Age- and sex-related changes in motor functions: a comprehensive assessment and component analysis.

Age-related motor impairments often cause caregiver dependency or even hospitalization. However, comprehensive investigations of the different motor abilities and the changes thereof across the adult lifespan remain sparse. We, therefore, extensively assessed essential basic and complex motor functions in 444 healthy adults covering a wide age range (range 21 to 88 years). Basic motor functions, here defined as simple isolated single or repetitive movements in one direction, were assessed by means of maximum grip strength (GS) and maximum finger-tapping frequency (FTF). Complex motor functions, comprising composite sequential movements involving both proximal and distal joints/muscle groups, were evaluated with the Action Research Arm Test (ARAT), the Jebsen-Taylor Hand Function Test (JTT), and the Purdue Pegboard Test. Men achieved higher scores than women concerning GS and FTF, whereas women stacked more pins per time than men during the Purdue Pegboard Test. There was no significant sex effect regarding JTT. We observed a significant but task-specific reduction of basic and complex motor performance scores across the adult lifespan. Linear regression analyses significantly predicted the participants' ages based on motor performance scores (R2 = 0.502). Of note, the ratio between the left- and right-hand performance remained stable across ages for all tests. Principal Component Analysis (PCA) revealed three motor components across all tests that represented dexterity, force, and speed. These components were consistently present in young (21-40 years), middle-aged (41-60 years), and older (61-88 years) adults, as well as in women and men. Based on the three motor components, K-means clustering analysis differentiated high- and low-performing participants across the adult life span. The rich motor data set of 444 healthy participants revealed age- and sex-dependent changes in essential basic and complex motor functions. Notably, the comprehensive assessment allowed for generating robust motor components across the adult lifespan. Our data may serve as a reference for future studies of healthy subjects and patients with motor deficits. Moreover, these findings emphasize the importance of comprehensively assessing different motor functions, including dexterity, force, and speed, to characterize human motor abilities and their age-related decline.

Status epilepticus in patients with brain tumors and metastases: A multicenter cohort study of 208 patients and literature review.

OBJECTIVE: Brain tumors and metastases account for approximately 10% of all status epilepticus (SE) cases. This study described the clinical characteristics, treatment, and short- and long-term outcomes of this population. METHODS: This retrospective, multi-center cohort study analyzed all brain tumor patients treated for SE at the university hospitals of Frankfurt and Marburg between 2011 and 2017. RESULTS: The 208 patients (mean 61.5 ± 14.7 years of age; 51% male) presented with adult-type diffuse gliomas (55.8%), metastatic entities (25.5%), intracranial extradural tumors (14.4%), or other tumors (4.3%). The radiological criteria for tumor progression were evidenced in 128 (61.5%) patients, while 57 (27.4%) were newly diagnosed with tumor at admission and 113 (54.3%) had refractory SE. The mean hospital length of stay (LOS) was 14.8 days (median 12.0, range 1-57), 171 (82.2%) patients required intensive care (mean LOS 8.9 days, median 5, range 1-46), and 44 (21.2%) were administered mechanical ventilation. All patients exhibited significant functional status decline (modified Rankin Scale) post-SE at discharge (p < 0.001). Mortality at discharge was 17.3% (n = 36), with the greatest occurring in patients with metastatic disease (26.4%, p = 0.031) and those that met the radiological criteria for tumor progression (25%, p < 0.001). Long-term mortality at one year (65.9%) was highest in those diagnosed with adult-type diffuse gliomas (68.1%) and metastatic disease (79.2%). Refractory status epilepticus cases showed lower survival rates than non-refractory SE patients (log-rank p = 0.02) and those with signs of tumor progression (log-rank p = 0.001). CONCLUSIONS: SE occurrence contributed to a decline in functional status in all cases, regardless of tumor type, tumor progression status, and SE refractoriness, while long-term mortality was increased in those with malignant tumor entities, tumor progressions, and refractory SE. SE prevention may preserve functional status and improve survival in individuals with brain tumors.

Behavioral and neuroanatomical correlates of facial emotion processing in post-stroke depression.

