MATLAB-based Methods Allow Precise, High-Throughput Quantification of Nuclear Morphology and Texture in...

Area of Science:

• Cardiovascular Pathology
• Computational Biology
• Histopathology

Background:

• Understanding cardiomyopathies is limited by a lack of quantitative histologic data.
• Ultrastructural remodeling in tachycardiomyopathy (T-CM) is not fully characterized.
• Existing methods lack the precision to quantify cellular and nuclear disarray.

Purpose of the Study:

• To develop and validate a MATLAB-based image analysis platform for quantifying nuclear and cellular disarray.
• To assess ultrastructural remodeling in an animal model of T-CM.
• To provide quantitative histologic data for cardiomyopathy research.

Main Methods:

• Developed a MATLAB platform for image analysis of nuclear morphometry, texture, orientation, and vascular architecture.
• Utilized an animal model of T-CM induced by high-rate pacing in rabbits (n=6).
• Compared T-CM group (n=3) with a sham-control group (n=3) using digitized left ventricular tissue.

Main Results:

• The software demonstrated high accuracy in nuclear segmentation, closely matching manual counts (r=0.981, p<0.001).
• T-CM hearts showed significantly enlarged nuclei (p=0.0042) and increased nuclear texture contrast (p=0.0149).
• Median vessel size increased in T-CM hearts (p<0.0001), indicating vascular remodeling.

Conclusions:

• The developed MATLAB platform enables high-throughput quantification of nuclear and extracellular disarray.
• The study identified nuclear enlargement and increased nuclear contrast as key features of T-CM ultrastructural remodeling.
• This tool provides valuable quantitative histologic data for studying cardiomyopathies.