VolumestJ: A New Method and Tool for Volumetric Estimation of Brain Structures After Serial Sectioning

Abstract

[EN]Volume estimations are crucial for many neuroscience studies, allowing the evaluation of changes in the size of brain areas that may have relevant functional consequences. Classical histological methods and modern human brain imaging techniques rely on obtaining physical or digital sections, with a known thickness, of the organ to be analyzed. This “slicing” strategy is associated with an ineludible loss of information about the three-dimensional organization of the analyzed structures, especially affecting the precision of volumetric measurements. To overcome this problem, several methods have been developed. One of the most commonly used approaches for volume estimation is the classical Cavalieri’s method. Within this book chapter, we provide first an overview of Cavalieri’s method and propose a new one, named the truncated cone shape (TCS) method, for the estimation of volumes from tissue sections. Second, we compare the accuracy of both methods using computer-generated objects of different shapes and sizes. We conclude that, more frequently, the TCS method provides a better estimate of real volumes than Cavalieri’s method. And third, we describe a protocol to estimate volumes using a self-developed and freely available tool for ImageJ: VolumestJ (https://github.com/Jorvalgl/VolumestJ). This new tool helps to implement both Cavalieri’s and TCS methods using digital images of tissue sections. We consider that VolumestJ will facilitate the labor of researchers interested in volume estimations.