Brain network topology influences response to intensive comprehensive aphasia treatment

Language and Attention Networks Have Distinct Roles in Language Improvement Following an Intensive Comprehensive Aphasia Program

BACKGROUND

Attention is known to play an important role in language, and attentional deficits have been associated with language impairments in people with aphasia (PWA). A prior study by our laboratory indicated that behavioral measures for PWA participating in an intensive comprehensive aphasia program (ICAP) clustered into 1 language and 1 attention-related factor, with each factor correlated with independent resting state functional connectivity (rsFC) networks. The present study includes additional attention measures and participants to better assess the relationship between attention, language, and rsFC.

METHODS

PWA participated in 120 hours of ICAP therapy over 4 weeks, between April 2018 and August 2022. Participants were evaluated with the Western Aphasia Battery and Conners' Continuous Performance Test, pre- and post-ICAP. rsFC data were collected during functional magnetic resonance imaging scans pre- and post-ICAP. Principal component analysis identified behavioral score associations pre- and post-ICAP. FC matrices and graph measures were evaluated for both PWA and healthy controls.

RESULTS

Twenty-three PWA participated (19 included in the final analysis). Data for 179 age and sex-matched healthy controls were taken from a public data set. The principal component analysis indicated 1 language and 2 attention-related principal components (PCs). The attention PCs were labeled Attention Accuracy and Attention Rate, in accordance with their best-associated behavioral measures. Importantly, each PC was associated with distinct networks, including higher-order networks, so-called because of their involvement in higher-order cognition. Notably, the language PC was significantly correlated with the ventral attention-memory-retrieval network rsFC (r=0.67, P=0.003) and the default mode-frontoparietal network rsFC (r=-0.56, P=0.019). Attention Accuracy was significantly correlated with cingulo-opercular-subcortical network rsFC (r=0.60, P=0.011). Attention Rate was significantly negatively correlated with visual-somatomotor network rsFC (r=-0.74, P=0.0007).

CONCLUSIONS

This study supports the notion that language improvements for PWAs participating in an ICAP are associated with distinct network changes. Importantly, these networks are not restricted to language networks but also include attention, and task-control networks.

A systematic review of Intensive Comprehensive Aphasia Programmes - who takes part, what is measured, what are the outcomes?

PURPOSE

This study synthesizes participant and outcome data from peer-reviewed Intensive Comprehensive Aphasia Programme (ICAP) studies.

METHODS

A systematic review was conducted following PRISMA guidelines. Study eligibility criteria were specified in relation to population, intervention, comparison, outcome, and design considerations. Data were extracted according to six research questions. Narrative synthesis was used.

RESULTS

Twenty-one studies were included covering 13 ICAPs (N = 485, aged 18-86 years, between 11 and 335 months post-stroke). Twenty-seven participant selection criteria were identified. Fifty-six outcome measures spanning the WHO-ICF were used, with the majority assessing the body function domain. Only eight studies employed an experimental design with data appropriate for analysis and synthesis. Risk of bias was noted across this sub-group. Participants improved in word-finding, communication, activity/participation, and communication-related quality of life, and maintained their gains; however, except for word finding, evidence of effect came from isolated studies. Factors influencing outcomes were rarely considered. Some drop-outs, missed sessions, and fatigue were noted. Some studies reported IPD alongside group analyses.

CONCLUSIONS

ICAP selection criteria need justification and should contribute to the understanding of candidacy for this treatment model. Rationalisation of ICAP treatment content and outcome measurement is required, spanning all WHO-ICF domains. Employment of the core outcome set for aphasia would enable data synthesis and facilitate comparisons between the ICAP and other therapy models.

