Dataset Information

Impact of Ischemic Lesion Location on the mRS Score in Patients with Ischemic Stroke: A Voxel-Based Approach.

ABSTRACT: BACKGROUND AND PURPOSE:Previous studies indicated that ischemic lesion volume might be a useful surrogate marker for functional outcome in ischemic stroke but should be considered in the context of lesion location. In contrast to previous studies using the ROI approach, which has several drawbacks, the present study aimed to measure the impact of ischemic lesion location on functional outcome using a more precise voxelwise approach. MATERIALS AND METHODS:Datasets of patients with acute ischemic strokes from the Multicenter Randomized Clinical Trial of Endovascular Therapy for Acute Ischemic Stroke in the Netherlands (MR CLEAN) were used. Primary outcome was functional outcome as assessed by the modified Rankin Scale 3 months after stroke. Ischemic lesion volume was determined on CT scans 3-9 days after stroke. Voxel-based lesion-symptom mapping techniques, including covariates that are known to be associated with functional outcome, were used to determine the impact of ischemic lesion location for outcome. RESULTS:Of the 500 patients in the MR CLEAN trial, 216 were included for analysis. The mean age was 63 years. Lesion-symptom mapping with inclusion of covariates revealed that especially left-hemispheric lesions in the deep periventricular white matter and adjacent internal capsule showed a great influence on functional outcome. CONCLUSIONS:Our study confirms that infarct location has an important impact on functional outcome of patients with stroke and should be considered in prediction models. After we adjusted for covariates, the left-hemispheric corticosubcortical fiber tracts seemed to be of higher functional importance compared with cortical lesions.

SUBMITTER: Ernst M

PROVIDER: S-EPMC7655370 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Impact of Ischemic Lesion Location on the mRS Score in Patients with Ischemic Stroke: A Voxel-Based Approach.

Ernst M M Boers A M M AMM Forkert N D ND Berkhemer O A OA Roos Y B YB Dippel D W J DWJ van der Lugt A A van Oostenbrugge R J RJ van Zwam W H WH Vettorazzi E E Fiehler J J Marquering H A HA Majoie C B L M CBLM Gellissen S S

AJNR. American journal of neuroradiology 20181004 11

<h4>Background and purpose</h4>Previous studies indicated that ischemic lesion volume might be a useful surrogate marker for functional outcome in ischemic stroke but should be considered in the context of lesion location. In contrast to previous studies using the ROI approach, which has several drawbacks, the present study aimed to measure the impact of ischemic lesion location on functional outcome using a more precise voxelwise approach.<h4>Materials and methods</h4>Datasets of patients with ...[more]

PMID: 30287456

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Project description:BackgroundVoxel-based lesion symptom mapping (VLSM) assesses the relation of lesion location at a voxel level with a specific clinical or functional outcome measure at a population level. Spatial normalization, that is, mapping the patient images into an atlas coordinate system, is an essential pre-processing step of VLSM. However, no consensus exists on the optimal registration approach to compute the transformation nor are downstream effects on VLSM statistics explored. In this work, we evaluate four registration approaches commonly used in VLSM pipelines: affine (AR), nonlinear (NLR), nonlinear with cost function masking (CFM), and enantiomorphic registration (ENR). The evaluation is based on a standard VLSM scenario: the analysis of statistical relations of brain voxels and regions in imaging data acquired early after stroke onset with follow-up modified Rankin Scale (mRS) values.Materials and methodsFluid-attenuated inversion recovery (FLAIR) MRI data from 122 acute ischemic stroke patients acquired between 2 and 3 days after stroke onset and corresponding lesion segmentations, and 30 days mRS values from a European multicenter stroke imaging study (I-KNOW) were available and used in this study. The relation of the voxel location with follow-up mRS was assessed by uni- as well as multi-variate statistical testing based on the lesion segmentations registered using the four different methods (AR, NLR, CFM, ENR; implementation based on the ANTs toolkit).ResultsThe brain areas evaluated as important for follow-up mRS were largely consistent across the registration approaches. However, NLR, CFM, and ENR led to distortions in the patient images after the corresponding nonlinear transformations were applied. In addition, local structures (for instance the lateral ventricles) and adjacent brain areas remained insufficiently aligned with corresponding atlas structures even after nonlinear registration.ConclusionsFor VLSM study designs and imaging data similar to the present work, an additional benefit of nonlinear registration variants for spatial normalization seems questionable. Related distortions in the normalized images lead to uncertainties in the VLSM analyses and may offset the theoretical benefits of nonlinear registration.

