Quantitative characterization of preneoplastic progression using single-cell computed tomography and...

Area of Science:

• Biomedical Engineering
• Cell Biology
• Medical Imaging

Background:

• Characterizing preneoplastic progression requires high-resolution 3D cell imaging and advanced image processing.
• Morphological biosignatures are crucial for precise preneoplastic characterization.

Purpose of the Study:

• To quantitatively characterize nuclear structure alterations in human esophageal epithelial cells during preneoplastic progression.
• To develop and apply automated 3D karyometry for analyzing morphological differences.

Main Methods:

• Utilized single-cell optical tomography to acquire 3D cell images from hematoxylin-stained esophageal epithelial cells.
• Developed novel, fully automated algorithms for 3D segmentation of cellular, nuclear, and subnuclear components.
• Computed 41 quantitative morphological descriptors and analyzed nuclear DNA spatial distribution and texture.

Main Results:

• Successfully discriminated between normal, metaplastic, and dysplastic esophageal cell lines using 3D karyometric descriptors.
• Identified key morphometric hallmarks of cancer progression, including increased nuclear size and altered chromatin texture.
• Demonstrated quantitative differences in morphology correlating with preneoplastic progression.

Conclusions:

• The developed 3D optical tomography and automated 3D karyometry method enables precise quantitative characterization of nuclear morphology.
• This approach effectively distinguishes between different stages of esophageal epithelial cell progression.
• The findings suggest potential clinical applications for early cancer detection through detailed cellular morphology analysis.