Fixel-based evidence of microstructural damage in crossing pathways improves language mapping in Post-stroke aphasia

Metric comparison of connectome-based lesion-symptom mapping in post-stroke aphasia

Connectome-based lesion-symptom mapping relates behavioural impairments to disruption of structural brain connectivity. Connectome-based lesion-symptom mapping can be based on different approaches (diffusion MRI versus lesion mask), network scales (whole brain versus regions of interest) and measure types (tract-based, parcel-based, or network-based metrics). We evaluated the similarity of different connectome-based lesion-symptom mapping processing choices and identified factors that influence the results using multiverse analysis-the strategy of conducting and displaying the results of all reasonable processing choices. Metrics derived from lesion masks and diffusion-weighted images were tested for association with Boston Naming Test and Token Test performance in a sample of 50 participants with aphasia following left hemispheric stroke. 'Direct' measures were derived from diffusion-weighted images. 'Indirect' measures were derived by overlaying lesion masks on a white matter atlas. Parcel-based connectomes were constructed for the whole brain and regions of interest (14 language-relevant parcels). Numerous tract-based and network-based metrics were calculated. There was a high discrepancy across processing approaches (diffusion-weighted images versus lesion masks), network scales (whole brain versus regions of interest) and metric types. Results indicate weak correlations and different connectome-based lesion-symptom mapping results across the processing choices. Substantial methodological work is needed to validate the various decision points that arise when conducting connectome-based lesion-symptom mapping analyses. Multiverse analysis is a useful strategy for evaluating the similarity across different processing choices in connectome-based lesion-symptom mapping.

Predicting Alzheimer's progression in MCI: a DTI-based white matter network model

OBJECTIVE

This study aimed to identify features of white matter network attributes based on diffusion tensor imaging (DTI) that might lead to progression from mild cognitive impairment (MCI) and construct a comprehensive model based on these features for predicting the population at high risk of progression to Alzheimer's disease (AD) in MCI patients.

METHODS

This study enrolled 121 MCI patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Among them, 36 progressed to AD after four years of follow-up. A brain network was constructed for each patient based on white matter fiber tracts, and network attribute features were extracted. White matter network features were downscaled, and white matter markers were constructed using an integrated downscaling approach, followed by forming an integrated model with clinical features and performance evaluation.

RESULTS

APOE4 and ADAS scores were used as independent predictors and combined with white matter network markers to construct a comprehensive model. The diagnostic efficacy of the comprehensive model was 0.924 and 0.919, sensitivity was 0.864 and 0.900, and specificity was 0.871 and 0.815 in the training and test groups, respectively. The Delong test showed significant differences (P < 0.05) in the diagnostic efficacy of the combined model and APOE4 and ADAS scores, while there was no significant difference (P > 0.05) between the combined model and white matter network biomarkers.

CONCLUSIONS

A comprehensive model constructed based on white matter network markers can identify MCI patients at high risk of progression to AD and provide an adjunct biomarker helpful in early AD detection.

Application of diffusion tensor imaging in the diagnosis of post-stroke aphasia: a meta-analysis and systematic review

Introduction

Diffusion Tensor Imaging (DTI) indicators of different white matter (WM) fibers and brain region lesions for post-stroke aphasia (PSA) are inconsistent in existing studies. Our study examines the consistency and differences between PSA tests performed with DTI. In addition, obtaining consistent and independent conclusions between studies was made possible by utilizing DTI in PSA assessment.

Methods

In order to gather relevant studies using DTI for diagnosing PSA, we searched the Web of Science, PubMed, Embase, and CNKI databases. Based on the screening and evaluation of the included studies, the meta-analysis was used to conduct a quantitative analysis. Narrative descriptions were provided for studies that met the inclusion criteria but lacked data.

