Performance of an Open-Source Large Language Model in Extracting Information from Free-Text Radiology Reports.

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To assess the performance of a local open-source large language model (LLM) on various information extraction tasks from real-life emergency brain MRI reports. Materials and Methods All consecutive emergency brain MRI reports written in 2022 from a French quaternary center were retrospectively reviewed. Two radiologists identified MRIs that were performed for headaches. Four radiologists scored reports' conclusions as normal or abnormal. Abnormalities were labeled as either headache-causing or incidental. Vicuna, an open-source LLM, performed the same tasks. Vicuna's performance metrics were evaluated using the radiologists' consensus as the reference standard. Results Among the 2398 reports during the study period, radiologists identified 595 that included headaches in their indication (median age of patients, 35 years [IQR, 26-51], 68% (403/595) female). A positive finding was reported in 227/595 (38%) cases, 136 of which could explain the headache. The LLM had a sensitivity/specificity (95%CI), respectively, of 98% (583/595)(97-99)/99% (1791/1803)(99-100) for detecting the presence of headache in the clinical context, 99% (514/517)(98-100)/99% (68/69)(92-100) for the use of contrast medium injection, 97% (219/227)(93-99)/99% (364/368)(97-100) for study categorization as normal or abnormal and 88% (120/136)(82- 93)/73% (66/91)(62-81) for causal inference between MRI findings and headache. Conclusion An open-source LLM was able to extract information from free-text radiology reports with excellent accuracy without requiring further training. ©RSNA, 2024.

Cognitive Impairment Is Part of the Phenotype of Cerebellar Ataxia, Neuropathy, Vestibular Areflexia Syndrome (CANVAS).

BACKGROUND: Little is known about the impact of the cerebellar ataxia, neuropathy, vestibular areflexia syndrome (CANVAS) on cognition. OBJECTIVE: Our objective was to determine the frequency and severity of cognitive impairment in RFC1-positive patients and describe the pattern of deficits. METHODS: Participants underwent a comprehensive neuropsychological assessment. Volume of the cerebellum and its lobules was measured in those who underwent a 3 Tesla-magnetic resonance scan. RESULTS: Twenty-one patients underwent a complete assessment, including 71% scoring lower than the cutoff at the Montreal Cognitive assessment and 71% having a definite cerebellar cognitive affective/Schmahmann syndrome. Three patients had dementia and seven met the criteria of mild cognitive impairment. Severity of cognitive impairment did not correlate with severity of clinical manifestations. Performance at memory and visuospatial functions tests negatively correlated with the severity of cerebellar manifestations. CONCLUSION: Cognitive manifestations are frequent in RFC1-related disorders. They should be included in the phenotype and screened systematically. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Clinical Associations and Prognostic Value of MRI-Visible Perivascular Spaces in Patients With Ischemic Stroke or TIA: A Pooled Analysis

BACKGROUND AND OBJECTIVES: Visible perivascular spaces are an MRI marker of cerebral small vessel disease and might predict future stroke. However, results from existing studies vary. We aimed to clarify this through a large collaborative multicenter analysis. METHODS: We pooled individual patient data from a consortium of prospective cohort studies. Participants had recent ischemic stroke or transient ischemic attack (TIA), underwent baseline MRI, and were followed up for ischemic stroke and symptomatic intracranial hemorrhage (ICH). Perivascular spaces in the basal ganglia (BGPVS) and perivascular spaces in the centrum semiovale (CSOPVS) were rated locally using a validated visual scale. We investigated clinical and radiologic associations cross-sectionally using multinomial logistic regression and prospective associations with ischemic stroke and ICH using Cox regression. RESULTS: We included 7,778 participants (mean age 70.6 years; 42.7% female) from 16 studies, followed up for a median of 1.44 years. Eighty ICH and 424 ischemic strokes occurred. BGPVS were associated with increasing age, hypertension, previous ischemic stroke, previous ICH, lacunes, cerebral microbleeds, and white matter hyperintensities. CSOPVS showed consistently weaker associations. Prospectively, after adjusting for potential confounders including cerebral microbleeds, increasing BGPVS burden was independently associated with future ischemic stroke (versus 0-10 BGPVS, 11-20 BGPVS: HR 1.19, 95% CI 0.93-1.53; 21+ BGPVS: HR 1.50, 95% CI 1.10-2.06; p = 0.040). Higher BGPVS burden was associated with increased ICH risk in univariable analysis, but not in adjusted analyses. CSOPVS were not significantly associated with either outcome. DISCUSSION: In patients with ischemic stroke or TIA, increasing BGPVS burden is associated with more severe cerebral small vessel disease and higher ischemic stroke risk. Neither BGPVS nor CSOPVS were independently associated with future ICH.

