Novel, braided, self-expandable stent designed for the treatment of pulsatile tinnitus caused by intracranial venous stenosis: first-in-human experience and long-term outcomes.

BACKGROUND: Pulsatile tinnitus (PT) can be a disabling clinical condition, which may be caused by a sigmoid/transverse sinus stenosis (STSS). Intracranial venous stenting with off-label carotid or peripheral venous stents has been used successfully to treat this condition. We present the results of a cohort of patients presenting with PT treated with a novel, dedicated, braided stent for the endovascular treatment of STSS. METHODS: Twelve patients presenting with PT and associated STSS were treated at our institution (December 2022-June 2023). All clinical and procedural variables were prospectively collected. We used the Tinnitus Function Index (TFI) and the Tinnitus Handicap Inventory (THI) scores to assess the impact of PT on quality of life before and after the treatment (mean follow-up: 10.3 months). RESULTS: Twelve women (mean age: 44±16.5 years) presenting with PT and STSS were treated. Mean pretreatment TFI/THI scores were 78.8/77. The BosStent was successfully deployed in all patients. We experienced no intraprocedural/postoperative complications. Intra-stent angioplasty was performed in three cases. All patients reported a complete resolution of PT symptoms within 1 month and remained stable and PT-free at the last follow-up (mean posttreatment TFI/THI score: 7.1/5, p<0001). CONCLUSIONS: The BosStent was successfully used in a cohort of patients with PT without any intraprocedural complications. All the patients experienced a complete resolution of PT symptoms after 1 month, which was stable during the follow-up period. Further studies with larger populations will be necessary to investigate the safety and effectiveness of this novel stent for the treatment of PT with STSS.

Volumetric microscopy of cerebral arteries with a miniaturized optical coherence tomography imaging probe.

Endovascular interventions are increasingly becoming the preferred approach for treating strokes and cerebral artery diseases. These procedures rely on sophisticated angiographical imaging guidance, which encounters challenges because of limited contrast and spatial resolution. Achieving a more precise visualization of the underlying arterial pathology and neurovascular implants is crucial for accurate procedural decision-making. In a human study involving 32 patients, we introduced the clinical application of a miniaturized endovascular neuro optical coherence tomography (nOCT) imaging probe. This technology was designed to navigate the tortuous paths of the cerebrovascular circulation and to offer high-resolution imaging in situ. The nOCT probe is compatible with standard neurovascular microcatheters, integrating with the procedural workflow used in clinical routine. Equipped with a miniaturized optical fiber and a distal lens, the probe illuminates the tissue and collects the backscattered, near-infrared light. While rotating the fiber and the lens at high speed, the probe is rapidly retracted, creating a spiral-shaped light pattern to comprehensively capture the arterial wall and implanted devices. Using nOCT, we demonstrated volumetric microscopy of cerebral arteries in patients undergoing endovascular procedures. We imaged the anterior and posterior circulation of the brain, including distal segments of the internal carotid and middle-cerebral arteries, as well as the vertebral, basilar, and posterior cerebral arteries. We captured a broad spectrum of neurovascular pathologies, such as brain aneurysms, ischemic stroke, arterial stenoses, dissections, and intracranial atherosclerotic disease. nOCT offered artifact-free, high-resolution visualizations of intracranial artery pathology and neurovascular devices.

Clinical uncertainty in large vessel occlusion ischemic stroke: does automated perfusion imaging make a difference? An intra-rater and inter-rater agreement study.

