Rosenberg Nahum
Specialists Center, National Insurance Institute, Pal Yam 8, Haifa 3309511, Israel.
Diagnostics (Basel). 2025 Jun 22;15(13):1581. doi: 10.3390/diagnostics15131581.
Musculoskeletal (MSK) pain is a leading contributor to global disability and healthcare burdens. While self-reported pain scales remain the clinical standard, they are limited by subjectivity and inter-individual variability. Therefore, objective assessment tools are increasingly sought to enhance diagnostic precision, guide treatment, and enable reproducible research outcomes. This comprehensive narrative review synthesizes evidence from physiological, behavioral, and neuroimaging approaches used to evaluate MSK pain objectively. Emphasis is placed on autonomic biomarkers (e.g., heart rate variability, skin conductance), facial expression analysis, electromyographic methods, and functional neuroimaging modalities such as fMRI and PET. Emerging applications of artificial intelligence and multimodal diagnostic strategies are also discussed. Physiological signals provide quantifiable correlations of pain-related autonomic activity but are influenced by psychological and contextual factors. Behavioral analyses, including facial action coding systems and reflex testing, offer complementary, though complex, indicators. Neuroimaging techniques have identified pain-related brain patterns, yet clinical translation is limited by variability and standardization issues. Integrative approaches show promise for improving diagnostic validity. Objective assessment of MSK pain remains methodologically challenging but holds substantial potential for enhancing clinical diagnostics and personalized management. Future research should focus on multimodal integration, standardization, and translational feasibility to bridge the gap between experimental tools and clinical practice.
肌肉骨骼(MSK)疼痛是导致全球残疾和医疗负担的主要因素。虽然自我报告的疼痛量表仍然是临床标准,但它们受到主观性和个体间差异的限制。因此,人们越来越多地寻求客观评估工具,以提高诊断精度、指导治疗并实现可重复的研究结果。这篇全面的叙述性综述综合了用于客观评估MSK疼痛的生理学、行为学和神经影像学方法的证据。重点关注自主生物标志物(如心率变异性、皮肤电导率)、面部表情分析、肌电图方法以及功能神经影像学模式,如功能磁共振成像(fMRI)和正电子发射断层扫描(PET)。还讨论了人工智能和多模态诊断策略的新兴应用。生理信号提供了与疼痛相关的自主活动的可量化相关性,但受到心理和情境因素的影响。行为分析,包括面部动作编码系统和反射测试,提供了互补但复杂的指标。神经影像学技术已经识别出与疼痛相关的脑模式,但临床转化受到变异性和标准化问题的限制。综合方法显示出提高诊断有效性的前景。MSK疼痛的客观评估在方法上仍然具有挑战性,但在增强临床诊断和个性化管理方面具有巨大潜力。未来的研究应侧重于多模态整合、标准化和转化可行性,以弥合实验工具与临床实践之间的差距。