The Use of Image Guided Programming to Improve Deep Brain Stimulation Workflows with Directional Leads in Parkinson's Disease.

BACKGROUND: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a preferred treatment for parkinsonian patients with severe motor fluctuations. Proper targeting of the STN sensorimotor segment appears to be a crucial factor for success of the procedure. The recent introduction of directional leads theoretically increases stimulation specificity in this challenging area but also requires more precise stimulation parameters. OBJECTIVE: We investigated whether commercially available software for image guided programming (IGP) could maximize the benefits of DBS by informing the clinical standard care (CSC) and improving programming workflows. METHODS: We prospectively analyzed 32 consecutive parkinsonian patients implanted with bilateral directional leads in the STN. Double blind stimulation parameters determined by CSC and IGP were assessed and compared at three months post-surgery. IGP was used to adjust stimulation parameters if further clinical refinement was required. Overall clinical efficacy was evaluated one-year post-surgery. RESULTS: We observed 78% concordance between the two electrode levels selected by the blinded IGP prediction and CSC assessments. In 64% of cases requiring refinement, IGP improved clinical efficacy or reduced mild side effects, predominantly by facilitating the use of directional stimulation (93% of refinements). CONCLUSIONS: The use of image guided programming saves time and assists clinical refinement, which may be beneficial to the clinical standard care for STN-DBS and further improve the outcomes of DBS for PD patients.

Fatigue after spontaneous intracerebral haemorrhage: prevalence and associated factors.

BACKGROUND: Fatigue is a major complaint in stroke survivors, but data focusing on intracerebral haemorrhage (ICH) survivors are scarce. In a cohort of spontaneous ICH survivors, we assessed the long-term prevalence of fatigue and its associated factors. METHODS: We included consecutive 1-year ICH survivors from the prospective, observational, single-centre Prognosis of Intracerebral Haemorrhage (PITCH) study. We evaluated fatigue (defined as a score ≥ 4 in Chalder Fatigue Scale); the severity of neurological, depressive, and anxiety symptoms; and functional disability 1, 3, and 6 years after ICH. We performed univariable and multivariable models to evaluate clinical factors and brain magnetic resonance imaging (MRI) small vessel disease (SVD) markers associated with fatigue. RESULTS: Of 255 1-year ICH survivors, 153 (60%) underwent fatigue screening and were included in this study. Seventy-eight patients (51%) reported fatigue at 1-year, 56/110 (51%) at 3-year, and 27/67 (40%) at 6-year follow-up. Patients with fatigue exhibited more severe concomitant depressive/anxiety symptoms, but the severity of depressive symptoms was the only clinical factor significantly associated with 1-year fatigue in multivariable analysis (adjusted odds ratio 1.4 for one-point increase; 95% confidence interval 1.2-1.6). Patients with severe cortical atrophy at baseline had increased risk of fatigue at 1-year follow-up compared to patients with mild/no cortical atrophy (adjusted odds ratio 2.5; 95% confidence interval 1.1-5.8). CONCLUSIONS: Fatigue after ICH is frequent and long-lasting, and it is associated with cortical atrophy (but not with other MRI markers of cerebral SVD). The link between fatigue and depressive symptoms may represent a potential therapeutic target.

A three-dimensional deep learning model for inter-site harmonization of structural MR images of the brain: Extensive validation with a multicenter dataset.

In multicenter MRI studies, pooling the imaging data can introduce site-related variabilities and can therefore bias the subsequent analyses. To harmonize the intensity distributions of brain MR images in a multicenter dataset, unsupervised deep learning methods can be employed. Here, we developed a model based on cycle-consistent adversarial networks for the harmonization of T1-weighted brain MR images. In contrast to previous works, it was designed to process three-dimensional whole-brain images in a stable manner while optimizing computation resources. Using six different MRI datasets for healthy adults (n=1525 in total) with different acquisition parameters, we tested the model in (i) three pairwise harmonizations with site effects of various sizes, (ii) an overall harmonization of the six datasets with different age distributions, and (iii) a traveling-subject dataset. Our results for intensity distributions, brain volumes, image quality metrics and radiomic features indicated that the MRI characteristics at the various sites had been effectively homogenized. Next, brain age prediction experiments and the observed correlation between the gray-matter volume and age showed that thanks to an appropriate training strategy and despite biological differences between the dataset populations, the model reinforced biological patterns. Furthermore, radiologic analyses of the harmonized images attested to the conservation of the radiologic information in the original images. The robustness of the harmonization model (as judged with various datasets and metrics) demonstrates its potential for application in retrospective multicenter studies.

