Stroke Magnetic Resonance Imaging Research Articles

St-RegSeg: an unsupervised registration-based framework for multimodal magnetic resonance imaging stroke lesion segmentation.

Stroke is one of the leading causes of disability and death worldwide. Ischemic stroke accounts for 75-90% of all stroke incidents. Assessing the size and location of the stroke lesion is crucial for treatment decisions, especially those related to urgent vascular reconstruction surgery. Magnetic resonance imaging (MRI) offers excellent soft tissue contrast and multimodal imaging characteristics, which can reflect changes in the physiological functions of brain soft tissues in patients with ischemic stroke. However, using deep learning (DL) techniques for MRI segmentation of stroke lesions still faces many challenges. On the one hand, single-modal segmentation models cannot effectively integrate multimodal information; on the other hand, there is a semantic content drift between multimodal stroke MRI images, leading to lower accuracy in subsequent multimodal image segmentation. To address these issues, we aimed to propose the stroke unsupervised registration and segmentation (St-RegSeg) framework. The St-RegSeg framework integrates an unsupervised registration model, ConvNXMorph, and a segmentation model, nnUNet-v2, enabling both registration and segmentation of multimodal MRI images. The St-RegSeg framework was evaluated on the ISLES'22 dataset from three centers. The St-RegSeg framework demonstrated significant improvements in performance metrics and computational efficiency. Compared to advanced normalization tools (ANTs) [symmetric normalization (SyN)] + nnUNet-v2, the St-RegSeg framework improved the Dice similarity coefficient (DSC) by 25.31% in the registration phase, reduced mean squared error (MSE) by 17.36%, increased normalized cross-correlation (NCC) by 16.06%, and enhanced mutual information (MI) by 17.09%. Additionally, in the segmentation phase, it increased the DSC by 0.84%, and the overall inference speed was increased by 40.91 times. Compared to the suboptimal TransMorph + nnUNet-v2, the St-RegSeg framework improved the DSC by 3.68% in the registration phase, reduced MSE by 8.91%, increased NCC by 8.49%, enhanced MI by 6.18%, and in the segmentation phase, it raised the DSC by 0.5%, with the overall inference speed increased by 2.13 times. The St-RegSeg framework provides a highly effective solution for the registration and segmentation of multimodal MRI images in ischemic stroke cases. Its performance metrics and computational efficiency significantly outperform existing methods, making it a promising tool for clinical applications. The code is open-sourced and available at: https://github.com/Cooper-Gu/St-RegSeg.

A lesion‐aware automated processing framework for clinical stroke magnetic resonance imaging

AbstractMagnetic resonance imaging (MRI) and MRI based computational modelling studies provide insights into severity and recovery of ischemic stroke patients. The presence of brain lesions, however, can heavily distort and impair state‐of‐the‐art processing frameworks due to abnormal intensity values and tissue distortions. In this study, we introduce and validate the novel “Lesion Aware automated Processing Pipeline (LeAPP).” LeAPP automatically processes clinical stroke MRI data while significantly reducing the impact of pathological artefacts on processing outputs such as structural and functional connectomes (SC, FC). This helps to advance the identification of biomarkers for recovery and mechanism‐based intervention planning using MRI as well as computational approaches. We extended existing frameworks, such as the Human Connectome Project (HCP) minimal processing pipeline, introducing correction steps, and implementing and modifying functional and diffusion processing to cope with MRI acquisition protocols more typical for the clinical context. A total of 51 participants (36 patients, 15 age‐matched controls) were processed across four time points for patients (3–5, 30–40, 85–95, 340–380 days after stroke onset) and one time point for controls. We validated performance using artificial lesioned brains (N = 81), derived from healthy brains and informed by real stroke lesions. The quality of reconstructing the ground truth was quantified on whole brain level and for lesion affected and unaffected regions‐of‐interest (ROIs) for brain parcellations and for SCs. Volume based agreement was evaluated using metrics such as dice coefficient, volume difference or ROI center‐of‐gravity distance while SC based agreement was defined as the difference in network metrics (e.g., node strength, clustering coefficient, or centrality). The observed deviations in reconstructed ground truth brain parcellations and structural connectomes from lesioned brains were significantly reduced for LeAPP, compared to the performance of existing pipelines such as HCP minimal processing pipeline. For instance, in the case of lesion affected ROIS we achieved a mean dice coefficient (where a value of one represents total agreement as defined by an exact overlap of both ROIs) of 0.81 with LeAPP, compared to 0.75 for HCP (p < .0001*). Additionally, the average measured ROI distance (where a value of zero represents no difference) for lesion ROIs was 0.87 for LeAPP in contrast to 1.7 for HCP (p < .0001*), indicating an overall superior performance of LeAPP. The pipeline generates standardized output files ready for brain network modelling for instance with The Virtual Brain software. This novel open‐source automated processing framework contributes to reproducible research and provides a robust framework for automated processing of clinical stroke MRI data, supporting the identification of brain network‐based biomarkers of stroke recovery.

