Dataset Information

Arterial Tortuosity and Its Correlation with White Matter Hyperintensities in Acute Ischemic Stroke.

ABSTRACT:

Introduction

The association between arterial tortuosity and acute ischemic stroke (AIS) has been reported, but showing inconsistent results. We hypothesized that tortuosity of extra- and intracranial large arteries might be higher in AIS patients. Furthermore, we explored the correlation between artery tortuosity and white matter hyperintensity (WMH) severity in AIS patients.

Methods

166 AIS patients identified as large artery atherosclerosis, and 83 control subjects were enrolled. All subjects received three-dimensional computed tomography angiography (CTA). Arterial tortuosity was evaluated using the tortuosity index. WMHs were evaluated using magnetic resonance imaging in all AIS patients.

Results

AIS patients showed significantly increased arterial tortuosity index relative to controls, including left carotid artery (CA) (p = 0.001), right CA (p < 0.001), left common carotid artery (CCA) (p < 0.001), right CCA (p < 0.001), left internal carotid artery (p = 0.001), right internal carotid artery (p = 0.01), left extracranial internal carotid artery (EICA) (p < 0.001), right EICA (p = 0.01), and vertebral artery dominance (VAD) (p = 0.001). The tortuosity of all above arteries was associated with the presence of AIS. AIS patients with moderate or severe WMHs had a higher tortuosity index in left CA (p = 0.005), left CCA (p = 0.003), left EICA (p = 0.07), and VAD (p = 0.001). In addition, the tortuosity of left EICA and VAD was associated with WMH severity in AIS patients.

Conclusions

Increased extra- and intracranial large arteries tortuosity is associated with AIS. The tortuosity of left carotid artery system and vertebral artery may be the independent risk factors for WMH severity in AIS patients. Clinical Trial Registration. This trial is registered with NCT03122002 (http://www.clinicaltrials.gov).

SUBMITTER: Shang K

PROVIDER: S-EPMC8970938 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Arterial Tortuosity and Its Correlation with White Matter Hyperintensities in Acute Ischemic Stroke.

Shang Ke K Chen Xiao X Cheng Chang C Luo Xiang X Xu Shabei S Wang Wei W Liu Chenchen C

Neural plasticity 20220324

<h4>Introduction</h4>The association between arterial tortuosity and acute ischemic stroke (AIS) has been reported, but showing inconsistent results. We hypothesized that tortuosity of extra- and intracranial large arteries might be higher in AIS patients. Furthermore, we explored the correlation between artery tortuosity and white matter hyperintensity (WMH) severity in AIS patients.<h4>Methods</h4>166 AIS patients identified as large artery atherosclerosis, and 83 control subjects were enrolle ...[more]

PMID: 35369646

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Project description:ObjectiveThe purpose of the current study is to explore the value of a nomogram that integrates clinical factors and MRI white matter hyperintensities (WMH) radiomics features in predicting the prognosis at 90 days for patients with acute ischemic stroke (AIS).MethodsA total of 202 inpatients with acute anterior circulation ischemic stroke from the Department of Neurology, Xuzhou Central Hospital between September 2023 and March 2024 were retrospectively enrolled. Inpatient clinical data and cranial MRI images were acquired. In this study, the sample was randomly divided into a training cohort comprising 141 cases and a validation cohort of 61 cases in a 7:3 ratio. WMH lesions on fluid-attenuated inversion recovery (FLAIR) sequences were automatically segmented and manually adjusted using Matlab and ITK-SNAP software. The segmentation led to the identification of total white matter hyperintensity (TWMH), periventricular white matter hyperintensity (PWMH), and deep white matter hyperintensity (DWMH). Subsequently, radiomics features were meticulously extracted from these three distinct regions of interest (ROIs). Radiomic models for the three ROIs were developed using six machine learning algorithms. The clinical model was built by identifying clinical risk factors through univariate and multivariate logistic regression analyses. A combined model was subsequently developed incorporating the best radiomics model with significant clinical factors. To illustrate these risk factors, a graphical representation known as a nomogram was devised.ResultsAge, previous stroke history, coronary artery disease, admission blood glucose levels, homocysteine levels, and infarct volume were identified as independent clinical predictors of AIS prognosis. A total of 16, 21, and 22 radiomics features were selected from TWMH, PWMH, and DWMH, respectively. The TWMH radiomics model using the SVM classifier exhibited the best predictive performance for AIS prognosis, achieving a sensitivity of 90.0%, a specificity of 81.3%, an accuracy of 85.3%, and an AUC of 0.916 in the validation set. The combined model outperformed both the clinical and radiomics models, exhibiting exceptional predictive capabilities with a validation cohort sensitivity of 89.3%, specificity of 84.8%, accuracy of 86.9%, and AUC of 0.939.ConclusionThe FLAIR sequence-based WMH radiomics approach demonstrates effective prediction of the 90-day functional prognosis in patients with AIS. The integration of TWMH radiomics and clinical factors in a combined model exhibits superior performance. This innovative model shows potential in aiding clinicians to enhance their assessment of patient prognosis and tailor personalized treatment strategies.Clinical trial numberNot applicable.