MRI BrainAGE demonstrates increased brain aging in systemic lupus erythematosus patients.

Introduction: Systemic lupus erythematosus (SLE) is an autoimmune connective tissue disease affecting multiple organs in the human body, including the central nervous system. Recently, an artificial intelligence method called BrainAGE (Brain Age Gap Estimation), defined as predicted age minus chronological age, has been developed to measure the deviation of brain aging from a healthy population using MRI. Our aim was to evaluate brain aging in SLE patients using a deep-learning BrainAGE model. Methods: Seventy female patients with a clinical diagnosis of SLE and 24 healthy age-matched control females, were included in this post-hoc analysis of prospectively acquired data. All subjects had previously undergone a 3 T MRI acquisition, a neuropsychological evaluation and a measurement of neurofilament light protein in plasma (NfL). A BrainAGE model with a 3D convolutional neural network architecture, pre-trained on the 3D-T1 images of 1,295 healthy female subjects to predict their chronological age, was applied on the images of SLE patients and controls in order to compute the BrainAGE. SLE patients were divided into 2 groups according to the BrainAGE distribution (high vs. low BrainAGE). Results: BrainAGE z-score was significantly higher in SLE patients than in controls (+0.6 [±1.1] vs. 0 [±1.0], p = 0.02). In SLE patients, high BrainAGE was associated with longer reaction times (p = 0.02), lower psychomotor speed (p = 0.001) and cognitive flexibility (p = 0.04), as well as with higher NfL after adjusting for age (p = 0.001). Conclusion: Using a deep-learning BrainAGE model, we provide evidence of increased brain aging in SLE patients, which reflected neuronal damage and cognitive impairment.

Characterization of theory of mind performance in patients with myotonic dystrophy type 1.

INTRODUCTION: Myotonic dystrophy type 1 (DM1) is associated with motor dysfunction as well as psychological and cognitive impairments, including altered social cognition. Theory of mind (ToM) impairments have been reported in this disease but their nature and their cognitive/cerebral correlates have yet to be determined. METHODS: Fifty DM1 patients and 50 healthy controls were assessed using the Movie for the Assessment of Social Cognition, which quantifies impairments in affective and cognitive components of ToM through the depiction of everyday situations. We also measured the study participants' cognitive, behavioral and social abilities, quality of life, and brain MRI characteristics. RESULTS: DM1 patients presented a significant impairment in ToM performance compared to controls (p < .001). The patients' errors were related to hypomentalizations (p < .001 vs controls) but not to hypermentalizations (p = .95). The affective component was affected (p < .001 vs controls) but not the cognitive component (p = .09). The ToM impairment was associated with demographic variables (older age and a lower educational level), genetic findings (a larger CTG triplets repeat expansion) and cognitive scores (slower information processing speed). Associations were also found with brain MRI variables (lower white matter and supratentorial volumes) but not with behavioral or social variables. DISCUSSION: DM1 patients display a ToM impairment, characterized by predominant hypomentalizations concerning the affective component. This impairment might result from structural brain abnormalities observed in DM1.

Anxiety in Parkinson's Disease Is Associated with Changes in Brain Structural Connectivity.

BACKGROUND: Anxiety in Parkinson's disease (PD) has been associated with grey matter changes and functional changes in anxiety-related neuronal circuits. So far, no study has analyzed white matter (WM) changes in patients with PD and anxiety. OBJECTIVE: The aim of this study was to identify WM changes by comparing PD patients with and without anxiety, using diffusion-tensor imaging (DTI). METHODS: 108 non-demented PD patients with (n = 31) and without (n = 77) anxiety as defined by their score on the Parkinson Anxiety Scale participated. DTI was used to determine the fractional anisotropy (FA) and mean diffusivity (MD) in specific tracts within anxiety-related neuronal circuits. Mean FA and MD were compared between groups and correlated with the severity of anxiety adjusted by sex, center, Hoehn & Yahr stage, levodopa equivalent daily dosage, and Hamilton depression rating scale. RESULTS: Compared to patients without anxiety, PD patients with anxiety showed lower FA within the striato-orbitofrontal, striato-cingulate, cingulate-limbic, and caudate-thalamic tracts; higher FA within the striato-limbic and accumbens-thalamic tracts; higher MD within the striato-thalamic tract and lower MD within the striato-limbic tract. CONCLUSIONS: Anxiety in PD is associated with microstructural alterations in anxiety-related neuronal circuits within the WM. This result reinforces the view that PD-related anxiety is linked to structural alteration within the anxiety-related brain circuits.

