Diagnosis of Unruptured Intracranial Aneurysms Using Proton-Density Magnetic Resonance Angiography: A Comparison With High-Resolution Time-of-Flight Magnetic Resonance Angiography.

OBJECTIVE: Differentiating intracranial aneurysms from normal variants using CT angiography (CTA) or MR angiography (MRA) poses significant challenges. This study aimed to evaluate the efficacy of proton-density MRA (PD-MRA) compared to high-resolution time-of-flight MRA (HR-MRA) in diagnosing aneurysms among patients with indeterminate findings on conventional CTA or MRA. MATERIALS AND METHODS: In this retrospective analysis, we included patients who underwent both PD-MRA and HR-MRA from August 2020 to July 2022 to assess lesions deemed indeterminate on prior conventional CTA or MRA examinations. Three experienced neuroradiologists independently reviewed the lesions using HR-MRA and PD-MRA with reconstructed voxel sizes of 0.253 mm3 or 0.23 mm3, respectively. A neurointerventionist established the gold standard with digital subtraction angiography. We compared the performance of HR-MRA, PD-MRA (0.253-mm3 voxel), and PD-MRA (0.23-mm3 voxel) in diagnosing aneurysms, both per lesion and per patient. The Fleiss kappa statistic was used to calculate inter-reader agreement. RESULTS: The study involved 109 patients (average age 57.4 ± 11.0 years; male:female ratio, 11:98) with 141 indeterminate lesions. Of these, 78 lesions (55.3%) in 69 patients were confirmed as aneurysms by the reference standard. PD-MRA (0.253-mm3 voxel) exhibited significantly higher per-lesion diagnostic performance compared to HR-MRA across all three readers: sensitivity ranged from 87.2%-91.0% versus 66.7%-70.5%; specificity from 93.7%-96.8% versus 58.7%-68.3%; and accuracy from 90.8%-92.9% versus 63.8%-69.5% (P ≤ 0.003). Furthermore, PD-MRA (0.253-mm3 voxel) demonstrated significantly superior per-patient specificity and accuracy compared to HR-MRA across all evaluators (P ≤ 0.013). The diagnostic accuracy of PD-MRA (0.23-mm3 voxel) surpassed that of HR-MRA and was comparable to PD-MRA (0.253-mm3 voxel). The kappa values for inter-reader agreements were significantly higher in PD-MRA (0.820-0.938) than in HR-MRA (0.447-0.510). CONCLUSION: PD-MRA outperformed HR-MRA in diagnostic accuracy and demonstrated almost perfect inter-reader consistency in identifying intracranial aneurysms among patients with lesions initially indeterminate on CTA or MRA.

Achieving imaging and computational reproducibility on multiparametric MRI radiomics features in brain tumor diagnosis: phantom and clinical validation.

OBJECTIVES: The Image Biomarker Standardization Initiative has helped improve the computational reproducibility of MRI radiomics features. Nonetheless, the MRI sequences and features with high imaging reproducibility are yet to be established. To determine reproducible multiparametric MRI radiomics features across test-retest, multi-scanner, and computational reproducibility comparisons, and to evaluate their clinical value in brain tumor diagnosis. METHODS: To assess reproducibility, T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and diffusion-weighted imaging (DWI) were acquired from three 3-T MRI scanners using standardized phantom, and radiomics features were extracted using two computational algorithms. Reproducible radiomics features were selected when the concordance correlation coefficient value above 0.9 across multiple sessions, scanners, and computational algorithms. Random forest classifiers were trained with reproducible features (n = 117) and validated in a clinical cohort (n = 50) to evaluate whether features with high reproducibility improved the differentiation of glioblastoma from primary central nervous system lymphomas (PCNSLs). RESULTS: Radiomics features from T2WI demonstrated higher repeatability (65-94%) than those from DWI (38-48%) or T1WI (2-92%). Across test-retest, multi-scanner, and computational comparisons, T2WI provided 41 reproducible features, DWI provided six, and T1WI provided two. The performance of the classification model with reproducible features was higher than that using non-reproducible features in both training set (AUC, 0.916 vs. 0.877) and validation set (AUC, 0.957 vs. 0.869). CONCLUSION: Radiomics features with high reproducibility across multiple sessions, scanners, and computational algorithms were identified, and they showed higher diagnostic performance than non-reproducible radiomics features in the differentiation of glioblastoma from PCNSL. CLINICAL RELEVANCE STATEMENT: By identifying the radiomics features showing higher multi-machine reproducibility, our results also demonstrated higher radiomics diagnostic performance in the differentiation of glioblastoma from PCNSL, paving the way for further research designs and clinical application in neuro-oncology. KEY POINTS: • Highly reproducible radiomics features across multiple sessions, scanners, and computational algorithms were identified using phantom and applied to clinical diagnosis. • Radiomics features from T2-weighted imaging were more reproducible than those from T1-weighted and diffusion-weighted imaging. • Radiomics features with good reproducibility had better diagnostic performance for brain tumors than features with poor reproducibility.

