Imaging of Ischemic Stroke

Brain Diffusion Changes in Perinatal Asphyxia Cases

BACKGROUND

Prolonged perinatal asphyxia (PA) may cause hypoxic-ischemic damage to the brain. The aim of this study was to investigate the brain diffusion changes of patients with PA and examine the relationship with brain damage.

METHODS

This retrospective study included 55 patients diagnosed with PA, separated into mild and severe PA groups. For the evaluation of brain damage in all the study neonates, brain and diffusion MRI scans were performed using a 3T device. The scans were taken between 5 and 10 days postnatal, after completion of hypothermia treatment, in accordance with the standard clinical protocol of our institution. Apparent diffusion coefficient (ADC) values of the lentiform nucleus, thalamus, frontal white matter, and posterior limbs of the internal capsule were measured. Minitab package programs and SPSS version 20.0 software were used for statistical analysis and graphic drawing. Spearman's rank correlation analysis was used.

RESULTS

The bilateral lentiform nucleus, thalamus, frontal white matter, and posterior limbs of the internal capsule ADC values were significantly higher in the severe PA group than in the mild PA group.

CONCLUSIONS

In neonates with severe perinatal asphyxia, brain damage can be evaluated on diffusion-weighted imaging (DWI) of the cerebral deep white matter and basal ganglia. DWI, imaging with conventional brain MRI comes to the fore in clinical importance in PA patients.

Automatic segmentation of medial temporal lobe subregions in multi-scanner, multi-modality MRI of variable quality

Background

Volumetry of subregions in the medial temporal lobe (MTL) computed from automatic segmentation in MRI can track neurodegeneration in Alzheimer's disease. However, image quality may vary in MRI. Poor quality MR images can lead to unreliable segmentation of MTL subregions. Considering that different MRI contrast mechanisms and field strengths (jointly referred to as "modalities" here) offer distinct advantages in imaging different parts of the MTL, we developed a muti-modality segmentation model using both 7 tesla (7T) and 3 tesla (3T) structural MRI to obtain robust segmentation in poor-quality images.

Method

MRI modalities including 3T T1-weighted, 3T T2-weighted, 7T T1-weighted and 7T T2-weighted (7T-T2w) of 197 participants were collected from a longitudinal aging study at the Penn Alzheimer's Disease Research Center. Among them, 7T-T2w was used as the primary modality, and all other modalities were rigidly registered to the 7T-T2w. A model derived from nnU-Net took these registered modalities as input and outputted subregion segmentation in 7T-T2w space. 7T-T2w images most of which had high quality from 25 selected training participants were manually segmented to train the multi-modality model. Modality augmentation, which randomly replaced certain modalities with Gaussian noise, was applied during training to guide the model to extract information from all modalities. To compare our proposed model with a baseline single-modality model in the full dataset with mixed high/poor image quality, we evaluated the ability of derived volume/thickness measures to discriminate Amyloid+ mild cognitive impairment (A+MCI) and Amyloid- cognitively unimpaired (A-CU) groups, as well as the stability of these measurements in longitudinal data.

Results

The multi-modality model delivered good performance regardless of 7T-T2w quality, while the single-modality model under-segmented subregions in poor-quality images. The multi-modality model generally demonstrated stronger discrimination of A+MCI versus A-CU. Intra-class correlation and Bland-Altman plots demonstrate that the multi-modality model had higher longitudinal segmentation consistency in all subregions while the single-modality model had low consistency in poor-quality images.

Conclusion

The multi-modality MRI segmentation model provides an improved biomarker for neurodegeneration in the MTL that is robust to image quality. It also provides a framework for other studies which may benefit from multimodal imaging.

The Association of High Lipoprotein(a) Concentration and Risk of Ischaemic Stroke in Atrial Fibrillation Patients

Background

Lipoprotein(a) [Lp(a)] is a well-established risk factor for ischaemic stroke (IS). It is unclear whether Lp(a) is associated with IS in patients with atrial fibrillation (AF). The aim of this study is to explore the association between the concentration of Lp(a) and the risk of IS in AF patients, hope to find the potential risk factor for the IS in AF patients.

Methods

This study is a retrospective cohort study. The screened AF patients between January 2017 and July 2021 were matched at 1:1 by the propensity score matching (PSM) method in the Second Affiliated Hospital of Nanchang University. Associations between Lp(a) and ischaemic stroke were analysed using logistic regression models, stratified analysis and sensitivity analysis. Statistical analyses were conducted using IBM SPSS software.

