Rosen G D, Harry J D
Dyslexia Neuroanatomical Research Laboratory, Beth Israel Hospital, Boston, MA 02215.
J Neurosci Methods. 1990 Nov;35(2):115-24. doi: 10.1016/0165-0270(90)90101-k.
Estimation of brain volume from serial sections typically involves using a rectangular. Cavalieri's, parabolic (Simpson's), or a trapezoidal rule to integrate numerically a curve of cross-sectional area measurements plotted against section number. We practically compare the efficacy of each of these methods using mathematical simulations of regularly- and irregularly-shaped "brain volumes" as well as actual morphometric measures from brain regions. There are no meaningful differences between the various estimates when many sections are used--with fewer sections. Cavalieri's estimator is most accurate. This confirms previous theoretical reports demonstrating the efficiency and accuracy of the Cavalieri estimator of volume, particularly when few sections are analyzed. While the Cavalieri approach provides a better approximation of volume under some circumstances, it requires equally spaced sections. We therefore describe methods for the estimation of brain volume from unequally spaced sections, including an estimator based on the fitting of piece-wise parabolic curves to the data. We outline a series of guidelines for the use of these mathematical rules in the estimation of brain volume from serial sections.
从连续切片估计脑容量通常涉及使用矩形、卡瓦列里法、抛物线(辛普森法)或梯形法则对绘制的截面积测量值与切片编号的曲线进行数值积分。我们通过对规则和不规则形状的“脑容量”进行数学模拟以及对脑区的实际形态测量,实际比较了这些方法的有效性。当使用许多切片时,各种估计之间没有显著差异——切片较少时,卡瓦列里估计器最准确。这证实了先前的理论报告,即证明了卡瓦列里体积估计器的效率和准确性,特别是在分析的切片较少时。虽然卡瓦列里方法在某些情况下能更好地近似体积,但它需要等间距的切片。因此,我们描述了从不等间距切片估计脑容量的方法,包括一种基于将分段抛物线曲线拟合到数据的估计器。我们概述了在从连续切片估计脑容量时使用这些数学规则的一系列指导方针。