Visualizing trigeminal neuralgia at 7 Tesla: Advancing etiological understanding and improving future clinical imaging protocols

7 特斯拉可视化三叉神经痛：促进病因学理解并改进未来的临床成像方案

• 批准号: 10667246
• 负责人: Priti Balchandani
• 金额: $ 53.21万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-06 至 2024-05-05
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10667246
• 关键词: Affect; Anatomy; Area; Automobile Driving; Blood Vessels; Brain; Brain Stem; Brain region; Cerebral cortex; Cerebrum; Chronic; Classification; Clinical; Cranial Nerves; Data; Demyelinations; Development; Devices; Diagnosis; Diffusion; Disease; Esthesia; Etiology; Evaluation; Face; Facial Pain; Functional Imaging; Functional disorder; Future; Hour; Image; Image Enhancement; Imaging Techniques; Incidence; Infarction; Inflammatory; Injury; Lead; Length; Lesion; Link; MRI Scans; Magnetic Resonance Imaging; Measurement; Measures; Methods; Multimodal Imaging; Multiple Sclerosis; Nerve; Neuropsychology; Noise; Operative Surgical Procedures; Pain; Pain intensity; Pathway Analysis; Pathway interactions; Patients; Persons; Pharmacology; Physiologic pulse; Plant Roots; Prospective Studies; Protocols documentation; Psyche structure; Recurrent pain; Resolution; Scanning; Sensitivity and Specificity; Sensory; Sensory Thresholds; Shock; Side; Signal Transduction; Somatosensory Cortex; Structure; Structure of trigeminal ganglion; Structure of trigeminal nerve spinal tract nucleus; Techniques; Testing; Thalamic structure; Translations; Treatment outcome; Trigeminal Neuralgia; Trigeminal System; Trigeminal nerve structure; base; brain abnormalities; clinical application; clinical imaging; clinically significant; connectome; effective therapy; experience; graph theory; gray matter; imaging biomarker; imaging modality; improved; magnetic field; member; multimodal data; multimodality; neurovascular; novel; pain sensation; radio frequency; side effect; standard of care; targeted treatment; tractography; tumor; white matter; wireless

Project Summary Trigeminal Neuralgia (TN) is one of the most painful disorders ever identified and affects 4.3 out of every 100,000 people in the US. In its most typical form, it causes brief attacks of intense shock-like pain on one side of the face. Although it is known to be associated with the trigeminal or 5th cranial nerve, its overall etiology remains poorly understood. A multitude of pharmacological and surgical methods have been used to treat TN, with varying levels of long-term efficacy, but treatment remains challenging given that TN pain may be caused by any of a myriad of underlying abnormalities that may not always be identifiable using current clinical workups. Clinically, magnetic resonance imaging (MRI) is used to detect neurovascular compression (NVC), conventionally understood to be a main cause of TN, and to rule out other potential etiologies such as lesions or multiple sclerosis. However, pain eventually recurs in nearly half of patients whose NVC was treated surgically, and NVC is often identified in people who do not have TN. Although current MRI protocols are important in the pre-surgical assessment of NVC, they likely lack the resolution, quantitative accuracy, and scope required to simultaneously interrogate the entire trigeminal sensory pathway, as well as the brain networks associated with the sensation, evaluation, and modulation of pain that may also contribute to TN. There remains a critical unmet need to comprehensively study the regions and networks implicated in TN and reliably and accurately identify the true cause of pain in TN patients. MRI at ultrahigh magnetic fields such as 7 Tesla (7T) provides increased signal to noise ratio, which yields images with exquisite resolution that can elucidate subtle anatomical, vascular, microstructural, and functional alterations in unprecedented detail. Therefore, we will perform a systematic prospective study of TN patients (half with identified NVC and half idiopathic) and matched healthy controls using a state-of-the-art, TN-specific, multimodal 7T MRI protocol composed of high-resolution structural, vascular, diffusion, and functional imaging sequences. We propose three aims directed towards our central hypothesis: 1) To develop new imaging techniques to better visualize all possible brain regions implicated in TN; 2) To perform qualitative and quantitative analysis of 7T multimodal images to characterize the structural integrity of the trigeminal sensory pathway along its entire length from the trigeminal ganglion to the primary somatosensory cortex; 3) To perform whole-brain structural and functional network analyses to reveal abnormalities in networks associated with pain sensation and modulation in TN patients; and 4) To evaluate translation of our 7T findings to 3 Tesla clinical scanners. Successful completion of this study should yield imaging markers that are tightly linked to the pathophysiology of TN, and could lead to a more complete understanding of TN, ultimately resulting in more targeted and effective treatments for this painful affliction.

项目摘要 三叉神经痛（TN）是有史以来最痛苦的疾病之一，影响4.3每一个 在美国有10万人。在其最典型的形式，它会导致短暂的攻击强烈休克一样的疼痛一侧 的脸。虽然已知其与三叉神经或第五脑神经有关，但其总体病因 仍然知之甚少。许多药物和手术方法已被用于治疗 TN，具有不同水平的长期疗效，但治疗仍然具有挑战性，因为TN疼痛可能 由无数潜在异常中的任何一种引起，这些异常可能并不总是可以使用电流识别 临床检查临床上，磁共振成像（MRI）用于检测神经血管 压缩（NVC），传统上被理解为TN的主要原因，并排除其他潜在的 病因如病变或多发性硬化症。然而，疼痛最终在近一半的患者中复发， NVC是通过手术治疗的，NVC通常在没有TN的人中发现。虽然目前的MRI 协议是重要的术前评估NVC，他们可能缺乏分辨率，定量 准确性和范围，同时询问整个三叉神经感觉通路，以及 与疼痛的感觉、评估和调节相关的大脑网络也可能有助于 TN.仍然有一个关键的未满足的需要，全面研究涉及TN的区域和网络 并可靠和准确地识别TN患者疼痛的真正原因。磁共振成像在低磁场， 因为7特斯拉（7 T）提供了更高的信噪比，从而产生具有精致分辨率的图像， 以前所未有的细节阐明微妙的解剖学、血管、显微结构和功能变化。 因此，我们将对TN患者进行系统的前瞻性研究（一半为确定的NVC，一半为确定的NVC）。 特发性）和匹配的健康对照，使用最先进的、TN特异性、多模式7 T MRI方案 由高分辨率结构、血管、扩散和功能成像序列组成。我们提出 我们的中心假设有三个目标：1）开发新的成像技术， 所有可能参与TN的脑区; 2）对7 T进行定性和定量分析 多模态图像来表征三叉神经感觉通路的结构完整性，沿着其整个 从三叉神经节到初级躯体感觉皮层的长度; 3）进行全脑结构检查 和功能网络分析，以揭示与疼痛感觉相关的网络异常， TN患者中的调制;以及4）评估我们的7 T发现到3特斯拉临床扫描仪的转化。 成功完成本研究应产生与病理生理学密切相关的成像标记物 的TN，并可能导致更完整的了解TN，最终导致更有针对性， 有效的治疗方法。