Gezginer Irmak, Chen Zhenyue, Yoshihara Hikari A I, Deán-Ben Xosé Luís, Razansky Daniel
Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Switzerland.
Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland.
Photoacoustics. 2023 Jun 9;31:100522. doi: 10.1016/j.pacs.2023.100522. eCollection 2023 Jun.
Optoacoustic tomography (OAT) provides a non-invasive means to characterize cerebral hemodynamics across an entire murine brain while attaining multi-parametric readouts not available with other modalities. This unique capability can massively impact our understanding of brain function. However, OAT largely lacks the soft tissue contrast required for unambiguous identification of brain regions. Hence, its accurate registration to a reference brain atlas is paramount for attaining meaningful functional readings. Herein, we capitalized on the simultaneously acquired bi-modal data from the recently-developed hybrid magnetic resonance optoacoustic tomography (MROT) scanner in order to devise an image coregistration paradigm that facilitates brain parcellation and anatomical referencing. We evaluated the performance of the proposed methodology by coregistering OAT data acquired with a standalone system using different registration methods. The enhanced performance is further demonstrated for functional OAT data analysis and characterization of stimulus-evoked brain responses. The suggested approach enables better consolidation of the research findings thus facilitating wider acceptance of OAT as a powerful neuroimaging tool to study brain functions and diseases.
光声断层扫描(OAT)提供了一种非侵入性方法,可在整个小鼠大脑中表征脑血流动力学,同时获得其他成像方式无法提供的多参数读数。这种独特的能力会极大地影响我们对脑功能的理解。然而,OAT在很大程度上缺乏明确识别脑区所需的软组织对比度。因此,将其精确配准到参考脑图谱对于获得有意义的功能读数至关重要。在此,我们利用最近开发的混合磁共振光声断层扫描(MROT)扫描仪同时获取的双模态数据,设计了一种图像配准范式,以促进脑区划分和解剖学参考。我们通过使用不同的配准方法对独立系统获取的OAT数据进行配准,评估了所提出方法的性能。在功能性OAT数据分析和刺激诱发脑反应的表征方面,进一步证明了该方法性能的提升。所建议的方法能够更好地整合研究结果,从而促进OAT作为一种强大的神经成像工具被更广泛地接受,用于研究脑功能和疾病。