BACKGROUND: Emotion processing deficits are known to accompany depressive symptoms and are often seen in stroke patients. Little is known about the influence of post-stroke depressive (PSD) symptoms and specific brain lesions on altered emotion processing abilities and how these phenomena develop over time. This potential relationship may impact post-stroke rehabilitation of neurological and psychosocial function. To address this scientific gap, we investigated the relationship between PSD symptoms and emotion processing abilities in a longitudinal study design from the first days post-stroke into the early chronic phase. METHODS: Twenty-six ischemic stroke patients performed an emotion processing task on videos with emotional faces ('happy,' 'sad,' 'anger,' 'fear,' and 'neutral') at different intensity levels (20%, 40%, 60%, 80%, 100%). Recognition accuracies and response times were measured, as well as scores of depressive symptoms (Montgomery-Åsberg Depression Rating Scale). Twenty-eight healthy participants matched in age and sex were included as a control group. Whole-brain support-vector regression lesion-symptom mapping (SVR-LSM) analyses were performed to investigate whether specific lesion locations were associated with the recognition accuracy of specific emotion categories. RESULTS: Stroke patients performed worse in overall recognition accuracy compared to controls, specifically in the recognition of happy, sad, and fearful faces. Notably, more depressed stroke patients showed an increased processing towards specific negative emotions, as they responded significantly faster to angry faces and recognized sad faces of low intensities significantly more accurately. These effects obtained for the first days after stroke partly persisted to follow-up assessment several months later. SVR-LSM analyses revealed that inferior and middle frontal regions (IFG/MFG) and insula and putamen were associated with emotion-recognition deficits in stroke. Specifically, recognizing happy facial expressions was influenced by lesions affecting the anterior insula, putamen, IFG, MFG, orbitofrontal cortex, and rolandic operculum. Lesions in the posterior insula, rolandic operculum, and MFG were also related to reduced recognition accuracy of fearful facial expressions, whereas recognition deficits of sad faces were associated with frontal pole, IFG, and MFG damage. CONCLUSION: PSD symptoms facilitate processing negative emotional stimuli, specifically angry and sad facial expressions. The recognition accuracy of different emotional categories was linked to brain lesions in emotion-related processing circuits, including insula, basal ganglia, IFG, and MFG. In summary, our study provides support for psychosocial and neural factors underlying emotional processing after stroke, contributing to the pathophysiology of PSD.

[Quality indicators artificial intelligence]. / Qualitätsindikatoren künstliche Intelligenz.

The ability of some artificial intelligence (AI) systems to autonomously evolve and the sometimes very limited possibilities to comprehend their decision-making processes present new challenges to our legal system. At a European level this has led to reform efforts, of which the proposal for a European AI regulation promises to close regulatory gaps in existing product safety law through cross-sectoral AI-specific safety requirements. A prerequisite, however, would be that the EU legislator does not only avoid duplications and contradictions with existing safety requirements but also refrains from imposing exaggerated and unattainable demands. If this were to be taken into consideration, the new safety requirements could also be used to specify the undefined standard of care in liability law. Nevertheless, challenges in the context of provability continue to remain unresolved, posing a risk of rendering the legal protection efforts of the aggrieved party ineffective. It remains to be seen whether the EU legislator will address this need for reform with the recently proposed reform of product liability law by the Commission.

Neuroanatomy of post-stroke depression: the association between symptom clusters and lesion location.

Post-stroke depression affects about 30% of stroke patients and often hampers functional recovery. The diagnosis of depression encompasses heterogeneous symptoms at emotional, motivational, cognitive, behavioural or somatic levels. Evidence indicates that depression is caused by disruption of bio-aminergic fibre tracts between prefrontal and limbic or striatal brain regions comprising different functional networks. Voxel-based lesion-symptom mapping studies reported discrepant findings regarding the association between infarct locations and depression. Inconsistencies may be due to the usage of sum scores, thereby mixing different symptoms of depression. In this cross-sectional study, we used multivariate support vector regression for lesion-symptom mapping to identify regions significantly involved in distinct depressive symptom domains and global depression. MRI lesion data were included from 200 patients with acute first-ever ischaemic stroke (mean 0.9 ± 1.5 days of post-stroke). The Montgomery-Åsberg Depression Rating interview assessed depression severity in five symptom domains encompassing motivational, emotional and cognitive symptoms deficits, anxiety and somatic symptoms and was examined 8.4 days of post-stroke (±4.3). We found that global depression severity, irrespective of individual symptom domains, was primarily linked to right hemispheric lesions in the dorsolateral prefrontal cortex and inferior frontal gyrus. In contrast, when considering distinct symptom domains individually, the analyses yielded much more sensitive results in regions where the correlations with the global depression score yielded no effects. Accordingly, motivational deficits were associated with lesions in orbitofrontal cortex, dorsolateral prefrontal cortex, pre- and post-central gyri and basal ganglia, including putamen and pallidum. Lesions affecting the dorsal thalamus, anterior insula and somatosensory cortex were significantly associated with emotional symptoms such as sadness. Damage to the dorsolateral prefrontal cortex was associated with concentration deficits, cognitive symptoms of guilt and self-reproach. Furthermore, somatic symptoms, including loss of appetite and sleep disturbances, were linked to the insula, parietal operculum and amygdala lesions. Likewise, anxiety was associated with lesions impacting the central operculum, insula and inferior frontal gyrus. Interestingly, symptoms of anxiety were exclusively left hemispheric, whereas the lesion-symptom associations of the other domains were lateralized to the right hemisphere. In conclusion, this large-scale study shows that in acute stroke patients, differential post-stroke depression symptom domains are associated with specific structural correlates. Our findings extend existing concepts on the neural underpinnings of depressive symptoms, indicating that differential lesion patterns lead to distinct depressive symptoms in the first weeks of post-stroke. These findings may facilitate the development of personalized treatments to improve post-stroke rehabilitation.