Results

The number of enrolled participates is 2258, which contains 1129 non-AF patients and 1129 AF patients. Among IS patients, the median Lp(a) concentration was higher than that of controls (17.03 vs. 15.36 mg/dL, P = 0.032). The Spearman rank-order correlation coefficients revealed significant positive relationships between IS and Lp(a) (P = 0.032). In addition, a significant increase in IS risk was associated with Lp(a) levels >30.00 mg/dL in unadjusted model [OR:1.263, 95% CI(1.046-1.523), P = 0.015], model 1 [OR:1.284, 95% CI(1.062,1.552), P = 0.010], model 2 [OR: 1.297, 95% CI(1.07,1.573). P = 0.008], and model 3 [OR: 1.290, 95% CI (1.064, 1.562). P = 0.009]. The stratified analysis indicated that this correlation was not affected by female sex [1.484 (1.117, 1.972), P = 0.006], age ≤ 60 [1.864 (1.067-3.254), P=0.029], hypertension [1.359 (1.074, 1.721), P = 0.011], or non-coronary heart disease (CHD) [1.388 (1.108, 1.738), P = 0.004].

Conclusion

High levels of Lp(a) were significantly related to IS in AF patients and may be a potential risk factor in the onset of an IS in AF patients.

Risk factors and characteristics analysis of cognitive impairment in patients with cerebral infarction during recovery period

OBJECTIVE

To analyze the risk factors and characteristics of cognitive impairment in patients with cerebral infarction during the recovery period.

METHODS

This retrospective case-control study included 183 patients with cerebral infarction in the recovery period. According to the MMSE score, they were divided into a cognitive impairment group of 79 cases and a cognitive normal group of 104 cases. Collect clinical data from all patients, including age, gender, body mass index, laboratory test results, past medical history, National Institute of Health Stroke Scale (NIHSS) score, modified Barthel index, Oxfordshire Community Stroke Project (OCSP) classification, and number of infarcted lesions. Multiple logistic regression analysis was used to identify risk factors related to cognitive impairment in patients with cerebral infarction.

RESULT

There were significant differences (p < 0.05) between the cognitive impairment group and the cognitive normal group in terms of age, body mass index, low-density lipoprotein level, NIHSS score, modified Barthel index, and number of infarcted lesions. Multivariate logistic regression analysis showed that age ≥ 65 years, stroke, carotid artery plaques, NIHSS score ≥ 5, anterior circulation infarction type, and multiple infarcted lesions were important risk factors for cognitive impairment.

CONCLUSION

Elderly age, presence of carotid artery plaques, high NIHSS score, multiple infarct lesions, and specific infarct types are important risk factors for cognitive dysfunction in patients during the recovery period of cerebral infarction.

Biochemical, biomechanical and imaging biomarkers of ischemic stroke: Time for integrative thinking

Stroke is one of the leading causes of adult disability affecting millions of people worldwide. Post-stroke cognitive and motor impairments diminish quality of life and functional independence. There is an increased risk of having a second stroke and developing secondary conditions with long-term social and economic impacts. With increasing number of stroke incidents, shortage of medical professionals and limited budgets, health services are struggling to provide a care that can break the vicious cycle of stroke. Effective post-stroke recovery hinges on holistic, integrative and personalized care starting from improved diagnosis and treatment in clinics to continuous rehabilitation and support in the community. To improve stroke care pathways, there have been growing efforts in discovering biomarkers that can provide valuable insights into the neural, physiological and biomechanical consequences of stroke and how patients respond to new interventions. In this review paper, we aim to summarize recent biomarker discovery research focusing on three modalities (brain imaging, blood sampling and gait assessments), look at some established and forthcoming biomarkers, and discuss their usefulness and complementarity within the context of comprehensive stroke care. We also emphasize the importance of biomarker guided personalized interventions to enhance stroke treatment and post-stroke recovery.

