Neurology

Radiographic evaluation of the psoas and iliopsoas muscle as predictors for spinal cord ischemia after fenestrated and branched endovascular aortic repair.

OBJECTIVE: This study aimed to investigate the association between sarcopenia and spinal cord ischemia (SCI) after fenestrated and branched endovascular aortic repair (F/B-EVAR) using two- and three-dimensional measurements of the psoas and iliopsoas muscles on preoperative computed tomography angiography (CTA). METHODS: A retrospective two-center study was conducted, and reported in accordance wi...

Carpal Tunnel Syndrome Diagnosis: A Narrative Review of Complementary Roles of Neuromuscular Ultrasound and Electrodiagnostic Studies.

Carpal tunnel syndrome (CTS), the most prevalent entrapment neuropathy of the upper extremities, presents diagnostic challenges due to nonspecific clinical symptoms and discrepancies between subjective experiences and objective findings. Traditional reliance on electrodiagnostic studies (EDX), including nerve conduction studies (NCS) and electromyography, as the traditional reference method for as...

Feasibility Randomized Controlled Trial of Real-Time fMRI Neurofeedback for Reading Rehabilitation in Aphasia.

BACKGROUND: Reading impairments are common in stroke-induced aphasia and limit participation in functional and leisure activities. Traditional rehabil...

Reachable Workspace as a Clinical Outcome for Upper Extremity Function: A Narrative Review.

Motion sensing technology can be utilized to capture detailed upper extremity (UE) motion to reconstruct an individual's three-dimensional (3D) reacha...

A machine-learning-based tool for stroke risk prediction in blunt cerebrovascular injury: development and preliminary evaluation.

PURPOSE: Stroke risk correlates with the Biffl grading system in blunt cerebrovascular injury (BCVI). Although anti-thrombotic therapy is the mainstay...

A graph deep learning method for diagnosis of Parkinson's disease using brain functional connectivity features.

Early and precise identification of Parkinson's disease (PD) is crucial for clinical intervention. Resting-state functional magnetic resonance imaging...

Consciousness Monitoring and Outcome Prediction Using EEG Connectivity in Severe Traumatic Brain Injury.

Neurological prognostication of patients in post-traumatic coma remains challenging due to the paucity of reliable markers in the acute phase. We aime...

Development of a machine learning model using structured and unstructured features for predicting surgery among patients with carpal tunnel syndrome: development and validation.

Carpal tunnel syndrome (CTS) is the most common entrapment neuropathy and often requires surgery when symptoms persist. However, identifying patients ...

Mechanized precision: the rise of robotic systems in spinal surgery.

BACKGROUND: Robot-assisted spinal surgery has rapidly evolved into a transformative innovation. Initially developed for pedicle screw placement, curre...

Enhanced Quantitative Phosphocreatine MR Imaging of Skeletal Muscle Using a Global-Local Two-Branch Deep Learning Model.

PURPOSE: Phosphocreatine (PCr) is an essential marker of muscle metabolism, and accurate quantification of its (fs) and its exchange rate (ksw) is ess...

Electronic health record-based prediction models for dementia detection: a systematic review of model performance and quality.

OBJECTIVES: Leveraging routine electronic health records (EHR) for dementia detection is a growing field, but quality and clinical utility of existing...

Lower-limb prosthetic mechanisms: recent progress, control innovations and barriers to real-world adoption.

Lower-limb impairments caused by amputation, stroke or paralysis severely impact mobility and independence. Assistive technologies for these condition...

Dual-model deep learning for Alzheimer's prognostication.

Disease-modifying therapies for Alzheimer's disease demand precise timing decisions, yet current predictive models require longitudinal clinical obser...

Vessel Wall Imaging at 7T: State of the Art.

Intracranial vessel wall imaging (VWI) has emerged as a critical tool in neurovascular diagnostics, enabling direct assessment of the vessel wall, whi...

Performance of Deep Learning Reconstruction for Detection of Early Ischemic Changes in NCCT: Comparison with ASIR-V in Acute Stroke.

PURPOSE: Evaluation of the impact of Deep Learning Image Reconstruction (DLIR) compared to Adaptive Statistical Iterative Reconstruction-Veo (ASIR-V) ...

Patient-specific instantaneous spatial temperature maps for MR-guided laser interstitial thermal therapy using a physics-assisted deep learning framework.

PURPOSE: Accurate prediction of the laser energy absorption and corresponding thermal spread is essential for safe and effective outcomes in magnetic ...

Classification of functional brain patterns elicited by deep brain stimulation of the subthalamic nucleus in Parkinson's disease.

Despite the remarkable success of deep brain stimulation (DBS) in alleviating Parkinson's disease (PD) symptoms, complexities arising from inherent in...

PhysioMotion Artifact: A task-driven EEG dataset with point-wise motion artifact annotations.

Physiological artifacts pose persistent challenges in electroencephalogram (EEG) data acquisition, often compromising interpretation and post-analysis...

Preoperative MRI-Derived Navigation Reduces Radiation Exposure in Pediatric Spinal Fusion.

BACKGROUND: Minimizing radiation exposure during pediatric spinal deformity correction is critical due to the cumulative lifetime effects of ionizing ...

Ischaemia in tuberculous meningitis: update on pathophysiology, clinical predictors and management.

PURPOSE OF REVIEW: Tuberculous meningitis (TBM) is a severe manifestation of Mycobacterium tuberculosis infection, associated with high mortality and ...