Objective: The effectiveness and optimal stimulation site of deep brain stimulation (DBS) for central poststroke pain (CPSP) remain elusive. The objective of this retrospective international multicenter study was to assess clinical as well as neuroimaging-based predictors of long-term outcomes after DBS for CPSP.
Methods: The authors analyzed patient-based clinical and neuroimaging data of previously published and unpublished cohorts from 6 international DBS centers. DBS leads were reconstructed and normalized. A stimulation map was constructed on the basis of individual stimulation settings and associated outcomes. Furthermore, the authors projected the individual segmented stroke lesions and volumes of tissue activated (VTAs) of the stimulating electrode onto a normalized human connectome to obtain the connectivity profiles of the individual lesions and VTAs.
Results: The authors analyzed the data of 54 patients, of whom 15 were excluded from the final analysis due to a lack of imaging data. Among the remaining 39 patients from 6 different cohorts, the authors found 14 (35.9%) responders who were defined by pain relief of at least 50% at 12-month follow-up. Stimulation mapping identified areas in the posterior limb of the internal capsule, the sensorimotor thalamus, and the medial and intralaminar thalamus as effective for pain reduction. Baseline characteristics did not differ between responders and nonresponders. The stimulation sites of the responders showed significantly reduced structural connectivity to the sensory areas of the cerebral cortex compared to nonresponders.
Conclusions: This comprehensive, multicenter analysis corroborates the efficacy of DBS in treating CPSP for a relevant number of patients. The posterior limb of the internal capsule and the sensorimotor thalamus emerged as potential stimulation sweet spots. The difference in structural connectivity between responders and nonresponders may constitute a biomarker of effective stimulation that can help guide surgical planning in future well-designed prospective trials.
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http://dx.doi.org/10.3171/2024.8.JNS24742 | DOI Listing |
Sci Rep
January 2025
Department of ECE, Kallam Haranadhareddy Institute of Technology, Guntur, Andhra Pradesh, India.
Cognitive load stimulates neural activity, essential for understanding the brain's response to stress-inducing stimuli or mental strain. This study examines the feasibility of evaluating cognitive load by extracting, selection, and classifying features from electroencephalogram (EEG) signals. We employed robust local mean decomposition (R-LMD) to decompose EEG data from each channel, recorded over a four-second period, into five modes.
View Article and Find Full Text PDFArch Dermatol Res
January 2025
Department of Dermatology, Zhejiang Provincial Hospital of Dermatology, Huzhou, 313200, China.
Psoriasis is a long-lasting inflammatory skin condition characterized by excessive keratinocyte growth. Recent studies have confirmed abnormal regulation of microRNAs (miRNAs/miRs) in individuals with psoriasis. This study aimed to investigate the function and specific mechanism of action of miR-128a-3p in interleukin-22 (IL-22)-stimulated HaCaT cells.
View Article and Find Full Text PDFInt J Comput Assist Radiol Surg
January 2025
Faculty of Computer Science and Research Campus STIMULATE, Otto-von-Guericke University of Magdeburg, Magdeburg, Germany.
Purpose: Structured abdominal examination is an essential part of the medical curriculum and surgical training, requiring a blend of theory and practice from trainees. Current training methods, however, often do not provide adequate engagement, fail to address individual learning needs or do not cover rare diseases.
Methods: In this work, an application for structured Abdominal Examination Training using Augmented Reality (AETAR) is presented.
World J Urol
January 2025
Department of Urology, Peking University People's Hospital, Beijing, 100044, China.
Purpose: This study aims to elucidate the role of pituitary adenylate cyclase-activating polypeptide (PACAP) in Hunner-type Interstitial Cystitis (HIC) and evaluate its potential as a therapeutic target.
Methods: Bladder tissue samples were obtained from HIC patients and normal bladder tissue from bladder cancer patients. PACAP expression was assessed through immunohistochemistry.
NPJ Digit Med
January 2025
Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.
Adaptive deep brain stimulation (DBS) provides individualized therapy for people with Parkinson's disease (PWP) by adjusting the stimulation in real-time using neural signals that reflect their motor state. Current algorithms, however, utilize condensed and manually selected neural features which may result in a less robust and biased therapy. In this study, we propose Neural-to-Gait Neural network (N2GNet), a novel deep learning-based regression model capable of tracking real-time gait performance from subthalamic nucleus local field potentials (STN LFPs).
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