Unveiling the Intricacies: A Comprehensive Review of Magnetic Resonance Imaging (MRI) Assessment of T2-Weighted Hyperintensities in the Neuroimaging Landscape

T2-weighted hyperintensities in neuroimaging represent areas of heightened signal intensity on magnetic resonance imaging (MRI) scans, holding crucial importance in neuroimaging. This comprehensive review explores the T2-weighted hyperintensities, providing insights into their definition, characteristics, clinical relevance, and underlying causes. It highlights the significance of these hyperintensities as sensitive markers for neurological disorders, including multiple sclerosis, vascular dementia, and brain tumors. The review also delves into advanced neuroimaging techniques, such as susceptibility-weighted and diffusion tensor imaging, and the application of artificial intelligence and machine learning in hyperintensities analysis. Furthermore, it outlines the challenges and pitfalls associated with their assessment and emphasizes the importance of standardized protocols and a multidisciplinary approach. The review discusses future directions for research and clinical practice, including the development of biomarkers, personalized medicine, and enhanced imaging techniques. Ultimately, the review underscores the profound impact of T2-weighted hyperintensities in shaping the landscape of neurological diagnosis, prognosis, and treatment, contributing to a deeper understanding of complex neurological conditions and guiding more informed and effective patient care.

CNN-Res: deep learning framework for segmentation of acute ischemic stroke lesions on multimodal MRI images

BACKGROUND

Accurate segmentation of stroke lesions on MRI images is very important for neurologists in the planning of post-stroke care. Segmentation helps clinicians to better diagnose and evaluation of any treatment risks. However, manual segmentation of brain lesions relies on the experience of neurologists and is also a very tedious and time-consuming process. So, in this study, we proposed a novel deep convolutional neural network (CNN-Res) that automatically performs the segmentation of ischemic stroke lesions from multimodal MRIs.

METHODS

CNN-Res used a U-shaped structure, so the network has encryption and decryption paths. The residual units are embedded in the encoder path. In this model, to reduce gradient descent, the residual units were used, and to extract more complex information in images, multimodal MRI data were applied. In the link between the encryption and decryption subnets, the bottleneck strategy was used, which reduced the number of parameters and training time compared to similar research.

RESULTS

CNN-Res was evaluated on two distinct datasets. First, it was examined on a dataset collected from the Neuroscience Center of Tabriz University of Medical Sciences, where the average Dice coefficient was equal to 85.43%. Then, to compare the efficiency and performance of the model with other similar works, CNN-Res was evaluated on the popular SPES 2015 competition dataset where the average Dice coefficient was 79.23%.

CONCLUSION

This study presented a new and accurate method for the segmentation of MRI medical images using a deep convolutional neural network called CNN-Res, which directly predicts segment maps from raw input pixels.

Biomarkers: Role and Scope in Neurological Disorders

Neurological disorders pose a great threat to social health and are a major cause for mortality and morbidity. Effective drug development complemented with the improved drug therapy has made considerable progress towards easing symptoms associated with neurological illnesses, yet poor diagnosis and imprecise understanding of these disorders has led to imperfect treatment options. The scenario is complicated by the inability to extrapolate results of cell culture studies and transgenic models to clinical applications which has stagnated the process of improving drug therapy. In this context, the development of biomarkers has been viewed as beneficial to easing various pathological complications. A biomarker is measured and evaluated in order to gauge the physiological process or a pathological progression of a disease and such a marker can also indicate the clinical or pharmacological response to a therapeutic intervention. The development and identification of biomarkers for neurological disorders involves several issues including the complexity of the brain, unresolved discrepant data from experimental and clinical studies, poor clinical diagnostics, lack of functional endpoints, and high cost and complexity of techniques yet research in the area of biomarkers is highly desired. The present work describes existing biomarkers for various neurological disorders, provides support for the idea that biomarker development may ease our understanding underlying pathophysiology of these disorders and help to design and explore therapeutic targets for effective intervention.

Comparison of Doppler Ultrasound and Computerized Tomographic Angiography in Evaluation of Cervical Arteries Stenosis in Stroke Patients, a Retrospective Single-Center Study

There are different diagnostic modalities to investigate atherosclerosis cervical artery disease in suspected stroke patients. We aimed to test the concordance of findings of the two most widely used diagnostic modalities in stroke patients: duplex ultrasound (DUS) and computerized tomographic angiography (CTA). A total of 100 stroke patients were retrospectively included in the study, all of them had DUS followed by CTA. Discrepancies of DUS compared to the CTA results in both the internal carotid and vertebral arteries were found in 44% of the patients. The patients with significant differences in diagnostic results were characterized by older age. Evaluation of the degree of carotid artery stenosis revealed vast differences in patients with 50-69% stenosis found by DUS, in which 45.5% of them had a different percentage of stenosis found by CTA. In studying the degree of stenosis of the vertebral artery, only 47.1% of the patients with more than 50% stenosis found by DUS had the same results with CTA, while the remaining revealed normal or less than 50% stenosis by CTA. The current study emphasizes that CTA is more accurate than DUS in the evaluation of stenosis of the cervical arteries including both the internal carotid and vertebral arteries.