Diffusion-Weighted Imaging Fluid-Attenuated Inversion Recovery Mismatch on Portable, Low-Field Magnetic Resonance Imaging Among Acute Stroke Patients.

For stroke patients with unknown time of onset, mismatch between diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) can guide thrombolytic intervention. However, access to MRI for hyperacute stroke is limited. Here, we sought to evaluate whether a portable, low-field (LF)-MRI scanner can identify DWI-FLAIR mismatch in acute ischemic stroke. Eligible patients with a diagnosis of acute ischemic stroke underwent LF-MRI acquisition on a 0.064-T scanner within 24 h of last known well. Qualitative and quantitative metrics were evaluated. Two trained assessors determined the visibility of stroke lesions on LF-FLAIR. An image coregistration pipeline was developed, and the LF-FLAIR signal intensity ratio (SIR) was derived. The study included 71 patients aged 71 ± 14 years and a National Institutes of Health Stroke Scale of 6 (interquartile range 3-14). The interobserver agreement for identifying visible FLAIR hyperintensities was high (κ = 0.85, 95% CI 0.70-0.99). Visual DWI-FLAIR mismatch had a 60% sensitivity and 82% specificity for stroke patients <4.5 h, with a negative predictive value of 93%. LF-FLAIR SIR had a mean value of 1.18 ± 0.18 <4.5 h, 1.24 ± 0.39 4.5-6 h, and 1.40 ± 0.23 >6 h of stroke onset. The optimal cut-point for LF-FLAIR SIR was 1.15, with 85% sensitivity and 70% specificity. A cut-point of 6.6 h was established for a FLAIR SIR <1.15, with an 89% sensitivity and 62% specificity. A 0.064-T portable LF-MRI can identify DWI-FLAIR mismatch among patients with acute ischemic stroke. Future research is needed to prospectively validate thresholds and evaluate a role of LF-MRI in guiding thrombolysis among stroke patients with uncertain time of onset. ANN NEUROL 2024;96:321-331.

Patient flow analysis with fast-track MRI for suspected stroke in the emergency department and associated non-comprehensive stroke center.

Good outcomes in stroke care require swift diagnostics, for which magnetic resonance imaging (MRI) as first-line brain imaging is superior to computed tomography scans. Reduced length of stay (LOS) in hospital and emergency departments (ED) may optimize resource use. Fast-track stroke MRI was implemented as the primary imaging technique for suspected stroke, in the ED at Copenhagen University Hospital-Herlev and Gentofte in 2020. We aimed to describe and compare LOS, MRI utilization, and the rate of strokes versus stroke-mimicking conditions on the stroke ward, before and after the implementation of fast-track MRI. In this cross-sectional study, we used data from admissions to the neurologic ED and associated non-comprehensive stroke unit. We compared two time periods, that is, January 1-December 31, 2019, and January 1-December 31, 2020, before and after the implementation of fast-track stroke MRI. There were 6650 admissions before and 7201 after implementation of fast-track stroke MRI. After implementation, we observed reductions in average LOS in hospitals from 56.0 to 38.6 h (p < 0.001), and LOS in ED from 9.17 to 8.63 h (p < 0.001). The use of inpatient MRI increased significantly, and the rate of acute ischemic stroke patients on the ward increased yet the rate of non-strokes remained unchanged. The association between shorter admissions and access to MRI remained (odds ratio 1.81, p < 0.001), after adjusting for sex, age, weekend admissions, and lockdown periods. Fast-track stroke MRI in ED associated with reduced LOS in hospital.