Behavioral, Functional Imaging, and Neurophysiological Outcomes of Transcranial Direct Current Stimulation and Speech-Language Therapy in an Individual with Aphasia

Speech-language therapy (SLT) is the most effective technique to improve language performance in persons with aphasia. However, residual language impairments remain even after intensive SLT. Recent studies suggest that combining transcranial direct current stimulation (tDCS) with SLT may improve language performance in persons with aphasia. However, our understanding of how tDCS and SLT impact brain and behavioral relation in aphasia is poorly understood. We investigated the impact of tDCS and SLT on a behavioral measure of scripted conversation and on functional connectivity assessed with multiple methods, both resting-state functional magnetic resonance imaging (rs-fMRI) and resting-state electroencephalography (rs-EEG). An individual with aphasia received 15 sessions of 20-min cathodal tDCS to the right angular gyrus concurrent with 40 min of SLT. Performance during scripted conversation was measured three times at baseline, twice immediately post-treatment, and at 4- and 8-weeks post-treatment. rs-fMRI was measured pre-and post-3-weeks of treatment. rs-EEG was measured on treatment days 1, 5, 10, and 15. Results show that both communication performance and left hemisphere functional connectivity may improve after concurrent tDCS and SLT. Results are in line with aphasia models of language recovery that posit a beneficial role of left hemisphere perilesional areas in language recovery.

Defining Trajectories of Linguistic, Cognitive-Communicative, and Quality of Life Outcomes in Aphasia: Longitudinal Observational Study Protocol

Objective

To describe the trajectories of linguistic, cognitive-communicative, and health-related quality of life (HRQOL) outcomes after stroke in persons with aphasia.

Design

Longitudinal observational study from inpatient rehabilitation to 18 months after stroke.

Setting

Four US mid-west inpatient rehabilitation facilities (IRFs).

Participants

We plan to recruit 400 adult (older than 21 years) English speakers who meet the following inclusion criteria: (1) Diagnosis of aphasia after a left-hemisphere infarct confirmed by CT scan or magnetic resonance imaging (MRI); (2) first admission for inpatient rehabilitation due to a neurologic event; and (3) sufficient cognitive capacity to provide informed consent and participate in testing. Exclusion criteria include any neurologic condition other than stroke that could affect language, cognition or speech, such as Parkinson's disease, Alzheimer's disease, traumatic brain injury, or the presence of right-hemisphere lesions.

Interventions

Not applicable.

Main Outcome Measures

Subjects are administered a test battery of linguistic, cognitive-communicative, and HRQOL measures. Linguistic measures include the Western Aphasia Battery-Revised and the Apraxia of Speech Rating Scale. Cognitive-communicative measures include the Communication Participation Item Bank, Connor's Continuous Performance Test-3, the Communication Confidence Rating Scale for Aphasia, the Communication Effectiveness Index, the Neurological Quality of Life measurement system (Neuro-QoL) Communication short form, and the Neuro-QoL Cognitive Function short form. HRQOL measures include the 39-item Stroke & Aphasia Quality of Life Scale, Neuro-QoL Fatigue, Sleep Disturbance, Depression, Ability to Participate in Social Roles & Activities, and Satisfaction with Social Roles & Activities tests, and the Patient-Reported Outcome Measurement and Information System 10-item Global Health short form. The test battery is administered initially during inpatient rehabilitation, and at 3-, 6-, 12-, and 18-months post-IRF discharge. Biomarker samples are collected via saliva samples at admission and a subgroup of participants also undergo resting state fMRI scans.

Results

Not applicable.

Conclusions

This longitudinal observational study will develop trajectory models for recovery of clinically relevant linguistic, cognitive-communicative, and quality of life outcomes over 18 months after inpatient rehabilitation. Models will identify individual differences in the patterns of recovery based on variations in personal, genetic, imaging, and therapy characteristics. The resulting models will provide an unparalleled representation of recovery from aphasia resulting from stroke. This improved understanding of recovery will enable clinicians to better tailor and plan rehabilitation therapies to individual patient's needs.