Inducible miR-1224 silences cerebrovascular Serpine1 and restores blood flow to the stroke-affected site of the brain

The α-tocotrienol (TCT) form of natural vitamin E is more potent than the better known α-tocopherol against stroke. Angiographic studies of canine stroke have revealed beneficial cerebrovascular effects of TCT. This work seeks to understand the molecular basis of such effect. In mice, TCT supplementation improved perfusion at the stroke-affected site by inducing miR-1224. miRNA profiling of a laser-capture-microdissected stroke-affected brain site identified miR-1224 as the only vascular miR induced. Lentiviral knockdown of miR-1224 significantly blunted the otherwise beneficial effects of TCT on stroke outcomes. Studies on primary brain microvascular endothelial cells revealed direct angiogenic properties of miR-1224. In mice not treated with TCT, advance stereotaxic delivery of an miR-1224 mimic to the stroke site markedly improved stroke outcomes. Mechanistic studies identified Serpine1 as a target of miR-1224. Downregulation of Serpine1 augmented the angiogenic response of the miR-1224 mimic in the brain endothelial cells. The inhibition of Serpine1, by dietary TCT and pharmacologically, increased cerebrovascular blood flow at the stroke-affected site and protected against stroke. This work assigns Serpine1, otherwise known to be of critical significance in stroke, a cerebrovascular function that worsens stroke outcomes. miR-1224-dependent inhibition of Serpine1 can be achieved by dietary TCT as well as by the small-molecule inhibitor TM5441.

Association of atrial 18F-fluorodeoxyglucose uptake and prior ischemic stroke in non-atrial fibrillation patients

BACKGROUND

Atrial cardiomyopathy has gained increasing attention in the field of ischemic stroke due to its prothrombotic substrate. Timely identification of high-risk individuals without atrial fibrillation (AF) is essential in secondary prevention. We sought to explore the feasibility of atrial 18F-fluorodeoxyglucose (FDG) imaging in detecting diseased atrial substrate and in identifying ischemic stroke in a non-AF population.

METHODS

1444 non-AF inpatients were initially identified. Among them, 196 patients had enhanced atrial FDG uptake, while 392 patients without atrial activity were selected as controls. Atrial activity, the history of ischemic stroke, and atrial cardiomyopathy were analyzed.

RESULTS

Patients with atrial cardiomyopathy had a higher prevalence of enhanced atrial activity (47.1% vs 26.0%, P < .001), and patients with increased atrial activity had a higher prevalence of a prior history of ischemic stroke (12.2% vs 3.3%, P < .001). Multivariate regression analysis demonstrated that atrial activity was independently related to ischemic stroke after adjustment for risk factors (OR 4.02, 95% CI 1.97-8.19, P < .001) and atrial cardiomyopathy (OR 3.63, 95% CI 1.51-8.74, P = .004).

CONCLUSIONS

This study identified an association between atrial FDG activity and a history of ischemic stroke and atrial cardiomyopathy in non-AF individuals. Further longitudinal study is warranted to demonstrate their causal relationship.

Changes in Long-Term Functional Independence in Patients with Moderate and Severe Ischemic Stroke: Comparison of the Responsiveness of the Modified Barthel Index and the Functional Independence Measure

This study investigated the long-term functional changes in patients with moderate-to-severe ischemic stroke. In addition, we investigated whether there was a difference between the modified Barthel Index (MBI) and Functional Independence Measure (FIM) according to severity. To evaluate the changes in the long-term functional independence of the subjects, six evaluations were conducted over 2 years, and the evaluation was performed using MBI and FIM. A total of 798 participants participated in this study, of which 673 were classified as moderate and 125 as severe. During the first 3 months, the moderate group showed greater recovery than the severe group. The period of significant change in the National Institutes of Health Stroke Scale (NIHSS) score was up to 6 months after onset in the moderate group, and up to 3 months after onset in the severe group. In the severe group, MBI evaluation showed significant changes up to 6 months after onset, whereas FIM showed significant changes up to 18-24 months. Our results showed that functional recovery of patients with ischemic stroke in the 3 months after onset was greater in the moderate group than in the severe group. FIM is more appropriate than MBI for evaluating the functional status of patients with severe stroke.

