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Internal Anatomy of the Kidney

Internal Anatomy of the Kidney

The kidneys are essential organs in the human body, performing a myriad of tasks that maintain homeostasis and overall health.
Anatomical Position and Dimensions
The kidneys are retroperitoneal organs positioned against the posterior abdominal wall on either side of the spine, roughly between the twelfth thoracic and third lumbar vertebrae. Each kidney is typically 10-12 cm long, 5-6 cm wide, and 3-4 cm thick, weighing about 150 grams.
Renal Cortex
The outermost region of the kidney is the...

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Related Experiment Video

Updated: May 6, 2026

Application of Laser Microdissection to Uncover Regional Transcriptomics in Human Kidney Tissue

Application of Laser Microdissection to Uncover Regional Transcriptomics in Human Kidney Tissue

Published on: June 9, 2020

Histopathologic Analysis of Human Kidney Spatial Transcriptomics Data: Toward Precision Pathology.

Pierre Isnard¹, Dian Li¹, Qiao Xuanyuan¹

¹Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri.

The American Journal of Pathology

|August 3, 2024

Summary

This summary is machine-generated.

Spatial transcriptomics (ST) data in nephrology can now be interpreted using morphology. This approach enhances understanding of kidney disease mechanisms at cellular and molecular levels, aiding precision pathology.

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Area of Science:

Nephrology
Genomics
Pathology

Background:

Spatial transcriptomics (ST) is revolutionizing tissue analysis, providing cellular and molecular insights in various diseases.
In nephrology, ST has enabled the creation of kidney atlases, but data interpretation often lacks morphologic correlation.
Current ST analysis typically superimposes computational clusters onto histology without initial morphologic or spatial identification.

Purpose of the Study:

To develop and validate a morphology-based approach for interpreting spatial transcriptomics data in human kidney samples.
To improve the understanding of cellular and molecular mechanisms underlying kidney diseases, particularly chronic kidney disease (CKD).
To establish pathology-based clusters as a reference for analyzing diverse kidney tissue samples.

Main Methods:

Modeled histopathologic ST data from a human kidney sample to closely match clinical biopsy samples.
Applied a morphology-based interpretation strategy to ST data, integrating tissue structure with molecular information.
Validated the projection of newly identified pathology-based clusters onto independent nephrectomy and needle biopsy slides.

Main Results:

Demonstrated the feasibility of a morphology-driven approach for ST data interpretation in nephrology.
Enhanced the understanding of lesion phenomena in chronic kidney disease at both cellular and molecular levels.
Successfully projected pathology-based clusters onto new kidney tissue samples, establishing them as reliable references.

Conclusions:

A morphology-based interpretation of ST data is feasible and beneficial for nephrology research and clinical practice.
This approach deepens the understanding of kidney disease pathogenesis and supports precision pathology.
Pathology-based ST clusters serve as a valuable reference for analyzing diverse kidney tissues, advancing molecular microscopy.