Low- or standard-dose edoxaban versus antiplatelet therapy for leaflet thrombus and cerebral thromboembolism after TAVR: A prespecified analysis of randomized ADAPT-TAVR trial.

BACKGROUND: The risks of leaflet thrombosis and the associated cerebral thromboembolism are unknown according to different anticoagulation dosing after transcatheter aortic valve replacement (TAVR). The aim was to evaluate the incidence of leaflet thrombosis and cerebral thromboembolism between low-dose (30 mg) or standard-dose (60 mg) edoxaban and dual antiplatelet therapy (DAPT) after TAVR. METHODS: In this prespecified subgroup analysis of the ADAPT-TAVR trial, the primary endpoint was the incidence of leaflet thrombosis on 4-dimensional computed tomography at 6-months. Key secondary endpoints were new cerebral lesions on brain magnetic resonance imaging and neurological and neurocognitive dysfunction. RESULTS: Of 229 patients enrolled in this study, 118 patients were DAPT group and 111 were edoxaban group (43 [39.1%] 60 mg vs 68 [61.3%] 30 mg). There was a significantly lower incidence of leaflet thrombosis in the standard-dose edoxaban group than in the DAPT group (2.4% vs 18.3%; odds ratio [OR] 0.11; 95% confidence interval [CI], 0.01-0.55; P = .03). However, no significant difference was observed between low-dose edoxaban and DAPT (15.0% vs 18.3%; OR 0.79; 95% CI, 0.32-1.81; P = .58). Irrespective of different antithrombotic regiments, the percentages of patients with new cerebral lesions on brain MRI and worsening neurological or neurocognitive function were not significantly different. CONCLUSIONS: In patients without an indication for anticoagulation after TAVR, the incidence of leaflet thrombosis was significantly lower with standard-dose edoxaban but not with low-dose edoxaban, as compared with DAPT. However, this differential effect of edoxaban on leaflet thrombosis was not associated with a reduction of new cerebral thromboembolism and neurological dysfunction.

Frequency, Predictors, and Clinical Impact of Valvular and Perivalvular Thrombus After Transcatheter Aortic Valve Replacement.

BACKGROUND: Subclinical aortic valve complex (valvular and perivalvular) thrombus is not rare after transcatheter aortic valve replacement (TAVR). The risk factors and clinical implications of these findings remain uncertain. OBJECTIVES: This study sought to evaluate the frequency, predictors, and clinical outcome of aortic valve complex thrombus after TAVR. METHODS: In the ADAPT-TAVR (Anticoagulation Versus Dual Antiplatelet Therapy for Prevention of Leaflet Thrombosis and Cerebral Embolization After Transcatheter Aortic Valve Replacement) trial comparing edoxaban vs dual antiplatelet therapy in TAVR patients without an indication for chronic anticoagulation, the frequency of valvular (subclinical leaflet thrombus) and perivalvular (supravalvular, subvalvular, and sinus of Valsalva) thrombus was evaluated by 4-dimensional computed tomography at 6 months. The association of these phenomena with new cerebral thromboembolism on brain magnetic resonance imaging, neurologic and neurocognitive dysfunction, and clinical outcomes was assessed. RESULTS: Among 211 patients with 6-month computed tomography evaluations, 91 patients (43.1%) had thrombus at any aortic valve complex, 30 (14.2%) patients had leaflet thrombus, and 78 (37.0%) patients had perivalvular thrombus. A small maximum diameter of the stent at the valve level and low body surface area were independent predictors of aortic valve complex and perivalvular thrombus, and decreased renal function was an independent predictor of leaflet thrombus. No significant differences were observed in new cerebral lesions, neurologic or neurocognitive functions, or clinical outcomes among patients with or without valvular or perivalvular thrombus. CONCLUSIONS: Subclinical aortic valve complex (valvular and perivalvular) thrombus was common in patients who had undergone successful TAVR. However, these imaging phenomena were not associated with new cerebral thromboembolism, neurologic or neurocognitive dysfunction, or adverse clinical outcomes. (Anticoagulation Versus Dual Antiplatelet Therapy for Prevention of Leaflet Thrombosis and Cerebral Embolization After Transcatheter Aortic Valve Replacement [ADAPT-TAVR]; NCT03284827).

Proposed Protocols for Artificial Intelligence Imaging Database in Acute Stroke Imaging.

