as in disease severity score between paired serial CT examinations, Tukey's honestly significant difference (HSD) test was performed among the three statuses. Stepwise regression analyses were performed to determine changes in each pulmonary functional parameter and all quantitative indexes between paired serial CT scans. RESULTS: Δ% normal lung, Δ% consolidation, Δ% ground glass opacity, Δ% reticulation, and Δdisease severity score showed significant differences among the three statuses (P < 0.05). All differences in pulmonary functional parameters were significantly affected by Δ% normal lung, Δ% reticulation, and Δ% honeycomb (0.16 ≤r2 ≤0.42; P < 0.05). CONCLUSION: ML-based CT texture analysis has better potential than qualitatively assessed thin-section CT for disease severity assessment and treatment response evaluation for CTD-ILD.

Evaluating diploic vein blood flow using time-resolved whole-head computed tomography angiography and determining the positional relationship between typical craniotomy approaches and diploic veins in patients with meningioma.

BACKGROUND: Diploic veins may act as collateral venous pathways in cases of meningioma with venous sinus invasion. Diploic vein blood flow should be preoperatively evaluated to consider preserving the veins. In this study, we evaluated the use of time-resolved whole-head computed tomography angiography (4D-CTA)-which is less patient-intensive than digital subtraction angiography (DSA)-for assessing diploic vein blood flow and the positional relationship between typical craniotomy approaches and diploic veins. METHODS: We retrospectively examined 231 patients who underwent surgery for intracranial meningioma. We performed contrast-enhanced magnetic resonance imaging (MRI) to evaluate diploic vein pathways and compared the visualization rates of diploic vein blood flow assessed using 4D-CTA and DSA. Subsequently, we evaluated the rates of the diploic veins transected during craniotomy by comparing the pre- and postoperative contrast-enhanced MRI. RESULTS: The diagnostic performance of 4D-CTA was assessed in 45 patients. Of the 320 diploic veins identified in these patients, blood flow in 70 (21.9%) diploic veins was identified by 4D-CTA and DSA, and both results were consistent. To assess the transection rates of the diploic veins, 150 patients were included. A trend towards a high transection rate of the diploic vein in the basal interhemispheric, frontotemporal, orbitozygomatic, combined transpetrosal, and convexity craniotomy approaches was observed. CONCLUSIONS: In patients with meningiomas, both 4D-CTA and DSA are useful in evaluating diploic vein blood flow. In meningiomas with venous sinus invasion, determining the extent of craniotomy after understanding the pathways and blood flow of diploic veins is recommended.

3D Oxygen-Enhanced MRI at 3T MR System: Comparison With Thin-Section CT of Quantitative Capability for Pulmonary Functional Loss Assessment and Clinical Stage Classification of COPD in Smokers.

BACKGROUND: Oxygen (O2 )-enhanced MRI is mainly performed by a 2D sequence using 1.5T MR systems but trying to be obtained by a 3D sequence using a 3T MR system. PURPOSE: To compare the capability of 3D O2 -enhanced MRI and that of thin-section computed tomography (CT) for pulmonary functional loss assessment and clinical stage classification of chronic obstructive pulmonary disease (COPD) in smokers. STUDY TYPE: Prospective study. POPULATION: Fifty six smokers were included. FIELD STRENGTH/ SEQUENCE: 3T, 3D O2 -enhanced MRIs were performed with a 3D T1 -weighted fast field echo pulse sequence using the multiple flip angles. ASSESSMENTS: Smokers were classified into four stages ("Without COPD," "Mild COPD," "Moderate COPD," "Severe or very severe COPD"). Maps of regional changes in T1 values were generated from O2 -enhanced MR data. Regions of interest (ROIs) were then placed over the lung on all slices and averaged to determine mean T1 value change (ΔT1 ). Quantitative CT used the percentage of low attenuation areas within the entire lung (LAA%). STATISTICAL TESTS: ΔT1 and LAA% were correlated with pulmonary functional parameters, and compared for four stages using Tukey's Honestly Significant Difference test. Discrimination analyses were performed and McNemar's test was used for a comparison of the accuracy of the indexes. RESULTS: There were significantly higher correlations between ΔT1 and pulmonary functional parameters (-0.83 ≤ r ≤ -0.71, P < 0.05) than between LAA% and the same pulmonary functional parameters (-0.76 ≤ r ≤ -0.69, P < 0.05). ΔT1 and LAA% of the "Mild COPD" and "Moderate COPD" groups were significantly different from those of the "Severe or Very Severe COPD" group (P < 0.05). Discriminatory accuracy of ΔT1 (62.5%) and ΔT1 with LAA% (67.9%) was significantly greater than that of LAA% (48.2%, P < 0.05). DATA CONCLUSION: Compared with thin-section CT, 3D O2 -enhanced MRI has a similar capability for pulmonary functional assessment but better potential for clinical stage classification in smokers. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 1.

