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diagnosis and imaging

Peri-Procedural Silent and Clinical Infarctions in Cardiovascular Procedures

Gurmeen Kaur, MBBS
@kaurgurmeen

Cho S-M, Deshpande A, Pasupuleti V, Hernandez AV, Uchino K. Radiographic and Clinical Brain Infarcts in Cardiac and Diagnostic Procedures: A Systematic Review and Meta-Analysis. Stroke. 2017

Cardiovascular procedures including Aortic Valve Replacement (AVR), coronary artery bypass grafting (CABG), and cardiac and cerebral catheterization have been associated with increased prevalence of peri-procedural acute ischemic brain lesions on magnetic resonance imaging (MRI).

In this systematic review, Cho et al compared the ratio of radiographic brain infarcts (RBI) to strokes and transient ischemic attacks across cardiac and vascular procedures. RBIs are common after invasive vascular procedures and are encountered a lot more frequently than clinical strokes or TIAs. Literature suggests that peri-procedural ischemic events might serve as a potential surrogate marker for optimizing invasive procedures, which is why an effort was made to compare the rates of RBIs to clinical events.

By |November 29th, 2017|clinical, diagnosis and imaging|0 Comments
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Using CT Perfusion to Predict Hemorrhagic Transformation

Brian Marcus, MD

Li Q, Gao X, Yao Z, Feng X, He H, Xue J, et al. Permeability Surface of Deep Middle Cerebral Artery Territory on Computed Tomographic Perfusion Predicts Hemorrhagic Transformation After Stroke. Stroke. 2017

The authors of this study utilized CT perfusion (CTP) to assess blood brain barrier integrity and to help predict which patients are at risk of hemorrhagic transformation after receiving tPA and/or mechanical thrombectomy. They note that patients who have proximal MCA-M1/distal ICA occlusions are at an increased susceptibility of hemorrhagic transformation, particularly in the deep MCA territory supplied by the lenticulostriate arteries. They aimed to explore the relationship and potential risk factors between permeability and hemorrhagic transformation in the deep MCA territory by utilizing CT perfusion imaging.

The authors performed a multisite retrospective study, specifically looking at patients that were found to have a deep MCA territory hemorrhagic transformation at 24 hours (and had received CT perfusion and CT angiography on admission). In their study, they noted that patients with a proximal MCA/distal ICA and poor collateral circulation had increased permeability in the deep MCA territory.

By |November 8th, 2017|clinical, diagnosis and imaging|0 Comments
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Hide and Seek: Using Cardiac MRI to Find a Hidden Clot in ESUS

Kevin S. Attenhofer, MD

Takasugi J, Yamagami H, Noguchi T, Morita Y, Tanaka T, Okuno Y, et al. Detection of Left Ventricular Thrombus by Cardiac Magnetic Resonance in Embolic Stroke of Undetermined Source. Stroke. 2017.

As has been reviewed in this blog many times before, embolic stroke of undetermined source (ESUS) is a novel clinical construct that is a hot topic for emerging diagnostic and therapeutic strategies. While many studies are evaluating methods to increase the detection rate of covert atrial fibrillation in this population, the authors of this paper demonstrate improved detection of left ventricular (LV) thrombi in ESUS patients using cardiac MRI versus TTE.

Currently, echocardiography is the test of choice when evaluating for intra-cardiac thrombus. Transesophageal echocardiography (TEE) is the gold standard technique for detecting left atrial or left atrial appendage thrombi. Transthoracic echocardiography (TTE) is used to evaluate the presence of LV thrombus, patent foramen ovale, depressed ejection fraction, etc. Recently, contrast enhanced cardiac magnetic resonance imaging (CE-CMR) has shown significantly better sensitivity than TTE for the diagnosis of LV thrombus (cardiac studies suggesting sensitivity of TTE was 40%, compared with 88% for CE-CMR) in patients with a history of myocardial infarction (MI) or LV dysfunction (LVEF < 30%).

By |November 3rd, 2017|clinical, diagnosis and imaging|0 Comments
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Author Interview: Ramin Zand, MD, and Vida Abedi, PhD

A conversation with Ramin Zand, MD, Neurology Director of Clinical Stroke Operations, Northeastern Regional Stroke Director, Geisinger Health System, and Associate Professor of Neurology, University of Tennessee Health Science Center, and Vida Abedi, PhD, Research Scientist, Geisinger Health System, and Adjunct Professor, Virginia Tech, about using an artificial neural network to screen for stroke.

Interviewed by José G. Merino, MD, Associate Professor of Neurology, University of Maryland School of Medicine.

They will be discussing the paper “Novel Screening Tool for Stroke Using Artificial Neural Network,” published in the June issue of Stroke.

