Comparative and Expansive Study on Diagnosis Methods of Myofascial Trigger Point
DOI:
https://doi.org/10.53469/jcmp.2025.07(04).35Keywords:
Myofascial trigger point, Diagnosis, Myofascial pain syndrome, Chronic pain, Biomaker, Pain assessmentAbstract
Background: Myofascial trigger points (MTrPs) are hyperexcitable areas in the skeletal muscle or fascia that cause muscle pain and dysfunction due to overuse, trauma, or neurological abnormalities. MTrPs are associated with palpable contracture nodules in tight bands. Various diagnostic methods exist for MTrPs; however, standard diagnostic criteria and procedures have yet to be established by international scholars. This lack of consensus can lead to confusion with other diseases. Aims: The objective of this systematic review is to survey the literature on MTrPs and myofascial pain syndrome (MPS). This paper analyzes evidence of MPS and MTrPs production and pain occurrence using electromyography, imaging, and biomarkers. Additionally, it identifies recent diagnostic methods for MTrPs and provides the latest evaluation and diagnostic criteria for MPS and MTrPs. The authors propose some accurate and easy-to-use diagnostic indicators and methods suitable for front-line clinicians. Methods: Literature published from February 2000-2023 was searched through PubMed and Google Scholar using the following search terms: myofascial trigger points, myofascial pain syndrome, diagnostic, ultrasound, electromyography, genetic and molecular biology. Results: Currently used diagnostic methods include physical examination, MTrPs partition table, ultrasonography, electromyography, and biomarkers. This paper thoroughly evaluates the advantages and disadvantages of various diagnostic methods and introduces some emerging methods, such as elastography and immunomarker analysis. Conclusions: Standardized, systematic, and reproducible diagnostic methods and procedures have not yet been developed for MTrPs, and the pathogenesis of MTrPs is still under investigation. In the future, specific biomarkers, genetic testing technology, and artificial intelligence-assisted diagnosis may become acceptable diagnostic tools.
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Copyright (c) 2025 Kaige Chen, Yindi Sun

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