Hypothalamic neuroglial plasticity is regulated by anti-Müllerian hormone and disrupted in polycystic ovary syndrome.

BACKGROUND: Polycystic ovary syndrome (PCOS) is the most common reproductive-endocrine disorder affecting between 5 and 18% of women worldwide. An elevated frequency of pulsatile luteinizing hormone (LH) secretion and higher serum levels of anti-Müllerian hormone (AMH) are frequently observed in women with PCOS. The origin of these abnormalities is, however, not well understood. METHODS: We studied brain structure and function in women with and without PCOS using proton magnetic resonance spectroscopy (MRS) and diffusion tensor imaging combined with fiber tractography. Then, using a mouse model of PCOS, we investigated by electron microscopy whether AMH played a role on the regulation of hypothalamic structural plasticity. FINDINGS: Increased AMH serum levels are associated with increased hypothalamic activity/axonal-glial signalling in PCOS patients. Furthermore, we demonstrate that AMH promotes profound micro-structural changes in the murine hypothalamic median eminence (ME), creating a permissive environment for GnRH secretion. These include the retraction of the processes of specialized AMH-sensitive ependymo-glial cells called tanycytes, allowing more GnRH neuron terminals to approach ME blood capillaries both during the run-up to ovulation and in a mouse model of PCOS. INTERPRETATION: We uncovered a central function for AMH in the regulation of fertility by remodeling GnRH terminals and their tanycytic sheaths, and provided insights into the pivotal role of the brain in the establishment and maintenance of neuroendocrine dysfunction in PCOS. FUNDING: INSERM (U1172), European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement n° 725149), CHU de Lille, France (Bonus H).

Cognitive Behavioral Therapy for Anxiety in Parkinson's Disease Induces Functional Brain Changes.

BACKGROUND: Cognitive behavioral therapy (CBT) reduces anxiety symptoms in patients with Parkinson's disease (PD). OBJECTIVE: The objective of this study was to identify changes in functional connectivity in the brain after CBT for anxiety in patients with PD. METHODS: Thirty-five patients with PD and clinically significant anxiety were randomized over two groups: CBT plus clinical monitoring (10 CBT sessions) or clinical monitoring only (CMO). Changes in severity of anxiety symptoms were assessed with the Parkinson Anxiety Scale (PAS). Resting-state functional brain MRI was performed at baseline and after the intervention. Functional networks were extracted by an Independent Component Analysis (ICA). Functional connectivity (FC) changes between structures involved in the PD-related anxiety circuits, such as the fear circuit (involving limbic, frontal, and cingulate structures) and the cortico-striato-thalamo-cortical limbic circuit, and both within and between functional networks were compared between groups and regressed with anxiety symptoms changes. RESULTS: Compared to CMO, CBT reduced the FC between the right thalamus and the bilateral orbitofrontal cortices and increased the striato-frontal FC. CBT also increased the fronto-parietal FC within the central executive network (CEN) and between the CEN and the salience network. After CBT, improvement of PAS-score was associated with an increased striato-cingulate and parieto-temporal FC, and a decreased FC within the default-mode network and between the dorsal attentional network and the language network. CONCLUSION: CBT in PD-patients improves anxiety symptoms and is associated with functional changes reversing the imbalance between PD-related anxiety circuits and reinforcing cognitive control on emotional processing.

Quantitative susceptibility mapping demonstrates different patterns of iron overload in subtypes of early-onset Alzheimer's disease.