Resting-state brain network connectivity is an independent predictor of responsiveness to language therapy in chronic post-stroke aphasia

Post-stroke aphasia recovery, especially in the chronic phase, is challenging to predict. Functional integrity of the brain and brain network topology have been suggested as biomarkers of language recovery. This study sought to investigate functional connectivity in four predefined brain networks (i.e., language, default mode, dorsal attention, and salience networks), in relation to aphasia severity and response to language therapy. Thirty patients with chronic post-stroke aphasia were recruited and received a treatment targeting word finding. Structural and functional brain scans were acquired at baseline and resting state functional connectivity for each network was calculated. Additionally, graph measures quantifying network properties were calculated for each network. These included global efficiency for all networks and average strength and clustering coefficient for the language network. Linear mixed effects models showed that mean functional connectivity in the default mode, dorsal attention, and salience networks as well as graph measures of all four networks are independent predictors of response to therapy. While greater mean functional connectivity and global efficiency of the dorsal attention and salience networks predicted greater treatment response, greater mean functional connectivity and global efficiency in the default mode network predicted poorer treatment response. Results for the language network were more nuanced with more efficient network configurations (as reflected in graph measures), but not mean functional connectivity, predicting greater treatment response. These findings highlight the prognostic value of resting-state functional connectivity in chronic treatment-induced aphasia recovery.

Methodologies for task-fMRI based prognostic biomarkers in response to aphasia treatment

With the diversity in aphasia coupled with diminished gains at the chronic phase, it is imperative to deliver effective rehabilitation plans. Treatment outcomes have therefore been predicted using lesion-to-symptom mapping, but this method lacks holistic functional information about the language-network. This study, therefore, aims to develop whole-brain task-fMRI multivariate analysis to neurobiologically inspect lesion impacts on the language-network and predict behavioral outcomes in persons with aphasia (PWA) undergoing language therapy. In 14 chronic PWA, semantic fluency task-fMRI and behavioral measures were collected to develop prediction methodologies for post-treatment outcomes. Then, a recently developed imaging-based multivariate method to predict behavior (i.e., LESYMAP) was optimized to intake whole-brain task-fMRI data, and systematically tested for reliability with mass univariate methods. We also accounted for lesion size in both methods. Results showed that both mass univariate and multivariate methods identified unique biomarkers for semantic fluency improvements from baseline to 2-weeks post-treatment. Additionally, both methods demonstrated reliable spatial overlap in task-specific areas including the right middle frontal gyrus when identifying biomarkers of language discourse. Thus whole-brain task-fMRI multivariate analysis has the potential to identify functionally meaningful prognostic biomarkers even for relatively small sample sizes. In sum, our task-fMRI based multivariate approach holistically estimates post-treatment response for both word and sentence production and may serve as a complementary tool to mass univariate analysis in developing brain-behavior relationships for improved personalization of aphasia rehabilitation regimens.

Predictors of Therapy Response in Chronic Aphasia: Building a Foundation for Personalized Aphasia Therapy

Chronic aphasia, a devastating impairment of language, affects up to a third of stroke survivors. Speech and language therapy has consistently been shown to improve language function in prior clinical trials, but few clinicially applicable predictors of individual therapy response have been identified to date. Consequently, clinicians struggle substantially with prognostication in the clinical management of aphasia. A rising prevalence of aphasia, in particular in younger populations, has emphasized the increasing demand for a personalized approach to aphasia therapy, that is, therapy aimed at maximizing language recovery of each individual with reference to evidence-based clinical recommendations. In this narrative review, we discuss the current state of the literature with respect to commonly studied predictors of therapy response in aphasia. In particular, we focus our discussion on biographical, neuropsychological, and neurobiological predictors, and emphasize limitations of the literature, summarize consistent findings, and consider how the research field can better support the development of personalized aphasia therapy. In conclusion, a review of the literature indicates that future research efforts should aim to recruit larger samples of people with aphasia, including by establishing multisite aphasia research centers.