Fronto-striatal dynamic connectivity is linked to dopaminergic motor response in Parkinson's disease.

INTRODUCTION: Differences in dopaminergic motor response in Parkinson's disease (PD) patients can be related to PD subtypes, and previous fMRI studies associated dopaminergic motor response with corticostriatal functional connectivity. While traditional fMRI analyses have assessed the mean connectivity between regions of interest, an important aspect driving dopaminergic response might lie in the temporal dynamics in corticostriatal connections. METHODS: This study aims to determine if altered resting-state dynamic functional network connectivity (DFC) is associated with dopaminergic motor response. To test this, static and DFC were assessed in 32 PD patients and 18 healthy controls (HC). Patients were grouped as low and high responders using a median split of their dopaminergic motor response. RESULTS: Patients featuring a high dopaminergic motor response were observed to spend more time in a regionally integrated state compared to HC. Furthermore, DFC between the anterior midcingulate cortex/dorsal anterior cingulate cortex (aMCC/dACC) and putamen was lower in low responders during a more segregated state and correlated with dopaminergic motor response. CONCLUSION: The findings of this study revealed that temporal dynamics of fronto-striatal connectivity are associated with clinically relevant information, which may be considered when assessing functional connectivity between regions involved in motor initiation.

Interhemispheric Structural Connectivity Underlies Motor Recovery after Stroke.

OBJECTIVE: Although ample evidence highlights that the ipsilesional corticospinal tract (CST) plays a crucial role in motor recovery after stroke, studies on cortico-cortical motor connections remain scarce and provide inconclusive results. Given their unique potential to serve as structural reserve enabling motor network reorganization, the question arises whether cortico-cortical connections may facilitate motor control depending on CST damage. METHODS: Diffusion spectrum imaging (DSI) and a novel compartment-wise analysis approach were used to quantify structural connectivity between bilateral cortical core motor regions in chronic stroke patients. Basal and complex motor control were differentially assessed. RESULTS: Both basal and complex motor performance were correlated with structural connectivity between bilateral premotor areas and ipsilesional primary motor cortex (M1) as well as interhemispheric M1 to M1 connectivity. Whereas complex motor skills depended on CST integrity, a strong association between M1 to M1 connectivity and basal motor control was observed independent of CST integrity especially in patients who underwent substantial motor recovery. Harnessing the informational wealth of cortico-cortical connectivity facilitated the explanation of both basal and complex motor control. INTERPRETATION: We demonstrate for the first time that distinct aspects of cortical structural reserve enable basal and complex motor control after stroke. In particular, recovery of basal motor control may be supported via an alternative route through contralesional M1 and non-crossing fibers of the contralesional CST. Our findings help to explain previous conflicting interpretations regarding the functional role of the contralesional M1 and highlight the potential of cortico-cortical structural connectivity as a future biomarker for motor recovery post-stroke. ANN NEUROL 2023;94:785-797.

Large-vessel-occlusion in patients with previous ischemic stroke: an analysis of adherence to secondary preventive medication for different etiologies.