BACKGROUND: Limited research exists regarding the impact of neuroimaging on endovascular thrombectomy (EVT) decisions for late-window cases of large vessel occlusion (LVO) stroke. OBJECTIVE: T0 assess whether perfusion CT imaging: (1) alters the proportion of recommendations for EVT, and (2) enhances the reliability of EVT decision-making compared with non-contrast CT and CT angiography. METHODS: We conducted a survey using 30 patients drawn from an institutional database of 3144 acute stroke cases. These were presented to 29 Canadian physicians with and without perfusion imaging. We used non-overlapping 95% confidence intervals and difference in agreement classification as criteria to suggest a difference between the Gwet AC1 statistics (κG). RESULTS: The percentage of EVT recommendations differed by 1.1% with or without perfusion imaging. Individual decisions changed in 21.4% of cases (11.3% against EVT and 10.1% in favor). Inter-rater agreement (κG) among the 29 raters was similar between non-perfusion and perfusion CT neuroimaging (κG=0.487; 95% CI 0.327 to 0.647 and κG=0.552; 95% CI 0.430 to 0.675). The 95% CIs overlapped with moderate agreement in both. Intra-rater agreement exhibited overlapping 95% CIs for all 28 raters. κG was either substantial or excellent (0.81-1) for 71.4% (20/28) of raters in both groups. CONCLUSIONS: Despite the minimal difference in overall EVT recommendations with either neuroimaging protocol one in five decisions changed with perfusion imaging. Regarding agreement we found that the use of automated CT perfusion images does not significantly impact the reliability of EVT decisions for patients with late-window LVO.

Endovascular treatment of wide-neck bifurcation aneurysms: the eCLIPs device.

The endovascular clip system device, eCLIPs (eVasc, Vancouver, British Columbia, Canada), was introduced almost a decade ago for the treatment of wide-neck bifurcation aneurysms,1-3 which represent a challenge for both endovascular and surgical approaches. Several techniques and devices (intrasaccular or intra-arterial) have been introduced and are currently available in order to improve the technical and clinical outcomes of aneurysm embolization. Flow diversion and flow disruption have shown controversial results in this subtype of aneurysm. In this video we present the use of the eCLIPs device to treat a ruptured, wide-neck aneurysm of the top of the basilar artery. The decisional approach, technical details, and the different steps of the endovascular treatment are described. The final part of the video is dedicated to the characteristics of the device for re-endothelialization4 and flow diversion (video 1).5 neurintsurg;16/3/229/V1F1V1Video 1 .

Deep learning-based cerebral aneurysm segmentation and morphological analysis with three-dimensional rotational angiography.

BACKGROUND: The morphological assessment of cerebral aneurysms based on cerebral angiography is an essential step when planning strategy and device selection in endovascular treatment, but manual evaluation by human raters only has moderate interrater/intrarater reliability. METHODS: We collected data for 889 cerebral angiograms from consecutive patients with suspected cerebral aneurysms at our institution from January 2017 to October 2021. The automatic morphological analysis model was developed on the derivation cohort dataset consisting of 388 scans with 437 aneurysms, and the performance of the model was tested on the validation cohort dataset consisting of 96 scans with 124 aneurysms. Five clinically important parameters were automatically calculated by the model: aneurysm volume, maximum aneurysm size, neck size, aneurysm height, and aspect ratio. RESULTS: On the validation cohort dataset the average aneurysm size was 7.9±4.6 mm. The proposed model displayed high segmentation accuracy with a mean Dice similarity index of 0.87 (median 0.93). All the morphological parameters were significantly correlated with the reference standard (all P<0.0001; Pearson correlation analysis). The difference in the maximum aneurysm size between the model prediction and reference standard was 0.5±0.7 mm (mean±SD). The difference in neck size between the model prediction and reference standard was 0.8±1.7 mm (mean±SD). CONCLUSION: The automatic aneurysm analysis model based on angiography data exhibited high accuracy for evaluating the morphological characteristics of cerebral aneurysms.

Safety and Efficacy of Flow Diverters for Treatment of Unruptured Anterior Communicating Artery Aneurysms: Retrospective Multicenter Study.