Behavioral interventions for poststroke aphasia

There is a long history of behavioral interventions for poststroke aphasia with hundreds of studies supporting the benefits of aphasia treatment. However, interventions for aphasia are complex with many interacting components, and no one treatment is appropriate for all persons with aphasia. We present a novel, simple framework for classifying aphasia interventions. The framework is incorporated within the overarching International Classification of Functioning, Disability, and Health (ICF) model and is consistent with the commonly-held definition that aphasia is a multimodality disorder that impairs, in varying degrees, the understanding and expression of both oral and written language modalities. Furthermore, within the language impairment level, it distinguishes between the linguistic areas of phonology, semantics, and syntax that may be impaired individually or in combination. We define the terminology of the proposed framework and then categorize some common examples of behavioral interventions for post-stroke aphasia. We describe some of these interventions in greater detail to illustrate the extensive toolbox of evidence-based treatments for aphasia. We address some key issues that clinicians, usually speech-language pathologists, consider when selecting interventions for their specific patients with aphasia, including dose. Finally, we address various models of service delivery for persons with aphasia such as Intensive Comprehensive Aphasia Programs (ICAPs) and Aphasia Centers.

The role of disrupted functional connectivity in aphasia

Language is one of the most complex and specialized higher cognitive processes. Brain damage to the distributed, primarily left-lateralized language network can result in aphasia, a neurologic disorder characterized by receptive and/or expressive deficits in spoken and/or written language. Most often, aphasia is the consequence of stroke-termed poststroke aphasia (PSA)-yet, aphasia can also manifest due to neurodegenerative disease, specifically, a disorder called primary progressive aphasia (PPA). In recent years, functional connectivity neuroimaging studies have provided emerging evidence supporting theories regarding the relationships between language impairments, structural brain damage, and functional network properties in these two disorders. This chapter reviews the current evidence for the "network phenotype of stroke injury" hypothesis (Siegel et al., 2016) as it pertains to PSA and the "network degeneration hypothesis" (Seeley et al., 2009) as it pertains to PPA. Methodologic considerations for functional connectivity studies, limitations of the current functional connectivity literature in aphasia, and future directions are also discussed.

Disrupted Brain Connectivity Networks in Aphasia Revealed by Resting-State fMRI

Aphasia is characterized by the disability of spontaneous conversation, listening, understanding, retelling, naming, reading, or writing. However, the neural mechanisms of language damage after stroke are still under discussion. This study aimed to investigate the global and nodal characterization of the functional networks in patients with aphasic stroke based on resting-state functional MRI (fMRI). Twenty-four right-handed patients with aphasia after stroke and 19 healthy controls (HC) underwent a 3-TfMRI scan. A whole-brain large-scale functional connectivity network was then constructed based on Power's atlas of 264 functional regions of interest, and the global and nodal topological properties of these networks were analyzed using graph theory approaches. The results showed that patients with aphasia had decreased in small-worldness (sigma), normalized clustering coefficient (gamma), and local efficiency (E_loc) values. Furthermore, E_loc was positively correlated with language ability, retelling, naming, and listening comprehension in patients with aphasia. Patients with aphasia also had decreased nodal degree and decreased nodal efficiency in the left postcentral gyrus, central opercular cortex, and insular cortex. Our results suggest that the global and local topology attributes were altered by injury in patients with aphasic stroke. We argue that the local efficiency of brain networks might be used as a potential indicator of basic speech function in patients with aphasia.

Novel Advances to Post-Stroke Aphasia Pharmacology and Rehabilitation

Aphasia is one of the most common clinical features of functional impairment after a stroke. Approximately 21–40% of stroke patients sustain permanent aphasia, which progressively worsens one’s quality of life and rehabilitation outcomes. Post-stroke aphasia treatment strategies include speech language therapies, cognitive neurorehabilitation, telerehabilitation, computer-based management, experimental pharmacotherapy, and physical medicine. This review focuses on current evidence of the effectiveness of impairment-based aphasia therapies and communication-based therapies (as well as the timing and optimal treatment intensities for these interventions). Moreover, we present specific interventions, such as constraint-induced aphasia therapy (CIAT) and melodic intonation therapy (MIT). Accumulated data suggest that using transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) is safe and can be used to modulate cortical excitability. Therefore, we review clinical studies that present TMS and tDCS as (possible) promising therapies in speech and language recovery, stimulating neuroplasticity. Several drugs have been used in aphasia pharmacotherapy, but evidence from clinical studies suggest that only nootropic agents, donepezil and memantine, may improve the prognosis of aphasia. This article is an overview on the current state of knowledge related to post-stroke aphasia pharmacology, rehabilitation, and future trends.