Magnetic Resonance Imaging in Acute Ischemic Stroke

Ischemic stroke is one of the leading causes of mortality and disability. The only effective non-surgical treatment for acute ischemic stroke within three to four and a half hours of the onset of symptoms is thrombolytic therapy. Time is of the essence when diagnosing and treating an acute ischemic stroke. After evaluating the advantages and disadvantages of thrombolysis, selecting the ideal patient for the indication is essential. Magnetic Resonance Imaging (MRI) is more sensitive and specific than Computed Tomography (CT) scans when identifying acute ischemic stroke. In approximately 80% of cases, infarcts are detectable within the first 24 hours. MRI can detect an ischemic stroke within a few hours of its onset. Multimodal imaging provides information for the diagnosis of ischemic stroke, patient selection for thrombolytic therapy, and prognosis estimation.

A Review of the Role of Transthoracic and Transesophageal Echocardiography, Computed Tomography, and Magnetic Resonance Imaging in Cardioembolic Stroke

Stroke is a major source of morbidity and mortality worldwide, accounting for the second largest cause of mortality and the third greatest cause of disability. Stroke is frequently preceded by a transient ischemic attack (TIA). The etiologies of 20-30% of ischemic strokes are unknown, and thus are termed "cryptogenic strokes". About 25% of ischemic strokes are cardioembolic. Strokes occur at a rate of around 2% per year in individuals with heart failure with reduced ejection fraction (HFrEF), with a strong correlation between stroke risk and the degree of ventricular impairment. Furthermore, stroke risk is augmented in the absence of anticoagulation therapy. Cardioembolic strokes, when treated inadequately, have a greater predilection for recurrences than atherothrombotic strokes, both early and late in life. The role of a patent foramen ovale in strokes, specifically in "cryptogenic strokes", is a matter of concern that deserves due attention. The use of tissue-engineered heart valves and aspirin for minimizing the risk of stroke is recommended. Transthoracic echocardiography (TTE) is advantageous for assessing heart function in the acute phase of ischemic stroke. Transesophageal echocardiography (TEE) is considered the criterion standard procedure for detecting LAA thrombi. Computed tomography (CT) scans are good imaging modalities for identifying and excluding bleeding. Magnetic resonance imaging (MRI) images are by far the most effective imaging technique available for assessing the brain parenchymal state. We conducted a thorough review of the literature on the use of imaging modalities, highlighting the important contribution of TTE, TEE, CT, and MRI in the evaluation of cardioembolic stroke.

Artificially-reconstructed brain images with stroke lesions from non-imaging data: modeling in categorized patients based on lesion occurrence and sparsity

Brain imaging is necessary for understanding disease symptoms, including stroke. However, frequent imaging procedures encounter practical limitations. Estimating the brain information (e.g., lesions) without imaging sessions is beneficial for this scenario. Prospective estimating variables are non-imaging data collected from standard tests. Therefore, the current study aims to examine the variable feasibility for modelling lesion locations. Heterogeneous variables were employed in the multivariate logistic regression. Furthermore, patients were categorized (i.e., unsupervised clustering through k-means method) by the charasteristics of lesion occurrence (i.e., ratio between the lesioned and total regions) and sparsity (i.e., density measure of lesion occurrences across regions). Considering those charasteristics in models improved estimation performances. Lesions (116 regions in Automated Anatomical Labeling) were adequately predicted (sensitivity: 80.0-87.5% in median). We confirmed that the usability of models was extendable to different resolution levels in the brain region of interest (e.g., lobes, hemispheres). Patients' charateristics (i.e., occurrence and sparsity) might also be explained by the non-imaging data as well. Advantages of the current approach can be experienced by any patients (i.e., with or without imaging sessions) in any clinical facilities (i.e., with or without imaging instrumentation).