OBJECTIVES: We aimed to define brain iron distribution patterns in subtypes of early-onset Alzheimer's disease (EOAD) by the use of quantitative susceptibility mapping (QSM). METHODS: EOAD patients prospectively underwent MRI on a 3-T scanner and concomitant clinical and neuropsychological evaluation, between 2016 and 2019. An age-matched control group was constituted of cognitively healthy participants at risk of developing AD. Volumetry of the hippocampus and cerebral cortex was performed on 3DT1 images. EOAD subtypes were defined according to the hippocampal to cortical volume ratio (HV:CTV). Limbic-predominant atrophy (LPMRI) is referred to HV:CTV ratios below the 25th percentile, hippocampal-sparing (HpSpMRI) above the 75th percentile, and typical-AD between the 25th and 75th percentile. Brain iron was estimated using QSM. QSM analyses were made voxel-wise and in 7 regions of interest within deep gray nuclei and limbic structures. Iron distribution in EOAD subtypes and controls was compared using an ANOVA. RESULTS: Sixty-eight EOAD patients and 43 controls were evaluated. QSM values were significantly higher in deep gray nuclei (p < 0.001) and limbic structures (p = 0.04) of EOAD patients compared to controls. Among EOAD subtypes, HpSpMRI had the highest QSM values in deep gray nuclei (p < 0.001) whereas the highest QSM values in limbic structures were observed in LPMRI (p = 0.005). QSM in deep gray nuclei had an AUC = 0.92 in discriminating HpSpMRI and controls. CONCLUSIONS: In early-onset Alzheimer's disease patients, we observed significant variations of iron distribution reflecting the pattern of brain atrophy. Iron overload in deep gray nuclei could help to identify patients with atypical presentation of Alzheimer's disease. KEY POINTS: • In early-onset AD patients, QSM indicated a significant brain iron overload in comparison with age-matched controls. • Iron load in limbic structures was higher in participants with limbic-predominant subtype. • Iron load in deep nuclei was more important in participants with hippocampal-sparing subtype.

Trial of Deferiprone in Parkinson's Disease.

BACKGROUND: Iron content is increased in the substantia nigra of persons with Parkinson's disease and may contribute to the pathophysiology of the disorder. Early research suggests that the iron chelator deferiprone can reduce nigrostriatal iron content in persons with Parkinson's disease, but its effects on disease progression are unclear. METHODS: We conducted a multicenter, phase 2, randomized, double-blind trial involving participants with newly diagnosed Parkinson's disease who had never received levodopa. Participants were assigned (in a 1:1 ratio) to receive oral deferiprone at a dose of 15 mg per kilogram of body weight twice daily or matched placebo for 36 weeks. Dopaminergic therapy was withheld unless deemed necessary for symptom control. The primary outcome was the change in the total score on the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS; range, 0 to 260, with higher scores indicating more severe impairment) at 36 weeks. Secondary and exploratory clinical outcomes at up to 40 weeks included measures of motor and nonmotor disability. Brain iron content measured with the use of magnetic resonance imaging was also an exploratory outcome. RESULTS: A total of 372 participants were enrolled; 186 were assigned to receive deferiprone and 186 to receive placebo. Progression of symptoms led to the initiation of dopaminergic therapy in 22.0% of the participants in the deferiprone group and 2.7% of those in the placebo group. The mean MDS-UPDRS total score at baseline was 34.3 in the deferiprone group and 33.2 in the placebo group and increased (worsened) by 15.6 points and 6.3 points, respectively (difference, 9.3 points; 95% confidence interval, 6.3 to 12.2; P<0.001). Nigrostriatal iron content decreased more in the deferiprone group than in the placebo group. The main serious adverse events with deferiprone were agranulocytosis in 2 participants and neutropenia in 3 participants. CONCLUSIONS: In participants with early Parkinson's disease who had never received levodopa and in whom treatment with dopaminergic medications was not planned, deferiprone was associated with worse scores in measures of parkinsonism than those with placebo over a period of 36 weeks. (Funded by the European Union Horizon 2020 program; FAIRPARK-II ClinicalTrials.gov number, NCT02655315.).

Conservative Iron Chelation for Neuroferritinopathy.

BACKGROUND: Neuroferritinopathy is a rare inherited neurodegenerative disease with brain iron accumulation characterized by brain iron overload resulting in progressive movement disorders. No treatment is currently available. OBJECTIVE: We assessed conservative iron chelation with deferiprone at 30 mg/kg/day on the disease progression with controlled periods of discontinuation. METHODS: Four patients with confirmed molecular diagnosis of neuroferritinopathy were given deferiprone at different stages of disease progression and with clinical and biological monitoring to control benefit and risk. RESULTS: The four patients showed slight to high improvement. In one case, we managed to stabilize disease progression for more than 11 years. In another case, we were able to reverse symptoms after a few months of treatment. The earliest the treatment was started, the most efficient it was on disease progression. CONCLUSIONS: Conservative iron chelation should be further assessed in neuroferritinopathy. © 2022 International Parkinson and Movement Disorder Society.