Neuroimaging in Cerebrovascular Accidents

Introduction: The incidence rate and the death rate from stroke increase dramatically with age. The one who survive are usually left with permanent disability. Thus, stroke has become a great medical and social problem. Accurate and early diagnosis may improve the morbidity and mortality rates in the future as newer and more effective therapies are currently being instituted. Neuroimaging in stroke patients, especially in acute ischemic stroke patients, plays an essential role. It helps to differentiate other causes of stroke (i.e., stroke mimics such as migraine headache, tumors, seizure, metabolic disturbance, and peripheral or cranial nerve disorders), early detection of hemorrhagic stroke, distinguish irreversible infarcted tissues from salvageable tissue, identify vascular malformations, treatment planning for intravenous thrombolysis and intra-arterial thrombectomy, and outcomes prediction. The aim of the study is to characterize type of stroke hemorrhagic vs. ischemic on neuroimaging. Radiological evaluation of stroke regarding –site, size, volume and duration. Correlation of neuroimaging findings with clinical findings and patient demographics. Materials and Methods: In 100 patient single-center, prospective observational study was conducted in the department of radiology, Shri Ram Murti Smarak Institute of Medical Sciences, Bareilly and adult patients with suspected stroke on computed tomography (CT) and magnetic resonance imaging (MRI) and characterization and correlation with clinical findings were done from the study. Infarcts were grouped into hyperacute (0–24 hours), (acute 1–7 days), early subacute (7–10 days), late subacute (10–21 days) Results: Out of 100 patients, the study showed male predominance. The majority of cases had a history of weakness. Comorbidities like diabetes, hypertension, and dyslipidemia increase the risk of stroke On the basis of GCS score the majority of the cases were, having GCS score greater than 10 (72.0%). Cranial nerve palsies and LOC were also common among patients of stroke. Out of a total 69 ischemic stroke cases, CT was positive in 55 patients, while MRI was positive in all the cases. Arterial infarcts (89.8%) are much more common than the venous infarcts 7 cases (10.2%). The majority of cases that reached our department were in the acute stage (56 cases, 81.2%), and the majority had MCA territory involvedThe basal ganglia complex was the most common location for the hemorrhage and was seen in 15 cases (48.3%). The mean volume of bleeding was large in cases of lobar bleeding. There was a strong positive correlation between altered sensorium (Phi value .64) and vomiting (.60), while the symptoms showed a positive correlation. The correlation of cerebrovascular accidents with age was seen more in patients aged &gt; 60 as compared to those age &lt; 60 (Phi value .1). Conclusion: This study depicts the predominance of the older age group (&gt; 40 years). The ischemic stroke was more common than the hemorrhagic stroke, the commonest cause being the MCA territory infarcts. In the cases of hemorrhagic stroke, the ganglion-capsular bleed was the commonest. Stroke imaging has undergone significant advances over last decade. It remains very crucial for the management of hyperacute stroke in the first few hours, where aim is to recognize patients eligible for thrombolytic therapy and expected to have good outcomes. Both CT, and MRI are useful for a comprehensive assessment of acute stroke MRI is sensitive for ischemic infarct detection and can provide important and necessary information for therapy planning. Both clinical examination and early diagnosis of stroke by imaging can lead to better patient outcomes.

Automated acute ischemic stroke lesion delineation based on apparent diffusion coefficient thresholds.

Automated lesion segmentation is increasingly used in acute ischemic stroke magnetic resonance imaging (MRI). We explored in detail the performance of apparent diffusion coefficient (ADC) thresholding for delineating baseline diffusion-weighted imaging (DWI) lesions. Retrospective, exploratory analysis of the prospective observational single-center 1000Plus study from September 2008 to June 2013 (clinicaltrials.org; NCT00715533). We built a fully automated lesion segmentation algorithm using a fixed ADC threshold (≤620 × 10-6 mm2/s) to delineate the baseline DWI lesion and analyzed its performance compared to manual assessments. Diagnostic capabilities of best possible ADC thresholds were investigated using receiver operating characteristic curves. Influential patient factors on ADC thresholding techniques' performance were studied by conducting multiple linear regression. 108 acute ischemic stroke patients were selected for analysis. The median Dice coefficient for the algorithm was 0.43 (IQR 0.20-0.64). Mean ADC values in the DWI lesion (β = -0.68, p < 0.001) and DWI lesion volumes (β = 0.29, p < 0.001) predicted performance. Optimal individual ADC thresholds differed between subjects with a median of ≤691 × 10-6 mm2/s (IQR ≤660-750 × 10-6 mm2/s). Mean ADC values in the DWI lesion (β = -0.96, p < 0.001) and mean ADC values in the brain parenchyma (β = 0.24, p < 0.001) were associated with the performance of individual thresholds. The performance of ADC thresholds for delineating acute stroke lesions varies substantially between patients. It is influenced by factors such as lesion size as well as lesion and parenchymal ADC values. Considering the inherent noisiness of ADC maps, ADC threshold-based automated delineation of very small lesions is not reliable.

Artificial Intelligence for Automated DWI/FLAIR Mismatch Assessment on Magnetic Resonance Imaging in Stroke: A Systematic Review.

