Current Endovascular Approach to the Management of Acute Ischemic Stroke

Clinical diagnostic reference levels in neuroradiology based on clinical indication

This study focuses on patient radiation exposure in interventional neuroradiology (INR) procedures, a field that has advanced significantly since its inception in the 1980s. INR employs minimally invasive techniques to treat complex cerebrovascular diseases in the head, neck, and spine. The study establishes diagnostic reference levels (DRLs) for three clinical indications (CIs): stroke (S), brain aneurysms (ANs), and brain arteriovenous malformation (AVM). Data from 209 adult patients were analyzed, and DRLs were determined in terms of various dosimetric and technical quantities. For stroke, the established DRLs median values were found to be 78 Gy cm2, 378 mGy, 118 mGy, 12 min, 442 images, and 15 runs. Similarly, DRLs for brain AN are 85 Gy cm2, 611 mGy, 95.5 mGy, 19.5, 717 images, and 26 runs. For brain AVM, the DRL's are 180 Gy cm2, 1144 mGy, 537 mGy, 36 min, 1375 images, and 31 runs. Notably, this study is unique in reporting DRLs for specific CIs within INR procedures, providing valuable insights for optimizing patient safety and radiation exposure management.

RU-Net: skull stripping in rat brain MR images after ischemic stroke with rat U-Net

BACKGROUND

Experimental ischemic stroke models play a fundamental role in interpreting the mechanism of cerebral ischemia and appraising the development of pathological extent. An accurate and automatic skull stripping tool for rat brain image volumes with magnetic resonance imaging (MRI) are crucial in experimental stroke analysis. Due to the deficiency of reliable rat brain segmentation methods and motivated by the demand for preclinical studies, this paper develops a new skull stripping algorithm to extract the rat brain region in MR images after stroke, which is named Rat U-Net (RU-Net).

METHODS

Based on a U-shape like deep learning architecture, the proposed framework integrates batch normalization with the residual network to achieve efficient end-to-end segmentation. A pooling index transmission mechanism between the encoder and decoder is exploited to reinforce the spatial correlation. Two different modalities of diffusion-weighted imaging (DWI) and T2-weighted MRI (T2WI) corresponding to two in-house datasets with each consisting of 55 subjects were employed to evaluate the performance of the proposed RU-Net.

RESULTS

Extensive experiments indicated great segmentation accuracy across diversified rat brain MR images. It was suggested that our rat skull stripping network outperformed several state-of-the-art methods and achieved the highest average Dice scores of 98.04% (p < 0.001) and 97.67% (p < 0.001) in the DWI and T2WI image datasets, respectively.

CONCLUSION

The proposed RU-Net is believed to be potential for advancing preclinical stroke investigation and providing an efficient tool for pathological rat brain image extraction, where accurate segmentation of the rat brain region is fundamental.

Oxidative stress in cerebrovascular disease and associated diseases

Cellular aging is the most severe risk factor for neurodegenerative disease. Simultaneously, oxidative stress (OS) is a critical factor in the aging process, resulting from an imbalance between reactive oxygen and nitrogen species and the antioxidant defense system. Emerging evidence indicates that OS is a common cause of several age-related brain pathologies, including cerebrovascular diseases. Elevated OS disrupts endothelial functional ability by diminishing the bioavailability of nitric oxide (a vascular dilator), induces atherosclerosis, and impairs vasculature, which are all common characteristics of cerebrovascular disease. In this review, we summarize evidence supporting an active role of OS in cerebrovascular disease progression, focusing primarily on stroke pathogenesis. We briefly discuss hypertension, diabetes, heart disease, and genetic factors that are often linked to OS and are considered associated factors influencing stroke pathology. Finally, we discuss the current pharmaceutics/therapeutics available for treating several cerebrovascular diseases.

Ultra-high b value DWI in distinguishing fresh gray matter ischemic lesions from white matter ones: a comparative study with routine and high b value DWI

Background

Fresh ischemic lesions (FILs) can occur in both the brain's gray matter (GM) and white matter (WM), with each location signifying a different prognosis for patients. This study aims to investigate the application of ultra-high b value diffusion-weighted imaging (DWI) in distinguishing FILs in these two areas via a comparative study with routine and high b value DWI.