Increased modularity of the resting-state network in children with nonsyndromic cleft lip and palate after speech rehabilitation

INTRODUCTION

Speech therapy is the primary management followed the physical management through surgery for children with nonsyndromic cleft lip and palate (NSCLP). However, the topological pattern of the resting-state network after rehabilitation remains poorly understood. We aimed to explore the functional topological pattern of children with NSCLP after speech rehabilitation compared with healthy controls.

METHODS

We examined 28 children with NSCLP after speech rehabilitation (age = 10.0 ± 2.3 years) and 28 healthy controls for resting-state functional MRI. We calculated functional connections and the degree strength, betweenness centrality, network clustering coefficient (Cp), characteristic path length (Lp), global network efficiency (Eg), local network efficiency (Eloc), modularity index (Q), module number, and participation coefficient for the between-group differences using two-sample t tests (corrected p < .05). Additionally, we performed a correlation analysis between the Chinese language clear degree scale (CLCDS) scores and topological properties in children with NSCLP.

RESULTS

We detected significant between-group differences in the areas under the curve (AUCs) of degree strength and betweenness centrality in language-related brain regions. There were no significant between-group differences in module number, participation coefficient, Cp, Lp, Eg, or Eloc. However, the Q (density: 0.05-0.30) and Q^AUC (t = 2.46, p = .02) showed significant between-group differences. Additionally, there was no significant correlation between topological properties of statistical between-group differences and CLCDS scores.

CONCLUSIONS

Although nodal metric differences existed in the language-related brain regions, the children with NSCLP after speech rehabilitation had similar global network properties, module numbers, and participation coefficient, but increased modularity. Our results suggested that children with NSCLP achieved speech rehabilitation through function specialization in the language-related brain regions. The resting-state topology pattern could be of substantive neurobiological importance and potential imaging biomarkers for speech rehabilitation.

Developments in the application of Intensive Comprehensive Aphasia Programs: an international survey of practice

PURPOSE

Intensive Comprehensive Aphasia Programs (ICAPs) were first described in 2013 with an international survey documenting 12 unique programs. ICAPs involve high dose intervention delivered in both group and individual settings, targeting communication across impairment, functioning, participation, and contextual domains. In this study, we aimed to investigate international growth in ICAPs.

MATERIALS AND METHODS

We developed a 43-item questionnaire expanding on the original 2013 version to investigate program modifications, activities, protocolised therapies, software and apps, and family involvement. The survey was disseminated to aphasia clinicians and researchers internationally (November 2019-February 2020).

RESULTS

Thirty-nine unique respondents completed the survey from nine countries. Twenty-one met the criteria for an ICAP or modified ICAP (mICAP): 14 ICAPs; 7 mICAPs, and 13 of these were new programs. ICAPs differed from mICAPs with greater emphasis on group sessions, use of technology, total communication, advocacy, and art activities. A large range of protocolised therapies were used across programs. An increased focus on mood and psychosocial well-being was observed compared to the 2013 survey.

CONCLUSIONS

The number and comprehensiveness of ICAPs has grown since 2013 with development of modified versions. Future research should focus on comparative efficacy of ICAPs/mICAPs and other forms of aphasia interventions and factors underpinning growth and sustainability.Implications for RehabilitationClinicians who coordinate or are considering commencing an ICAP in future can use these results to consider the design of their program.Coordinators should carefully consider the components of their ICAPs and advise consumers whether they meet the definition of an ICAP or a mICAP.With the increasing number of ICAPs across the globe, clinicians commencing an ICAP may wish to contact existing ICAPs within their country for advice.Program sustainability may be challenging and these results provide an indication of some of the key challenges coordinators may face.