We conducted this Systematic Review to create an overview of the currently existing Artificial Intelligence (AI) methods for Magnetic Resonance Diffusion-Weighted Imaging (DWI)/Fluid-Attenuated Inversion Recovery (FLAIR)-mismatch assessment and to determine how well DWI/FLAIR mismatch algorithms perform compared to domain experts. We searched PubMed Medline, Ovid Embase, Scopus, Web of Science, Cochrane, and IEEE Xplore literature databases for relevant studies published between 1 January 2017 and 20 November 2022, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We assessed the included studies using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Five studies fit the scope of this review. The area under the curve ranged from 0.74 to 0.90. The sensitivity and specificity ranged from 0.70 to 0.85 and 0.74 to 0.84, respectively. Negative predictive value, positive predictive value, and accuracy ranged from 0.55 to 0.82, 0.74 to 0.91, and 0.73 to 0.83, respectively. In a binary classification of ±4.5 h from stroke onset, the surveyed AI methods performed equivalent to or even better than domain experts. However, using the relation between time since stroke onset (TSS) and increasing visibility of FLAIR hyperintensity lesions is not recommended for the determination of TSS within the first 4.5 h. An AI algorithm on DWI/FLAIR mismatch assessment focused on treatment eligibility, outcome prediction, and consideration of patient-specific data could potentially increase the proportion of stroke patients with unknown onset who could be treated with thrombolysis.

Varicella Zoster Vasculopathy Exacerbated by Tofacitinib in a Patient With Ulcerative Colitis

HomeStrokeAhead of PrintVaricella Zoster Vasculopathy Exacerbated by Tofacitinib in a Patient With Ulcerative Colitis No AccessCase ReportRequest AccessAboutView PDFSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toNo AccessCase ReportRequest AccessVaricella Zoster Vasculopathy Exacerbated by Tofacitinib in a Patient With Ulcerative Colitis Kyle A. Lyman, Anirudh Sreekrishnan, Prateek Thatikunta, Ryan McConnell, Maarten G. Lansberg and Christina M. Mijalski Sells Kyle A. LymanKyle A. Lyman https://orcid.org/0000-0002-3309-7211 Department of Neurology and Neurological Sciences, Stanford University School of Medicine, CA (K.A.L., A.S., P.T., M.G.L., C.M.M.S.). Search for more papers by this author , Anirudh SreekrishnanAnirudh Sreekrishnan https://orcid.org/0000-0001-7251-7189 Department of Neurology and Neurological Sciences, Stanford University School of Medicine, CA (K.A.L., A.S., P.T., M.G.L., C.M.M.S.). Search for more papers by this author , Prateek ThatikuntaPrateek Thatikunta https://orcid.org/0000-0001-6542-2827 Department of Neurology and Neurological Sciences, Stanford University School of Medicine, CA (K.A.L., A.S., P.T., M.G.L., C.M.M.S.). Search for more papers by this author , Ryan McConnellRyan McConnell Department of Gastroenterology, Palo Alto Medical Foundation, CA (R.M.). Search for more papers by this author , Maarten G. LansbergMaarten G. Lansberg https://orcid.org/0000-0002-3545-6927 Department of Neurology and Neurological Sciences, Stanford University School of Medicine, CA (K.A.L., A.S., P.T., M.G.L., C.M.M.S.). Search for more papers by this author and Christina M. Mijalski SellsChristina M. Mijalski Sells Correspondence to: Christina M. Mijalski Sells, MD, MPH, Department of Neurology and Neurological Sciences, Center for Academic Medicine, 453 Quarry Rd, Stanford, CA 94305. Email E-mail Address: [email protected] Department of Neurology and Neurological Sciences, Stanford University School of Medicine, CA (K.A.L., A.S., P.T., M.G.L., C.M.M.S.). Search for more papers by this author Originally published6 Apr 2023https://doi.org/10.1161/STROKEAHA.122.042228Stroke. 2023;0FootnotesFor Sources of Funding and Disclosures, see page XXX.Correspondence to: Christina M. Mijalski Sells, MD, MPH, Department of Neurology and Neurological Sciences, Center for Academic Medicine, 453 Quarry Rd, Stanford, CA 94305. Email [email protected]edu Previous Back to top Next FiguresReferencesRelatedDetails Advertisement Article InformationMetrics © 2023 American Heart Association, Inc.https://doi.org/10.1161/STROKEAHA.122.042228PMID: 37021571 Originally publishedApril 6, 2023 Keywordsseizureshumansherpes zosterprednisoneagedbrainPDF download Advertisement SubjectsCerebrovascular Disease/StrokeIschemic StrokeMagnetic Resonance Imaging (MRI)

A standardized protocol for manually segmenting stroke lesions on high-resolution T1-weighted MR images.