PURPOSE: To propose standardized and feasible imaging protocols for constructing artificial intelligence (AI) database in acute stroke by assessing the current practice at tertiary hospitals in South Korea and reviewing evolving AI models. MATERIALS AND METHODS: A nationwide survey on acute stroke imaging protocols was conducted using an electronic questionnaire sent to 43 registered tertiary hospitals between April and May 2021. Imaging protocols for endovascular thrombectomy (EVT) in the early and late time windows and during follow-up were assessed. Clinical applications of AI techniques in stroke imaging and required sequences for developing AI models were reviewed. Standardized and feasible imaging protocols for data curation in acute stroke were proposed. RESULTS: There was considerable heterogeneity in the imaging protocols for EVT candidates in the early and late time windows and posterior circulation stroke. Computed tomography (CT)-based protocols were adopted by 70% (30/43), and acquisition of noncontrast CT, CT angiography and CT perfusion in a single session was most commonly performed (47%, 14/30) with the preference of multiphase (70%, 21/30) over single phase CT angiography. More hospitals performed magnetic resonance imaging (MRI)-based protocols or additional MRI sequences in a late time window and posterior circulation stroke. Diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) were most commonly performed MRI sequences with considerable variation in performing other MRI sequences. AI models for diagnostic purposes required noncontrast CT, CT angiography and DWI while FLAIR, dynamic susceptibility contrast perfusion, and T1-weighted imaging (T1WI) were additionally required for prognostic AI models. CONCLUSION: Given considerable heterogeneity in acute stroke imaging protocols at tertiary hospitals in South Korea, standardized and feasible imaging protocols are required for constructing AI database in acute stroke. The essential sequences may be noncontrast CT, DWI, CT/MR angiography and CT/MR perfusion while FLAIR and T1WI may be additionally required.

Impact of leaflet thrombosis on valve haemodynamic status after transcatheter aortic valve replacement.

OBJECTIVES: The effect of subclinical leaflet thrombosis, characterised by hypoattenuated leaflet thickening (HALT), on the valve haemodynamic function and durability of the bioprosthetic valve, is not yet determined. We determined the impact of HALT on valve haemodynamics after transcatheter aortic valve replacement (TAVR) and the predictors of haemodynamic structural valve deterioration (SVD). METHODS: The Anticoagulation vs Dual Antiplatelet Therapy for Prevention of Leaflet Thrombosis and Cerebral Embolization after Transcatheter Aortic Valve Replacement(ADAPT-TAVR) trial is a multicenter, randomised trial that compared edoxaban and dual antiplatelet therapy in patients who had undergone successful TAVR. The presence of HALT was evaluated by four-dimensional CT at 6 months and serial echocardiography performed at baseline, immediately post-TAVR and after 6 months. SVD was defined as at least one of the following: (1) mean transprosthetic gradient ≥20 mm Hg, (2) change in the mean gradient ≥10 mm Hg from baseline, or (3) new or increase in intraprosthetic aortic regurgitation of at least ≥1 grade, resulting in moderate or greater regurgitation. RESULTS: At 6 months, HALT was found in 30 of 211 (14.2%) patients. The presence of HALT did not significantly affect aortic valve mean gradients (with vs without HALT; 14.0±4.8 mm Hg vs 13.7±5.5 mm Hg; p=0.74) at 6 months. SVD was reported in 30 of 206 patients (14.6%) at 6-month follow-up echocardiography. Older age (OR: 1.138; 95% CI: 1.019 to 1.293; p=0.033), use of aortic valve size ≤23 mm (OR: 6.254; 95% CI: 2.230 to 20.569; p=0.001) and mean post-TAVR pressure gradient (OR: 1.233; 95% CI: 1.123 to 1.371; p<0.001) were independent predictors of haemodynamic SVD; however, the presence of HALT was not identified as a predictor of SVD. CONCLUSIONS: In patients who had undergone successful TAVR, aortic valve haemodynamic status was not influenced by the presence of HALT. Although HALT was not a predictor of haemodynamic SVD at 6 months, it warrants further longer-term follow-up to evaluate the effect on long-term valve durability. TRIAL REGISTRATION NUMBER: NCT03284827 (https://www. CLINICALTRIALS: gov).

Automated detection of intracranial aneurysms using skeleton-based 3D patches, semantic segmentation, and auxiliary classification for overcoming data imbalance in brain TOF-MRA.

Accurate and reliable detection of intracranial aneurysms is vital for subsequent treatment to prevent bleeding. However, the detection of intracranial aneurysms can be time-consuming and even challenging, and there is great variability among experts, especially in the case of small aneurysms. This study aimed to detect intracranial aneurysms accurately using a convolutional neural network (CNN) with 3D time-of-flight magnetic resonance angiography (TOF-MRA). A total of 154 3D TOF-MRA datasets with intracranial aneurysms were acquired, and the gold standards were manually drawn by neuroradiologists. We also obtained 113 subjects from a public dataset for external validation. These angiograms were pre-processed by using skull-stripping, signal intensity normalization, and N4 bias correction. The 3D patches along the vessel skeleton from MRA were extracted. Values of the ratio between the aneurysmal and the normal patches ranged from 1:1 to 1:5. The semantic segmentation on intracranial aneurysms was trained using a 3D U-Net with an auxiliary classifier to overcome the imbalance in patches. The proposed method achieved an accuracy of 0.910 in internal validation and external validation accuracy of 0.883 with a 2:1 ratio of normal to aneurysmal patches. This multi-task learning method showed that the aneurysm segmentation performance was sufficient to be helpful in an actual clinical setting.

