Background: Research on the brain mechanisms underlying manual therapy (MT)-induced analgesia has been conducted worldwide. However, no bibliometric analysis has been performed on functional magnetic resonance imaging (fMRI) studies of MT analgesia. To provide a theoretical foundation for the practical application of MT analgesia, this study examined the current incarnation, hotspots, and frontiers of fMRI-based MT analgesia research over the previous 20 years.
Methods: All publications were obtained from the Science Citation Index-Expanded (SCI-E) of Web of Science Core Collection (WOSCC). We used CiteSpace 6.1.R3 to analyze publications, authors, cited authors, countries, institutions, cited journals, references, and keywords. We also evaluated keyword co-occurrences and timelines, and citation bursts. The search was conducted from 2002-2022 and was completed within one day on October 7, 2022.
Results: In total, 261 articles were retrieved. The total number of annual publications showed a fluctuating but overall increasing trend. Author B. Humphreys had the highest number of publications (eight articles) and J. E. Bialosky had the highest centrality (0.45). The United States of America (USA) was the country with the most publications (84 articles), accounting for 32.18% of all publications. Output institutions were mainly the University of Zurich, University of Switzerland, and the National University of Health Sciences of the USA. The Spine (118) and the Journal of Manipulative and Physiological Therapeutics (80) were most frequently cited. The four hot topics in fMRI studies on MT analgesia were "low back pain", "magnetic resonance imaging", "spinal manipulation", and "manual therapy." The frontier topics were "clinical impacts of pain disorders" and "cutting-edge technical capabilities offered by magnetic resonance imaging".
Conclusion: fMRI studies of MT analgesia have potential applications. fMRI studies of MT analgesia have linked several brain areas, with the default mode network (DMN) garnering the most attention. Future research should include international collaboration and RCTs on this topic.
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http://dx.doi.org/10.2147/JPR.S412658 | DOI Listing |
Sci Rep
December 2024
Department of Diagnostic Radiology, Dalhousie University, Halifax, Canada.
The goal of this study was to determine how radiologists' rating of image quality when using 0.5T Magnetic Resonance Imaging (MRI) compares to Computed Tomography (CT) for visualization of pathology and evaluation of specific anatomic regions within the paranasal sinuses. 42 patients with clinical CT scans opted to have a 0.
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December 2024
Department of Internal Medicine, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, Busan, 48108, Republic of Korea.
This study aimed to investigate alterations in a multilayer network combining structural and functional layers in patients with end-stage kidney disease (ESKD) compared with healthy controls. In all, 38 ESKD patients and 43 healthy participants were prospectively enrolled. They exhibited normal brain magnetic resonance imaging (MRI) without any structural lesions.
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December 2024
Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Republic of Korea.
Vertebral collapse (VC) following osteoporotic vertebral compression fracture (OVCF) often requires aggressive treatment, necessitating an accurate prediction for early intervention. This study aimed to develop a predictive model leveraging deep neural networks to predict VC progression after OVCF using magnetic resonance imaging (MRI) and clinical data. Among 245 enrolled patients with acute OVCF, data from 200 patients were used for the development dataset, and data from 45 patients were used for the test dataset.
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December 2024
Academy of Medical Engineering and Translational Medicine (AMT), Tianjin University, Tianjin, China.
Generalization is central to motor learning. However, few studies are on the learning generalization of BCI-actuated supernumerary robotic finger (BCI-SRF) for human-machine interaction training, and no studies have explored its longitudinal neuroplasticity mechanisms. Here, 20 healthy right-handed participants were recruited and randomly assigned to BCI-SRF group or inborn finger group (Finger) for 4-week training and measured by novel SRF-finger opposition sequences and multimodal MRI.
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December 2024
Institute of Informatics, HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland, Sierre, Switzerland.
Manual segmentation of lesions, required for radiotherapy planning and follow-up, is time-consuming and error-prone. Automatic detection and segmentation can assist radiologists in these tasks. This work explores the automated detection and segmentation of brain metastases (BMs) in longitudinal MRIs.
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