Advanced magnetic resonance imaging (MRI) techniques are transforming the study of movement disorders by providing valuable insights into disease mechanisms. This narrative review presents a comprehensive overview of their applications in this field, offering an updated perspective on their potential for early diagnosis, disease monitoring, and therapeutic evaluation. Emerging MRI modalities such as neuromelanin-sensitive imaging, diffusion-weighted imaging, magnetization transfer imaging, and relaxometry provide sensitive biomarkers that can detect early microstructural degeneration, iron deposition, and connectivity disruptions in key regions like the substantia nigra. These techniques enable earlier and more accurate differentiation of movement disorders, including Parkinson's disease, progressive supranuclear palsy, multiple system atrophy, corticobasal degeneration, Lewy body and frontotemporal dementia, Huntington's disease, and dystonia. Furthermore, MRI provides objective metrics for tracking disease progression and assessing therapeutic efficacy, making it an indispensable tool in clinical trials. Despite these advances, the absence of standardized protocols limits their integration into routine clinical practice. Addressing this gap and incorporating these techniques more systematically could bring the field closer to leveraging advanced MRI for personalized treatment strategies, ultimately improving outcomes for individuals with movement disorders.
Objectives: The aim of the present study was to examine the growth dynamics of the first sacral vertebra and its ossification center in the human fetus, based on their linear, planar, and volumetric parameters.
Methods: The examinations were carried out on 54 human fetuses of both sexes (26 males and 28 females) aged 18-30 weeks of gestation, which had been preserved in 10% neutral formalin solution. Using CT, digital image analysis software, 3D reconstruction, and statistical methods, the size of the first sacral vertebra and its ossification center was evaluated.
Results: The first sacral vertebra and its ossification center grew proportionately according to fetal weeks.
Conclusions: The numerical data obtained from computed tomography and the growth patterns of the body of the first sacral vertebra and its ossification center may serve as age-specific normative intervals relevant for gynecologists, obstetricians, pediatricians, and radiologists during fetal ultrasound screening. Our findings on the growth of the body of the first sacral vertebra and its ossification center may be useful in daily clinical practice, particularly in ultrasonic monitoring of normal fetal growth and in screening for congenital defects and skeletal dysplasias.
The significant correlation between ancient medicinal practices and brain function marks a revolutionary frontier in the field of neuroscience. Acupuncture, a traditional oriental medicine, can affect brain regions, such as the hypothalamus, anterior cingulate, posterior cingulate, and hippocampus, and produces specific therapeutic effects, such as pain relief, suppression of hypertension, and alleviation of drug addiction. Among the brain regions, the hypothalamus, a small yet critical region in the brain, plays a pivotal role in maintaining homeostasis by regulating a wide array of physiological processes, including stress responses, energy balance, and pain modulation. Emerging evidence suggests that acupuncture may exert its therapeutic effects by modulating the activity of the hypothalamus and its associated neural circuits, particularly in relation to pain, stress, and metabolic regulation. Thus, we conducted a comprehensive review of past and current research on the role of the hypothalamus in mediating the therapeutic effects of acupuncture.
Background/Objectives: Narration is a sensitive tool for the assessment of language in children with high-functioning autism spectrum disorder (HF-ASD) since mild language deficits beyond the sentential level are not always noticeable through the administration of standardized language tests targeting the lexical or sentential level. This study investigated the narrative ability of monolingual Greek-speaking HF-ASD children in comparison to that of their typically developing (TD) peers and explored the associations between narrative variables, ADHD symptomatology, and memory skills in the participants on the autistic spectrum. Methods: The participants were 39 children aged 7 to 12 years, 19 with HF-ASD and 20 age-matched, vocabulary-matched, and cognitively matched TD peers. Results: The two groups were similar in most microstructural and macrostructural variables but differed significantly in syntactic complexity (p = 0.024; d = 0.754) and subordination (p < 0.001; d = -1.576) indices, implying that the HF-ASD group presented syntactic delay in comparison to their TD peers. The HF-ASD participants showed significantly higher heterogeneity in the amount of information generated for the story's main character (p = 0.004; d = -0.093) in comparison to their TD peers. Significant associations were observed between verbal and visual memory, complex syntactic structures, and Theory of Mind-related internal state terms. ADHD symptomatology was negatively correlated with the generation of simple and coordinated clauses. Finally, complex syntax and delayed vSTM were correlated with retelling total scores, indicating that language ability and verbal memory compensate for narrative competence in HF-ASD children. Conclusions: The findings highlight the impact that language skills, memory ability, and ADHD symptomatology have on narrative competence in children with HF-ASD, as well as the importance of narrative use for assessing the language skills in populations with mild language impairment.