BACKGROUND: The anterior communicating artery (AComm) region is the most common site of intracranial aneurysms, with increased rupture risk compared with other locations. Overall, flow diverters present as a safe and efficacious treatment for intracranial aneurysms, but there is paucity of data for their use in the treatment of unruptured AComm aneurysms. We present the largest multicentric analysis evaluating the outcomes of flow diverters in AComm aneurysm treatment. METHODS: Databases from 10 centers were retrospectively reviewed for unruptured AComm aneurysms treated with flow diverters. Demographics, clinical presentation, radiographic characteristics, procedural complications, and outcomes were assessed. RESULTS: A total of 144 patients harboring 147 AComm aneurysms were treated between January 2012 and December 2021. Seventy-four were women (51.4%) and median age was 60 (IQR 50-67) years. All were unruptured AComm aneurysms. Half of the cohort had similar anterior cerebral artery sizes (51.4%). The most common morphology was saccular (94.6%), with a branch involvement in 32.7% of cases. Median vessel diameter was 2.4 mm, and the Pipeline Flex was the most prevalent device (32.7%). Median follow-up time was 17 months, with complete occlusion in 86.4% at the last follow-up. Functional independence (modified Rankin Scale score 0-2) was reported in 95.1%. Intraprocedural complications occurred in 5.6%, and postoperative complications were noted in 9.7% of cases. Combined major complication and mortality rate was 2.1%. CONCLUSIONS: Our study suggests that flow diverters are a useful treatment for AComm aneurysms. Mid-term results indicated favorable aneurysm occlusion with a good safety profile. Additional prospective studies with longer follow-up periods and independent adjudication are warranted to better assess these results.

Automatic Ischemic Core Estimation Based on Noncontrast-Enhanced Computed Tomography.

BACKGROUND: Evaluating the extent of ischemic change is an important step in deciding whether to use thrombolysis or mechanical thrombectomy, but the current standard method, Alberta Stroke Program Early CT Score, is semiquantitative and has low consistency among raters. We aim to create and test a fully automated machine learning-based ischemic core segmentation model using only noncontrast-enhanced computed tomography images. METHODS: In this multicenter retrospective study, patients with anterior circulation acute ischemic stroke who received both computed tomography (CT) and magnetic resonance imaging before thrombolysis or recanalization treatment between 2013 and 2019 were included. On CT, the ischemic core was manually delineated using the diffusion-weighted image and apparent diffusion coefficient maps. A deep learning-based ischemic core segmentation model (DL model) was developed using data from 3 institutions (n=272), and the model performance was validated using data from 3 institutions (n=106 Results: The median time ).between CT and magnetic resonance imaging in the validation cohort was 18 min. The DL model calculated ischemic core volume was significantly correlated with the reference standard (intraclass correlation coefficient, 0.90, P<0.01). Both the early time window (≤4.5 hours from onset; intraclass correlation coefficient, 0.90, P<0.01) and the late time window (>4.5 hours from onset; intraclass correlation coefficient, 0.93, P<0.01) had significant correlations. The median difference in ivolume between the model and the reference standard was 4.7 mL (interquartile range, 0.8-12.4 mL). The DL model performed well in distinguishing large ischemic cores (>70 mL), with a sensitivity of 84.2%, specificity of 97.7%, and area under the curve of 0.91. CONCLUSIONS: The deep learning-based ischemic core segmentation model, which was based on noncontrast-enhanced CT, demonstrated high accuracy in assessing ischemic core volume in patients with anterior circulation acute ischemic stroke.

Bioresorbable Poly (L-Lactic Acid) Flow Diverter Versus Cobalt-Chromium Flow Diverter: In Vitro and In Vivo Analysis.