Effect of Edoxaban Versus Antiplatelet Therapy on Leaflet Thrombosis and Cerebral Thromboembolism After TAVI According to Major Clinical and Anatomic Factors in Prespecified Subgroup Analysis from the ADAPT-TAVR Trial.

It is unknown whether edoxaban versus dual antiplatelet therapy (DAPT) has differential treatment effects on leaflet thrombosis, cerebral thromboembolism, and neurologic or neurocognitive dysfunction according to clinical and anatomic factors after transcatheter aortic valve implantation. To investigate the relative effects of edoxaban and DAPT on leaflet and cerebral thromboembolism in patients with major risk factors. The primary end point of this study was the incidence of leaflet thrombosis on computed tomography at 6 months. The secondary end points were new cerebral lesions on brain magnetic resonance imaging and neurologic and neurocognitive dysfunction between baseline and 6-month follow-up. Cox regression models assessed the consistency of the treatment effects in the prespecified subgroups. The favorable effect of edoxaban versus DAPT on the leaflet thrombosis was consistent across multiple clinical or anatomic subgroups, without significant interaction between the drug effect and each subgroup (p for interaction for age = 0.597, gender = 0.557, body mass index = 0.866, Society of Thoracic Surgeons score = 0.307, valve type = 0.702, edoxaban reduction criteria = 0.604, and valve morphology = 0.688). However, the incidence of new cerebral lesions on brain magnetic resonance imaging and worsening of neurologic and neurocognitive function were not significantly different between the groups among the various key subgroups. The relative effects of edoxaban and DAPT on the risk of leaflet thrombosis, cerebral thromboembolism, and neurologic dysfunction were consistent across a diverse spectrum of clinical or anatomical factors. Further studies are required to define tailored antithrombotic therapy for high-risk groups with specific clinical or anatomic characteristics.

Feasibility and intra-and interobserver reproducibility of quantitative susceptibility mapping with radiomic features for intracranial dissecting intramural hematomas and atherosclerotic calcifications.

Quantitative susceptibility mapping (QSM) for 61 patients with dissecting intramural hematomas (n = 36) or atherosclerotic calcifications (n = 25) in intracranial vertebral arteries were collected to assess intra- and interobserver reproducibility in a 3.0-T MR system between January 2015 and December 2017. Two independent observers each segmented regions of interest for lesions twice. The reproducibility was evaluated using intra-class correlation coefficients (ICC) and within-subject coefficients of variation (wCV) for means and concordance correlation coefficients (CCC) and ICC for radiomic features (CCC and ICC > 0.85) were used. Mean QSM values were 0.277 ± 0.092 ppm for dissecting intramural hematomas and - 0.208 ± 0.078 ppm for atherosclerotic calcifications. ICCs and wCVs were 0.885-0.969 and 6.5-13.7% in atherosclerotic calcifications and 0.712-0.865 and 12.4-18.7% in dissecting intramural hematomas, respectively. A total of 9 and 19 reproducible radiomic features were observed in dissecting intramural hematomas and atherosclerotic calcifications, respectively. QSM measurements in dissecting intramural hematomas and atherosclerotic calcifications were feasible and reproducible between intra- and interobserver comparisons, and some reproducible radiomic features were demonstrated.

Impact of lesion size on reproducibility of quantitative measurement and radiomic features in vessel wall MRI.