Background: Clinicians are challenged by the ambiguity and uncertainty in assessing level of consciousness in individuals with disorder of consciousness (DoC). There are numerous challenges to valid and reliable neurobehavioral assessment and classification of DoC due to multiple environmental and patient-related biases including behavioral fluctuation and confounding or co-occurring medical conditions. Addressing these biases could impact accuracy of assessment and is an important aspect of the DoC assessment process.
Methods: A pre-assessment checklist was developed by a group of interdisciplinary DoC clinical experts and researchers based on the existing literature, current validated tools, and expert opinions. Once finalized, the checklist was electronically distributed to clinicians with a range of experience in neurobehavioral assessment with DoC. Respondents were asked to use the checklist prior to completing a neurobehavioral assessment. A survey was also provided to respondents to obtain feedback regarding checklist feasibility and utility in optimizing the behavioral assessments.
Results: Thirty-three clinicians completed the survey after using the checklist. Over half of the respondents were a combination of physicians, neuropsychologists, and physical therapists. All respondents served the adult DoC population and 42% percent had over ten years of clinical experience. Eighty percent reported they found the format of the checklist useful and easy to use. All respondents reported the checklist was relevant to preparing for behavioral assessment in the DoC population. Eighty-four percent reported they would recommend the use of the tool to other clinicians.
Conclusions: The use of a pre-assessment checklist was found to be feasible and efficacious in increasing interdisciplinary clinician's ability to optimize the patient and environment in preparation for neurobehavioral assessment. Initial results of clinicians' perception of the utility of a pre-assessment checklist were positive. However, further validation of the tool is needed with larger sample sizes to improve representation of clinical use across disciplines and care settings.
Background/objectives: This study aimed to address limitations of the pilot reliability study on the Sensory-Motor Dysfunction Questionnaire (SMD-Q) in two parts. Part 1 evaluated the intra-rater reliability of SMD-Q version 2 (V2). Part 2 addressed V2's limitations before assessing the intra-rater reliability of version 3 (V3). V2 framed questions as "over the past week", whereas V3 also framed questions as "in a typical/usual week".
Methods: The SMD-Q was administered via QualtricsTM at baseline and 4 to 7 days later to subclinical neck pain participants, 51 in part 1 (32 F; mean age ± SD: 21.17 ± 2.66 y) and 27 in part 2 (20 F; mean age ± SD: 21.89 ± 2.81 y). Reliability statistics (quadratic weighted kappa (Kw) and Cronbach's alpha (α)) were calculated for all items (V2) and total scores (V2 and V3).
Results: There was excellent agreement for V2 total scores (Kw ≥ 0.75), and V3 total scores for "in a typical/usual week" (Kw ≥ 0.75), but fair to good agreement for V3 total scores of "over the past week" (0.40 < Kw < 0.75). V2 had acceptable (0.7 ≤ α < 0.8) to good internal consistency (0.8 ≤ α < 0.9), while V3 had good internal consistency for both administrations.
Conclusions: Versions 2 and 3 of the SMD-Q appear to reliably capture disordered sensorimotor integration in people with subclinical neck pain, with improved reliability in V3 when questions are framed as "in a typical/usual week". However, further research is needed to confirm this finding.
Background/objectives: The classification of psychological disorders has gained significant importance due to recent advancements in signal processing techniques. Traditionally, research in this domain has focused primarily on binary classifications of disorders. This study aims to classify five distinct states, including one control group and four categories of psychological disorders.