Dr. Merino: Could you please briefly summarize the key findings and put them in context of what was known before you did the study (i.e. an “elevator pitch” about your research)?

Vida Abedi, PhD

Vida Abedi, PhD

Drs. Zand and Abedi: We have developed ​a new computational method based on artificial intelligence to screen for the stroke in an emergency setting. Previous studies have shown that up to 25% of strokes can be initially misdiagnosed in the emergency department. The failure to recognize stroke in the emergency department is a missed opportunity for intervention. The goal of our study was to test if a supervised learning method could recognize and differentiate stroke from stroke mimics based on the patient demographics, risk factors, and certain clinical elements. Our results showed that in 6 out of the 10 data sets, the precision of our tool for the diagnosis of stroke was >90%. We believe that these methods can serve as a clinical decision support system and assist the emergency providers with early recognition of stroke.

Ramin Zand, MD

Ramin Zand, MD

By |November 1st, 2017|author interview, clinical, diagnosis and imaging|0 Comments
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Author Interview: Seung-Hoon Lee, MD, PhD

Seung-Hoon Lee

Seung-Hoon Lee

A conversation with Seung-Hoon Lee, MD, PhD, Professor of Neurology, Seoul National University Hospital, about the role of the susceptibility vessel sign on SWI to predict stroke subtype and recanalization.

Interviewed by José G. Merino, MD, Associate Professor of Neurology, University of Maryland School of Medicine.

They will be discussing the paper, “Prediction of Stroke Subtype and Recanalization Using Susceptibility Vessel Sign on Susceptibility-Weighted Magnetic Resonance Imaging,” published in the June 2017 issue of Stroke.

Dr. Merino: Could you please briefly describe the study and summarize the key findings, putting them into context of what was known before you did the study?

Dr. Lee: I’m glad to talk about our research in this interview. Thrombi in the cerebral arteries appear hypointense on susceptibility-weighted MRI (SWMRI). We call them “the susceptibility vessel sign” (SVS). The methodological strength of this study is that SWI MRI is much more sensitive than GRE and thus can quantify the size of the SVS. In this study, we analyzed the relationship between the size of the SVS, the stroke mechanism, and whether successful recanalization occurred in patients receiving endovascular treatment. Cardiac emboli are large but fragile because they are rich in RBCs but have scant platelets. We hypothesized that because the SVS reflects the red blood cell component of the clot, patients with larger SVS are more likely to have a cardioembolic source and thus more likely to have successful recanalization. We found that as the SVS size increased, the probability of cardioembolic stroke was higher, but that SVS size did not show any positive or negative correlation with successful recanalization. This is probably due to the high recanalization rate with the stent-retrievers, irrespective of stroke etiology. No association between SVS size and recanalization can be partly explained by clot fragility in cardioembolic stroke.

By |July 26th, 2017|author interview, clinical, diagnosis and imaging|0 Comments
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Predicting Hemorrhagic Transformation Following tPA Using CT and CT Perfusion Images

Sami Al Kasab, MD

Batchelor C, Pordeli P, d’Esterre CD, Najm M, Al-Ajlan FS, Boesen ME, et al. Use of Noncontrast Computed Tomography and Computed Tomographic Perfusion in Predicting Intracerebral Hemorrhage After Intravenous Alteplase Therapy. Stroke. 2017

Intracerebral hemorrhage (ICH) is a known complication of intravenous alteplase. The rates of symptomatic intracerebral hemorrhage following intravenous alteplase administration have varied between 1-4% depending on the definition used and the study.

In this study, Drs. Connor et al analyze the association between multimodal CT imaging parameters, including NCCT hypo attenuation degree, vlCBV, impaired blood-brain barrier permeability surface product, clinical and laboratory data at baseline, early reperfusion status, and development of parenchymal hemorrhage (PH) on follow-up imaging. All patients received NCCT, CT angiography, and CT perfusion at baseline. A 24 to 48 hour scan (either NCCT or MRI) was obtained. Imaging analyses were performed by readers blinded to other imaging and patient outcomes. All NCCT were scored for ASPECTS scores, the degree of hypo attenuation within the ischemic region using a 3-point grading system. Functional parametric maps of cerebral blood flow (CBF), CBV, Tmax, and a modified CTP algorithm for permeability calculations were used.

