High precision vibration sectioning for 3D imaging of the whole central nervous system

Canzhen Ma; Debin Xia; Shichang Huang; Qing Du; Jiajun Liu; Bo Zhang; Qingyuan Zhu; Guoqiang Bi; Hao Wang; Ronald X Xu

doi:10.1016/j.jneumeth.2023.109966

High precision vibration sectioning for 3D imaging of the whole central nervous system

J Neurosci Methods. 2023 Nov 1:399:109966. doi: 10.1016/j.jneumeth.2023.109966. Epub 2023 Sep 2.

Authors

Canzhen Ma¹, Debin Xia², Shichang Huang³, Qing Du⁴, Jiajun Liu², Bo Zhang², Qingyuan Zhu³, Guoqiang Bi⁵, Hao Wang⁶, Ronald X Xu⁷

Affiliations

¹ School of Engineering Science, University of Science and Technology of China, Hefei 230027, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China; School of Biomedical Engineering, University of Science and Technology of China, Suzhou 215123, China.
² Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China; National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei 230027, China.
³ Hefei National Laboratory for Physical Sciences at the Microscale, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230027, China.
⁴ Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China.
⁵ Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China; Hefei National Laboratory for Physical Sciences at the Microscale, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230027, China.
⁶ Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China; National Engineering Laboratory for Brain-inspired Intelligence Technology and Application, University of Science and Technology of China, Hefei 230027, China. Electronic address: haowang@ustc.edu.cn.
⁷ School of Engineering Science, University of Science and Technology of China, Hefei 230027, China; School of Biomedical Engineering, University of Science and Technology of China, Suzhou 215123, China. Electronic address: xux@ustc.edu.cn.

PMID: 37666283
DOI: 10.1016/j.jneumeth.2023.109966

Abstract

Background: Imaging and reconstruction of the morphology of neurons within the entire central nervous system (CNS) is important for deciphering the neural circuitry and related brain functions. With combination of tissue clearing and light sheet microscopy, previous studies have imaged the mouse CNS at cellular resolution, while remaining single axons unresolvable due to the tradeoff between sample size and imaging resolution. This could be improved by sectioning the sample into thick slices and imaged with high resolution light sheet microscopy as described in our previous study. However, the achievable quality for 3D imaging of serial thick slices is often hindered by surface undulation and other artifacts introduced by sectioning and handling limitations.

New methods: In order to improve the imaging quality for mouse CNS, we develop a high-performance vibratome system for sample sectioning and handling automation. The sectioning mechanism of the system was modeled theoretically and verified experimentally. The effects of process parameters and sample properties on sectioning accuracy were studied to optimize the sectioning outcome. The resultant imaging outcome was demonstrated on mouse samples.

Results: Our theoretical model of vibratome effectively depicts the relationship between the sample surface undulation errors and the sectioning parameters. With the guidance of the theoretical model, the vibratome is able to achieve a local surface undulation error of ±0.5 µm and a surface arithmetic mean deviation (Sa) of 220 nm for 300-μm-thick tissue slices. Imaging results of mouse CNS show the continuous sectioning capability of the vibratome.

Comparison with existing method: Our automatic sectioning and handling system is able to process serial thick slices for 3D imaging of the whole CNS at a single-axon resolution, superior to the commercially available vibratome devices.

Conclusion: Our automatic sectioning and handling system can be optimized to prepare thick sample slices with minimal surface undulation and manual manipulation in support of 3D brain mapping with high-throughput and high-accuracy.

Keywords: CNS imaging; Precision; Sectioning parameters; Single axon resolution; Vibratome.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Brain* / anatomy & histology
Central Nervous System / diagnostic imaging
Imaging, Three-Dimensional* / methods
Mice
Neurons / physiology
Vibration