Methods

Multiple b value DWI (b=0, 500, 1,000, 2,000, 4,000, 6,000, 8,000, 10,000 s/mm²) was performed on 47 patients with suspected acute ischemic stroke (AIS). Apparent diffusion coefficient (ADC) maps, including ADC₅₀₀, ADC_1,000, ADC_2,000, ADC_4,000, ADC_6,000, ADC_8,000, and ADC_10,000, were calculated, and the mean ADC value of the FILs in the GM and WM on each map was obtained by referring to the structural magnetic resonance imaging (MRI). ADC value differences of the FILs in the GM and WM were compared using Mann-Whitney U tests, and receiver operating characteristic (ROC) curves evaluated the diagnostic efficiency of each ADC value in distinguishing FILs in the two areas.

Results

In the enrolled 34 patients, 145 FILs were identified, of which 42 involved the GM, 87 the WM, and 16 both the GM and WM. A total of 161 regions were delineated, 58 in the GM and 103 in the WM. The values of FILs in the WM on ADC_2,000, ADC_4,000, ADC_6,000, ADC_8,000, and ADC_10,000 maps were significantly lower than those in the GM (P=0.007, P<0.001, P<0.001, P<0.001 and P<0.001, respectively), while no significant differences were found on ADC₅₀₀ and ADC_1,000 maps (P=0.427 and P=0.225, respectively). ROC curves demonstrated that the area under the curve (AUC) paralleled the increasing b value, ascending from ADC₅₀₀ to ADC_10,000 (0.538, 0.558, 0.629, 0.766, 0.827, 0.859, 0.872, in that order).

Conclusions

Ultra-high b value DWI is extremely sensitive to the slight diffusion difference between FILs in the GM and the WM. Its sensitivity parallels the increasing b value, indicating its clinical advantage in identifying the microstructure of FILs.

Effects of Bone Marrow Stromal Cells (BMSCs) on Behavior, Infarct Size and HIF-1α Expression in Stroke Rats

This study aims to assess BMSCs’ effect on the behavior, infarct size and HIF-1α expression in stroke rats. Rats were separated into sham group, CVA group and BMSCs group with 10 rats in each group followed by analysis of neuroethology scores, brain tissue pathology and infarct size, and HIF-1α level in brain tissues. No difference of neurological scores was found between CVA group and BMSCs group after 3 hours (P > 0.05). After BMSCs transplantation, the nerve score was significantly reduced (P < 0.05) and cognitive function was significantly improved compared to CVA group. Compared with sham rats, CAV rats had a larger area of infarction and the infarcted tissue cells showed degeneration or necrosis with reduced cell number and obvious edema, which were all improved in BMSCs group. CVA group showed a larger area of infarct tissue (P < 0.05), which was reduced in BMSCs group (P < 0.05). Compared with sham group, CVA group showed significantly upregulated HIF-1α level (P < 0.05) which was reduced in BMSCs group (P < 0.05). BMSCs has a certain repair effect on the ethology of stroke rats possibly via inhibition of HIF-1α level in cerebral infarction and brain tissue.

Automatic brain extraction and hemisphere segmentation in rat brain MR images after stroke using deformable models

PURPOSE

Experimental ischemic stroke models play an essential role in understanding the mechanisms of cerebral ischemia and evaluating the development of pathological extent. An important precursor to the investigation of ischemic strokes associated with rodents is the brain extraction and hemisphere segmentation in rat brain diffusion-weighted imaging (DWI) and T2-weighted MRI (T2WI) images. Accurate and reliable image segmentation tools for extracting the rat brain and hemispheres in the MR images are critical in subsequent processes, such as lesion identification and injury analysis. This study is an attempt to investigate rat brain extraction and hemisphere segmentation algorithms that are practicable in both DWI and T2WI images.