By |July 19th, 2017|clinical, diagnosis and imaging|2 Comments
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Blood Biomarkers in Ischemic Stroke

Ilana Spokoyny, MD

Blood biomarkers are an active research interest, with the potential for predicting ischemic stroke via identification of novel risk pathways. The authors of this paper tested the associations between ischemic stroke and three blood markers: procalcitonin (PCT), copeptin, and midregional-pro-atrial natriuretic peptide (MRproANP). These biomarkers were chosen because they represent three different pathophysiological processes. Procalcitonin is associated with bacterial infections and was chosen with the hope of finding a link between infection and ischemic (especially non-cardioembolic) stroke. Copeptin is a hypothalamic stress hormone, which was chosen because chronic activation of the hypothalamic-pituitary-adrenal axis and the sympathetic nervous system may promote vascular risk factors. MRproANP was hypothesized to be a marker of hemodynamic dysfunction and thereby a potential marker of (especially cardioembolic) stroke.


A nested case-control study was performed among initially stroke-free patients enrolled in the Northern Manhattan Study (NOMAS). 172 cases of first ischemic stroke were compared to 344 randomly selected controls. Primary endpoint (occurrence of first ischemic stroke) was detected using phone calls and prospective monitoring of hospital admissions and discharges. Patients with intracerebral hemorrhage were excluded.

PCT levels in the blood may reflect ongoing subclinical inflammatory processes triggered by bacterial endotoxins. It is unclear why there was an association of PCT with specifically small vessel stroke subtype. MRproANP was associated with cardioembolic stroke subtype, which may represent cardiac pathology (which has also been linked to ANP) causing cardioembolic strokes. Interventions based on these associations must be validated in prospective clinical trials, but this is a strong first step in developing better risk models and blood-based diagnostic tools for ischemic stroke. If these are validated and incorporated into clinical practice, one could imagine using MRproANP to help distinguish cardioembolic from non-cardioembolic sources of cryptogenic stroke, or using procalcitonin as one of the factors helping to distinguish mild strokes or TIAs from mimics. 
The adjusted hazard ratios for new ischemic stroke comparing the highest to lowest quartiles of PCT and MRproANP were 1.9 (1.0-3.8) and 3.5 (1.6-7.5), respectively. Stroke etiology was determined using based on the TOAST criteria. High PCT levels (top quartile) were associated with small vessel stroke (HR 5.1, 1.4-18.7) and high MRproANP levels (top quartile) were associated with cardioembolic stroke (HR 16.3, 3.7-70.9). 
By |June 29th, 2016|diagnosis and imaging|0 Comments
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Relevance of Carotid Plaque Characteristics for Ischemic Stroke and Coronary Heart Disease


Citing the systemic nature of atherosclerosis, the authors of this paper studied the association between extracranial carotid atherosclerosis features and prior ischemic stroke (IS) and coronary heart disease (CHD). 

Patients were selected from the Rotterdam Study. Participants with at least 2.5mm of carotid intima media thickness (IMT) were eligible for this study. Of 3,795 eligible participants, 1,982 underwent MRI of bilateral carotid arteries. MRI was performed on 1.5-Tesla scanners with a carotid artery protocol. All plaques of at least 2mm of thickness were assessed for intraplaque hemorrhage (IPH), lipid core, and calcification. Additionally, wall thickness and degree of stenosis were determined. Participants’ history was queried for prior IS and CHD (non-fatal MI or myocardial revascularization). Covariates were age, sex, smoking status, lipid measurements, BMI, diabetes, and hypertension.

Binomial logistic regression was used to determine the association between individual plaque characteristics and history of IS and CHD. Men and women were examined separately.

One thousand seven hundred thirty-one participants were ultimately included. The mean age was 73 years, and 55% were male. A majority of patients had a history of smoking. IS and CHD were much more common in men, as were vascular risk factors. The mean carotid wall thickness was 3.6mm, and the mean degree of stenosis was 13%. IPH was present in 35%, lipid core in 41%, and calcification in 82%. In terms of outcomes, 105 had a history of IS, and 199 had a history of CHD.

In the overall population, in multivariate analysis, only degree of stenosis was associated with IS. For men, stenosis and IPH were associated with IS. In both the overall population and when stratified by sex, only carotid stenosis was associated with CHD. 

The key finding is that whereas plaque thickness or stenosis were associated with both IS and CHD, IPH was only associated with IS (in men). The dependence on prevalence data and the lack of clinical data (e.g. stroke laterality or mechanism) limit the conclusions that can be drawn from this study. However, this work may foreshadow and stimulate prospective, mechanistically enlightening studies that capitalize on the granularity of MRI data.
By |June 27th, 2016|diagnosis and imaging|0 Comments
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Intracranial Atherosclerosis and Coronary Atherosclerosis: Two Twigs from the Same Vascular Branch

Peggy Nguyen, MD

Chung J-W, Bang OY, Lee MJ, Hwang J, Cha J, Choi J-H, et al. Echoing Plaque Activity of the Coronary and Intracranial Arteries in Patients With Stroke. Stroke. 2016