OBJECTIVES: To investigate reproducibility of quantitative measurement and radiomic features in vessel wall MRI (VW-MRI), evaluate the impact of lesion size, and identify reproducible radiomic features. METHODS: This retrospective, single-center study included 251 patients (mean age, 53 ± 12 years; 128 women) with atherosclerosis, dissection, aneurysm, moyamoya disease, and vasculitis of the intracranial arteries who underwent three-dimensional turbo spin echo T1-weighted image. Lesion thickness, volume, and signal intensity were measured, and 157 radiomic features were extracted. Intra-observer reproducibility of quantitative measurement and radiomic features was evaluated by calculating the concordance correlation coefficient (CCC) and proportion of radiomic features above the predefined CCC. The reproducibility of quantitative measurement and radiomic features according to lesion size (binary comparison and stratification into 5 and 18 groups) was evaluated. RESULTS: There was an overall serial increase in CCC for thickness measurement when stratified by lesion thickness and volume. There was an overall serial increase in the median CCC for radiomic features and proportion of radiomic features with CCC > 0.85 when stratified by lesion thickness and volume. Reproducibility of radiomic features was higher in the lesions with thickness ≥ 2.5 mm (median CCC, 0.97 vs. 0.89, p < .001; proportion with CCC > 0.85, 88.5% vs. 59.6%, p < .001) and volume ≥ 50 mm3 (median CCC, 0.97 vs. 0.88, p < .001; proportion with CCC > 0.85, 90.4% vs. 59.0%, p < .001). Intensity-based statistical features remained most reproducible in the thinnest and smallest lesions. CONCLUSIONS: Intra-observer reproducibility of thickness measurement and radiomic features was affected by lesion size in VW-MRI although intensity-based statistical features remained most reproducible. KEY POINTS: • There was an overall serial increase in CCC for thickness measurement when stratified by lesion size. • There was an overall serial increase in the median CCC for radiomic features and proportion of radiomic features with CCC > 0.85 when stratified by lesion size. • Intensity-based statistical features remained most reproducible in the thinnest and smallest lesions.

Sequence-Type Classification of Brain MRI for Acute Stroke Using a Self-Supervised Machine Learning Algorithm.

We propose a self-supervised machine learning (ML) algorithm for sequence-type classification of brain MRI using a supervisory signal from DICOM metadata (i.e., a rule-based virtual label). A total of 1787 brain MRI datasets were constructed, including 1531 from hospitals and 256 from multi-center trial datasets. The ground truth (GT) was generated by two experienced image analysts and checked by a radiologist. An ML framework called ImageSort-net was developed using various features related to MRI acquisition parameters and used for training virtual labels and ML algorithms derived from rule-based labeling systems that act as labels for supervised learning. For the performance evaluation of ImageSort-net (MLvirtual), we compare and analyze the performances of models trained with human expert labels (MLhumans), using as a test set blank data that the rule-based labeling system failed to infer from each dataset. The performance of ImageSort-net (MLvirtual) was comparable to that of MLhuman (98.5% and 99%, respectively) in terms of overall accuracy when trained with hospital datasets. When trained with a relatively small multi-center trial dataset, the overall accuracy was relatively lower than that of MLhuman (95.6% and 99.4%, respectively). After integrating the two datasets and re-training them, MLvirtual showed higher accuracy than MLvirtual trained only on multi-center datasets (95.6% and 99.7%, respectively). Additionally, the multi-center dataset inference performances after the re-training of MLvirtual and MLhumans were identical (99.7%). Training of ML algorithms based on rule-based virtual labels achieved high accuracy for sequence-type classification of brain MRI and enabled us to build a sustainable self-learning system.

Edoxaban Versus Dual Antiplatelet Therapy for Leaflet Thrombosis and Cerebral Thromboembolism After TAVR: The ADAPT-TAVR Randomized Clinical Trial.

BACKGROUND: It is unknown whether the direct oral anticoagulant edoxaban can reduce leaflet thrombosis and the accompanying cerebral thromboembolic risk after transcatheter aortic valve replacement. In addition, the causal relationship of subclinical leaflet thrombosis with cerebral thromboembolism and neurological or neurocognitive dysfunction remains unclear. METHODS: We conducted a multicenter, open-label randomized trial comparing edoxaban with dual antiplatelet therapy (aspirin plus clopidogrel) in patients who had undergone successful transcatheter aortic valve replacement and did not have an indication for anticoagulation. The primary end point was an incidence of leaflet thrombosis on 4-dimensional computed tomography at 6 months. Key secondary end points were the number and volume of new cerebral lesions on brain magnetic resonance imaging and the serial changes of neurological and neurocognitive function between 6 months and immediately after transcatheter aortic valve replacement. RESULTS: A total of 229 patients were included in the final intention-to-treat population. There was a trend toward a lower incidence of leaflet thrombosis in the edoxaban group compared with the dual antiplatelet therapy group (9.8% versus 18.4%; absolute difference, -8.5% [95% CI, -17.8% to 0.8%]; P=0.076). The percentage of patients with new cerebral lesions on brain magnetic resonance imaging (edoxaban versus dual antiplatelet therapy, 25.0% versus 20.2%; difference, 4.8%; 95% CI, -6.4% to 16.0%) and median total new lesion number and volume were not different between the 2 groups. In addition, the percentages of patients with worsening of neurological and neurocognitive function were not different between the groups. The incidence of any or major bleeding events was not different between the 2 groups. We found no significant association between the presence or extent of leaflet thrombosis with new cerebral lesions and a change of neurological or neurocognitive function. CONCLUSIONS: In patients without an indication for long-term anticoagulation after successful transcatheter aortic valve replacement, the incidence of leaflet thrombosis was numerically lower with edoxaban than with dual antiplatelet therapy, but this was not statistically significant. The effects on new cerebral thromboembolism and neurological or neurocognitive function were also not different between the 2 groups. Because the study was underpowered, the results should be considered hypothesis generating, highlighting the need for further research. REGISTRATION: URL: https://www. CLINICALTRIALS: gov. Unique identifier: NCT03284827.