BACKGROUND: Large vessel occlusion (LVO) is a severe condition that carries a high risk of morbidity and mortality, underscoring the importance of effective prevention strategies. This retrospective study aimed to analyze the intake of preventive medication at the time of hospitalization in a cohort of recurrent stroke patients presenting with acute LVO. METHODS: The study assessed the intake of either platelet aggregation inhibitors (PAI), oral anticoagulants (OAC) or statins at admission in patients with recurrent stroke and correlated it with the final classification of LVO. The frequency of those secondary preventive medication in recurrent stroke patients was defined as primary endpoint. The Modified Rankin Scale (mRS) at discharge was used as a functional outcome and defined as a secondary outcome measure. RESULTS: This study included 866 patients who were treated for LVO between 2016 and 2020, of whom 160 (18.5%) had a recurrent ischemic stroke. OAC (25.6% vs. 14.1%, p < 0.01), PAI (50.0% vs. 26.0%, p < 0.01), or statin therapy (50.6% vs. 20.8%, p < 0.01) at admission were significantly more frequent in recurrent stroke patients compared to patients with a first-time stroke. Concerning LVO etiology in recurrent stroke patients, OAC at admission was taken in 46.8% of cardioembolic LVO, whereas PAI and statin at admission in macroangiopathic LVO were administered to 40.0%; neither PAI nor OAC was taken in 26.0%, 28.3%, and 31.6% of cardioembolic, macroangiopathic, or cryptogenic strokes, respectively. Regardless of stroke recurrence or etiology, there was an increase in mRS at discharge. CONCLUSIONS: Despite high-quality healthcare, this study suggested a significant proportion of patients with recurrent stroke who were either non-adherent or insufficiently adherent to secondary preventive medication. Given the disability associated with LVO, improving patients' medication adherence and identifying unknown stroke causes are crucial for effective prevention strategies.

Brain-oscillation-synchronized stimulation to enhance motor recovery in early subacute stroke: a randomized controlled double-blind three- arm parallel-group exploratory trial comparing personalized, non- personalized and sham repetitive transcranial magnetic stimulation (Acronym: BOSS-STROKE).

BACKGROUND: Stroke is a major cause of death and the most frequent cause of permanent disability in western countries. Repetitive transcranial brain stimulation (rTMS) has been used to enhance neuronal plasticity after stroke, yet with only moderate effect sizes. Here we will apply a highly innovative technology that synchronizes rTMS to specific brain states identified by real-time analysis of electroencephalography. METHODS: One hundred forty-four patients with early subacute ischemic motor stroke will be included in a multicenter 3-arm parallel, randomized, double-blind, standard rTMS and sham rTMS-controlled exploratory trial in Germany. In the experimental condition, rTMS will be synchronized to the trough of the sensorimotor µ-oscillation, a high-excitability state, over ipsilesional motor cortex. In the standard rTMS control condition the identical protocol will be applied, but non-synchronized to the ongoing µ-oscillation. In the sham condition, the same µ-oscillation-synchronized protocol as in experimental condition will be applied, but with ineffective rTMS, using the sham side of an active/placebo TMS coil. The treatment will be performed over five consecutive work days (1,200 pulses per day, 6,000 pulses total). The primary endpoint will be motor performance after the last treatment session as measured by the Fugl-Meyer Assessment Upper Extremity. DISCUSSION: This study investigates, for the first time, the therapeutic efficacy of personalized, brain-state-dependent rTMS. We hypothesize that synchronization of rTMS with a high-excitability state will lead to significantly stronger improvement of paretic upper extremity motor function than standard or sham rTMS. Positive results may catalyze a paradigm-shift towards personalized brain-state-dependent stimulation therapies. TRIAL REGISTRATION: This study was registered at ClinicalTrials.gov (NCT05600374) on 10-21-2022.

To engage or not engage: Early incentive motivation prevents symptoms of chronic post-stroke depression - A longitudinal study.