BACKGROUND: Permanent metallic flow diverter (FD) implantation for treatment of intracranial aneurysms requires antiplatelet therapy for an unclear duration and restricts postprocedural endovascular access. Bioresorbable FDs are being developed as a solution to these issues, but the biological reactions and phenomena induced by bioresorbable FDs have not been compared with those of metallic FDs. METHODS: We have developed a bioresorbable poly (L-lactic acid) FD (PLLA-FD) and compared it with an FD composed of cobalt-chromium and platinum-tungsten (CoCr-FD). FD mechanical performance and in vitro degradation of the PLLA-FD were evaluated. For in vivo testing in a rabbit aneurysm model, FDs were implanted at the aneurysm site and the abdominal aorta in the PLLA-FD group (n=21) and CoCr-FD group (n=15). Aneurysm occlusion rate, branch patency, and thrombus formation within the FD were evaluated at 3, 6, and 12 months. Local inflammation and neointima structure were also evaluated. RESULTS: Mean strut, porosity, and pore density for the PLLA-FD were 41.7 µm, 60%, and 20 pores per mm2, respectively. The proportion of aneurysms exhibiting a neck remnant or complete occlusion did not significantly differ between the groups; however, the complete occlusion rate was significantly higher in the PLLA-FD group (48% versus 13%; P=0.0399). Branch occlusion and thrombus formation within the FD were not observed in either group. In the PLLA-FD group, CD68 immunoreactivity was significantly higher, but neointimal thickness decreased over time and did not significantly differ from that of the CoCr-FD at 12 months. Collagen fibers significantly predominated over elastic fibers in the neointima in the PLLA-FD group. The opposite was observed in the CoCr-FD group. CONCLUSIONS: The PLLA-FD was as effective as the CoCr-FD in this study and is feasible for aneurysm treatment. No morphological or pathological problems were observed with PLLA-FD over a 1-year period.

Effect of gait distance during robot training on walking independence after acute brain injury.

This study aimed to determine whether the distance of gait training using a hybrid assistive limb (HAL) is related to the improvement of walking independence in patients with acute brain injury. This was an exploratory, observational study. Thirty patients having hemiplegia (functional ambulation category, FAC score ≤2) with acute stroke or after brain tumor surgery were included. Patients performed 4 sessions of gait training using HAL (60 min/session), 1-3 sessions/week, combined with conventional physical therapy. The gait distance achieved in the four training sessions using HAL was measured. FAC score was measured before and after intervention. Patients were divided into groups A, B, and C, for FAC score improvements of 0, 1, and ≥2, respectively. Gait distance was compared among groups using one-way analysis of variance. Gait distance in group C was significantly longer than that ingroup A [mean (standard deviation): 2527 (1725) m vs. 608 (542) m]. This study suggested that the gait distance achieved during training using the HAL may be a clinical indicator of the effectiveness of the HAL on gait training in patients with acute brain injury.Clinical trial registration number: UMIN000012764 R000014756.

Motion artifact correction for cone beam CT stroke imaging: a prospective series.

BACKGROUND: Imaging assessment for acute ischemic stroke (AIS) patients in the angiosuite using cone beam CT (CBCT) has created increased interest since endovascular treatment became the first line therapy for proximal vessel occlusions. One of the main challenges of CBCT imaging in AIS patients is degraded image quality due to motion artifacts. This study aims to evaluate the prevalence of motion artifacts in CBCT stroke imaging and the effectiveness of a novel motion artifact correction algorithm for image quality improvement. METHODS: Patients presenting with acute stroke symptoms and considered for endovascular treatment were included in the study. CBCT scans were performed using the angiosuite X-ray system. All CBCT scans were post-processed using a motion artifact correction algorithm. Motion artifacts were scored before and after processing using a 4-point scale. RESULTS: We prospectively included 310 CBCT scans from acute stroke patients. 51% (n=159/310) of scans had motion artifacts, with 24% being moderate to severe. The post-processing algorithm improved motion artifacts in 91% of scans with motion (n=144/159), restoring clinical diagnostic capability in 34%. Overall, 76% of the scans were sufficient for clinical decision-making before correction, which improved to 93% (n=289/310) after post-processing with our algorithm. CONCLUSIONS: Our results demonstrate that CBCT motion artifacts are significantly reduced using a novel post-processing algorithm, which improved brain CBCT image quality and diagnostic assessment for stroke. This is an important step on the road towards a direct-to-angio approach for endovascular thrombectomy (EVT) treatment.

Machine Learning Risk Prediction for Incident Heart Failure in Patients With Atrial Fibrillation.

