Applications of functional and structural MRI features of the brain in pathomechanisms investigation, diagnosis, and rehabilitation of fibromyalgia

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题名:	Applications of functional and structural MRI features of the brain in pathomechanisms investigation, diagnosis, and rehabilitation of fibromyalgia
作者:	NHU, NGUYEN THANH
贡献者:	國際醫學研究博士學位學程康峻宏
关键词:	Fibromyalgia;MRI;Rehabilitation;Diagnosis;Chronic pain Fibromyalgia;MRI;Rehabilitation;Diagnosis;Chronic pain
日期:	2024-07-06
上传时间:	2024-11-06 13:33:53 (UTC+8)
摘要:	Fibromyalgia (FM) is characterized by widespread pain and psychological distress with unclear pathomechanisms. Previous studies used magnetic resonance imaging (MRI) to explore specific changes in the brains of FM patients, but the whole picture of neural changes and their applications in FM management are not completely understood. This dissertation aimed to investigate the MRI applications to pathomechanism understanding (Aim 1), diagnosis (Aim 2), and rehabilitation (Aim 3) in FM. FM patients and healthy controls were recruited. The participant's clinical presentation was assessed. Functional and structural MRIs were acquired and analyzed. For the first aim, the changes in the visual network (Study 1) and the associations between the brain-gut axis and psychological distress (Study 2) were explored. For the second aim, machine learning on fMRI features were used to classify FM patients from healthy controls (Study 3). For the third aim, we investigated the associations between clinical changes and MRI changes after rehabilitation (cognitive behavioral therapy [CBT]) in FM (Study 4). To support Study 4, we also systematically reviewed current evidence regarding the changes in fMRI features during rehabilitation and its predictive values in tracking rehabilitation in FM (Study 5). We found that fMRI features of visual networks were changed and associated with FM symptoms. The brain-gut axis, measured by fMRI and microbiota analysis, was associated with psychological distress in FM. The machine learning model of fMRI features identified FM patients with high performance. Our clinical trial and systematic review showed that fMRI features were specifically changed and might be used to track patient responses. In conclusion, MRI signals might serve as biomarkers for FM. The findings provided new insight into FM pathomechanisms and supported further studies addressing effective diagnosis methods and targeted therapies for FM using MRI features. Fibromyalgia (FM) is characterized by widespread pain and psychological distress with unclear pathomechanisms. Previous studies used magnetic resonance imaging (MRI) to explore specific changes in the brains of FM patients, but the whole picture of neural changes and their applications in FM management are not completely understood. This dissertation aimed to investigate the MRI applications to pathomechanism understanding (Aim 1), diagnosis (Aim 2), and rehabilitation (Aim 3) in FM. FM patients and healthy controls were recruited. The participant's clinical presentation was assessed. Functional and structural MRIs were acquired and analyzed. For the first aim, the changes in the visual network (Study 1) and the associations between the brain-gut axis and psychological distress (Study 2) were explored. For the second aim, machine learning on fMRI features were used to classify FM patients from healthy controls (Study 3). For the third aim, we investigated the associations between clinical changes and MRI changes after rehabilitation (cognitive behavioral therapy [CBT]) in FM (Study 4). To support Study 4, we also systematically reviewed current evidence regarding the changes in fMRI features during rehabilitation and its predictive values in tracking rehabilitation in FM (Study 5). We found that fMRI features of visual networks were changed and associated with FM symptoms. The brain-gut axis, measured by fMRI and microbiota analysis, was associated with psychological distress in FM. The machine learning model of fMRI features identified FM patients with high performance. Our clinical trial and systematic review showed that fMRI features were specifically changed and might be used to track patient responses. In conclusion, MRI signals might serve as biomarkers for FM. The findings provided new insight into FM pathomechanisms and supported further studies addressing effective diagnosis methods and targeted therapies for FM using MRI features.
描述:	博士指導教授：康峻宏口試委員：康峻宏口試委員：徐慈妤口試委員：羅?君口試委員：周立偉口試委員：韓德生
附注:	論文公開日期：2026-01-01
数据类型:	thesis
显示于类别:	[國際醫學研究碩博士學位學程] 博碩士論文

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