METHODS

To automatically perform brain extraction, the proposed framework is based on an efficient geometric deformable model. By introducing an additional image force in response to the rat brain characteristics into the skull stripping model, we establish a unique rat brain extraction scheme in DWI and T2WI images. For the subsequent hemisphere segmentation, we develop an efficient brain feature detection algorithm to approximately separate the rat brain. A refinement process is enforced by constructing a gradient vector flow in the proximity of the midsurface, where a parametric active contour is attracted to achieve hemisphere segmentation.

RESULTS

Extensive experiments with 55 DWI and T2WI subjects were executed in comparison with the state-of-the-art methods. Experimental results indicated that our rat brain extraction and hemisphere segmentation schemes outperformed the competitive methods and exhibited high performance both qualitatively and quantitatively. For rat brain extraction, the average Dice scores were 97.13% and 97.42% in DWI and T2WI image volumes, respectively. Rat hemisphere segmentation results based on the Hausdorff distance metric revealed average values of 0.17 and 0.15 mm for DWI and T2WI subjects, respectively.

CONCLUSIONS

We believe that the established frameworks are advantageous to facilitate preclinical stroke investigation and relevant neuroscience research that requires accurate brain extraction and hemisphere segmentation using rat DWI and T2WI images.

Improving Collateral Circulation: A Potential Adjunctive Strategy to Prevent or Slow the Progression of Vascular Dementia

Vascular dementia (VaD), a cognitive disorder caused by cerebrovascular pathologies, is the most common cause of dementia in the elderly, being second only to Alzheimer's disease. Researches have shown that adequate cerebral blood flow (CBF) is the first condition for maintaining the structural integrity and normal function of the brain, and VaD is generally considered to be resulted from neuronal loss due to reduced CBF. Collateral circulation, a compensation mechanism for CBF, provides an alternative vascular pathway for blood to reach ischemic tissues, which has been confirmed to be associated with better clinical outcomes of ischemic diseases. At present, considerable effort has been devoted to enhancing the functional prognosis of acute ischemic stroke by improving collateral circulation. Since ischemic stroke is the primary contributor to VaD, it is necessary to explore whether improving collateral circulation is beneficial to prevent or slow the progression of VaD. This article reviews the compensatory characteristics of different levels of cerebral collateral circulation, addresses the relationship between collateral circulation and VaD, and highlights that improving collateral circulation may be a potential adjunctive strategy in preventing and slowing the progression of VaD.

Diffusion kurtosis imaging of microstructural changes in brain tissue affected by acute ischemic stroke in different locations

The location of an acute ischemic stroke is associated with its prognosis. The widely used Gaussian model-based parameter, apparent diffusion coefficient (ADC), cannot reveal microstructural changes in different locations or the degree of infarction. This prospective observational study was reviewed and approved by the Institutional Review Board of Xiamen Second Hospital, China (approval No. 2014002). Diffusion kurtosis imaging (DKI) was used to detect 199 lesions in 156 patients with acute ischemic stroke (61 males and 95 females), mean age 63.15 ± 12.34 years. A total of 199 lesions were located in the periventricular white matter (n = 52), corpus callosum (n = 14), cerebellum (n = 29), basal ganglia and thalamus (n = 21), brainstem (n = 21) and gray-white matter junctions (n = 62). Percentage changes of apparent diffusion coefficient (ΔADC) and DKI-derived indices (fractional anisotropy [ΔFA], mean diffusivity [ΔMD], axial diffusivity [ΔD_a], radial diffusivity ΔD_r, mean kurtosis [ΔMK], axial kurtosis [ΔK_a], and radial kurtosis [ΔK_r]) of each lesion were computed relative to the normal contralateral region. The results showed that (1) there was no significant difference in ΔADC, ΔMD, ΔD_a or ΔD_r among almost all locations. (2) There was significant difference in ΔMK among almost all locations (except basal ganglia and thalamus vs. brain stem; basal ganglia and thalamus vs. gray-white matter junctions; and brainstem vs. gray-white matter junctions. (3) The degree of change in diffusional kurtosis in descending order was as follows: corpus callosum > periventricular white matter > brainstem > gray-white matter junctions > basal ganglia and thalamus > cerebellum. In conclusion, DKI could reveal the differences in microstructure changes among various locations affected by acute ischemic stroke, and performed better than diffusivity among all groups.