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Updated: Oct 25, 2026

Focussed Ion Beam Milling and Scanning Electron Microscopy of Brain Tissue
Published on: July 6, 2011
Histology-Guided Serial-Section Framework for Quasi-3D ToF-SIMS Molecular Imaging of Rat Brain Lipid Ions
Yuxuan Zhang1, Xiaoni Li1, Hao Wang2
1Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Center for Imaging and Systems Biology, College of Life and Environmental Sciences, Minzu University of China, Beijing100081, China.
Abstract:
Time-of-flight secondary ion mass spectrometry (ToF-SIMS) provides label-free molecular images of biological tissues, but an isolated two-dimensional brain section cannot represent variation along the anterior-posterior axis. Here, we developed a histology-guided workflow for serial, sparsely sampled sections that organizes ToF-SIMS ion images into anatomically referenced quasi-three-dimensional (quasi-3D) representations. Adjacent hematoxylin and eosin (H&E)-stained sections guided cross-modal alignment, and intensity-filtered point clouds supported brain-wide and region-of-interest (ROI) visualization. Parameter-sensitivity tests showed that major high-contrast anatomical patterns remained stable across intermediate threshold and interpolation settings; lower-intensity signals were progressively lost as the threshold increased, whereas greater interpolation density primarily improved display smoothness. Application to four independently acquired single-brain datasets showed that the same workflow accommodated differences in tissue geometry and signal distribution. Section-resolved principal component analysis and total-ion-current-normalized abundance summaries were used as exploratory outputs rather than treatment-effect tests because one brain was imaged per condition. This framework provides a reproducible way to organize serial, sparsely sampled ToF-SIMS data for quasi-3D visualization and anatomically referenced exploratory profiling when dense volumetric acquisition is not feasible within the available acquisition time and data volume.