Project description:IntroductionIt is well known that post-stroke depression (PSD) is a psychiatric complication after stroke which leads to worse functional outcome and poorer quality of life. Some risk factors including gender, stroke severity, lesion location, homocysteine (HCY), and so on are associated with PSD. This study aims to further explore the possible relationship between serum levels of HCY and early-onset PSD and the predictive value of HCY combined with stroke characteristics for early-onset PSD.MethodsTwo hundred forty-five patients with acute ischemic stroke who met the criteria were included in this study from March 2015 to March 2017. PSD was diagnosed at 2 weeks after stroke. The severity of depressive symptoms was evaluated with the Hamilton depression scale 17 items (HAMD-17), and patients with HAMD scores ≥7 were included in the PSD group. The demographic data, clinical characteristics, serum levels of HCY, and detailed radiological variables (e.g., lesion location and quantity of the brain infarct) were also examined.ResultsIn total, 97 (39.6%) patients of the 245 patients were diagnosed with depression. The univariate analyses suggested that patients in PSD group had a higher NIHSS score, modified Rankin Scale score, and HCY levels than patients in non-PSD group (p < .001). The patients with PSD had higher proportion of multiple-site acute infarcts and frontal lobe lesion (p < .05). In multivariate logistic regression analysis, NIHSS score at admission, serum levels of HCY, and multiple-site lesions were independently related to early-onset PSD. Based on receiver operating characteristic curves analysis, the combination of HCY, NIHSS scores, multiple-site lesions, and lesion location revealed a highest area under the curve of 0.807 (95% confidence interval [CI]: 0.748-0.865, p < .001). Furthermore, there was a significantly increased risk of early-onset PSD associated with serum levels of HCY ≥16.98 μmol/L (odds ratio [OR] = 10.976, 95% CI: 5.585-21.573, p < .001).ConclusionsOur study indicated that higher NIHSS score, elevated serum levels of HCY, and multiple-site lesions may be independent risk factors of early-onset PSD. The combination of HCY, NIHSS scores, multiple-site lesions, and lesion location may provide greater predictive value than HCY alone for early-onset PSD. Early intervention for elevated serum levels of HCY may be a potential target for the intervention and prevention of PSD.

Project description:BackgroundMagnetic Resonance Spectroscopy (MRS) can measure in vivo brain tissue metabolism that exhibits unique biochemical characteristics in brain tumors. For clinical application, an efficient and versatile quantification method of MRS would be an important tool for medical research, particularly for exploring the scientific problem of tumor monitoring. The objective of our study is to propose an automated MRS quantitative approach and assess the feasibility of this approach for glioma grading, prognosis and boundary detection.MethodsAn automated quantitative approach based on a convex envelope (AQoCE) is proposed in this paper, including preprocessing, convex-envelope based baseline fitting, bias correction, sectional baseline removal, and peak detection, in a total of 5 steps. Some metabolic ratios acquired by this quantification are selected for statistical analysis. An independent sample t-test and the Kruskal-Wallis test are used for distinguishing low-grade gliomas (LGG) and high-grade gliomas (HGG) and for detecting the tumor, peritumoral and contralateral areas, respectively. Seventy-eight cases of pre-operative brain gliomas with pathological reports are included in this study.ResultsCho/NAA, Cho/Cr and Lip-Lac/Cr (LL/Cr) calculated by AQoCE in the tumor area differ significantly between LGG and HGG, with p≤0.005. Using logistic regression combining Cho/NAA, Cho/Cr and LL/Cr to generate a ROC curve, AQoCE achieves a sensitivity of 92.9%, a specificity of 72.2%, and an area under ROC curve (AUC) of 0.860. Moreover, both Cho/NAA and Cho/Cr in the AQoCE approach show a significant difference (p≤0.019) between tumoral, peritumoral, and contralateral areas. The comparison between the results of AQoCE and Siemens MRS processing software are also discussed in this paper.ConclusionsThe AQoCE approach is an automated method of residual water removal and metabolite quantification. It can be applied to multi-voxel 1H-MRS for evaluating brain glioma grading and demonstrating characteristics of brain glioma metabolism. It can also detect infiltration in the peritumoral area. Under the limited clinical data used, AQoCE is significantly more versatile and efficient compared to the reference approach of Siemens.

Dataset Information

Impact of Ischemic Lesion Location on the mRS Score in Patients with Ischemic Stroke: A Voxel-Based Approach.

Publications

Impact of Ischemic Lesion Location on the mRS Score in Patients with Ischemic Stroke: A Voxel-Based Approach.

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