Results

First, we reported on the left hemisphere. The meta-analysis showed that fractional anisotropy (FA) of the arcuate fasciculus (AF) and superior longitudinal fasciculus (SLF), inferior frontal-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), and uncinate fasciculus (UF) were decreased in the PSA group in comparison with the healthy controls (p < 0.00001). However, in the comparison of axial diffusivity (AD), there was no statistically significant difference in white matter fiber tracts in the dual-stream language model of the PSA group. Elevated radial diffusivity (RD) was seen only in the IFOF and ILF (PIFOF = 0.01; PILF = 0.05). In the classic Broca's area, the FA of the PSA group was decreased (p < 0.00001) while the apparent diffusion coefficient was elevated (p = 0.03). Secondly, we evaluated the white matter fiber tracts in the dual-stream language model of the right hemisphere. The FA of the PSA group was decreased only in the IFOF (p = 0.001). AD was elevated in the AF and UF (PAF < 0.00001; PUF = 0.009). RD was elevated in the AF and UF (PAF = 0.01; PUF = 0.003). The other fiber tracts did not undergo similar alterations.

Conclusion

In conclusion, DTI is vital for diagnosing PSA because it detects WM changes effectively, but it still has some limitations. Due to a lack of relevant language scales and clinical manifestations, diagnosing and differentiating PSA independently remain challenging.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=365897.

Early white matter connectivity and plasticity in post stroke aphasia recovery

A disruption of white matter connectivity is negatively associated with language (recovery) in patients with aphasia after stroke, and behavioral gains have been shown to coincide with white matter neuroplasticity. However, most brain-behavior studies have been carried out in the chronic phase after stroke, with limited generalizability to earlier phases. Furthermore, few studies have investigated neuroplasticity patterns during spontaneous recovery (i.e., not related to a specific treatment) in the first months after stroke, hindering the investigation of potential early compensatory mechanisms. Finally, the majority of previous research has focused on damaged left hemisphere pathways, while neglecting the potential protective value of their right hemisphere counterparts for language recovery. To address these outstanding issues, we present a longitudinal study of thirty-two patients with aphasia (21 males and 11 females, M = 69.47 years, SD = 10.60 years) who were followed up for a period of 1 year with test moments in the acute (1-2 weeks), subacute (3-6 months) and chronic phase (9-12 months) after stroke. Constrained Spherical Deconvolution-based tractography was performed in the acute and subacute phase to measure Fiber Bundle Capacity (FBC), a quantitative connectivity measure that is valid in crossing fiber regions, in the bilateral dorsal arcuate fasciculus (AF) and the bilateral ventral inferior fronto-occipital fasciculus (IFOF). First, concurrent analyses revealed positive associations between the left AF and phonology, and between the bilateral IFOF and semantics in the acute - but not subacute - phase, supporting the dual-stream language model. Second, neuroplasticity analyses revealed a decrease in connection density of the bilateral AF - but not the IFOF - from the acute to the subacute phase, possibly reflecting post stroke white matter degeneration in areas adjacent to the lesion. Third, predictive analyses revealed no contribution of acute FBC measures to the prediction of later language outcomes over and above the initial language scores, suggesting no added value ofthe diffusion measures for languageprediction. Our study provides new insights on (changes in) connectivity of damaged and undamaged language pathways in patients with aphasia in the first months after stroke, as well as if/how such measures are related to language outcomes at different stages of recovery. Individual results are discussed in the light of current frameworks of language processing and aphasia recovery.

Advanced Diffusion MRI of Stroke Recovery

There is an urgent need for ways to improve our understanding of poststroke recovery to inform the development of novel rehabilitative interventions, and improve the clinical management of stroke patients. Supported by the notion that predictive information on poststroke recovery is embedded not only in the individual brain regions, but also the connections throughout the brain, majority of previous investigations have focused on the relationship between brain functional connections and post-stroke deficit and recovery. However, considering the fact that it is the static anatomical brain connections that constrain and facilitate the dynamic functional brain connections, the microstructures and structural connections of the brain may potentially be better alternatives to the functional MRI-based biomarkers of stroke recovery. This review, therefore, seeks to provide an overview of the basic concept and applications of two recently proposed advanced diffusion MRI techniques, namely lesion network mapping and fixel-based morphometry, that may be useful for the investigation of stroke recovery at the local and global levels of the brain. This review will also highlight the application of some of other emerging advanced diffusion MRI techniques that warrant further investigation in the context of stroke recovery research.