Background: Atrial fibrillation (AF) increases the risk of heart failure (HF); however, little focus is placed on the risk stratification for, and prevention of, incident HF in patients with AF. Objectives: This study aimed to construct and validate a machine learning (ML) prediction model for HF hospitalization in patients with AF. Methods: The Fushimi AF Registry is a community-based prospective survey of patients with AF in Fushimi-ku, Kyoto, Japan. We divided the data set of the registry into derivation (n = 2,383) and validation (n = 2,011) cohorts. An ML model was built to predict the incidence of HF hospitalization using the derivation cohort, and predictive ability was examined using the validation cohort. Results: HF hospitalization occurred in 606 patients (14%) during a median follow-up period of 4.4 years in the entire registry. Data of transthoracic echocardiography and biomarkers were frequently nominated as important predictive variables across all 6 ML models. The ML model based on a random forest algorithm using 7 variables (age, history of HF, creatinine clearance, cardiothoracic ratio on x-ray, left ventricular [LV] ejection fraction, LV end-systolic diameter, and LV asynergy) had high prediction performance (area under the receiver operating characteristics curve [AUC]: 0.75) and was significantly superior to the Framingham HF risk model (AUC: 0.67; P < 0.001). Based on Kaplan-Meier curves, the ML model could stratify the risk of HF hospitalization during the follow-up period (log-rank; P < 0.001). Conclusions: The ML model revealed important predictors and helped us to stratify the risk of HF, providing opportunities for the prevention of HF in patients with AF.

A multicenter prospective registry of Borden type I dural arteriovenous fistula: results of a 3-year follow-up study.

PURPOSE: Although intracranial dural arteriovenous fistula (DAVF) without retrograde leptomeningeal venous drainage (Borden type I) is reported to have a benign nature, no study has prospectively determined its clinical course. Here, we report a 3-year prospective observational study of Borden type I DAVF. METHODS: From April 2013 to March 2016, consecutive patients with DAVF were screened at 13 study institutions. We collected data on baseline characteristics, clinical symptoms, angiography, and neuroimaging. Patients with Borden type I DAVF received conservative care while palliative intervention was considered when the neurological symptoms were intolerable, and were followed at 6, 12, 24, and 36 months after inclusion. RESULTS: During the study period, 110 patients with intracranial DAVF were screened and 28 patients with Borden type I DAVF were prospectively followed. None of the patients had conversion to higher type of Borden classification or intracranial hemorrhage during follow-up. Five patients showed spontaneous improvement or disappearance of neurological symptoms (5/28, 17.9%), and 5 patients showed a spontaneous decrease or disappearance of shunt flow on imaging during follow-up (5/28, 17.9%). Stenosis or occlusion of the draining sinuses on initial angiography was significantly associated with shunt flow reduction during follow-up (80.0% vs 21.7%, p = 0.02). CONCLUSION: In this 3-year prospective study, patients with Borden type I DAVF showed benign clinical course; none of these patients experienced conversion to higher type of Borden classification or intracranial hemorrhage. The restrictive changes of the draining sinuses at initial diagnosis might be an imaging biomarker for future shunt flow reduction.

Predicting cerebral infarction in patients with atrial fibrillation using machine learning: The Fushimi AF registry.

The CHADS2 and CHA2DS2-VASc scores are widely used to assess ischemic risk in the patients with atrial fibrillation (AF). However, the discrimination performance of these scores is limited. Using the data from a community-based prospective cohort study, we sought to construct a machine learning-based prediction model for cerebral infarction in patients with AF, and to compare its performance with the existing scores. All consecutive patients with AF treated at 81 study institutions from March 2011 to May 2017 were enrolled (n = 4396). The whole dataset was divided into a derivation cohort (n = 1005) and validation cohort (n = 752) after excluding the patients with valvular AF and anticoagulation therapy. Using the derivation cohort dataset, a machine learning model based on gradient boosting tree algorithm (ML) was built to predict cerebral infarction. In the validation cohort, the receiver operating characteristic area under the curve of the ML model was higher than those of the existing models according to the Hanley and McNeil method: ML, 0.72 (95%CI, 0.66-0.79); CHADS2, 0.61 (95%CI, 0.53-0.69); CHA2DS2-VASc, 0.62 (95%CI, 0.54-0.70). As a conclusion, machine learning algorithm have the potential to perform better than the CHADS2 and CHA2DS2-VASc scores for predicting cerebral infarction in patients with non-valvular AF.