Prediction of Cognitive Recovery After Stroke: The Value of Diffusion-Weighted Imaging-Based Measures of Brain Connectivity

BACKGROUND AND PURPOSE

Prediction of long-term recovery of a poststroke cognitive disorder (PSCD) is currently inaccurate. We assessed whether diffusion-weighted imaging (DWI)-based measures of brain connectivity predict cognitive recovery 1 year after stroke in patients with PSCD in addition to conventional clinical, neuropsychological, and imaging variables.

METHODS

This prospective monocenter cohort study included 217 consecutive patients with a clinical diagnosis of ischemic stroke, aged ≥50 years, and Montreal Cognitive Assessment score below 26 during hospitalization. Five weeks after stroke, patients underwent DWI magnetic resonance imaging. Neuropsychological assessment was performed 5 weeks and 1 year after stroke and was used to classify PSCD as absent, modest, or marked. Cognitive recovery was operationalized as a shift to a better PSCD category over time. We evaluated 4 DWI-based measures of brain connectivity: global network efficiency and mean connectivity strength, both weighted for mean diffusivity and fractional anisotropy. Conventional predictors were age, sex, level of education, clinical stroke characteristics, neuropsychological variables, and magnetic resonance imaging findings (eg, infarct size). DWI-based measures of brain connectivity were added to a multivariable model to assess additive predictive value.

RESULTS

Of 135 patients (mean age, 71 years; 95 men [70%]) with PSCD 5 weeks after ischemic stroke, 41 (30%) showed cognitive recovery. Three of 4 brain connectivity measures met the predefined threshold of P<0.1 in univariable regression analysis. There was no added value of these measures to a multivariable model that included level of education and infarct size as significant predictors of cognitive recovery.

CONCLUSIONS

Current DWI-based measures of brain connectivity appear to predict recovery of PSCD but at present have no added value over conventional predictors.

Predicting language recovery in post-stroke aphasia using behavior and functional MRI

Language outcomes after speech and language therapy in post-stroke aphasia are challenging to predict. This study examines behavioral language measures and resting state fMRI (rsfMRI) as predictors of treatment outcome. Fifty-seven patients with chronic aphasia were recruited and treated for one of three aphasia impairments: anomia, agrammatism, or dysgraphia. Treatment effect was measured by performance on a treatment-specific language measure, assessed before and after three months of language therapy. Each patient also underwent an additional 27 language assessments and a rsfMRI scan at baseline. Patient scans were decomposed into 20 components by group independent component analysis, and the fractional amplitude of low-frequency fluctuations (fALFF) was calculated for each component time series. Post-treatment performance was modelled with elastic net regression, using pre-treatment performance and either behavioral language measures or fALFF imaging predictors. Analysis showed strong performance for behavioral measures in anomia (R² = 0.948, n = 28) and for fALFF predictors in agrammatism (R² = 0.876, n = 11) and dysgraphia (R² = 0.822, n = 18). Models of language outcomes after treatment trained using rsfMRI features may outperform models trained using behavioral language measures in some patient populations. This suggests that rsfMRI may have prognostic value for aphasia therapy outcomes.

Implementation Cost Analysis of an Intensive Comprehensive Aphasia Program

OBJECTIVE

To identify and measure the costs of implementing an intensive comprehensive aphasia program (ICAP).

DESIGN

Retrospective cost analysis of a clinical ICAP. Cost inputs were gathered directly from the provider of the ICAP. We performed several sensitivity analyses to examine major cost drivers and to separate start-up costs from operating costs.

SETTING

Urban rehabilitation hospital.

PARTICIPANTS

Adults with aphasia.

MAIN OUTCOME MEASURES

Total implementation cost to the provider.

RESULTS

Implementation cost of running the ICAP for the first time was $133,644 for a cohort of 8 participants with aphasia. Break-even charges per participant ranged from $15,278 for 10 participants to $19,700 for 6 participants. After accounting for start-up costs and efficiencies gained, the fourth and subsequent programs were estimated to cost $84,855 each. The majority of the costs were personnel costs, and the cost of the speech language pathologist's time was the main cost driver in this analysis.