Although automated methods for stroke lesion segmentation exist, many researchers still rely on manual segmentation as the gold standard. Our detailed, standardized protocol for stroke lesion tracing on high-resolution 3D T1-weighted (T1w) magnetic resonance imaging (MRI) has been used to trace over 1,300 stroke MRI. In the current study, we describe the protocol, including a step-by-step method utilized for training multiple individuals to trace lesions ("tracers") in a consistent manner and suggestions for distinguishing between lesioned and non-lesioned areas in stroke brains. Inter-rater and intra-rater reliability were calculated across six tracers trained using our protocol, resulting in an average intraclass correlation of 0.98 and 0.99, respectively, as well as a Dice similarity coefficient of 0.727 and 0.839, respectively. This protocol provides a standardized guideline for researchers performing manual lesion segmentation in stroke T1-weighted MRI, with detailed methods to promote reproducibility in stroke research.

MRI Generated from CT for Acute Ischemic Stroke Combining Radiomics and Generative Adversarial Networks.

Compared to computed tomography (CT), magnetic resonance imaging (MRI) is more sensitive to acute ischemic stroke lesion. However, MRI is time-consuming, expensive, and susceptible to interference from metal implants. Generating MRI images from CT images can address the limitations of MRI. The key problem in the process is obtaining lesion information from CT. In this study, we propose a cross-modal image generation algorithm from CT to MRI for acute ischemic stroke by combining radiomics with generative adversarial networks. First, the lesion candidate region was obtained using radiomics, the radiomic features of the region were extracted, and the feature with the largest information gain was selected and visualized as a feature map. Then, the concatenation of the extracted feature map and the CT image was input in the generator. We added a residual module after the downsampling of the generator, following the general shape of U-Net, which can deepen the network without causing degradation problems. In addition, we introduced the lesion feature similarity loss function to focus the model on the similarity of the lesion. Through the subjective judgment of two experienced radiologists and using evaluation metrics, the results showed that the generated MRI images were very similar to the real MRI images. Moreover, the locations of the lesions were correct, and the shapes of lesions were similar to those of the real lesions, which can help doctors with timely diagnosis and treatment.

Predictors of post-stroke cognitive impairment using acute structural MRI neuroimaging: A systematic review and meta-analysis.

Stroke survivors are at an increased risk of developing post-stroke cognitive impairment and post-stroke dementia; those at risk could be identified by brain imaging routinely performed at stroke onset. This systematic review aimed to identify features which are associated with post-stroke cognitive impairment (including dementia) on magnetic resonance imaging (MRI) performed at stroke diagnosis. We searched the literature from inception to January 2022 and identified 10,284 records. We included studies that performed MRI at the time of stroke (0-30 days after a stroke) and assessed cognitive outcome at least 3 months after stroke. We synthesized findings from 26 papers, comprising 27 stroke-populations (N = 13,114, average age range = 40-80 years, 19-62% female). When data were available, we pooled unadjusted (ORu) and adjusted (ORa) odds ratios.We found associations between cognitive outcomes and presence of cerebral atrophy (three studies, N = 453, ORu = 2.48, 95% CI = 1.15-4.62), presence of microbleeds (two studies, N = 9151, ORa = 1.36, 95% CI = 1.08-1.70), and increasing severity of white matter hyperintensities (three studies, N = 704, ORa = 1.26, 95% CI = 1.06-1.49). Increasing cerebral small vessel disease score was associated with cognitive outcome following unadjusted analysis only (two studies, N = 499, ORu = 1.34, 95%CI = 1.12-1.61; three studies, N = 950, ORa = 1.23, 95% CI = 0.96-1.57). Associations remained after controlling for pre-stroke cognitive impairment. We did not find associations between other stroke features and cognitive outcome, or there were insufficient data. Acute stroke MRI features may enable healthcare professionals to identify patients at risk of post-stroke cognitive problems. However, there is still substantial uncertainty about the prognostic utility of acute MRI for this.

Imaging of the extracranial internal carotid artery in acute ischemic stroke: assessment of stenosis, plaques, and image quality using relaxation-enhanced angiography without contrast and triggering (REACT).