Effects of periodic robot rehabilitation using the Hybrid Assistive Limb for a year on gait function in chronic stroke patients.

Using a robot for gait training in stroke patients has attracted attention for the last several decades. Previous studies reported positive effects of robot rehabilitation on gait function in the short term. However, the long-term effects of robot rehabilitation for stroke patients are still unclear. The purpose of the present study was to investigate the long-term effects of periodic gait training using the Hybrid Assistive Limb (HAL) on gait function in chronic stroke patients. Seven chronic stroke patients performed 8 gait training sessions using the HAL 3 times every few months. The maximal 10-m walk test and the 2-minute walking distance (2MWD) were measured before the first intervention and after the first, second, and third interventions. Gait speed, stride length, and cadence were calculated from the 10-m walk test. Repeated one-way analysis of variance showed a significant main effect on evaluation time of gait speed (F = 7.69, p < 0.01), 2MWD (F = 7.52, p < 0.01), stride length (F = 5.24, p < 0.01), and cadence (F = 8.43, p < 0.01). The effect sizes after the first, second, and third interventions compared to pre-intervention in gait speed (d = 0.39, 0.52, and 0.59) and 2MWD (d = 0.35, 0.46, and 0.57) showed a gradual improvement of gait function at every intervention. The results of the present study showed that gait function of chronic stroke patients improved over a year with periodic gait training using the HAL every few months.

PON1 Q192R is associated with high platelet reactivity with clopidogrel in patients undergoing elective neurointervention: A prospective single-center cohort study.

BACKGROUND AND PURPOSE: The impact of the paraoxonase-1 (PON1) polymorphism, Q192R, on platelet inhibition in response to clopidogrel remains controversial. We aimed to investigate the association between carrier status of PON1 Q192R and high platelet reactivity (HPR) with clopidogrel in patients undergoing elective neurointervention. METHODS: Post-clopidogrel platelet reactivity was measured using a VerifyNow® P2Y12 assay in P2Y12 reaction units (PRU) for consecutive patients before the treatment. Genotype testing was performed for PON1 Q192R and CYP2C19*2 and *3 (no function alleles), and *17. PRU was corrected on the basis of hematocrit. We investigated associations between factors including carrying ≥1 PON1 192R allele and HPR defined as original and corrected PRU ≥208. RESULTS: Of 475 patients (232 men, median age, 68 years), HPR by original and corrected PRU was observed in 259 and 199 patients (54.5% and 41.9%), respectively. Carriers of ≥1 PON1 192R allele more frequently had HPR by original and corrected PRU compared with non-carriers (91.5% vs 85.2%, P = 0.031 and 92.5% vs 85.9%, P = 0.026, respectively). In multivariate analyses, carrying ≥1 PON1 192R allele was associated with HPR by original (odds ratio [OR] 1.96, 95% confidence interval [CI] 1.03-3.76) and corrected PRU (OR 2.34, 95% CI 1.21-4.74) after adjustment for age, sex, treatment with antihypertensive medications, hematocrit, platelet count, total cholesterol, and carrying ≥1 CYP2C19 no function allele. CONCLUSIONS: Carrying ≥1 PON1 192R allele is associated with HPR by original and corrected PRU with clopidogrel in patients undergoing elective neurointervention, although alternative results related to other genetic polymorphisms cannot be excluded.

Characteristics and clinical outcomes in atrial fibrillation patients classified using cluster analysis: the Fushimi AF Registry.

