Noori Mirtaheri Parsia, Mehrtabar Saba, Shah Hosseini Reza, Shahryari Kianoush, Pakmehr SeyedAbbas, Rahimi Arash, Mohammad Hashem Sourena, Shahidi Marnani Seyed Amirabbas, Karami Shaghayegh, Sadeghi Mahsa, Azhdary Moghaddam Yeganeh, Azhdari Moghaddam Aida, Deravi Niloofar, Asadi Anar Mahsa
School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
Gastroenterol Hepatol Bed Bench. 2025;18(2):164-176. doi: 10.22037/ghfbb.v18i2.2987.
Functional gastrointestinal disorders (FGID) are prevalent illnesses associated with diminished quality of life and increased healthcare utilization. These conditions influence gut sensitivity, motility, microbiota, immunological function, and nervous processing in the brain. Chronic symptoms, including pain and dyspepsia, are exacerbated by maladaptive patient behaviors, stress, and co-morbidity. Studies of functional neuroimaging reveal increased brain responses in regions associated with gut sensory processing and salient cues, altered central regulation of endocrine and autonomic nerve responses, and aberrant connections in pain processing and the default mode network. This neuroimaging helps us understand the pathophysiology and outcomes of patients better. From the standpoint of brain connection, research in this area can further our understanding of the central pathophysiology of FGID and pave the way for the objective diagnosis and development of novel therapeutics for FGID. Prospective Neuroimaging research may change from brain mapping to clinical prognosis prediction due to technological advances in machine learning algorithms used in imaging. The usefulness and revelations of functional brain imaging are highlighted in this review, along with the areas that require development and, lastly, recommendations for future research.
功能性胃肠疾病(FGID)是常见疾病,与生活质量下降和医疗保健利用率增加有关。这些病症会影响肠道敏感性、蠕动、微生物群、免疫功能以及大脑中的神经处理过程。慢性症状,包括疼痛和消化不良,会因患者的适应不良行为、压力和共病而加剧。功能性神经影像学研究显示,与肠道感觉处理和显著线索相关的脑区反应增强,内分泌和自主神经反应的中枢调节改变,以及疼痛处理和默认模式网络中的连接异常。这种神经影像学有助于我们更好地理解患者的病理生理学和病情结果。从脑连接的角度来看,该领域的研究可以加深我们对FGID中枢病理生理学的理解,并为FGID的客观诊断和新型治疗方法的开发铺平道路。由于成像中使用的机器学习算法的技术进步,前瞻性神经影像学研究可能会从脑图谱转向临床预后预测。本综述强调了功能性脑成像的实用性和启示,以及需要发展的领域,最后还提出了未来研究的建议。