In stroke magnetic resonance imaging (MRI), contrast-enhanced magnetic resonance angiography (CE-MRA) is the clinical standard to depict extracranial arteries but native MRA techniques are of increased interest to facilitate clinical practice. The purpose of this study was to assess the detection of extracranial internal carotid artery (ICA) stenosis and plaques as well as the image quality of cervical carotid arteries between a novel flow-independent relaxation-enhanced angiography without contrast and triggering (REACT) sequence and CE-MRA in acute ischemic stroke (AIS). In this retrospective, single-center study, 105 consecutive patients (65.27±18.74 years, 63 males) were included, who received a standard stroke protocol at 3T in clinical routine including Compressed SENSE (CS) accelerated (factor 4) 3D isotropic REACT (fixed scan time: 02:46 min) and CS accelerated (factor 6) 3D isotropic CE-MRA. Three radiologists independently assessed scans for the presence of extracranial ICA stenosis and plaques (including hyper-/hypointense signal) with concomitant diagnostic confidence using 3-point scales (3= excellent). Vessel quality, artifacts, and image noise of extracranial carotid arteries were subjectively scored on 5-point scales (5= excellent/none). Wilcoxon tests were used for statistical comparison. Considering CE-MRA as the standard of reference, REACT provided a sensitivity of 89.8% and specificity of 95.2% for any and of 93.5% and 95.8% for clinically relevant (≥50%) extracranial ICA stenosis and yielded a to CE-MRA comparable diagnostic confidence [mean ± standard deviation (SD), median (interquartile range): 2.8±0.5, 3 (3-3) vs. 2.7±0.5, 3 (2-3), P=0.03]. Using REACT, readers detected more plaques overall (n=57.3 vs. 47.7, P<0.001) and plaques of hyperintense signal (n=12.3 vs. 5.7, P=0.02) with higher diagnostic confidence [2.8±0.5, 3 (3-3) vs. 2.6±0.7, 3 (2-3), P<0.001] than CE-MRA. After analyzing a total of 1,260 segments, the vessel quality of all segments combined [4.61±0.66 vs. 4.58±0.68, 5 (4-5) vs. 5 (4-5), P=0.0299] and artifacts [4.51±0.70 vs. 4.44±0.73, 5 (4-5) vs. 5 (4-5), P>0.05] were comparable between the sequences with REACT showing a lower image noise [4.43±0.67 vs. 4.25±0.71, 5 (4-5) vs. 4 (4-5), P<0.001]. Without the use of gadolinium-based contrast agents or triggering, REACT provides a high sensitivity and specificity for extracranial ICA stenosis and a potential improved depiction of adjacent plaques while yielding to CE-MRA comparable vessel quality in a large patient cohort with AIS.

Clinical utility of MRI in acute stroke beyond reperfusion therapy.

ABSTRACTBackground:Stroke is primarily a clinical diagnosis. It can be hemorrhagic or ischemic in etiology. Computed tomography (CT) brain is usually the initial investigation in most patients with suspected stroke. Although it has excellent accuracy in diagnosing hemorrhage, ischemic changes may not be apparent in the first few hours. Some centers use focused magnetic resonance imaging (MRI) studies to help in selecting appropriate patients for reperfusion therapy. However, clinicians often use this investigation even when reperfusion therapy is not being considered. This study aims to find out whether doing an MRI in addition to a CT scan has any clinical utility in this situation.Primary Objective:To determine the proportion of patients who undergo a change in their management based on MRI findings.Secondary Objectives:1. To determine the time duration from the onset of symptoms to presentation at the hospital. 2. To determine the time duration from presentation to the hospital to get CT performed. 3. To determine the proportion of patients who had MRI in addition to CT. 4. To determine the time duration from CT performed to MRI performed.Materials and Methods: Study Design:Retrospective, descriptive observational study.Inclusion Criteria:Patients above age 18 admitted at a tertiary hospital with a clinical diagnosis of stroke between 1/8/2018 and 30/7/2019.Exclusion Criteria:Patients who had already undergone MRI before presentation to the hospital and patients undergoing thrombolysis. Patients meeting the inclusion and exclusion criteria were identified from the hospital information system and the ward admission register and by manual examination of the patients’ case notes. Relevant data were obtained from the case notes and collected on a google form and downloaded in Microsoft Excel 2019. SPSS version 22 was used for data analysis.Results:Out of the 106 patients, 54% (n = 57) were diagnosed as having ischemic stroke, whereas 46% (n = 49) were diagnosed with hemorrhagic stroke after initial assessment and CT scan. Only 2.8% (n = 3) of the patients presented within 4.5 hours of the onset of symptoms. 43.4% (n = 46) presented between 4.5 and 24 hours from the onset, whereas 53.8% (n = 57) presented more than 24 hours after the onset. Twenty-seven patients had their CT scan performed prior to their presentation at the center. For the remaining 79, the median time from presentation to CT scanning was 2 ± 1.5 hours. 24.5% (n = 26) of all patients had an MRI performed in addition to the CT scan. There was wide variation in the time from CT scanning to the MRI. Among the patients who had an MRI, additional information was obtained by the investigation in 58% (n = 15). However, this led to a change in management in only three (11.5%) of the patients. On review, it was found that the change was justified in only two patients. Furthermore, one patient who was diagnosed with tuberculoma had a long history of fever which was missed on initial evaluation. Considering these, MRI can be credited for a meaningful change in management in only 4% (n = 1) of the cases.Conclusion:The findings of this study do not support the routine use of MRI in patients who are not candidates for reperfusion therapy. Their use should be restricted to cases where some specific information is sought or where there is diagnostic uncertainty. Allocation of resources in developing integrated acute stroke pathways is likely to give a better value for money.