Structural Changes of Intra and Extracranial Artery Dissection: a Study of High-Resolution Magnetic Resonance Imaging.

OBJECTIVES: The prognosis of a cerebral artery dissection is known to be benign, but the structural changes of vessel wall at follow-up are not well known. The natural course of an intracranial and extracranial artery dissection may differ due to structural differences. We aimed to figure out how stenosis and other wall features change, according to the dissection location. MATERIALS AND METHODS: We retrospectively enrolled patients who suffered an ischemic stroke or transient ischemic attack due to a dissection and who had undergone both initial and follow-up high-resolution magnetic resonance imaging (HRMRI). Patients were dichotomized to intracranial or extracranial dissection group. The clinical and HRMRI characteristics of two groups were compared. Factors associated with stenosis changes were also investigated. RESULTS: A total of 57 patients (intracranial, n = 43; and extracranial, n = 14) were enrolled. The mean age (45.6 vs. 32.2, p < 0.001) was higher and hypertension (37.2% vs. 7.1%, p = 0.04) was more frequent in the intracranial dissection group. In HRMRI analysis, stenosis improvement (27.9% vs. 85.7%, p < 0.001) were more frequent whereas residual wall enhancement (86.0% vs. 46.2%, p = 0.006) and intramural hematoma (62.8% vs. 21.4%, p = 0.007) were less frequent in the extracranial dissection group. Multivariate analysis indicated that extracranial location was the only independent factor (odds ratio 8.98, 95 % confidence interval 1.45-55.65; p = 0.02) associated with stenosis improvement. CONCLUSIONS: Younger age, stenosis improvement, disappearance of wall enhancement and intramural hematoma were more frequent in an extracranial dissection compared with an intracranial dissection. An extracranial location is independently associated with stenosis improvement in dissection patients.

Stability of MRI radiomic features according to various imaging parameters in fast scanned T2-FLAIR for acute ischemic stroke patients.

From May 2015 to June 2016, data on 296 patients undergoing 1.5-Tesla MRI for symptoms of acute ischemic stroke were retrospectively collected. Conventional, echo-planar imaging (EPI) and echo train length (ETL)-T2-FLAIR were simultaneously obtained in 118 patients (first group), and conventional, ETL-, and repetition time (TR)-T2-FLAIR were simultaneously obtained in 178 patients (second group). A total of 595 radiomics features were extracted from one region-of-interest (ROI) reflecting the acute and chronic ischemic hyperintensity, and concordance correlation coefficients (CCC) of the radiomics features were calculated between the fast scanned and conventional T2-FLAIR for paired patients (1st group and 2nd group). Stabilities of the radiomics features were compared with the proportions of features with a CCC higher than 0.85, which were considered to be stable in the fast scanned T2-FLAIR. EPI-T2-FLAIR showed higher proportions of stable features than ETL-T2-FLAIR, and TR-T2-FLAIR also showed higher proportions of stable features than ETL-T2-FLAIR, both in acute and chronic ischemic hyperintensities of whole- and intersection masks (p < .002). Radiomics features in fast scanned T2-FLAIR showed variable stabilities according to the sequences compared with conventional T2-FLAIR. Therefore, radiomics features may be used cautiously in applications for feature analysis as their stability and robustness can be variable.

Reproducibility of radiomic features in SENSE and compressed SENSE: impact of acceleration factors.

