Del Mauro Gianpaolo, Li Yiran, Yu Jiaao, Kochunov Peter, Sevel Landrew Samuel, Boissoneault Jeff, Chen Shuo, Wang Ze
Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
J Pain. 2025 Jul;32:105421. doi: 10.1016/j.jpain.2025.105421. Epub 2025 Apr 30.
Chronic pain is a debilitating clinical condition and a severe public health issue that demands to be addressed. Neuroimaging-based techniques have been widely adopted to investigate the neural underpinnings of chronic pain. Despite the efforts the complex nature of pain experience as well as the heterogeneity of chronic pain have made the identification of neuroimaging-based biomarkers extremely challenging. In this study, resting-state fMRI-based brain entropy, a measure reflecting the "irregularity" of brain activity, was adopted as a biomarker of chronic pain by comparing individuals with chronic pain and healthy controls in a sample of middle-to-old-age participants (n > 30,000) drawn from the UK Biobank database. Abnormal brain entropy is associated with altered brain dynamics and may serve as a potential marker of disrupted pain processing in individuals with chronic pain. Compared to healthy controls, individuals with chronic pain exhibited increased brain entropy in a broad set of regions including the frontal, temporal, and occipital lobes, as well as the cerebellum. In addition, individuals with a more distributed chronic pain showed increased brain entropy in occipital lobes. When examining distinct types of chronic pain individually, only participants with headache and pain all over the body showed brain entropy differences compared to a matched sample of healthy controls. PERSPECTIVE: This article investigates the neural substrates of chronic pain using brain entropy, a measure of the randomness and irregularity of brain activity. This measure could potentially aid in the assessment and treatment of chronic pain.
慢性疼痛是一种使人衰弱的临床病症，也是一个亟待解决的严重公共卫生问题。基于神经成像的技术已被广泛用于研究慢性疼痛的神经基础。尽管付出了诸多努力，但疼痛体验的复杂性以及慢性疼痛的异质性使得基于神经成像的生物标志物识别极具挑战性。在本研究中，通过比较从英国生物银行数据库中选取的中老年参与者样本（n>30,000）中的慢性疼痛个体与健康对照，采用基于静息态功能磁共振成像的脑熵（一种反映大脑活动“不规则性”的指标）作为慢性疼痛的生物标志物。异常脑熵与大脑动力学改变相关，可能是慢性疼痛个体疼痛处理中断的潜在标志物。与健康对照相比，慢性疼痛个体在包括额叶、颞叶、枕叶以及小脑在内的广泛区域表现出脑熵增加。此外，慢性疼痛分布更广泛的个体在枕叶表现出脑熵增加。当单独检查不同类型的慢性疼痛时，与匹配的健康对照样本相比，只有头痛和全身疼痛的参与者表现出脑熵差异。观点：本文使用脑熵（一种衡量大脑活动随机性和不规则性的指标）研究慢性疼痛的神经基础。这一指标可能有助于慢性疼痛的评估和治疗。