CONCLUSIONS

Initial implementation costs are high compared with subsequent programs. Future work should examine effectiveness of an ICAP compared with other treatments to determine its cost-effectiveness.

Path-dependent connectivity, not modularity, consistently predicts controllability of structural brain networks

The human brain displays rich communication dynamics that are thought to be particularly well-reflected in its marked community structure. Yet, the precise relationship between community structure in structural brain networks and the communication dynamics that can emerge therefrom is not well understood. In addition to offering insight into the structure-function relationship of networked systems, such an understanding is a critical step toward the ability to manipulate the brain's large-scale dynamical activity in a targeted manner. We investigate the role of community structure in the controllability of structural brain networks. At the region level, we find that certain network measures of community structure are sometimes statistically correlated with measures of linear controllability. However, we then demonstrate that this relationship depends on the distribution of network edge weights. We highlight the complexity of the relationship between community structure and controllability by performing numerical simulations using canonical graph models with varying mesoscale architectures and edge weight distributions. Finally, we demonstrate that weighted subgraph centrality, a measure rooted in the graph spectrum, and which captures higher order graph architecture, is a stronger and more consistent predictor of controllability. Our study contributes to an understanding of how the brain's diverse mesoscale structure supports transient communication dynamics.

Pre-treatment graph measures of a functional semantic network are associated with naming therapy outcomes in chronic aphasia

Naming treatment outcomes in post-stroke aphasia are variable and the factors underlying this variability are incompletely understood. In this study, 26 patients with chronic aphasia completed a semantic judgment fMRI task before receiving up to 12 weeks of naming treatment. Global (i.e., network-wide) and local (i.e., regional) graph theoretic measures of pre-treatment functional connectivity were analyzed to identify differences between patients who responded most and least favorably to treatment (i.e., responders and nonresponders) and determine if network measures predicted naming improvements. Responders had higher levels of global integration (i.e., average network strength and global efficiency) than nonresponders, and these measures predicted treatment effects after controlling for lesion volume and age. Group differences in local measures were identified in several regions associated with a variety of cognitive functions. These results suggest there is a meaningful and possibly prognostically-informative relationship between patients' functional network properties and their response to naming therapy.

Extent to Which Network Hubs Are Affected by Ischemic Stroke Predicts Cognitive Recovery

Background and Purpose—

It is uncertain what determines the potential for cognitive recovery after ischemic stroke. The extent to which strategic areas of the brain network, so-called hubs, are affected by the infarct could be a key factor. We developed a lesion impact score, which estimates the damage to network hubs by integrating information on infarct size with healthy brain network topology. We verified whether the lesion impact score indeed reflects global network disturbances in patients and assessed if it could predict cognitive recovery.

Methods—

Seventy-five ischemic stroke patients without signs of a prestroke cognitive disorder were included, all with evidence of a cognitive disorder during hospitalization. A brain magnetic resonance imaging and neuropsychological assessment were performed 5 weeks (±1 week) after stroke. Neuropsychological testing was repeated after 1 year to assess cognitive recovery. Brain networks were reconstructed from diffusion-weighted data and consisted of 90 gray matter regions (ie, network nodes). A standard brain network map, indicating the hub-score of each node, was obtained from network data of 44 cognitively healthy adults. For each patient, we calculated the lesion impact score by multiplying the percentage of node volume affected by the infarct with the node’s corresponding hub-score. The patients’ maximum lesion impact score was used as outcome predictor.

Results—

A higher lesion impact score in patients, indicating an increasing infarct size in nodes with a higher hub-score, was related to lower global brain network efficiency (β=−0.528 [−0.776 to −0.277]; P <0.001), independent of age, brain volume, infarct volume, and white matter hyperintensity severity. A lower lesion impact score, however, was an independent predictor of cognitive recovery 1 year after stroke (odds ratio=0.434 [0.193–0.978]; P =0.044).

Conclusions—

We introduced a lesion impact score that combines information on infarct size and network topology to predict long-term recovery after stroke. This score can potentially be used in a clinical setting, also without availability of high-resolution diffusion-weighted magnetic resonance imaging.