Primary central nervous system lymphomas with massive intratumoral hemorrhage: Clinical, radiological, pathological, and molecular features of six cases.

Primary central nervous system lymphomas (PCNSLs) rarely exhibit intratumoral hemorrhage. The differential diagnosis of hemorrhagic neoplasms of the central nervous system (CNS) currently includes metastatic carcinomas, melanomas, choriocarcinomas, oligodendrogliomas, and glioblastomas. Here we present the clinical, radiological, pathological, and molecular genetic features of six cases of PCNSL associated with intratumoral hemorrhage. The median age of patients was 75 years, with male predominance. While conventional PCNSLs were associated with low cerebral blood volume (CBV), perfusion magnetic resonance imaging (MRI) revealed elevated CBV in three cases, consistent with vascular proliferation. All six cases were diagnosed pathologically as having diffuse large B-cell lymphoma (DLBCL) with a non-germinal center B-cell-like (non-GCB) phenotype; marked histiocytic infiltrates and abundant non-neoplastic T-cells were observed in most cases. Expression of vascular endothelial growth factor and CD105 in the lymphoma cells and the small vessels, respectively, suggested angiogenesis within the neoplasms. Neoplastic cells were immunohistochemically negative for programmed cell death ligand 1 (PD-L1), while immune cells in the microenvironment were positive for PD-L1. Mutations in the MYD88 gene (MYD88) (L265P) and the CD79B gene (CD79B) were detected in five and one case, respectively. As therapeutic modalities used for PCNSLs differ from those that target conventional hemorrhagic neoplasms, full tissue diagnoses of all hemorrhagic CNS tumors are clearly warranted.

Objective and quantitative evaluation of angiographic vascularity in meningioma: parameters of dynamic susceptibility contrast-perfusion-weighted imaging as clinical indicators of preoperative embolization.

Digital subtraction angiography (DSA) assesses the necessity of preoperative embolization in meningioma cases but entails complication risks. Previous studies evaluating meningiomas' angiographic vascularity using perfusion-weighted imaging (PWI) have performed subjective visual assessments, not managing to assess the need for preoperative embolization. We objectively assessed the angiographic stain of meningiomas and examined the usefulness of two parameters of dynamic susceptibility contrast (DSC)-PWI, normalized cerebral blood volume (nCBV) and cerebral blood flow (nCBF), in predicting vascularity and the necessity of preoperative embolization. We retrospectively examined 52 patients who underwent surgery for primary meningioma and preoperative DSA and DSC-PWI. We calculated the normalized luminance (nLum) of the tumor stain in DSA. In 29 meningioma cases with a single feeding artery, we determined the DSC-PWI parameter that correlated with meningioma angiographic vascularity and predicted the necessity of preoperative embolization. We also compared vascularity between meningiomas with single and multiple feeding arteries and between convexity and skull-base meningiomas. nCBF (cut off: 3.66, P = 0.03, area under the curve [AUC] = 0.80) alone could predict the necessity of preoperative embolization and was more significantly correlated with the nLum than nCBV (P = 0.08, AUC = 0.73). Vascularity did not differ between meningiomas with single and multiple feeding arteries; skull-base meningiomas were more vascularized than convexity meningiomas (P = 0.0027). Our objective, quantitative assessments revealed nCBF as the most suitable parameter for evaluating meningioma vascularity. Tumor vascularity assessment using nCBF values and CBF images may aid predicting the necessity of preoperative DSA.