OBJECTIVES: To investigate the impact of acceleration factors on reproducibility of radiomic features in sensitivity encoding (SENSE) and compressed SENSE (CS), compare between SENSE and CS, and identify reproducible radiomic features. METHODS: Three-dimensional turbo spin echo T1-weighted imaging was performed in 14 healthy volunteers (mean age, 57 years; range, 33-67 years; 7 men) under SENSE and CS with accelerator factors of 5.5, 6.8, and 9.7. Eight anatomical locations (brain parenchyma, salivary glands, masseter muscle, tongue, pharyngeal mucosal space, eyeballs) were evaluated. Reproducibility of radiomic features was evaluated by calculating concordance correlation coefficient (CCC) in reference to the original image (SENSE with acceleration factor of 3.5). Reproducibility of radiomic features among acceleration factors and between SENSE and CS was compared. RESULTS: Proportion of radiomic features with CCC > 0.85 in reference to the original image was lower with higher acceleration factors in both SENSE and CS across all anatomical locations (p < .001). Proportion of radiomic features with CCC > 0.85 in reference to the original image was higher in SENSE compared with CS (SENSE, 6.7-7.3% vs CS, 4.4-5.0%; p < .001). Run percentage of gray-level run-length matrix (GLRLM) with wavelet D showed CCC > 0.85 in reference to the original image in both SENSE and CS at acceleration factor of 9.7 in the highest number of anatomical locations. CONCLUSIONS: Higher acceleration factors resulted in lower reproducibility of radiomic features in both SENSE and CS, and SENSE showed higher reproducibility of radiomic features than CS in reference to the original image. Run percentage of GLRLM with wavelet D was identified as the most reproducible feature. KEY POINTS: • Reproducibility of radiomic features in reference to the original image was lower with higher acceleration factors in both sensitivity encoding (SENSE) and compressed SENSE (CS) across all anatomical locations (p < .001). • SENSE showed higher proportions of radiomic features with CCC > 0.85 in reference to the original image (SENSE, 6.7-7.3% vs CS, 4.4-5.0%; p < .001) compared with CS. • Run percentage of gray-level run-length matrix (GLRLM) with wavelet D showed CCC > 0.85 in reference to the original image in both SENSE and CS with the highest acceleration factor.

Rationale and design of the ADAPT-TAVR trial: a randomised comparison of edoxaban and dual antiplatelet therapy for prevention of leaflet thrombosis and cerebral embolisation after transcatheter aortic valve replacement.

INTRODUCTION: Optimal antithrombotic strategy following transcatheter aortic valve replacement (TAVR) is still unknown. We hypothesised that the direct factor Xa inhibitor edoxaban can potentially prevent subclinical leaflet thrombosis and cerebral embolisation compared with conventional dual antiplatelet therapy (DAPT) in patients undergoing TAVR. METHODS AND ANALYSIS: The ADAPT-TAVR trial is an international, multicentre, randomised, open-label, superiority trial comparing edoxaban-based strategy and DAPT strategy in patients without an indication for oral anticoagulation who underwent successful TAVR. A total of 220 patients are randomised (1:1 ratio), 1-7 days after successful TAVR, to receive either edoxaban (60 mg daily or 30 mg daily if patients had dose-reduction criteria) or DAPT using aspirin (100 mg daily) plus clopidogrel (75 mg daily) for 6 months. The primary endpoint was an incidence of leaflet thrombosis on four-dimensional, volume-rendered cardiac CT imaging at 6 months post-TAVR. The key secondary endpoints were the number of new lesions and new lesion volume on brain diffusion-weighted MRI and the changes in neurological and neurocognitive function assessment between immediate post-TAVR and 6 months of study drug administration. Detailed clinical information on thromboembolic and bleeding events were also assessed. ETHICS AND DISSEMINATION: Ethic approval has been obtained from the Ethics Committee/Institutional Review Board of Asan Medical Center (approval number: 2017-1317) and this trial is also approved by National Institute of Food and Drug Safety Evaluation of Republic of Korea (approval number: 31511). Results of this study will be disseminated in scientific publication in reputed journals. TRIAL REGISTRATION NUMBER: NCT03284827.

A Multicenter Survey of Acute Stroke Imaging Protocols for Endovascular Thrombectomy.

PURPOSE: Identifying current practices in acute stroke imaging is essential for establishing optimal imaging protocols. We surveyed and assessed the current status of acute stroke imaging for endovascular thrombectomy (EVT) at tertiary hospitals throughout South Korea. MATERIALS AND METHODS: An electronic questionnaire on imaging protocols for EVT in patients with acute ischemic stroke was e-mailed to physicians at 42 registered tertiary hospitals, and their responses were collected between February and March 2020. RESULTS: Of the 36 hospitals participating in the survey, 69% (25/36) adopted computed tomography (CT)-based protocols, whereas 31% (11/36) adopted magnetic resonance (MR)-based protocols. Non-enhanced CT (NECT) was the initial imaging study at 28%, NECT with CT angiography (CTA) at 36%, and NECT with CTA and CT perfusion (CTP) at 33% of hospitals. Perfusion imaging was performed at 61% (22/36), CTP at 44% (16/36), and MR perfusion at 17% (6/36) of hospitals. Multiphase CTA was performed at 67%, single-phase CTA at 11%, time-of-flight MR angiography (MRA) at 8%, contrast-enhanced MRA at 8%, and both at 6% of hospitals. For late time window stroke, 50% of hospitals used identical imaging protocols to those for early time window stroke, 39% used additional MR imaging (MRI), and 6% converted the imaging strategy from CT to MRI. Post-processing programs were used at 28% (10/36), and RAPID software at 14% (5/36) of hospitals, respectively. Most hospitals (92%) used the same imaging protocols for posterior and anterior circulation strokes. CONCLUSION: Our multicenter survey demonstrated considerable heterogeneity in acute stroke imaging protocols across South Korean tertiary hospitals, suggesting that hospitals refine their imaging protocols according to hospital-specific conditions.

