Structural Connectivity Affecting Aspiration After Stroke

Dysphagia in primary progressive aphasia: Clinical predictors and neuroanatomical basis

BACKGROUND AND PURPOSE

Dysphagia is an important feature of neurodegenerative diseases and potentially life-threatening in primary progressive aphasia (PPA) but remains poorly characterized in these syndromes. We hypothesized that dysphagia would be more prevalent in nonfluent/agrammatic variant (nfv)PPA than other PPA syndromes, predicted by accompanying motor features, and associated with atrophy affecting regions implicated in swallowing control.

METHODS

In a retrospective case-control study at our tertiary referral centre, we recruited 56 patients with PPA (21 nfvPPA, 22 semantic variant [sv]PPA, 13 logopenic variant [lv]PPA). Using a pro forma based on caregiver surveys and clinical records, we documented dysphagia (present/absent) and associated, potentially predictive clinical, cognitive, and behavioural features. These were used to train a machine learning model. Patients' brain magnetic resonance imaging scans were assessed using voxel-based morphometry and region-of-interest analyses comparing differential atrophy profiles associated with dysphagia presence/absence.

RESULTS

Dysphagia was significantly more prevalent in nfvPPA (43% vs. 5% svPPA and no lvPPA). The machine learning model revealed a hierarchy of features predicting dysphagia in the nfvPPA group, with excellent classification accuracy (90.5%, 95% confidence interval = 77.9-100); the strongest predictor was orofacial apraxia, followed by older age, parkinsonism, more severe behavioural disturbance, and more severe cognitive impairment. Significant grey matter atrophy correlates of dysphagia in nfvPPA were identified in left middle frontal, right superior frontal, and right supramarginal gyri and right caudate.

CONCLUSIONS

Dysphagia is a common feature of nfvPPA, linked to underlying corticosubcortical network dysfunction. Clinicians should anticipate this symptom particularly in the context of other motor features and more severe disease.

Impact of the Alberta Stroke Program CT Score subregions on long-term functional outcomes in acute ischemic stroke: Results from two multicenter studies in China

Background and Objectives

The Alberta Stroke Program CT Score (ASPECTS) is a widely used rating system for assessing infarct extent and location. We aimed to investigate the prognostic value of ASPECTS subregions' involvement in the long-term functional outcomes of acute ischemic stroke (AIS).

Materials and Methods

Consecutive patients with AIS and anterior circulation large-vessel stenosis and occlusion between January 2019 and December 2020 were included. The ASPECTS score and subregion involvement for each patient was assessed using posttreatment magnetic resonance diffusion-weighted imaging. Univariate and multivariable regression analyses were conducted to identify subregions related to 3-month poor functional outcome (modified Rankin Scale scores, 3-6) in the reperfusion and medical therapy cohorts, respectively. In addition, prognostic efficiency between the region-based ASPECTS and ASPECTS score methods were compared using receiver operating characteristic curves and DeLong's test.

Results

A total of 365 patients (median age, 64 years; 70% men) were included, of whom 169 had poor outcomes. In the reperfusion therapy cohort, multivariable regression analyses revealed that the involvement of the left M4 cortical region in left-hemisphere stroke (adjusted odds ratio [aOR] 5.39, 95% confidence interval [CI] 1.53-19.02) and the involvement of the right M3 cortical region in right-hemisphere stroke (aOR 4.21, 95% CI 1.05-16.78) were independently associated with poor functional outcomes. In the medical therapy cohort, left-hemisphere stroke with left M5 cortical region (aOR 2.87, 95% CI 1.08-7.59) and caudate nucleus (aOR 3.14, 95% CI 1.00-9.85) involved and right-hemisphere stroke with right M3 cortical region (aOR 4.15, 95% CI 1.29-8.18) and internal capsule (aOR 3.94, 95% CI 1.22-12.78) affected were related to the increased risks of poststroke disability. In addition, region-based ASPECTS significantly improved the prognostic efficiency compared with the conventional ASPECTS score method.

Conclusion

The involvement of specific ASPECTS subregions depending on the affected hemisphere was associated with worse functional outcomes 3 months after stroke, and the critical subregion distribution varied by clinical management. Therefore, region-based ASPECTS could provide additional value in guiding individual decision making and neurological recovery in patients with AIS.

Disconnection-Based Prediction of Poststroke Dysphagia

BACKGROUND AND PURPOSE

Dysphagia is a common deficit after a stroke and is associated with serious complications. It is not yet fully clear which brain regions are directly related to swallowing. Previous lesion symptom mapping studies may have overlooked structural disconnections that could be responsible for poststroke dysphagia. Here, we aimed to predict and explain the relationship between poststroke dysphagia and the topologic distribution of structural disconnection via a multivariate predictive framework.

MATERIALS AND METHODS

We enrolled first-ever ischemic stroke patients classified as full per-oral nutrition (71 patients) and nonoral nutrition necessary (43 patients). After propensity score matching, 43 patients for each group were enrolled (full per-oral nutrition group with 17 women, 68 ± 15 years; nonoral nutrition necessary group with 13 women, 75 ± 11 years). The structural disconnectome was estimated by using the lesion segmented from acute phase diffusion-weighted images. The prediction of poststroke dysphagia by using the structural disconnectome and demographics was performed in a leave-one-out manner.