Evaluation of Post-Stroke Impairment in Fine Tactile Sensation by Electroencephalography (EEG)-Based Machine Learning

Electroencephalography (EEG)-based measurements of fine tactile sensation produce large amounts of data, with high costs for manual evaluation. In this study, an EEG-based machine-learning (ML) model with support vector machine (SVM) was established to automatically evaluate post-stroke impairments in fine tactile sensation. Stroke survivors (n = 12, stroke group) and unimpaired participants (n = 15, control group) received stimulations with cotton, nylon, and wool fabrics to the different upper limbs of a stroke participant and the dominant side of the control. The average and maximal values of relative spectral power (RSP) of EEG in the stimulations were used as the inputs to the SVM-ML model, which was first optimized for classification accuracies for different limb sides through hyperparameter selection (γ, C) in radial basis function (RBF) kernel and cross-validation during cotton stimulation. Model generalization was investigated by comparing accuracies during stimulations with different fabrics to different limbs. The highest accuracies were achieved with (γ = 21, C = 23) for the RBF kernel (76.8%) and six-fold cross-validation (75.4%), respectively, in the gamma band for cotton stimulation; these were selected as optimal parameters for the SVM-ML model. In model generalization, significant differences in the post-stroke fabric stimulation accuracies were shifted to higher (beta/gamma) bands. The EEG-based SVM-ML model generated results similar to manual evaluation of cortical responses to fabric stimulations; this may aid automatic assessments of post-stroke fine tactile sensations.

Salivary Xanthine Oxidase as a Potential Biomarker in Stroke Diagnostics

Stroke is one of the most common cerebrovascular diseases. Despite significant progress in understanding stroke pathogenesis, cases are still increasing. Thus, laboratory biomarkers of stroke are sought to allow rapid and non-invasive diagnostics. Ischemia-reperfusion injury is an inflammatory process with characteristic cellular changes leading to microvascular disruption. Several studies have shown that hyperactivation of xanthine oxidase (XO) is a major pathogenic factor contributing to brain dysfunction. Given the critical role of XO in stroke complications, this study aimed to evaluate the activity of the enzyme and its metabolic products in the saliva of stroke subjects. Thirty patients in the subacute phase of stroke were included in the study: 15 with hemorrhagic stroke and 15 with ischemic stroke. The control group consisted of 30 healthy subjects similar to the cerebral stroke patients regarding age, gender, and status of the periodontium, dentition, and oral hygiene. The number of individuals was determined a priori based on our previous experiment (power of the test = 0.8; α = 0.05). The study material was mixed non‐stimulated whole saliva (NWS) and stimulated saliva (SWS). We showed that activity, specific activity, and XO output were significantly higher in NWS of ischemic stroke patients than in hemorrhagic stroke and healthy controls. Hydrogen peroxide and uric acid levels were also considerably higher in NWS of ischemic stroke patients. Using receiver operating curve (ROC) analysis, we demonstrated that XO-specific activity in NWS distinguishes ischemic stroke from hemorrhagic stroke (AUC: 0.764) and controls (AUC: 0.973) with very high sensitivity and specificity. Saliva collection is stress-free, requires no specialized medical personnel, and allows continuous monitoring of the patient’s condition through non-invasive sampling multiple times per day. Salivary XO also differentiates with high accuracy (100%) and specificity (93.75%) between stroke patients with mild to moderate cognitive decline (AUC = 0.988). Thus, salivary XO assessment may be a potential screening tool for a comprehensive neuropsychological evaluation. To summarize, our study demonstrates the potential utility of salivary XO in the differential diagnosis of stroke.

Portable, low-field magnetic resonance imaging enables highly accessible and dynamic bedside evaluation of ischemic stroke

Brain imaging is essential to the clinical management of patients with ischemic stroke. Timely and accessible neuroimaging, however, can be limited in clinical stroke pathways. Here, portable magnetic resonance imaging (pMRI) acquired at very low magnetic field strength (0.064 T) is used to obtain actionable bedside neuroimaging for 50 confirmed patients with ischemic stroke. Low-field pMRI detected infarcts in 45 (90%) patients across cortical, subcortical, and cerebellar structures. Lesions as small as 4 mm were captured. Infarcts appeared as hyperintense regions on T2-weighted, fluid-attenuated inversion recovery and diffusion-weighted imaging sequences. Stroke volume measurements were consistent across pMRI sequences and between low-field pMRI and conventional high-field MRI studies. Low-field pMRI stroke volumes significantly correlated with stroke severity and functional outcome at discharge. These results validate the use of low-field pMRI to obtain clinically useful imaging of stroke, setting the stage for use in resource-limited environments.

