Data_Sheet_1_Identification of resting-state networks using dynamic brain perfusion SPECT imaging: A fSPECT case report.pdf

Connectivity studies with nuclear medicine systems are scarce in literature. They mainly employ PET imaging and group level analyses due to the low temporal resolution of PET and especially SPECT imaging. Our current study analyses connectivity at an individual level using dynamic SPECT imaging, which has been enabled by the improved temporal resolution performances provided by the 360°CZT cameras. We present the case of an 80-year-old man referred for brain perfusion SPECT imaging for cognitive disorders for whom a dynamic SPECT acquisition was performed utilizing a 360°CZT camera (temporal sampling of 15 frames × 3 s, 10 frames × 15 s, 14 frames × 30 s), followed by a conventional static acquisition of 15 m. Functional SPECT connectivity (fSPECT) was assessed through a seed correlation analysis and 5 well-known resting-state networks were identified: the executive, the default mode, the sensory motor, the salience, and the visual networks. This case report supports the feasibility of fSPECT imaging to identify well known resting-state networks, thanks to the novel properties of a 360°CZT camera, and opens the way to the development of more dedicated functional connectivity studies using brain perfusion SPECT imaging.

核医学系统相关的脑连接研究在学术文献中较为罕见。由于正电子发射断层扫描（Positron Emission Tomography, PET）尤其是单光子发射计算机断层扫描（Single-Photon Emission Computed Tomography, SPECT）的时间分辨率较低，此类研究多采用PET成像与组水平分析策略。本研究借助360° CZT探测器相机提升的时间分辨率性能，采用动态SPECT成像技术开展个体水平的脑连接分析。我们报告一例因认知障碍就诊、接受脑灌注SPECT成像的80岁男性病例：该病例采用360° CZT探测器相机完成动态SPECT采集（时间采样方案为15帧×3秒、10帧×15秒、14帧×30秒），随后进行15分钟常规静态采集。通过种子相关分析评估功能SPECT连接（fSPECT），共识别出5种经典静息态网络：执行控制网络、默认模式网络、感觉运动网络、突显网络及视觉网络。本病例报告证实，依托360° CZT探测器相机的新型性能，采用fSPECT成像识别经典静息态网络具备可行性，同时为基于脑灌注SPECT成像的专业化功能连接研究开辟了新路径。