RESULTS

Using both direct and indirect disconnection matrices of the motor network, the disconnectome-based prediction model could predict poststroke dysphagia above the level of chance (accuracy = 68.6%, permutation P = .001). When combined with demographic data, the classification accuracy reached 72.1%. The edges connecting the right insula and left motor strip were the most informative in prediction.

CONCLUSIONS

Poststroke dysphagia could be predicted by using the structural disconnectome derived from acute phase diffusion-weighted images. Specifically, the direct and indirect disconnection within the motor network was the most informative in predicting poststroke dysphagia.

Construction of a Nomogram Prediction Model for Prognosis in Patients with Large Artery Occlusion-Acute Ischemic Stroke

BACKGROUND

Patients with large artery occlusion-acute ischemic stroke (LAO-AIS) can experience adverse outcomes, such as brain herniation due to complications. This study aimed to construct a nomogram prediction model for prognosis in patients with LAO-AIS in order to maximize the benefits for clinical patients.

METHODS

Retrospective analysis of 243 patients with LAO-AIS from January 2019 to January 2022 with medical history data and blood examination at admission. Univariate and multivariate analyses were conducted through binary logistic regression equation analysis, and a nomogram prediction model was constructed.

RESULTS

Results of this study showed that hyperlipidemia (odds ratio [OR] = 2.849, 95% confidence interval [CI] = 1.100-7.375, P = 0.031), right cerebral infarction (OR = 2.144, 95% CI = 1.106-4.156, P = 0.024), D-Dimer>500 ng/mL (OR = 2.891, 95% CI = 1.398-5.980, P = 0.004), and neutrophil-lymphocyte ratio >7.8 (OR = 2.149, 95% CI = 1.093-4.225, P = 0.027) were independent risk factors for poor early prognosis in patients with LAO-AIS. In addition, hypertension (OR = 1.947, 95% CI = 1.114-3.405, P = 0.019), hyperlipidemia (OR = 2.594, 95% CI = 1.281-5.252, P = 0.008), smoking (OR = 2.414, 95% CI = 1.368-4.261, P = 0.002), D-dimer>500 ng/mL (OR = 3.170, 95% CI = 1.533-6.553, P = 0.002), and neutrophil-lymphocyte ratio >7.8 (OR = 2.144, 95% CI = 1.231-3.735, P = 0.007) were independent risk factors for poor long-term prognosis. The early prognosis nomogram receiver operating characteristic curve area under the curve value was 0.688 for the training set and 0.805 for the validation set, which was highly differentiated. The mean error was 0.025 for the training set calibration curve and 0.016 for the validation set calibration curve. Both the training and validation set decision curve analyses indicated that the clinical benefit of the nomogram was significant. The long-term prognosis nomogram receiver operating characteristic curve area under the curve values was 0.697 for the training set and 0.735 for the validation set, showing high differentiation. The mean error was 0.041 for the training set calibration curve and 0.021 for the validation set calibration curve. Both of the training and validation set decision curve analyses demonstrated a substantial clinical benefit of the nomogram.

CONCLUSIONS

The nomogram prediction model based on admission history data and blood examination are easy-to-use tools that provide an accurate individualized prediction for patients with LAO-AIS and can assist in early clinical decisions and in obtaining an early prognosis.

Neural basis of dysphagia in stroke: A systematic review and meta-analysis

Objectives

Dysphagia is a major cause of stroke infection and death, and identification of structural and functional brain area changes associated with post-stroke dysphagia (PSD) can help in early screening and clinical intervention. Studies on PSD have reported numerous structural lesions and functional abnormalities in brain regions, and a systematic review is lacking. We aimed to integrate several neuroimaging studies to summarize the empirical evidence of neurological changes leading to PSD.

Methods

We conducted a systematic review of studies that used structural neuroimaging and functional neuroimaging approaches to explore structural and functional brain regions associated with swallowing after stroke, with additional evidence using a live activation likelihood estimation (ALE) approach.

Results

A total of 35 studies were included, including 20 studies with structural neuroimaging analysis, 14 studies with functional neuroimaging analysis and one study reporting results for both. The overall results suggest that structural lesions and functional abnormalities in the sensorimotor cortex, insula, cerebellum, cingulate gyrus, thalamus, basal ganglia, and associated white matter connections in individuals with stroke may contribute to dysphagia, and the ALE analysis provides additional evidence for structural lesions in the right lentiform nucleus and right thalamus and functional abnormalities in the left thalamus.

Conclusion

Our findings suggest that PSD is associated with neurological changes in brain regions such as sensorimotor cortex, insula, cerebellum, cingulate gyrus, thalamus, basal ganglia, and associated white matter connections. Adequate understanding of the mechanisms of neural changes in the post-stroke swallowing network may assist in clinical diagnosis and provide ideas for the development of new interventions in clinical practice.