Revealing the Neuroimaging Mechanism of Acupuncture for Poststroke Aphasia: A Systematic Review

Background

Aphasia is a common symptom in stroke patients, presenting with the impairment of spontaneous speech, repetition, naming, auditory comprehension, reading, and writing function. Multiple rehabilitation methods have been suggested for the recovery of poststroke aphasia, including medication treatment, behavioral therapy, and stimulation approach. Acupuncture has been proven to have a beneficial effect on improving speech functions in repetition, oral speech, reading, comprehension, and writing ability. Neuroimaging technology provides a visualized way to explore cerebral neural activity, which helps reveal the therapeutic effect of acupuncture therapy. In this systematic review, we aim to reveal and summarize the neuroimaging mechanism of acupuncture therapy on poststroke aphasia to provide the foundation for further study.

Methods

Seven electronic databases were searched including PubMed, Web of Science, Embase, Cochrane Central Register of Controlled Trials, China National Knowledge Infrastructure, the Wanfang databases, and the Chinese Scientific Journal Database. After screening the studies according to the inclusion and exclusion criteria, we summarized the neuroimaging mechanism of acupuncture on poststroke aphasia, as well as the utilization of acupuncture therapy and the methodological characteristics.

Result

After searching, 885 articles were retrieved. After removing the literature studies, animal studies, and case reports, 16 studies were included in the final analysis. For the acupuncture type, 10 studies used manual acupuncture and 5 studies used electroacupuncture, while body acupuncture (10 studies), scalp acupuncture (7 studies), and tongue acupuncture (8 studies) were applied for poststroke aphasia patients. Based on blood oxygen level-dependent (BOLD) and diffusion tensor imaging (DTI) technologies, 4 neuroimaging analysis methods were used including amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), seed-based analysis, and independent component analysis (ICA). Two studies reported the instant acupuncture effect, and 14 studies reported the constant acupuncture's effect on poststroke aphasia patients. 5 studies analyzed the correlation between the neuroimaging outcomes and the clinical language scales.

Conclusion

In this systematic review, we found that the mechanism of acupuncture's effect might be associated with the activation and functional connectivity of language-related brain areas, such as brain areas around Broca's area and Wernicke's area in the left inferior temporal gyrus, supramarginal gyrus, middle frontal gyrus, and inferior frontal gyrus. However, these studies were still in the preliminary stage. Multicenter randomized controlled trials (RCT) with large sample sizes were needed to verify current evidence, as well as to explore deeply the neuroimaging mechanisms of acupuncture's effects.

The Progress of Functional Magnetic Resonance Imaging in Patients with Poststroke Aphasia

Aphasia after stroke is one of the common complications of cerebral infarction. Early diagnosis and treatment of aphasia after stroke is of great significance for the recovery of language function. At present, there are different views on the pathogenesis of aphasia after stroke. Functional magnetic resonance imaging (fMRI) can reflect the brain function, brain tissue metabolism, and the level of brain local blood flow. It has the advantages of noninvasive, high resolution and sensitivity, low price, and so on. It has been widely used in the study of sensory aphasia after stroke. This study focuses on the development of functional magnetic resonance imaging in patients with poststroke aphasia and summarizes the published studies on functional magnetic resonance imaging in patients with poststroke aphasia. Evidence acquisition: A literature search was conducted in PubMed, Hindawi, PLoS, IEEE, Wiley, ScienceDirect, Springer, EMBASE, and web of science, with the keywords of "stroke" and "Aphasia" and "functional magnetic resonance imaging", "RS fMRI", or "DTI", to review the research of functional magnetic resonance imaging in patients with aphasia after stroke. The results included clinical evaluation, diagnostic scale, and imaging analysis; the study design was a randomized controlled trial, case series and case report, and observational study. A total of 67 articles were identified in the first search and 43 after the second search. Based on the analysis of 43 selected articles, 19 articles were included, and 24 articles were excluded. The selected information is shown in Table 1. Eleven of them did not contain imaging-related data. Six articles are related review articles. Four studies were conducted on patients without poststroke aphasia. Three studies studied the effect of poststroke aphasia on patients' social participation.