Can Dopamine Responsiveness Be Predicted in Parkinson's Disease Without an Acute Administration Test?

BACKGROUND: Dopamine responsiveness (dopa-sensitivity) is an important parameter in the management of patients with Parkinson's disease (PD). For quantification of this parameter, patients undergo a challenge test with acute Levodopa administration after drug withdrawal, which may lead to patient discomfort and use of significant resources. OBJECTIVE: Our objective was to develop a predictive model combining clinical scores and imaging. METHODS: 350 patients, recruited by 13 specialist French centers and considered for deep brain stimulation, underwent an acute L-dopa challenge (dopa-sensitivity > 30%), full assessment, and MRI investigations, including T1w and R2* images. Data were randomly divided into a learning base from 10 centers and data from the remaining centers for testing. A machine selection approach was applied to choose the optimal variables and these were then used in regression modeling. Complexity of the modelling was incremental, while the first model considered only clinical variables, the subsequent included imaging features. The performances were evaluated by comparing the estimated values and actual valuesResults:Whatever the model, the variables age, sex, disease duration, and motor scores were selected as contributors. The first model used them and the coefficients of determination (R2) was 0.60 for the testing set and 0.69 in the learning set (p < 0.001). The models that added imaging features enhanced the performances: with T1w (R2 = 0.65 and 0.76, p < 0.001) and with R2* (R2 = 0.60 and 0.72, p < 0.001). CONCLUSION: These results suggest that modeling is potentially a simple way to estimate dopa-sensitivity, but requires confirmation in a larger population, including patients with dopa-sensitivity < 30.

Cerebral Microbleeds During Transcatheter Aortic Valve Replacement: A Prospective Magnetic Resonance Imaging Cohort.

BACKGROUND: Cerebral microbleeds (CMBs) have been observed in healthy elderly people undergoing systematic brain magnetic resonance imaging. The potential role of acute triggers on the appearance of CMBs remains unknown. We aimed to describe the incidence of new CMBs after transcatheter aortic valve replacement (TAVR) and to identify clinical and procedural factors associated with new CMBs including hemostatic measures and anticoagulation management. METHODS: We evaluated a prospective cohort of patients with symptomatic aortic stenosis referred for TAVR for CMBs (METHYSTROKE [Identification of Epigenetic Risk Factors for Ischemic Complication During the TAVR Procedure in the Elderly]). Standardized neurologic assessment, brain magnetic resonance imaging, and analysis of hemostatic measures including von Willebrand factor were performed before and after TAVR. Numbers and location of microbleeds on preprocedural magnetic resonance imaging and of new microbleeds on postprocedural magnetic resonance imaging were reported by 2 independent neuroradiologists blinded to clinical data. Measures associated with new microbleeds and postprocedural outcome including neurologic functional outcome at 6 months were also examined. RESULTS: A total of 84 patients (47% men, 80.9±5.7 years of age) were included. On preprocedural magnetic resonance imaging, 22 patients (26% [95% CI, 17%-37%]) had at least 1 microbleed. After TAVR, new microbleeds were observed in 19 (23% [95% CI, 14%-33%]) patients. The occurrence of new microbleeds was independent of the presence of microbleeds at baseline and of diffusion-weighted imaging hypersignals. In univariable analysis, a previous history of bleeding (P=0.01), a higher total dose of heparin (P=0.02), a prolonged procedure (P=0.03), absence of protamine reversion (P=0.04), higher final activated partial thromboplastin time (P=0.05), lower final von Willebrand factor high-molecular-weight:multimer ratio (P=0.007), and lower final closure time with adenosine-diphosphate (P=0.02) were associated with the occurrence of new postprocedural microbleeds. In multivariable analysis, a prolonged procedure (odds ratio, 1.22 [95% CI, 1.03-1.73] for every 5 minutes of fluoroscopy time; P=0.02) and postprocedural acquired von Willebrand factor defect (odds ratio, 1.42 [95% CI, 1.08-1.89] for every lower 0.1 unit of high-molecular-weight:multimer ratio; P=0.004) were independently associated with the occurrence of new postprocedural microbleeds. New CMBs were not associated with changes in neurologic functional outcome or quality of life at 6 months. CONCLUSIONS: One out of 4 patients undergoing TAVR has CMBs before the procedure and 1 out of 4 patients develops new CMBs. Procedural or antithrombotic management and persistence of acquired von Willebrand factor defect were associated with the occurrence of new CMBs. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT02972008.

