7 T and beyond: toward a synergy between fMRI-based presurgical mapping at ultrahigh magnetic fields, AI, and robotic neurosurgery.

IF 3.7 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING European Radiology Experimental Pub Date : 2024-07-01 DOI:10.1186/s41747-024-00472-y
Mohamed L Seghier
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Abstract

Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce postsurgical morbidity. Here, we discuss presurgical fMRI mapping at ultra-high magnetic fields (UHF), i.e., ≥ 7 T, in the light of the current growing interest in artificial intelligence (AI) and robot-assisted neurosurgery. The potential of submillimetre fMRI mapping can help better appreciate uncertainty on resection margins, though geometric distortions at UHF might lessen the accuracy of fMRI maps. A useful trade-off for UHF fMRI is to collect data with 1-mm isotropic resolution to ensure high sensitivity and subsequently a low risk of false negatives. Scanning at UHF might yield a revival interest in slow event-related fMRI, thereby offering a richer depiction of the dynamics of fMRI responses. The potential applications of AI concern denoising and artefact removal, generation of super-resolution fMRI maps, and accurate fusion or coregistration between anatomical and fMRI maps. The latter can benefit from the use of T1-weighted echo-planar imaging for better visualization of brain activations. Such AI-augmented fMRI maps would provide high-quality input data to robotic surgery systems, thereby improving the accuracy and reliability of robot-assisted neurosurgery. Ultimately, the advancement in fMRI at UHF would promote clinically useful synergies between fMRI, AI, and robotic neurosurgery.Relevance statement This review highlights the potential synergies between fMRI at UHF, AI, and robotic neurosurgery in improving the accuracy and reliability of fMRI-based presurgical mapping.Key points• Presurgical fMRI mapping at UHF improves spatial resolution and sensitivity.• Slow event-related designs offer a richer depiction of fMRI responses dynamics.• AI can support denoising, artefact removal, and generation of super-resolution fMRI maps.• AI-augmented fMRI maps can provide high-quality input data to robotic surgery systems.

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7 T 及以上:实现超高磁场下基于 fMRI 的术前绘图、人工智能和机器人神经外科手术之间的协同作用。
通过功能磁共振成像(fMRI)进行术前评估可降低术后发病率。鉴于目前人们对人工智能(AI)和机器人辅助神经外科手术的兴趣与日俱增,我们在此讨论超高磁场(UHF)(即≥ 7 T)下的术前 fMRI 映像。亚毫米级 fMRI 图谱的潜力有助于更好地了解切除边缘的不确定性,不过超高频的几何失真可能会降低 fMRI 图谱的准确性。超高频 fMRI 的一个有效权衡方法是收集 1 毫米各向同性分辨率的数据,以确保高灵敏度和较低的假阴性风险。超高频扫描可能会重新激发对慢速事件相关 fMRI 的兴趣,从而提供更丰富的 fMRI 反应动态描述。人工智能的潜在应用涉及去噪和去除伪影、生成超分辨率 fMRI 图谱以及解剖图和 fMRI 图之间的精确融合或核心配准。后者可受益于 T1 加权回声平面成像的使用,以更好地显示大脑激活。这种人工智能增强的 fMRI 地图将为机器人手术系统提供高质量的输入数据,从而提高机器人辅助神经外科手术的准确性和可靠性。最终,超高频 fMRI 的进步将促进 fMRI、人工智能和机器人神经外科之间产生临床有用的协同效应。 相关性声明 本综述强调了超高频 fMRI、人工智能和机器人神经外科之间在提高基于 fMRI 的术前映射的准确性和可靠性方面的潜在协同效应。人工智能可支持去噪、去除伪影和生成超分辨率的 fMRI 地图,人工智能增强的 fMRI 地图可为机器人手术系统提供高质量的输入数据。
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来源期刊
European Radiology Experimental
European Radiology Experimental Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
6.70
自引率
2.60%
发文量
56
审稿时长
18 weeks
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