Diploic veins as collateral venous pathways in patients with dural venous sinus invasion by meningiomas.

BACKGROUND: Although it is known that diploic veins frequently communicate with the dural venous sinuses, the role of diploic veins in patients with venous sinus invasion from meningiomas remains unknown. METHODS: We retrospectively examined the medical records of 159 patients who underwent their first craniotomies for intracranial meningiomas. Contrast-enhanced magnetic resonance imaging was used to evaluate diploic vein routes, and digital subtraction angiography (DSA) was used to evaluate diploic vein blood flow. When high blood flow was visualized concurrently with the venous sinuses, the veins were classified as of the "early type." Diploic vein routes were classified into five routes. RESULTS: DSA was performed in 110 patients, with 14 showing superior sagittal sinus (SSS) invasion (SSS group) and 23 showing non-SSS venous sinus invasion (non-SSS group). The proportion of early type diploic veins was significantly higher in the SSS group (27.1%) than in other patients (patients without venous sinus invasion, 2.1%; non-SSS, 4.3%) (p < 0.01). In patients not in the SSS group, diploic veins were sacrificed during craniotomy in 76 patients, including four patients with veins of the early type. No patients demonstrated new neurological deficits postoperatively. In the SSS group, diploic veins were sacrificed in all patients, and early type diploic veins were cut in five patients. Two of these five patients showed postoperative neurological deficits. CONCLUSIONS: In the SSS group, diploic veins may function as collateral venous pathways, and attention is recommended for their interruption. In patients without SSS invasion, diploic veins, even of the early type, can be sacrificed.

Cortical Blood Flow Insufficiency Scores with Computed Tomography Perfusion can Predict Outcomes in Aneurysmal Subarachnoid Hemorrhage Patients: A Cohort Study.

BACKGROUND: The World Federation of Neurosurgical Societies (WFNS) scale is widely accepted for predicting outcomes for subarachnoid hemorrhage (SAH) patients. However, it is difficult to definitely predict outcomes for the most poor grade, WFNS grade 5. The present study aimed to investigate the prognostic ability of a novel classification using computed tomography perfusion (CTP) findings, called the cortical blood flow insufficiency (CBFI) scores. METHODS: CTP was performed on admission for aneurysmal SAH followed by radical treatments within 72 hours of onset. Twenty-four cerebral cortex regions of interest (ROIs) were defined. CBFI was defined as Tmax > 4 s in each ROI, and CBFI scores were calculated based on the total number of ROIs with CBFI. Using the optimal cutoff value based on receiver operating characteristics (ROC) analysis to predict patient functional outcomes, CBFI scores were divided into "high" or "low" CBFI scores. Patient functional outcomes at 90 days were categorized based on modified Rankin Scale scores (0-3, favorable group; 4-6 unfavorable group) (0-4, non-catastrophic group; 5-6, catastrophic group). RESULTS: Fifty-seven patients were included in this study, of whom 21 (36.8%) and 13 (22.8%) were in the unfavorable and the catastrophic groups, respectively. A factor predicting unfavorable and catastrophic outcomes was CBFI score cutoff value of 7 points (area under the curve, 0.73 and 0.81, respectively). In multivariable logistic regression analysis for unfavorable outcome, high CBFI scores (odds ratio (OR), 8.6; 95% confidence interval (CI), 1.1-65.4; P = 0.04) and WFNS grade 5 (OR, 30.0; 95% CI, 4.5-201.0; P < 0.001) remained as independent predictors, while for catastrophic outcome, high CBFI scores (OR, 25.3; 95% CI, 3.3-194.0; P = 0.002) and age (OR, 1.1; 95% CI, 1.0-1.2; P = 0.02) remained as independent predictors. Conversely, WFNS grade 5 was not an independent predictor of catastrophic outcomes (OR, 3.8; 95% CI, 0.6-24.0; P = 0.15). In high CBFI scores, the OR of the delayed cerebral ischemia (DCI) occurrence was 9.6 (95% CI, 1.5-61.4; P = 0.02) after adjusting for age. CONCLUSION: High CBFI scores could predict unfavorable and catastrophic outcomes for aneurysmal SAH patients and DCI occurrence.