Network impact score is an independent predictor of post-stroke cognitive impairment: A multicenter cohort study in 2341 patients with acute ischemic stroke.

BACKGROUND: Post-stroke cognitive impairment (PSCI) is a common consequence of stroke. Accurate prediction of PSCI risk is challenging. The recently developed network impact score, which integrates information on infarct location and size with brain network topology, may improve PSCI risk prediction. AIMS: To determine if the network impact score is an independent predictor of PSCI, and of cognitive recovery or decline. METHODS: We pooled data from patients with acute ischemic stroke from 12 cohorts through the Meta VCI Map consortium. PSCI was defined as impairment in ≥ 1 cognitive domain on neuropsychological examination, or abnormal Montreal Cognitive Assessment. Cognitive recovery was defined as conversion from PSCI < 3 months post-stroke to no PSCI at follow-up, and cognitive decline as conversion from no PSCI to PSCI. The network impact score was related to serial measures of PSCI using Generalized Estimating Equations (GEE) models, and to PSCI stratified according to post-stroke interval (<3, 3-12, 12-24, >24 months) and cognitive recovery or decline using logistic regression. Models were adjusted for age, sex, education, prior stroke, infarct volume, and study site. RESULTS: We included 2341 patients with 4657 cognitive assessments. PSCI was present in 398/844 patients (47%) <3 months, 709/1640 (43%) at 3-12 months, 243/853 (28%) at 12-24 months, and 208/522 (40%) >24 months. Cognitive recovery occurred in 64/181 (35%) patients and cognitive decline in 26/287 (9%). The network impact score predicted PSCI in the univariable (OR 1.50, 95%CI 1.34-1.68) and multivariable (OR 1.27, 95%CI 1.10-1.46) GEE model, with similar ORs in the logistic regression models for specified post-stroke intervals. The network impact score was not associated with cognitive recovery or decline. CONCLUSIONS: The network impact score is an independent predictor of PSCI. As such, the network impact score may contribute to a more precise and individualized cognitive prognostication in patients with ischemic stroke. Future studies should address if multimodal prediction models, combining the network impact score with demographics, clinical characteristics and other advanced brain imaging biomarkers, will provide accurate individualized prediction of PSCI. A tool for calculating the network impact score is freely available at https://metavcimap.org/features/software-tools/lsm-viewer/.

Heterogeneity of PD-MCI in Candidates to Subthalamic Deep Brain Stimulation: Associated Cortical and Subcortical Modifications.

BACKGROUND: Parkinson's disease mild cognitive impairment (PD-MCI) is frequent and heterogenous. There is no consensus about its influence on subthalamic deep brain stimulation (STN-DBS) outcomes. OBJECTIVE: To determine the prevalence of PD-MCI and its subtypes in candidates to STN-DBS. Secondarily, we sought to identify MRI structural markers associated with cognitive impairment in these subgroups. METHODS: Baseline data from the French multicentric PREDISTIM cohort were used. Candidates to STN-DBS were classified according to their cognitive performance in normal cognition (PD-NC) or PD-MCI. The latter included frontostriatal (PD-FS) and posterior cortical (PD-PC) subtypes. Between-group comparisons were performed on demographical and clinical variables as well as on T1-weighted MRI sequences at the cortical and subcortical levels. RESULTS: 320 patients were included: 167 (52%) PD-NC and 153 (48%) PD-MCI patients. The latter group included 123 (80%) PD-FS and 30 (20%) PD-PC patients. There was no between-group difference regarding demographic and clinical variables. PD-PC patients had significantly lower global efficiency than PD-FS patients and significantly worse performance on visuospatial functions, episodic memory, and language. Compared to PD-NC, PD-MCI patients had cortical thinning and radiomic-based changes in the left caudate nucleus and hippocampus. There were no significant differences between the PD-MCI subtypes. CONCLUSION: Among the candidates to STN-DBS, a significant proportion has PD-MCI which is associated with cortical and subcortical alterations. Some PD-MCI patients have posterior cortical deficits, a subtype known to be at higher risk of dementia.