AIMS: The risk of adverse events in atrial fibrillation (AF) patients was commonly stratified by risk factors or clinical risk scores. Risk factors often do not occur in isolation and are often found in multimorbidity 'clusters' which may have prognostic implications. We aimed to perform cluster analysis in a cohort of AF patients and to assess the outcomes and prognostic implications of the identified comorbidity cluster phenotypes. METHODS AND RESULTS: The Fushimi AF Registry is a community-based prospective survey of the AF patients in Fushimi-ku, Kyoto, Japan. Hierarchical cluster analysis was performed on 4304 patients (mean age: 73.6 years, female; 40.3%, mean CHA2DS2-VASc score 3.37 ± 1.69), using 42 baseline clinical characteristics. On hierarchical cluster analysis, AF patients could be categorized into six statistically driven comorbidity clusters: (i) younger ages (mean age: 48.3 years) with low prevalence of risk factors and comorbidities (n = 209); (ii) elderly (mean age: 74.0 years) with low prevalence of risk factors and comorbidities (n = 1301); (iii) those with high prevalence of atherosclerotic risk factors, but without atherosclerotic disease (n = 1411); (iv) those with atherosclerotic comorbidities (n = 440); (v) those with history of any-cause stroke (n = 681); and (vi) the very elderly (mean age: 83.4 years) (n = 262). Rates of all-cause mortality and major adverse cardiovascular or neurological events can be stratified by these six identified clusters (log-rank test; P < 0.001 and P < 0.001, respectively). CONCLUSIONS: We identified six clinically relevant phenotypes of AF patients on cluster analysis. These phenotypes can be associated with various types of comorbidities and associated with the incidence of clinical outcomes. CLINICAL TRIAL REGISTRATION INFORMATION: https://www.umin.ac.jp/ctr/index.htm. Unique identifier: UMIN000005834.

A Case of Intracerebral Hemorrhage During the Untreated Course of a Benign Dural Arteriovenous Fistula.

BACKGROUND: The natural history of cranial dural arteriovenous fistulas (DAVFs) without cortical venous drainage (i.e., benign DAVF) is considered a potential predictor of a benign clinical course. We report a case of intracerebral hemorrhage due to the conversion from a benign to an aggressive DAVF during 10 months of conservative therapy, which, to the best of our knowledge, is the first reported case of its kind. CASE DESCRIPTION: A woman in her 70s without neurological symptoms was diagnosed with DAVF of the right transverse-sigmoid sinus with Borden type I. After conservative therapy was maintained for 10 months, she had a slight headache without neurological deficits and magnetic resonance imaging revealed intracerebral hemorrhage in the right temporooccipital area. Routine laboratory tests revealed a slight elevation of D-dimer. Emergent digital subtraction angiography demonstrated new cortical venous drainage and stenosis of the venous outlet. The refluxed cortical vein and right transverse-sigmoid sinus including fistulas were occluded with coils via transvenous embolization. She had no neurological deficits in the postoperative state. CONCLUSIONS: Conversion to aggressive DAVF in this patient was probably due to spontaneous stenosis or thrombosis of the venous outflow. Intracranial hemorrhage can occur within 1 year from the detection of benign DAVFs, and elevated D-dimer may predict the conversion to aggressive DAVFs.

Activatable Fluorescence Imaging of Macrophages in Cerebral Aneurysms Using Iron Oxide Nanoparticles Conjugated With Indocyanine Green.

BACKGROUND AND PURPOSE: Chronic inflammation is involved in the formation and enlargement of cerebral aneurysms (CAs), with macrophages playing a key role in the process. The present study evaluated visualization of macrophages present in CAs using an activatable fluorescent probe (IONP-ICG) comprising an iron oxide nanoparticles (IONPs) conjugated with indocyanine green (ICG). METHODS: IONP-ICG was intravenously administered to 15-week-old CA model rats (n = 8), and ex vivo near-infrared fluorescence (NIRF) imaging and histological assessment of exposed CAs and cerebral arteries were performed 48 h later. Similar evaluations were performed in the control group, which included CA model rats given IONPs or ICG (n = 8 each). RESULTS: ICG-derived NIRF signals were detected in three IONP-ICG group rats but not in IONP or ICG control groups. Among the three rats that exhibited signals, NIRF signal accumulation was observed in the CA of two rats and at the site of hemodynamic stress in the left posterior cerebral artery in one rat. Histologically, NIRF signals correlated strongly with macrophage localization. A total of 13 CAs formed in the IONP-ICG group. The number of macrophages in the CA wall was significantly greater in the two CAs that exhibited NIRF signals compared to the remaining 11 CAs that did not (P = 0.037). Moreover, all 11 CAs that did not exhibit NIRF signals were iron-negative, while the two CAs that exhibited NIRF signals were both iron-positive (P = 0.013). CONCLUSION: NIRF imaging using an activatable IONP-ICG probe is feasible for detecting the macrophage-rich regions in CAs and the cerebral artery wall, which is considered an early lesion in the process of CA formation.