Factors associated with silent cerebral events during atrial fibrillation ablation in patients on uninterrupted oral anticoagulation.

INTRODUCTION: Silent cerebral events (SCEs) are related to the potential thromboembolic risk in atrial fibrillation (AF) ablation. Periprocedural uninterrupted oral anticoagulation (OAC) reportedly reduced the risk of SCEs, but the incidence still remains. METHODS AND RESULTS: AF patients undergoing catheter ablation were eligible. All patients took non-vitamin K antagonist oral anticoagulants (NOACs; n = 248) or vitamin K antagonist (VKA; n = 37) for periprocedural OAC (>4 weeks) without interruption during the procedure. Brain magnetic resonance imaging was performed within 2 days after the procedure to detect SCEs. Clinical characteristics and procedure-related parameters were compared between patients with and without SCEs. SCEs were detected in 66 patients (23.1%; SCE[+]) but were not detected in 219 patients (SCE[-]). Age was higher in SCE[+] than in SCE[-] (66 ± 10 vs. 62 ± 12 years; p < .05). Persistent AF prevalence, CHADS2 /CHA2 DS2 -VASc scores, serum NT-ProBNP levels, left atrial dimension (LAD), and spontaneous echo contrast prevalence in transesophageal echocardiography significantly increased in SCE[+] versus SCE[-]. SCE[+] had lower baseline activated clotting time (ACT) before heparin injection and longer time to reach optimal ACT (>300 s) than SCE[-] (146 ± 27 vs. 156 ± 29 s and 44 ± 30 vs. 35 ± 25 min; p < .05, respectively). In multivariate analysis, age, LAD, baseline ACT, and time to reach the optimal ACT were predictors for SCEs. The average values of the ACT parameters were significantly different among NOACs/VKA. CONCLUSION: Age, LAD, and intraprocedural ACT kinetics significantly affect SCEs during AF ablation. Different anticoagulants have different impacts on ACT during the procedure, which should be considered when estimating the risk of SCEs.

An epilepsy-associated glioneuronal tumor with mixed morphology harboring FGFR1 mutation.

Glioneuronal tumor (GNT) is a rare central nervous system neoplasm composed of glial and neuronal components. Making the specific diagnosis of GNT can be challenging due to histopathological and genetical similarities among some GNTs and low-grade gliomas. We report a case of GNT with rosette-forming glioneuronal tumor, dysembryoplastic neuroepithelial tumor, and pilocytic astrocytoma-like morphology harboring FGFR1 mutation. A 16-year-old female presented with absence seizures. Magnetic resonance imaging revealed a right temporal lobe mass with multinodular enhancement by gadolinium administration. The tumor was mostly composed of oligodendrocyte-like cells (OLCs) with variable perinuclear haloes. Abundant Rosenthal fibers and eosinophilic granular bodies were identified. Neither mitotic figures nor areas of necrosis were seen. Focal neurocytic rosette features, involving ring-like arrays of OLCs around eosinophilic cores, were observed. Direct sequencing showed a missense mutation in FGFR1 K656E, whereas FGFR1 N546K, PIK3CA, and BRAF V600E were intact. KIAA1549-BRAF fusion was not detected by fluorescence in situ hybridization analysis.

MR neurography for the evaluation of CIDP.