Should Primary Stroke Centers Perform Advanced Imaging?

Should Primary Stroke Centers Perform Advanced Imaging?

Noncontrast Computed Tomography vs Computed Tomography Perfusion or Magnetic Resonance Imaging Selection in Late Presentation of Stroke With Large-Vessel Occlusion

Advanced imaging for patient selection in mechanical thrombectomy is not widely available. To compare the clinical outcomes of patients selected for mechanical thrombectomy by noncontrast computed tomography (CT) vs those selected by computed tomography perfusion (CTP) or magnetic resonance imaging (MRI) in the extended time window. This multinational cohort study included consecutive patients with proximal anterior circulation occlusion stroke presenting within 6 to 24 hours of time last seen well from January 2014 to December 2020. This study was conducted at 15 sites across 5 countries in Europe and North America. The duration of follow-up was 90 days from stroke onset. Computed tomography with Alberta Stroke Program Early CT Score, CTP, or MRI. The primary end point was the distribution of modified Rankin Scale (mRS) scores at 90 days (ordinal shift). Secondary outcomes included the rates of 90-day functional independence (mRS scores of 0-2), symptomatic intracranial hemorrhage, and 90-day mortality. Of 2304 patients screened for eligibility, 1604 patients were included, with a median (IQR) age of 70 (59-80) years; 848 (52.9%) were women. A total of 534 patients were selected to undergo mechanical thrombectomy by CT, 752 by CTP, and 318 by MRI. After adjustment of confounders, there was no difference in 90-day ordinal mRS shift between patients selected by CT vs CTP (adjusted odds ratio [aOR], 0.95 [95% CI, 0.77-1.17]; P = .64) or CT vs MRI (aOR, 0.95 [95% CI, 0.8-1.13]; P = .55). The rates of 90-day functional independence (mRS scores 0-2 vs 3-6) were similar between patients selected by CT vs CTP (aOR, 0.90 [95% CI, 0.7-1.16]; P = .42) but lower in patients selected by MRI than CT (aOR, 0.79 [95% CI, 0.64-0.98]; P = .03). Successful reperfusion was more common in the CT and CTP groups compared with the MRI group (474 [88.9%] and 670 [89.5%] vs 250 [78.9%]; P < .001). No significant differences in symptomatic intracranial hemorrhage (CT, 42 [8.1%]; CTP, 43 [5.8%]; MRI, 15 [4.7%]; P = .11) or 90-day mortality (CT, 125 [23.4%]; CTP, 159 [21.1%]; MRI, 62 [19.5%]; P = .38) were observed. In patients undergoing proximal anterior circulation mechanical thrombectomy in the extended time window, there were no significant differences in the clinical outcomes of patients selected with noncontrast CT compared with those selected with CTP or MRI. These findings have the potential to widen the indication for treating patients in the extended window using a simpler and more widespread noncontrast CT-only paradigm.

Patent Foramen Ovale Closure Decreases the Incidence but Not the Size of New Brain Infarction on Magnetic Resonance Imaging: An Analysis of the REDUCE Trial.

Randomized patent foramen ovale closure trials have used open-label end point ascertainment which increases the risk of bias and undermines confidence in the conclusions. The Gore REDUCE trial prospectively performed baseline and follow-up magnetic resonance imaging (MRIs) for all subjects providing an objective measure of the effectiveness of closure. We performed blinded evaluations of the presence, location, and volume of new infarct on diffusion-weighted imaging of recurrent clinical stroke or new infarct (>3 mm) on T2/fluid attenuated inversion recovery from baseline to follow-up MRI at 2 years, comparing closure to medical therapy alone. We also examined the effect of shunt size and the development of atrial fibrillation on infarct burden at follow-up. At follow-up, new clinical stroke or silent MRI infarct occurred in 18/383 (4.7%) patients who underwent closure and 19/177 (10.7%) medication-only patients (relative risk, 0.44 [95% CI, 0.24–0.81], P=0.02). Clinical strokes were less common in closure patients compared with medically treated patients, 5 (1.3%) versus 12 (6.8%), P=0.001, while silent MRI infarcts were similar, 13 (3.4%) versus 7 (4.0%), P=0.81. There were no differences in number, volumes, and distribution of new infarct comparing closure patients to those treated with medication alone. There were also no differences of number, volumes, and distribution comparing silent infarcts to clinical strokes. Infarct burden was also similar for patients who developed atrial fibrillation and for those with large shunts. The REDUCE trial demonstrates that patent foramen ovale closure prevents recurrent brain infarction based on the objective outcome of new infarcts on MRI. Only clinical strokes were reduced by closure while silent infarctions were similar between study arms, and there were no differences in infarct volume or location comparing silent infarcts to clinical strokes. URL: https://www.clinicaltrials.gov; Unique identifier: NCT00738894.