BACKGROUND: Although post-stroke depression (PSD) is known to disrupt motor rehabilitation after stroke, PSD is often undertreated and its relationship with motor impairment remains poorly understood. METHODS: In a longitudinal study design we investigated, which factors at the early post-acute stage may increase the risk for PSD symptoms. We were especially interested in whether interindividual differences in the motivational drive to engage in physically demanding tasks indicate PSD development in patients suffering from motor impairments. Accordingly, we used a monetary incentive grip force task where participants were asked to hold their grip force for high and low rewards at stake to maximize their monetary outcome. Individual grip force was normalized according to the maximal force prior to the experiment. Experimental data, depression, and motor impairment were assessed from 20 stroke patients (12 male; 7.7 ± 6.78 days post-stroke) with mild-to-moderate hand motor impairment and 24 age-matched healthy participants (12 male). RESULTS: Both groups showed incentive motivation as indicated by stronger grip force for high versus low reward trials and the overall monetary outcome in the task. In stroke patients, severely impaired patients showed stronger incentive motivation, whereas early PSD symptoms were associated with reduced incentive motivation in the task. Larger lesions in corticostriatal tracts correlated with reduced incentive motivation. Importantly, chronic motivational deficits were preceded by initially reduced incentive motivation and larger corticostriatal lesions in the early stage post-stroke. CONCLUSIONS: More severe motor impairment motivates reward-dependent motor engagement, whereas PSD and corticostriatal lesions potentially disturb incentive motivational behavior, thereby increasing the risk of chronic motivational PSD symptoms. Acute interventions should address motivational aspects of behavior to improve motor rehabilitation post-stroke.

The role of corticospinal and extrapyramidal pathways in motor impairment after stroke.

Anisotropy of descending motor pathways has repeatedly been linked to the severity of motor impairment following stroke-related damage to the corticospinal tract. Despite promising findings consistently tying anisotropy of the ipsilesional corticospinal tract to motor outcome, anisotropy is not yet utilized as a biomarker for motor recovery in clinical practice as several methodological constraints hinder a conclusive understanding of degenerative processes in the ipsilesional corticospinal tract and compensatory roles of other descending motor pathways. These constraints include estimating anisotropy in voxels with multiple fibre directions, sampling biases and confounds due to ageing-related atrophy. The present study addressed these issues by combining diffusion spectrum imaging with a novel compartmentwise analysis approach differentiating voxels with one dominant fibre direction (one-directional voxels) from voxels with multiple fibre directions. Compartmentwise anisotropy for bihemispheric corticospinal and extrapyramidal tracts was compared between 25 chronic stroke patients, 22 healthy age-matched controls, and 24 healthy young controls and its associations with motor performance of the upper and lower limbs were assessed. Our results provide direct evidence for Wallerian degeneration along the entire length of the ipsilesional corticospinal tract reflected by decreased anisotropy in descending fibres compared with age-matched controls, while ageing-related atrophy was observed more ubiquitously across compartments. Anisotropy of descending ipsilesional corticospinal tract voxels showed highly robust correlations with various aspects of upper and lower limb motor impairment, highlighting the behavioural relevance of Wallerian degeneration. Moreover, anisotropy measures of two-directional voxels within bihemispheric rubrospinal and reticulospinal tracts were linked to lower limb deficits, while anisotropy of two-directional contralesional rubrospinal voxels explained gross motor performance of the affected hand. Of note, the relevant extrapyramidal structures contained fibres crossing the midline, fibres potentially mitigating output from brain stem nuclei, and fibres transferring signals between the extrapyramidal system and the cerebellum. Thus, specific parts of extrapyramidal pathways seem to compensate for impaired gross arm and leg movements incurred through stroke-related corticospinal tract lesions, while fine motor control of the paretic hand critically relies on ipsilesional corticospinal tract integrity. Importantly, our findings suggest that the extrapyramidal system may serve as a compensatory structural reserve independent of post-stroke reorganization of extrapyramidal tracts. In summary, compartment-specific anisotropy of ipsilesional corticospinal tract and extrapyramidal tracts explained distinct aspects of motor impairment, with both systems representing different pathophysiological mechanisms contributing to motor control post-stroke. Considering both systems in concert may help to develop diffusion imaging biomarkers for specific motor functions after stroke.

Recovered grasping performance after stroke depends on interhemispheric frontoparietal connectivity.