Atherosclerosis is a diffuse process that can affect both the coronary and carotid arteries, but while previous studies have suggested a strong correlation between coronary atherosclerosis and extracranial carotid atherosclerosis, the correlation with intracranial atherosclerosis is less clear. Whereas the mechanism of myocardial infarction from coronary atherosclerosis is likely more similar to ischemic stroke caused by extracranial atherosclerosis, ischemic stroke caused by intracranial atherosclerosis typically falls into two etiologies: branch occlusive disease-type (B-type), where atherosclerosis occludes a perforating artery, versus coronary-type plaque rupture of plaque (C-type), where the atherosclerotic plaque ruptures, causing a shower of multiple embolic infarcts distally. This study attempts to characterize intracranial plaque phenotypes and correlate asymptomatic coronary artery disease (CAD) with intracranial atherosclerotic disease (ICAD) burden.

A total of 81 patients were included the final analysis, drawn from a population of patients admitted within 7 days of symptom onset for treatment of acute ischemic stroke with intracranial atherosclerosis. Patients who had known histories of coronary artery disease were excluded. B-type ICAS was differentiated from C-type ICAS in both anterior and posterior territory strokes. An ICAD score was calculated on the basis of intracranial atherosclerotic burden, with 0 points given for stenosis less than 50%, 1 point for stenosis of 50-99% and 2 points for an occlusion, with all involved intracranial vessels summed for a total score

Asymptomatic CAD was quite common, with a prevalence of just over 80% in the study population. The prevalence of asymptomatic CAD was relatively similar in both B-type and C-type ICAS groups (48% vs 52%) and, as might be expected, the burden of ICAD was positively correlated with the burden of CAD, although non-calcified coronary artery plaque morphology was independently associated with C-type ICAS. As non-calcified coronary plaque increased, remodeling also increased in the symptomatic arteries of patients with ICAS.

This study provides evidence of a positive relationship between coronary and intracranial atherosclerotic burden, and that coronary artery plaque composition (calcified vs non-calcified) might predict intracranial atherosclerosis morphology. The investigators suggest that this should prompt us as clinician to take a more holistic approach to the entire vascular system, rather than solely focus on, for example, the cerebral vasculature, or the coronary arteries. Certainly this might prompt the clinician to, when faced with a stroke patient with C-type ICAS, be more cognizant of the type of likely associated CAD burden, but a study evaluating whether this might also be predictive of acute coronary syndrome, would be of additional benefit.

By |June 24th, 2016|diagnosis and imaging|0 Comments
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Fractional Anisotropy Change in Acute Phase of Stroke and its Correlation with Motor Recovery at 3 Months

Qing Hao, MD, PhD


“Doctor, will my father move his right arm again? How much do you think he can recover from this stroke?” As stroke neurologists, we are often asked about the prognosis after the stroke and most time the answer would be, “I am not exactly sure”.
Neuroimaging, especially MRI brain, has been very helpful in prognostication. Previous studies performed on chronic stroke patients demonstrated integrity/ atrophy of cortical spinal tract (CST) and signals indicative Wallerian degeneration (WD) on MRI in the chronic phase closely correlated with motor outcome.

Any neuroimaging markers in the acute phase of stroke can predict motor outcome? CST lesion load (based on initial motor impairment, lesion size and location) and CST integrity still played important roles. When talking about CST integrity, we can’t ignore fractional anisotropy (FA), an imaging marker derived from diffusion tensor imaging, which quantifies the organization (e.g. degree of alignment) and integrity of white matter tracts.
In this article, the author focused on FA in acute phase—they sought to investigate if FA difference in acute phase can be detected and how it predict motor outcome measured by upper extremity Fugl-Meyer score at 3 months.

Retrospective analyses were performed on a prospectively collected cohort of 58 patients with first time ischemic hemispheric stroke. MRI was done within 80 hours after stroke onset. FA values were determined in two regions of interest for 50 patients: cerebral peduncle and a stretch of the CST caudal to each stroke lesion (Nearest-5-Slice – N5S).
The authors were able to detect subtle asymmetry of FA changes (lower FA in the ipsilesional CST), most significantly in the slice that was closest to the ischemic lesion, not in the cerebral peduncle. The slope of the FA laterality index for the nearest-5-slices showed a weak but significant prediction (R2=0.11, p=0,022) for 3-month UE-FM score in univariate analysis, not in multivariate analysis. Not surprisingly, initial UE-FM, weighted CTS lesion load and days of therapy were stronger predictors (R2 =0.69, 0.71 and 0.249 respectively, p< 0.001) for 3-months UE-FM score.
CST integrity may be a dynamic change and its predictive value for motor recovery may be different at various stages after stroke. We look forward to more precise prediction models that would help us answer those challenging prognostication questions.
By |June 9th, 2016|diagnosis and imaging|0 Comments
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