Methods: Our investigation will utilize algorithms based on Granger causality and local graph structures to improve classification accuracy. Feature extraction from connectivity matrices was performed using local structure graphs. The extracted features were subsequently classified employing K-Nearest Neighbors (KNN), Support Vector Machine (SVM), AdaBoost, and Naïve Bayes classifiers.
Results: The KNN classifier demonstrated the highest accuracy in the gamma band for the depression category, achieving an accuracy of 89.36%, a sensitivity of 89.57%, an F1 score of 94.30%, and a precision of 99.90%. Furthermore, the SVM classifier surpassed the other machine learning algorithms when all features were integrated, attaining an accuracy of 89.06%, a sensitivity of 88.97%, an F1 score of 94.16%, and a precision of 100% for the discrimination of depression in the gamma band.
Conclusions: The proposed methodology provides a novel approach for analyzing EEG signals and holds potential applications in the classification of psychological disorders.
Background: The brainstem auditory-evoked response (BAER) is an established electrophysiological measure of neural activity from the auditory nerve up to the brain stem. The BAER is used to diagnose abnormalities in auditory pathways and in neurophysiological human and animal research. However, normative data for BAERs in sheep, which represent an adequate large animal model for translational and basic otological research, are lacking. Objective: The aim of this study was to assess the function of the ovine auditory nervous system by determining normative values for the BAER and to compare sheep with human BAER data. Methods: In this retrospective study, BAER data for click stimuli at a range of sound pressure levels (SPLs) were analyzed. A series of 15 samples from six sheep with a mean age of 41.8 months was included. Results: The mean BAER threshold was 45.3 dB SPL. At 100 dB SPL, the mean (±standard deviation, SD) latency of wave V was 4.35 (±0.18) ms, that of wave III was 2.44 (±0.15) ms, and that of wave I was 0.88 (±0.13) ms. At 100 dB SPL, the mean interpeak latency of waves I-III was 1.56 (±0.18) ms, that of waves III-V was 1.91 (±0.16) ms, and that of waves I-V was 3.47 (±0.20) ms. The mean amplitudes at 100 dB SPL were 0.04 (±0.03) µV for wave I, 0.50 (±0.24) µV for wave III, and 0.40 (±0.25) µV for wave V. Conclusions: The normative values for sheep BAERs were reproducible and similar to those of humans. The normative BAER values further support sheep as an adequate animal model for otological research.
Background: Diffusion tensor imaging (DTI), a variant of Diffusion Weighted Imaging (DWI), enables a neuroanatomical microscopic-like examination of the brain, which can detect brain damage using physical parameters. DTI's application to traumatic brain injury (TBI) has the potential to reveal radiological features that can assist in predicting the clinical outcomes of these patients. What is the ongoing role of DTI in detecting brain alterations and predicting neurological outcomes in patients with moderate to severe traumatic brain injury and/or diffuse axonal injury? Methods: A scoping review of the PubMed, Scopus, EMBASE, and Cochrane databases was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. The aim was to identify all potentially relevant studies concerning the role of DTI in TBI. From an initial pool of 3527 publications, 26 articles were selected based on relevance. These studies included a total of 729 patients with moderate to severe TBI and/or diffuse axonal injury. DTI parameters were analyzed to determine their relationship with neurological outcomes post-TBI, with assessments of several brain functions and regions. Results: The studies included various DTI parameters, identifying significant relationships between DTI variations and neurological outcomes following TBI. Multiple brain functions and regions were evaluated, demonstrating the capability of DTI to detect brain alterations with higher accuracy, sensitivity, and specificity than MRI alone. Conclusions: DTI is a valuable tool for detecting brain alterations in TBI patients, offering enhanced accuracy, sensitivity, and specificity compared to MRI alone. Recent studies confirm its effectiveness in identifying neurological impairments and predicting outcomes in patients following brain trauma, underscoring its utility in clinical settings for managing TBI.
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