Magnetic Resonance pH Imaging in Stroke – Combining the Old With the New

The study of stroke has historically made use of traditional spectroscopy techniques to provide the ground truth for parameters like pH. However, techniques like ³¹P spectroscopy have limitations, in particular poor temporal and spatial resolution, coupled with a need for a high field strength and specialized coils. More modern magnetic resonance spectroscopy (MRS)-based imaging techniques like chemical exchange saturation transfer (CEST) have been developed to counter some of these limitations but lack the definitive gold standard for pH that ³¹P spectroscopy provides. In this perspective, both the traditional (³¹P spectroscopy) and emerging (CEST) techniques in the measurement of pH for ischemic imaging will be discussed. Although each has its own advantages and limitations, it is likely that CEST may be preferable simply due to the hardware, acquisition time and image resolution advantages. However, more experiments on CEST are needed to determine the specificity of endogenous CEST to absolute pH, and ³¹P MRS can be used to calibrate CEST for pH measurement in the preclinical model to enhance our understanding of the relationship between CEST and pH. Combining the two imaging techniques, one old and one new, we may be able to obtain new insights into stroke physiology that would not be possible otherwise with either alone.

The strange role of brain lesion size in cognitive neuropsychology

The size of brain lesions is a variable that is frequently considered in cognitive neuropsychology. In particular, lesion-deficit inference studies often control for lesion size, and the association of lesion size with post-stroke cognitive deficits and its predictive value are studied. In the present article, the role of lesion size in cognitive deficits and its computational or design-wise consideration is discussed and questioned. First, I argue that the commonly discussed role or effect of lesion size in cognitive deficits eludes us. A generally valid understanding of the causal relation of lesion size, lesion location, and cognitive deficits is unachievable. Second, founded on the theory of causal inference, I argue that lesion size control is no generally appropriate covariate control. Instead, it is identified as a procedure with only situational benefits, which is supported by empirical data. This theoretical background is used to suggest possible research practices in lesion-deficit inference, post-stroke outcome prediction, and behavioural studies. Last, control for lesion size is put into a bigger historical context - it is identified to relate to a long-known association problem in neuropsychology, which was previously discussed from the perspectives of a mislocalisation in lesion-deficit mapping and the symptom complex approach.

Salivary cytokine profile in patients with ischemic stroke

Inflammation plays a crucial role in stroke pathogenesis. Thus, it is not surprising that cytokines, chemokines, and growth factors have been advocated in stroke diagnostics. Our study is the first to evaluate the salivary cytokine profile in patients with ischemic stroke. Twenty-five patients with subacute ischemic stroke and an age-, sex-, and oral hygiene status-matched control group were enrolled in the study. The number of patients was set a priori based on our previous experiment (α = 0.05, test power = 0.9). Salivary concentrations of tumor necrosis factor α (TNF-α), interleukin 6 (IL-6), and interleukin 10 (IL-10) were assessed using an ELISA method. We showed that salivary TNF-α and IL-6 were significantly higher, whereas IL-10 content was statistically lower in both non-stimulated (NWS) and stimulated (SWS) whole saliva of ischemic stroke patients. However, evaluation of cytokines in NWS rather than in SWS may be of greater diagnostic value. Of particular note is salivary TNF-α, which may indicate cognitive/physical impairment in post-stroke individuals. This parameter distinguishes stroke patients from healthy controls and correlates with cognitive decline and severity of functional impairment. It also differentiates (with high sensitivity and specificity) stroke patients with normal cognition from mild to moderate cognitive impairment. Saliva may be an alternative to blood for assessing cytokines in stroke patients, although further studies on a larger patient population are needed.

Utilization of Cerebral Blood Flow Study With Computed Tomography for Subdural Hematoma Management

Stroke is among the leading causes of death in the United States, and with our aging population, it will remain a pertinent obstacle in the acute setting. While the field of neuroradiology has advanced tremendously over the years, particularly in improving what we can visualize and quantify, the phrase “time is brain” yet dominates acute stroke management. Optimizing diagnostic protocols for suspected stroke requires a careful balance of data acquisition and speed, as well as taking into account available resources. We present a case of a middle-aged patient with notable risk factors for stroke presenting to the emergency department with altered mental status and suspected stroke. Radiography revealed a large subacute subdural hematoma (SDH) with a mild mass effect on the surface of the brain. The evaluation was supplemented by a computed tomography (CT) and perfusion cerebral blood flow (CBF) study indicating cortical ischemia with penumbra from the SDH compression. SDH evacuation was successfully performed, and patient recovery was achieved within the intensive care unit (ICU). Rapid data acquisition via CBF with CT imaging is crucial for guiding treatment decisions for SDHs. While protocols for ischemic stroke are well-established, SDH protocols are not studied. Thus, we discuss the value of a multimodal CT imaging approach, including CBF studies, in SDH evaluation.

