Investigating quantitative histological characteristics in renal pathology using HistoLens

Area of Science:

• Digital pathology
• Computational biology
• Medical imaging analysis

Background:

• Histological analysis is crucial for diagnosing diseases.
• Quantitative analysis of whole slide images (WSIs) presents challenges.
• Characterizing subtle histological differences between disease states requires advanced tools.

Purpose of the Study:

• To introduce HistoLens, an open-source MATLAB-based graphical user interface (GUI).
• To enable efficient visual and quantitative analysis of histological datasets, particularly WSIs.
• To facilitate the characterization of histological differences between disease and experimental groups.

Main Methods:

• HistoLens utilizes MATLAB AppDesigner for GUI development.
• It allows interrogation of digitally annotated WSIs.
• The tool visualizes 448 hand-engineered features (color, texture, morphology, distribution) across microanatomic sub-compartments.
• It enables mapping of differentially detected image features within images.

Main Results:

• HistoLens identified features correlating with renal glomerular characteristics distinguishing diabetic nephropathy and amyloid nephropathy from minimal change disease.
• The tool discovered quantitative glomerular features differentiating Tg26 transgenic mice (HIV-associated nephropathy model) from wild-type mice.
• These features corresponded to a progressive renal disease phenotype in the mouse model.

Conclusions:

• HistoLens provides an off-the-shelf, ready-to-use toolkit for quantitative renal pathology.
• The software facilitates the discovery and characterization of histological features relevant to kidney diseases.
• It aids in distinguishing between different nephropathies and understanding disease progression using quantitative image analysis.