Clinical translation of amide proton transfer (APT) MRI for ischemic stroke: a systematic review (2003-2020).

Amide proton transfer (APT) magnetic resonance imaging (MRI) is a pH-sensitive imaging technique that can potentially complement existing clinical imaging protocol for the assessment of ischemic stroke. This review aims to summarize the developments in the clinical research of APT imaging of ischemic stroke after 17 years of progress since its first preclinical study in 2003. Three electronic databases: PubMed, Scopus, and Cochrane Library were systematically searched for articles reporting clinical studies on APT imaging of ischemic stroke. Only articles in English published between 2003 to 2020 that involved patients presenting ischemic stroke-like symptoms that underwent APT MRI were included. Of 1,093 articles screened, 14 articles met the inclusion criteria with a total of 282 patients that had been scanned using APT imaging. Generally, the clinical studies agreed APT effect to be hypointense in ischemic tissue compared to healthy tissue, allowing for the detection of ischemic stroke. Other uses of APT imaging have also been investigated in the studies, including penumbra identification, predicting long term clinical outcome, and serving as a biomarker for supportive treatment monitoring. The published results demonstrated the potential of APT imaging in these applications, but further investigations and larger trials are needed for conclusive evidence. Future studies are recommended to report the result of asymmetry analysis at 3.5 ppm along with the findings of the study to reduce this contribution to the heterogeneity of experimental methods observed and to facilitate effective comparison of results between studies and centers. In addition, it is important to focus on the development of fast 3D imaging for full volumetric ischemic tissue assessment for clinical translation.

Analysis of image information of diffusion weighted image (DWI) MRI on stroke ischemic using unsharp mask technique

Magnetic Resonance Imaging (MRI) is one of the modalities that can be used to diagnose stroke ischemic using the Diffusion Weighted Image (DWI) sequence. However, DWI sequence has a weakness. It is the presence of low signal levels which will result an image bluring. One way to reduce the bluring is by adding Propeller technique. Yet, the disadvantage of using this technique is that it takes longer time to do it. The unsharp mask technique is a post processing technique that is used to improve an edge information on the image and reduce bluring from the image. The purpose of this study is to determine the difference in image information after the unsharp mask technique is performed on the Ischemic Brain Stroke MRI Examination on DWI Sequences. This research is a quasi experimental with a Pre Post Test Only Group Design. The resulting image is given unsharp mask techniques with matrix variations 3x3, 5x5, and 7x7. The Friedman statistical test results for image information obtained p-value <0,05 which means that there is a difference in image information between before and after unsharp mask technique with increase the detail and edge on digital image and produces image information optimally by giving a 3x3 matrix.

23 Na MRI in ischemic stroke: Acquisition time reduction using postprocessing with convolutional neural networks.

Quantitative 23 Na magnetic resonance imaging (MRI) provides tissue sodium concentration (TSC), which is connected to cell viability and vitality. Long acquisition times are one of the most challenging aspects for its clinical establishment. K-space undersampling is an approach for acquisition time reduction, but generates noise and artifacts. The use of convolutional neural networks (CNNs) is increasing in medical imaging and they are a useful tool for MRI postprocessing. The aim of this study is 23 Na MRI acquisition time reduction by k-space undersampling. CNNs were applied to reduce the resulting noise and artifacts. A retrospective analysis from a prospective study was conducted including image datasets from 46 patients (aged 72 ± 13 years; 25 women, 21 men) with ischemic stroke; the 23 Na MRI acquisition time was 10 min. The reconstructions were performed with full dataset (FI) and with a simulated dataset an image that was acquired in 2.5 min (RI). Eight different CNNs with either U-Net-based or ResNet-based architectures were implemented with RI as input and FI as label, using batch normalization and the number of filters as varying parameters. Training was performed with 9500 samples and testing included 400 samples. CNN outputs were evaluated based on signal-to-noise ratio (SNR) and structural similarity (SSIM). After quantification, TSC error was calculated. The image quality was subjectively rated by three neuroradiologists. Statistical significance was evaluated by Student's t-test. The average SNR was 21.72 ± 2.75 (FI) and 10.16 ± 0.96 (RI). U-Nets increased the SNR of RI to 43.99 and therefore performed better than ResNet. SSIM of RI to FI was improved by three CNNs to 0.91 ± 0.03. CNNs reduced TSC error by up to 15%. The subjective rating of CNN-generated images showed significantly better results than the subjective image rating of RI. The acquisition time of 23 Na MRI can be reduced by 75% due to postprocessing with a CNN on highly undersampled data.

November 2020 Stroke Highlights.

November 2020 Stroke Highlights.