Activity changes in the ipsi- and contralesional parietal cortex and abnormal interhemispheric connectivity between these regions are commonly observed after stroke, however, their significance for motor recovery remains poorly understood. We here assessed the contribution of ipsilesional and contralesional anterior intraparietal cortex (aIPS) for hand motor function in 18 recovered chronic stroke patients and 18 healthy control subjects using a multimodal assessment consisting of resting-state functional MRI, motor task functional MRI, online-repetitive transcranial magnetic stimulation (rTMS) interference, and 3D movement kinematics. Effects were compared against two control stimulation sites, i.e. contralesional M1 and a sham stimulation condition. We found that patients with good motor outcome compared to patients with more substantial residual deficits featured increased resting-state connectivity between ipsilesional aIPS and contralesional aIPS as well as between ipsilesional aIPS and dorsal premotor cortex. Moreover, interhemispheric connectivity between ipsilesional M1 and contralesional M1 as well as ipsilesional aIPS and contralesional M1 correlated with better motor performance across tasks. TMS interference at individual aIPS and M1 coordinates led to differential effects depending on the motor task that was tested, i.e. index finger-tapping, rapid pointing movements, or a reach-grasp-lift task. Interfering with contralesional aIPS deteriorated the accuracy of grasping, especially in patients featuring higher connectivity between ipsi- and contralesional aIPS. In contrast, interference with the contralesional M1 led to impaired grasping speed in patients featuring higher connectivity between bilateral M1. These findings suggest differential roles of contralesional M1 and aIPS for distinct aspects of recovered hand motor function, depending on the reorganization of interhemispheric connectivity.

Advancing brain network models to reconcile functional neuroimaging and clinical research.

Functional magnetic resonance imaging (fMRI) captures information on brain function beyond the anatomical alterations that are traditionally visually examined by neuroradiologists. However, the fMRI signals are complex in addition to being noisy, so fMRI still faces limitations for clinical applications. Here we review methods that have been proposed as potential solutions so far, namely statistical, biophysical and decoding models, with their strengths and weaknesses. We especially evaluate the ability of these models to directly predict clinical variables from their parameters (predictability) and to extract clinically relevant information regarding biological mechanisms and relevant features for classification and prediction (interpretability). We then provide guidelines for useful applications and pitfalls of such fMRI-based models in a clinical research context, looking beyond the current state of the art. In particular, we argue that the clinical relevance of fMRI calls for a new generation of models for fMRI data, which combine the strengths of both biophysical and decoding models. This leads to reliable and biologically meaningful model parameters, which thus fulfills the need for simultaneous interpretability and predictability. In our view, this synergy is fundamental for the discovery of new pharmacological and interventional targets, as well as the use of models as biomarkers in neurology and psychiatry.

Different facets of object-use pantomime: online TMS evidence on the role of the supramarginal gyrus.

BACKGROUND: A key question in apraxia research is which specific cognitive processes in pantomiming the parietal cortex supports. The manipulation-based hypothesis and the technical-reasoning hypothesis ascribe different roles to the inferior parietal lobule (IPL). OBJECTIVE: We elucidated the role of the left supramarginal gyrus (SMG, i.e., part of IPL) during the processing of different aspects of object-use pantomime. METHODS: Thirty-one healthy participants matched pantomimes with the corresponding object (PO) or the corresponding situation (PS) during online transcranial magnetic stimulation (TMS) interference applied to left SMG, compared to a control stimulation (vertex). Notably, the object corresponding to a given pantomime was explicitly not shown in the PS task, excluding the possibility to analyse a physical object. Matching an object to the corresponding situation (OS) served as a control task. RESULTS: TMS interference with left SMG significantly affected response times for both investigated pantomime tasks (PO and PS); the effect in the PO task significantly correlated with that in the PS task. As expected, no TMS effect was observed in the control task (OS). CONCLUSION: Left SMG does not only establish a link between pantomime and a manipulable object but is also involved in pantomime recognition and comprehension. That TMS interfered with both pantomime tasks supports the manipulation-based hypothesis, assuming that the IPL recruits stored gesture engrams whenever pantomimes are processed.

Surgery of Motor Eloquent Glioblastoma Guided by TMS-Informed Tractography: Driving Resection Completeness Towards Prolonged Survival.

