Fiala J C, Harris K M
Boston University, Boston, MA 02215, USA.
J Am Med Inform Assoc. 2001 Jan-Feb;8(1):1-16. doi: 10.1136/jamia.2001.0080001.
Analysis of brain ultrastructure is needed to reveal how neurons communicate with one another via synapses and how disease processes alter this communication. In the past, such analyses have usually been based on single or paired sections obtained by electron microscopy. Reconstruction from multiple serial sections provides a much needed, richer representation of the three-dimensional organization of the brain. This paper introduces a new reconstruction system and new methods for analyzing in three dimensions the location and ultrastructure of neuronal components, such as synapses, which are distributed non-randomly throughout the brain.
Volumes are reconstructed by defining transformations that align the entire area of adjacent sections. Whole-field alignment requires rotation, translation, skew, scaling, and second-order nonlinear deformations. Such transformations are implemented by a linear combination of bivariate polynomials. Computer software for generating transformations based on user input is described. Stereological techniques for assessing structural distributions in reconstructed volumes are the unbiased bricking, disector, unbiased ratio, and per-length counting techniques. A new general method, the fractional counter, is also described. This unbiased technique relies on the counting of fractions of objects contained in a test volume. A volume of brain tissue from stratum radiatum of hippocampal area CA1 is reconstructed and analyzed for synaptic density to demonstrate and compare the techniques.
Reconstruction makes practicable volume-oriented analysis of ultrastructure using such techniques as the unbiased bricking and fractional counter methods. These analysis methods are less sensitive to the section-to-section variations in counts and section thickness, factors that contribute to the inaccuracy of other stereological methods. In addition, volume reconstruction facilitates visualization and modeling of structures and analysis of three-dimensional relationships such as synaptic connectivity.
需要对脑超微结构进行分析，以揭示神经元如何通过突触相互通信，以及疾病过程如何改变这种通信。过去，此类分析通常基于通过电子显微镜获得的单张或配对切片。从多个连续切片进行重建能提供对大脑三维组织结构急需的、更丰富的呈现。本文介绍一种新的重建系统以及用于三维分析神经元成分（如突触）的位置和超微结构的新方法，这些成分在整个大脑中呈非随机分布。
通过定义使相邻切片的整个区域对齐的变换来重建体积。全场对齐需要旋转、平移、倾斜、缩放和二阶非线性变形。此类变换通过二元多项式的线性组合来实现。描述了基于用户输入生成变换的计算机软件。用于评估重建体积中结构分布的体视学技术有无偏砌砖法、间隔叠代法、无偏比率法和每长度计数法。还描述了一种新的通用方法——分数计数器法。这种无偏技术依赖于对测试体积中所含物体分数的计数。对来自海马体CA1区辐射层的脑组织体积进行重建，并分析其突触密度，以演示和比较这些技术。
重建使得使用无偏砌砖法和分数计数器法等技术对超微结构进行切实可行的基于体积的分析成为可能。这些分析方法对计数的切片间变化和切片厚度不太敏感，而这些因素会导致其他体视学方法不准确。此外，体积重建有助于结构的可视化和建模以及对三维关系（如突触连接性）的分析。