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.

Development and Validation of a LASSO Prediction Model for Better Identification of Ischemic Stroke: A Case-Control Study in China

Background

Timely diagnosis of ischemic stroke (IS) in the acute phase is extremely vital to achieve proper treatment and good prognosis. In this study, we developed a novel prediction model based on the easily obtained information at initial inspection to assist in the early identification of IS.

Methods

A total of 627 patients with IS and other intracranial hemorrhagic diseases from March 2017 to June 2018 were retrospectively enrolled in the derivation cohort. Based on their demographic information and initial laboratory examination results, the prediction model was constructed. The least absolute shrinkage and selection operator algorithm was used to select the important variables to form a laboratory panel. Combined with the demographic variables, multivariate logistic regression was performed for modeling, and the model was encapsulated within a visual and operable smartphone application. The performance of the model was evaluated on an independent validation cohort, formed by 304 prospectively enrolled patients from June 2018 to May 2019, by means of the area under the curve (AUC) and calibration.

Results

The prediction model showed good discrimination (AUC = 0.916, cut-off = 0.577), calibration, and clinical availability. The performance was reconfirmed in the more complex emergency department. It was encapsulated as the Stroke Diagnosis Aid app for smartphones. The user can obtain the identification result by entering the values of the variables in the graphical user interface of the application.

Conclusion

The prediction model based on laboratory and demographic variables could serve as a favorable supplementary tool to facilitate complex, time-critical acute stroke identification.

Markers of Coagulation and Fibrinolysis Predicting the Outcome of Acute Ischemic Stroke Thrombolysis Treatment: A Review of the Literature

Intravenous administration of recombinant tissue plasminogen activator (rt-PA) has been proven to be safe and effective in the treatment of acute ischemic stroke. Little is known, however, why this treatment is less effective in some patients while in others life-threatening side-effects, e.g., symptomatic intracerebral hemorrhage might occur. Clinical failure of thrombolysis related to absent or partial recanalization or reocclusion as well as hemorrhagic complications of thrombolysis are possibly related to hemostatic events. Data on markers of coagulation and/or fibrinolysis in acute stroke patients are numerous and may provide indications regarding therapy outcomes. Better understanding of the hemostatic and fibrinolytic system during rt-PA therapy might be clinically useful and ultimately might lead to an improvement in the efficacy or safety of this treatment. Studies on thrombus composition retrieved from cerebral arteries may also advance our knowledge and provide a key to improve acute stroke therapy. Here we provide a comprehensive review on a wide range of factors and markers of coagulation and fibrinolysis that have been studied in the context of thrombolysis outcome in ischemic stroke patients. Moreover, a brief summary is given on the most recent research on thrombus composition having a potential influence on outcomes.

Brain Functional Reserve in the Context of Neuroplasticity after Stroke

Stroke is the second cause of death and more importantly first cause of disability in people over 40 years of age. Current therapeutic management of ischemic stroke does not provide fully satisfactory outcomes. Stroke management has significantly changed since the time when there were opened modern stroke units with early motor and speech rehabilitation in hospitals. In recent decades, researchers searched for biomarkers of ischemic stroke and neuroplasticity in order to determine effective diagnostics, prognostic assessment, and therapy. Complex background of events following ischemic episode hinders successful design of effective therapeutic strategies. So far, studies have proven that regeneration after stroke and recovery of lost functions may be assigned to neuronal plasticity understood as ability of brain to reorganize and rebuild as an effect of changed environmental conditions. As many neuronal processes influencing neuroplasticity depend on expression of particular genes and genetic diversity possibly influencing its effectiveness, knowledge on their mechanisms is necessary to understand this process. Epigenetic mechanisms occurring after stroke was briefly discussed in this paper including several mechanisms such as synaptic plasticity; neuro-, glio-, and angiogenesis processes; and growth of axon.