Abstract
The kidney is a structurally and functionally complex organ responsible for the control of water, ion, and other solute homeostasis. Moreover, the kidneys excrete metabolic waste products and produce hormones, such as renin and erythropoietin. The functional unit of the kidney is the nephron, which is composed by a serial arrangement of a filter unit called the renal corpuscle and several tubular segments that modulate the filtered fluid by reabsorption and secretion. Within each kidney, thousands of nephrons are closely intermingled and surrounded by an intricate network of blood vessels and various interstitial cell types, including fibroblasts and immune cells. This complex tissue architecture is essential for proper kidney function. In fact, kidney disease is often reflected or even caused by a derangement of the histologic structures. Frequently, kidney histology is studied using microscopic analysis of 2-dimensional tissue sections, which, however, misses important 3-dimensional spatial information. Reconstruction of serial sections tries to overcome this limitation, but is technically challenging, time-consuming, and often inherently linked to sectioning artifacts. In recent years, advances in tissue preparation (e.g., optical clearing) and new light- and electron-microscopic methods have provided novel avenues for 3-dimensional kidney imaging. Combined with novel machine-learning algorithms, these approaches offer unprecedented options for large-scale and automated analysis of kidney structure and function. This review provides a brief overview of these emerging imaging technologies and presents key examples of how these approaches are already used to study the normal and the diseased kidney.
Santos, Rui