Project description:BackgroundThe progression of FLAIR white matter hyperintensities (WMHs) on MRI heralds vascular-mediated cognitive decline. Even before FLAIR WMH progression, adjacent normal appearing white matter (NAWM) already demonstrates microstructural deterioration on diffusion tensor imaging (DTI). We hypothesized that elevated DTI free water (FW) would precede FLAIR WMH progression, implicating interstitial fluid accumulation as a key pathological step in the progression of cerebral small vessel disease.MethodsParticipants at least 3 months after an ischemic stroke or TIA with WMH on MRI underwent serial brain MRIs every 3 months over the subsequent year. For each participant, the WMHs were automatically segmented, serial MRIs were aligned, and a region of WMH penumbra tissue at risk was defined by dilating lesions at any time point and subtracting baseline lesions. Penumbra voxels were classified as either stable or progressing to WMH if they were segmented as new lesions and demonstrated increasing FLAIR intensity over time. Aligned DTI images included FW and FW-corrected fractional anisotropy (FATissue) and mean diffusivity (MDTissue). Logistic regression and area under the receiver-operator characteristic curve (AUC) were used to test whether baseline DTI predicted voxel-wise classification of stable penumbra or progression to WMH while covarying for clinical risk factors.ResultsIn the included participants (n = 26, mean age 71 ± 9 years, 31% female), we detected a median annual voxel-wise WMH growth of 2.9 ± 2.6 ml. Each baseline DTI metric was associated with lesion progression in the penumbra, but FW had the greatest AUC of 0.732 (0.730 - 0.733) for predicting voxel-wise WMH progression pooled across participants.DiscussionBaseline increased interstitial fluid, estimated as FW on DTI, predicted the progression of NAWM to WMH over the following year. These results implicate the presence of FW in the pathogenesis of cerebral small vessel disease progression.

Project description:Background This study was conducted to compare frequencies of chronic brain infarctions (CBIs) and white matter hyperintensities (WMHs) as well as their associations with established early recurrence risk scores in patients with transient ischemic attack (TIA) and stroke mimics compared with ischemic stroke. Methods and Results Single-center cohort study including consecutive patients with TIA, stroke mimics, and acute ischemic stroke, with available magnetic resonance imaging from January 2015 to December 2017. Blinded raters adjudicated WMH (age-related white matter changes score) and CBI according to established definitions. A total of 2112 patients (median [Q1-Q3] age 71 [59-80] years, 43% women, National Institutes of Health Stroke Scale score of 2 [1-7], 80% ischemic stroke, 18% TIA, 2% stroke mimics) were included. While CBIs were present in only 10% of patients with stroke mimic, they were detected in 28% of TIAs and 38% of ischemic strokes (P<0.001). WMHs were less pronounced (0, 0-1) in patients with stroke mimic, but there was no difference between TIA (1, 1-2) and ischemic stroke (0, 1-2) patients. CBIs (adjusted odds ratio, 0.3; 95% CI, 0.1-0.9) were associated with a lower rate of stroke mimic as the final diagnosis, while WMHs were not (adjusted odds ratio per point, 1.3; 95% CI, 0.7-2.2). WMH (β per point, 0.4; 95% CI, 0.3-0.6) and presence of CBI (β, 0.6; 95% CI, 0.3-0.9) were associated with a higher cardiovascular risk profile according to the ABCD3-I score. The accuracy of prediction was good for high-risk TIA (cross-validated area under the receiver operating characteristic curve, 0.89; 95% CI, 0.79-0.93) on the basis of brain imaging, age, and sex. Conclusions CBI and WMH differ between patients with stroke mimic and patients with TIA/ischemic stroke and are closely associated with established recurrence risk scores. Prospective studies need to clarify whether including brain frailty markers may contribute to the refinement of current management algorithms and risk stratifications.

Project description:To report a patient in whom an acute ischemic stroke precipitated chronic blood-brain barrier (BBB) disruption and expansion of vascular white matter hyperintensities (WMH) into regions of normal appearing white matter (NAWM) during the following year. WMH are a common finding in patients with vascular risk factors such as a history of stroke. The pathophysiology of WMH is not fully understood; however, there is growing evidence to suggest that the development of WMH may be preceded by the BBB disruption in the NAWM. We studied a patient enrolled in the National Institutes of Health Natural History of Stroke Study who was scanned with magnetic resonance imaging (MRI) after presenting to the emergency room with an acute stroke. After a treatment with IV tPA, she underwent further MRI scanning at 2 h, 24 h, 5 days, 30 days, 90 days, 6 months, and 1-year post stroke. BBB permeability images were generated from the perfusion weighted imaging (PWI) source images. MRIs from each time point were co-registered to track changes in BBB disruption and WMH over time. An 84-year-old woman presented after acute onset right hemiparesis, right-sided numbness and aphasia with an initial NIHSS of 13. MRI showed diffusion restriction in the left frontal lobe and decreased blood flow on perfusion imaging. Fluid attenuated inversion recovery (FLAIR) imaging showed bilateral confluent WMH involving the deep white matter and periventricular regions. She was treated with IV tPA without complication and her NIHSS improved initially to 3 and ultimately to 0. Permeability maps identified multiple regions of chronic BBB disruption remote from the acute stroke, predominantly spanning the junction of WMH and NAWM. The severity of BBB disruption was greatest at 24 h after the stroke but persisted on subsequent MRI scans. Progression of WMH into NAWM over the year of observation was detected bilaterally but was most dramatic in the regions adjacent to the initial stroke. WMH-associated BBB disruption may be exacerbated by an acute stroke, even in the contralateral hemisphere, and can persist for months after the initial event. Transformation of NAWM to WMH may be evident in areas of BBB disruption within a year after the stroke. Further studies are needed to investigate the relationship between chronic BBB disruption and progressive WMH in patients with a history of cerebrovascular disease and the potential for acute stroke to trigger or exacerbate the process leading to the development of WMH.

Dataset Information

Arterial Tortuosity and Its Correlation with White Matter Hyperintensities in Acute Ischemic Stroke.

Introduction

Methods

Results

Conclusions

Publications

Arterial Tortuosity and Its Correlation with White Matter Hyperintensities in Acute Ischemic Stroke.

Similar Datasets

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