Pretreatment brain volumes can affect the effectiveness of deep brain stimulation in Parkinson's disease patients.

We aimed to assess whether brain volumes may affect the results of deep brain stimulation (DBS) in patients with Parkinson's disease (PD). Eighty-one consecutive patients with PD (male:female 40:41), treated with DBS between June 2012 and December 2017, were enrolled. Total and regional brain volumes were measured using automated brain volumetry (NeuroQuant). The Unified Parkinson Disease Rating Scale motor score quotient was used to assess changes in clinical outcome and compare the preoperative regional brain volume in patients categorized into the higher motor improvement and lower motor improvement groups based on changes in the postoperative scores. The study groups showed significant volume differences in multiple brain areas. In the higher motor improvement group, the anterior cingulate and right thalamus showed high volumes after false discovery rate (FDR) correction. In the lower motor improvement group, the left caudate, paracentral, right primary sensory and left primary motor cortex showed high volume, but no area showed high volumes after FDR correction. Our data suggest that the effectiveness of DBS in patients with PD may be affected by decreased brain volume in different areas, including the cingulate gyrus and thalamus. Preoperative volumetry could help predict outcomes in patients with PD undergoing DBS.

Added diagnostic values of three-dimensional high-resolution proton density-weighted magnetic resonance imaging for unruptured intracranial aneurysms in the circle-of-Willis: Comparison with time-of-flight magnetic resonance angiography.

BACKGROUND: Advanced imaging methods can enhance the identification of aneurysms of the infundibula, which can reduce unnecessary follow-ups or further work-up, fear, and anxiety in patients. PURPOSE: This study aimed to evaluate the added diagnostic value of three-dimensional proton density-weighted vessel wall magnetic resonance imaging (3D-PD MRI) in identifying aneurysms from index lesions refer to vascular bulging lesions without vessels arising from the apex, observed using volume-rendered TOF-MRA in the circle-of-Willis compared with time-of-flight magnetic resonance angiography (TOF-MRA). STUDY TYPE: Retrospective. POPULATION: A total of 299 patients who underwent 3D-PD MRI, digital subtraction angiography (DSA), and TOF-MRA between January 2012 and December 2016 were retrospectively enrolled in this study. FIELD STRENGTH/SEQUENCE: 3 Tesla, 3D-PD MRI. ASSESSMENT: Three neuroradiologists independently evaluated TOF-MRA and 3D-PD MRI combined with TOF-MRA for the determination of intracranial aneurysms in patients with index lesions within the circle of Willis. Final diagnoses were made by another neuroradiologist and neurointerventionist in consensus using DSA as the reference standard. The diagnostic performance and proportions of undetermined lesions on TOF-MRA and 3D-PD MRI with TOF-MRA were assessed based on the final diagnoses. STATISTICAL TESTS: The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for the diagnosis of unruptured intracranial aneurysms were calculated for each imaging modality. RESULTS: Of 452 lesions identified on volume-rendered TOF-MRA images, 173 (38%) aneurysms and 276 (61%) infundibula were finally diagnosed on DSA. 3D-PD MRI with TOF-MRA showed superior diagnostic performance (p = .001; accuracy, 85.5% versus 95.4%), superior area under the receiver operating characteristic curve over TOF-MRA (p = .001; 0.837 versus 0.947), and a lower proportion of undetermined lesions than TOF-MRA (p = .001; 25.1% versus 2.3%). DATA CONCLUSION: For unruptured intracranial aneurysms in the circle of Willis, 3D-PD MRI can complement TOF-MRA to improve diagnostic performance and lower the proportion of undetermined lesions.

Deep-learning-based image quality enhancement of compressed sensing magnetic resonance imaging of vessel wall: comparison of self-supervised and unsupervised approaches.

While high-resolution proton density-weighted magnetic resonance imaging (MRI) of intracranial vessel walls is significant for a precise diagnosis of intracranial artery disease, its long acquisition time is a clinical burden. Compressed sensing MRI is a prospective technology with acceleration factors that could potentially reduce the scan time. However, high acceleration factors result in degraded image quality. Although recent advances in deep-learning-based image restoration algorithms can alleviate this problem, clinical image pairs used in deep learning training typically do not align pixel-wise. Therefore, in this study, two different deep-learning-based denoising algorithms-self-supervised learning and unsupervised learning-are proposed; these algorithms are applicable to clinical datasets that are not aligned pixel-wise. The two approaches are compared quantitatively and qualitatively. Both methods produced promising results in terms of image denoising and visual grading. While the image noise and signal-to-noise ratio of self-supervised learning were superior to those of unsupervised learning, unsupervised learning was preferable over self-supervised learning in terms of radiomic feature reproducibility.