INTRODUCTION: To visualize peripheral nerves in patients with chronic inflammatory demyelinating polyneuropathy (CIDP), we used MR imaging. We also quantified the volumes of the brachial and lumbar plexus and their nerve roots. METHODS: Thirteen patients with CIDP and 12 healthy volunteers were enrolled. Whole-body MR neurography based on diffusion-weighted whole-body imaging with background body signal suppression (DWIBS) was performed. Peripheral nerve volumes were calculated from serial axial MR images. RESULTS: The peripheral nervous system was visualized with 3-dimensional reconstruction. Volumes ranged from 8.7 to 49.5 cm3 /m2 in the brachial plexus and nerve roots and from 10.2 to 53.5 cm3 /m2 in the lumbar plexus and nerve roots. Patients with CIDP had significantly larger volumes than controls (P < 0.05), and volume was positively correlated with disease duration. CONCLUSIONS: MR neurography and the measurement of peripheral nerve volume are useful for diagnosing and assessing CIDP. Muscle Nerve 55: 483-489, 2017.

Prediction of genetic subgroups in adult supra tentorial gliomas by pre- and intraoperative parameters.

Recent progress in neuro-oncology has validated the significance of genetic diagnosis in gliomas. We previously investigated IDH1/2 and TP53 mutations via Sanger sequencing for adult supratentorial gliomas and reported that PCR-based sequence analysis classified gliomas into three genetic subgroups that have a strong association with patient prognosis: IDH mutant gliomas without TP53 mutations, IDH and TP53 mutant gliomas, and IDH wild-type gliomas. Furthermore, this analysis had a strong association with patient prognosis. To predict genetic subgroups prior to initial surgery, we retrospectively investigated preoperative radiological data using CT and MRI, including MR spectroscopy (MRS), and evaluated positive 5-aminolevulinic acid (5-ALA) fluorescence as an intraoperative factor. We subsequently compared these factors to differentiate each genetic subgroup. Multiple factors such as age at diagnosis, tumor location, gadolinium enhancement, 5-ALA fluorescence, and several tumor metabolites according to MRS, such as myo-inositol (myo-inositol/total choline) or lipid20, were statistically significant factors for differentiating IDH mutant and wild-type, suggesting that these two subtypes have totally distinct characteristics. In contrast, only calcification, laterality, and lipid13 (lipid13/total Choline) were statistically significant parameters for differentiating TP53 wild-type and mutant in IDH mutant gliomas. In this study, we detected several pre- and intraoperative factors that enabled us to predict genetic subgroups for adult supratentorial gliomas and clarified that lipid13 quantified by MRS is the key tumor metabolite that differentiates TP53 wild-type and mutant in IDH mutant gliomas. These results suggested that each genetic subtype in gliomas selects the distinct lipid synthesis pathways in the process of tumorigenesis.

Shortened Mean Transit Time in CT Perfusion With Singular Value Decomposition Analysis in Acute Cerebral Infarction: Quantitative Evaluation and Comparison With Various CT Perfusion Parameters.

OBJECTIVE: We aimed to clarify the cause of shortened mean transit time (MTT) in acute ischemic cerebrovascular disease and examined its relationship with reperfusion. METHODS: Twenty-three patients with acute ischemic cerebrovascular disease underwent whole-brain computed tomography perfusion (CTP). The maximum MTT (MTTmax), minimum MTT (MTTmin), ratio of maximum and minimum MTT (MTTmin/max), and minimum cerebral blood volume (CBV) (CBVmin) were measured by automatic region of interest analysis. Diffusion weighted image was performed to calculate infarction volume. We compared these CTP parameters between reperfusion and nonreperfusion groups and calculated correlation coefficients between the infarction core volume and CTP parameters. RESULTS: Significant differences were observed between reperfusion and nonreperfusion groups (MTTmin/max: P = 0.014; CBVmin ratio: P = 0.038). Regression analysis of CTP and high-intensity volume on diffusion weighted image showed negative correlation (CBVmin ratio: r = -0.41; MTTmin/max: r = -0.30; MTTmin ratio: r = -0.27). CONCLUSIONS: A region of shortened MTT indicated obstructed blood flow, which was attributed to the singular value decomposition method error.