Background: Surgical treatment of patients with glioblastoma affecting motor eloquent brain regions remains critically discussed given the risk-benefit dilemma of prolonging survival at the cost of motor-functional damage. Tractography informed by navigated transcranial magnetic stimulation (nTMS-informed tractography, TIT) provides a rather robust estimate of the individual location of the corticospinal tract (CST), a highly vulnerable structure with poor functional reorganisation potential. We hypothesised that by a more comprehensive, individualised surgical decision-making using TIT, tumours in close relationship to the CST can be resected with at least equal probability of gross total resection (GTR) than less eloquently located tumours without causing significantly more gross motor function harm. Moreover, we explored whether the completeness of TIT-aided resection translates to longer survival. Methods: A total of 61 patients (median age 63 years, m = 34) with primary glioblastoma neighbouring or involving the CST were operated on between 2010 and 2015. TIT was performed to inform surgical planning in 35 of the patients (group T; vs. 26 control patients). To achieve largely unconfounded group comparisons for each co-primary outcome (i.e., gross-motor functional worsening, GTR, survival), (i) uni- and multivariate regression analyses were performed to identify features of optimal outcome prediction; (ii), optimal propensity score matching (PSM) was applied to balance those features pairwise across groups, followed by (iii) pairwise group comparison. Results: Patients in group T featured a significantly higher lesion-CST overlap compared to controls (8.7 ± 10.7% vs. 3.8 ± 5.7%; p = 0.022). The frequency of gross motor worsening was higher in group T, albeit non-significant (n = 5/35 vs. n = 0/26; p = 0.108). PSM-based paired-sample comparison, controlling for the confounders of preoperative tumour volume and vicinity to the delicate vasculature of the insula, showed higher GTR rates in group T (77% vs. 69%; p = 0.025), particularly in patients with a priori intended GTR (87% vs. 78%; p = 0.003). This translates into a prolonged PFS in the same PSM subgroup (8.9 vs. 5.8 months; p = 0.03), with GTR representing the strongest predictor of PFS (p = 0.001) and OS (p = 0.0003) overall. Conclusion: The benefit of TIT-aided GTR appears to overcome the drawbacks of potentially elevated motor functional risk in motor eloquent tumour localisation, leading to prolonged survival of patients with primary glioblastoma close to the CST.

Development and Validation of Prediction Models for Severe Complications After Acute Ischemic Stroke: A Study Based on the Stroke Registry of Northwestern Germany.

Background The treatment of stroke has been undergoing rapid changes. As treatment options progress, prediction of those under risk for complications becomes more important. Available models have, however, frequently been built based on data no longer representative of today's care, in particular with respect to acute stroke management. Our aim was to build and validate prediction models for 4 clinically important, severe outcomes after stroke. Methods and Results We used German registry data from 152 710 patients with acute ischemic stroke obtained in 2016 (development) and 2017 (validation). We took into account potential predictors that were available at admission and focused on in-hospital mortality, intracranial mass effect, secondary intracerebral hemorrhage, and deep vein thrombosis as outcomes. Validation cohort prediction and calibration performances were assessed using the following 4 statistical approaches: logistic regression with backward selection, l1-regularized logistic regression, k-nearest neighbor, and gradient boosting classifier. In-hospital mortality and intracranial mass effects could be predicted with high accuracy (both areas under the curve, 0.90 [95% CI, 0.90-0.90]), whereas the areas under the curve for intracerebral hemorrhage (0.80 [95% CI, 0.80-0.80]) and deep vein thrombosis (0.73 [95% CI, 0.73-0.73]) were considerably lower. Stroke severity was the overall most important predictor. Models based on gradient boosting achieved better performances than those based on logistic regression for all outcomes. However, area under the curve estimates differed by a maximum of 0.02. Conclusions We validated prediction models for 4 severe outcomes after acute ischemic stroke based on routinely collected, recent clinical data. Model performance was superior to previously proposed approaches. These predictions may help to identify patients at risk early after stroke and thus facilitate an individualized level of care.

Recovery after stroke: the severely impaired are a distinct group.

INTRODUCTION: Stroke causes different levels of impairment and the degree of recovery varies greatly between patients. The majority of recovery studies are biased towards patients with mild-to-moderate impairments, challenging a unified recovery process framework. Our aim was to develop a statistical framework to analyse recovery patterns in patients with severe and non-severe initial impairment and concurrently investigate whether they recovered differently. METHODS: We designed a Bayesian hierarchical model to estimate 3-6 months upper limb Fugl-Meyer (FM) scores after stroke. When focusing on the explanation of recovery patterns, we addressed confounds affecting previous recovery studies and considered patients with FM-initial scores <45 only. We systematically explored different FM-breakpoints between severe/non-severe patients (FM-initial=5-30). In model comparisons, we evaluated whether impairment-level-specific recovery patterns indeed existed. Finally, we estimated the out-of-sample prediction performance for patients across the entire initial impairment range. RESULTS: Recovery data was assembled from eight patient cohorts (n=489). Data were best modelled by incorporating two subgroups (breakpoint: FM-initial=10). Both subgroups recovered a comparable constant amount, but with different proportional components: severely affected patients recovered more the smaller their impairment, while non-severely affected patients recovered more the larger their initial impairment. Prediction of 3-6 months outcomes could be done with an R2=63.5% (95% CI=51.4% to 75.5%). CONCLUSIONS: Our work highlights the benefit of simultaneously modelling recovery of severely-to-non-severely impaired patients and demonstrates both shared and distinct recovery patterns. Our findings provide evidence that the severe/non-severe subdivision in recovery modelling is not an artefact of previous confounds. The presented out-of-sample prediction performance may serve as benchmark to evaluate promising biomarkers of stroke recovery.

Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence.

Stroke ranks among the leading causes for morbidity and mortality worldwide. New and continuously improving treatment options such as thrombolysis and thrombectomy have revolutionized acute stroke treatment in recent years. Following modern rhythms, the next revolution might well be the strategic use of the steadily increasing amounts of patient-related data for generating models enabling individualized outcome predictions. Milestones have already been achieved in several health care domains, as big data and artificial intelligence have entered everyday life. The aim of this review is to synoptically illustrate and discuss how artificial intelligence approaches may help to compute single-patient predictions in stroke outcome research in the acute, subacute and chronic stage. We will present approaches considering demographic, clinical and electrophysiological data, as well as data originating from various imaging modalities and combinations thereof. We will outline their advantages, disadvantages, their potential pitfalls and the promises they hold with a special focus on a clinical audience. Throughout the review we will highlight methodological aspects of novel machine-learning approaches as they are particularly crucial to realize precision medicine. We will finally provide an outlook on how artificial intelligence approaches might contribute to enhancing favourable outcomes after stroke.

Dynamic connectivity predicts acute motor impairment and recovery post-stroke.

Thorough assessment of cerebral dysfunction after acute lesions is paramount to optimize predicting clinical outcomes. We here built random forest classifier-based prediction models of acute motor impairment and recovery post-stroke. Predictions relied on structural and resting-state fMRI data from 54 stroke patients scanned within the first days of symptom onset. Functional connectivity was estimated via static and dynamic approaches. Motor performance was phenotyped in the acute phase and 6 months later. A model based on the time spent in specific dynamic connectivity configurations achieved the best discrimination between patients with and without motor impairments (out-of-sample area under the curve, 95% confidence interval: 0.67 ± 0.01). In contrast, patients with moderate-to-severe impairments could be differentiated from patients with mild deficits using a model based on the variability of dynamic connectivity (0.83 ± 0.01). Here, the variability of the connectivity between ipsilesional sensorimotor cortex and putamen discriminated the most between patients. Finally, motor recovery was best predicted by the time spent in specific connectivity configurations (0.89 ± 0.01) in combination with the initial impairment. Here, better recovery was linked to a shorter time spent in a functionally integrated configuration. Dynamic connectivity-derived parameters constitute potent predictors of acute impairment and recovery, which, in the future, might inform personalized therapy regimens to promote stroke recovery.

Early motor network connectivity after stroke: An interplay of general reorganization and state-specific compensation.

Motor recovery after stroke relies on functional reorganization of the motor network, which is commonly assessed via functional magnetic resonance imaging (fMRI)-based resting-state functional connectivity (rsFC) or task-related effective connectivity (trEC). Measures of either connectivity mode have been shown to successfully explain motor impairment post-stroke, posing the question whether motor impairment is more closely reflected by rsFC or trEC. Moreover, highly similar changes in ipsilesional and interhemispheric motor network connectivity have been reported for both rsFC and trEC after stroke, suggesting that altered rsFC and trEC may capture similar aspects of information integration in the motor network reflecting principle, state-independent mechanisms of network reorganization rather than state-specific compensation strategies. To address this question, we conducted the first direct comparison of rsFC and trEC in a sample of early subacute stroke patients (n = 26, included on average 7.3 days post-stroke). We found that both rsFC and trEC explained motor impairment across patients, stressing the clinical potential of fMRI-based connectivity. Importantly, intrahemispheric connectivity between ipsilesional M1 and premotor areas depended on the activation state, whereas interhemispheric connectivity between homologs was state-independent. From a mechanistic perspective, our results may thus arise from two distinct aspects of motor network plasticity: task-specific compensation within the ipsilesional hemisphere and a more fundamental form of reorganization between hemispheres.