Deep Learning-Derived High-Level Neuroimaging Features Predict Clinical Outcomes for Large Vessel Occlusion.

Background and Purpose- For patients with large vessel occlusion, neuroimaging biomarkers that evaluate the changes in brain tissue are important for determining the indications for mechanical thrombectomy. In this study, we applied deep learning to derive imaging features from pretreatment diffusion-weighted image data and evaluated the ability of these features in predicting clinical outcomes for patients with large vessel occlusion. Methods- This multicenter retrospective study included patients with anterior circulation large vessel occlusion treated with mechanical thrombectomy between 2013 and 2018. We designed a 2-output deep learning model based on convolutional neural networks (the convolutional neural network model). This model employed encoder-decoder architecture for the ischemic lesion segmentation, which automatically extracted high-level feature maps in its middle layers, and used its information to predict the clinical outcome. Its performance was internally validated with 5-fold cross-validation, externally validated, and the results compared with those from the standard neuroimaging biomarkers Alberta Stroke Program Early CT Score and ischemic core volume. The prediction target was a good clinical outcome, defined as a modified Rankin Scale score at 90-day follow-up of 0 to 2. Results- The derivation cohort included 250 patients, and the validation cohort included 74 patients. The convolutional neural network model showed the highest area under the receiver operating characteristic curve: 0.81±0.06 compared with 0.63±0.05 and 0.64±0.05 for the Alberta Stroke Program Early CT Score and ischemic core volume models, respectively. In the external validation, the area under the curve for the convolutional neural network model was significantly superior to those for the other 2 models. Conclusions- Compared with the standard neuroimaging biomarkers, our deep learning model derived a greater amount of prognostic information from pretreatment neuroimaging data. Although a confirmatory prospective evaluation is needed, the high-level imaging features derived by deep learning may offer an effective prognostic imaging biomarker.

Biodegradable Flow Diverter for the Treatment of Intracranial Aneurysms: A Pilot Study Using a Rabbit Aneurysm Model.

Background Herein, we report an in vivo study of a biodegradable flow diverter (BDFD) for aneurysm occlusion. Conceptually, BDFDs induce a temporal flow-diverting effect and provide a vascular scaffold for neointimal formation at the neck of the aneurysm until occlusion. This offers several potential advantages, including a reduced risk of remote ischemic complications and more treatment options in case of device failure to occlude the aneurysm. Methods and Results A BDFD consisting of 48 poly-l-lactic acid wires with radiopaque markers at both ends was prepared. An in vitro degradation test of the BDFD was performed. Thirty-six BDFDs were implanted in a rabbit aneurysm model. Digital angiography, optical coherence tomography, histopathology, and scanning electron microscopy were performed after 1, 3, and 6 months, and 1 year. The in vitro degradation test showed that the BDFD was almost degraded in 1.5 years. In the in vivo experiment, aneurysm occlusion rates were 0% at 1 month, 20% at 3 months, 50% at 6 months, and 33% at 1 year. Optical coherence tomography showed that luminal area stenosis was the highest at 3 months (16%) and decreased afterward. Immunohistochemical analysis showed that more than half of the luminal surface area was covered by endothelial cells at 1 month. Device fragmentation was not observed in any lesions. Conclusions This first in vivo study of a BDFD shows the feasibility of using BDFDs for treating aneurysms; however, a longer follow-up is required for comprehensive evaluation of the biological and mechanical behavior peculiar to biodegradable devices.