Background: Recent literature suggests that taking into consideration and evaluating preoperative expectations of Parkinson's disease (PD) patients candidates to deep brain stimulation (DBS), can contribute to treatment effectiveness. However, few validated instruments investigating preoperative expectations are available. We present the development and validation of the DBS-PS (Deep Brain Stimulation - Perception Scale).
Methods: The DBS-PS is an 11 questions self-administered scale, with answers rated on a 10-point Likert scale (1 completely false, 10 completely true). Items were generated on the basis of patient's interviews analyzed by an expert group and reached consensus. The scale is divided into three domains: expectations for PD, expectations for social-life and leisure, expectations for intimate life. Exploratory factor analysis (EFA) completed by item response theory (IRT) analysis was conducted to validate the theoretical structure of the DBS-PS.
Results: 64 PD patients aged 59.18 (SD = 5.74) years with PD diagnosed since 9.36 (SD = 4.09) years completed the DBS-PS preoperatively. EFA confirmed a 3 factors scale structure (eigenvalue >1) explaining 69% of variance (factor 1: 43%; factor 2: 17%; factor 3: 9%). Reliability (Cronbach's α: 0.714 for factor 1, 0.781 for factor 2, 0.889 for factor 3) and discriminant validity (Pearson coefficient r < 0.50) were satisfactory. IRT showed good model fit, preserved unidimensionality, but some local dependences were observed.
Conclusion: The DBS-PS shows satisfactory psychometric properties. It is easy to administer in routine practice with preoperative PD patients. It constitutes an interesting basis for cognitive restructuring before neurosurgery, by highlighting dysfunctional cognitions and measuring the benefits of cognitive restructuring therapy.
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http://dx.doi.org/10.1016/j.jns.2024.123093 | DOI Listing |
J Magn Reson Imaging
January 2025
Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway.
Background: Deep learning-based segmentation of brain metastases relies on large amounts of fully annotated data by domain experts. Semi-supervised learning offers potential efficient methods to improve model performance without excessive annotation burden.
Purpose: This work tests the viability of semi-supervision for brain metastases segmentation.
Eur Radiol Exp
January 2025
Laboratory of Molecular Imaging, Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Background: We examined chronic gadolinium retention impact on gene expression in the mouse central nervous system (CNS) after injection of linear or macrocyclic gadolinium-based contrast agents (GBCAs).
Methods: From 05/2022 to 07/2023, 36 female mice underwent weekly intraperitoneal injections of gadodiamide (2.5 mmol/kg, linear), gadobutrol (2.
Cureus
December 2024
Department of Technology and Clinical Trials, Advanced Research, Deerfield Beach, USA.
This paper investigates the potential of artificial intelligence (AI) and machine learning (ML) to enhance the differentiation of cystic lesions in the sellar region, such as pituitary adenomas, Rathke cleft cysts (RCCs) and craniopharyngiomas (CP), through the use of advanced neuroimaging techniques, particularly magnetic resonance imaging (MRI). The goal is to explore how AI-driven models, including convolutional neural networks (CNNs), deep learning, and ensemble methods, can overcome the limitations of traditional diagnostic approaches, providing more accurate and early differentiation of these lesions. The review incorporates findings from critical studies, such as using the Open Access Series of Imaging Studies (OASIS) dataset (Kaggle, San Francisco, USA) for MRI-based brain research, highlighting the significance of statistical rigor and automated segmentation in developing reliable AI models.
View Article and Find Full Text PDFNeuroethics
July 2024
Department of Philosophy, Savery Hall, University of Washington, Seattle, WA, 98195, USA.
Neurotechnological cognitive enhancement has become an area of intense scientific, policy, and ethical interest. However, while work has increasingly focused on ethical views of the general public, less studied are those with personal connections to cognitive impairment. Using a mixed-methods design, we surveyed attitudes regarding implantable neurotechnological cognitive enhancement in individuals who self-identified as having increased likelihood of developing dementia (n=25; 'Our Study'), compared to a nationally representative sample of Americans (n=4726; 'Pew Study').
View Article and Find Full Text PDFClin Neuropsychol
January 2025
Department of Neurology, Emory University School of Medicine, Emory University, Atlanta, GA, USA.
To introduce ABBA Letter Alternation (ABBA) as a computerized measure of response inhibition/response alternation developed for telehealth following restrictions of in-person testing due to COVID-19. ABBA consists of two PowerPoint-administered trials: Letter Reading of 25 capital As or Bs individually presented, and Letter Alternation with instructions to say the opposite letter to what is presented. We obtained initial normative ABBA performance from 899 healthy research volunteers participating in the Emory Healthy Brain Study (EHBS) with Montreal Cognitive Assessment (MoCA) scores 24/30 and higher.
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