Statistical image processing quantifies the changes in cytoplasmic texture associated with aging in Caenorhabditis...

Area of Science:

• Cell biology
• Developmental biology
• Gerontology

Background:

• Oocyte quality declines with age, leading to reproductive errors.
• Oocyte appearance changes with age, suggesting a link to quality.
• Objective methods to quantify age-related oocyte appearance changes are lacking.

Purpose of the Study:

• To develop and validate quantitative methods for assessing age-associated changes in oocyte appearance.
• To utilize statistical image processing for objective oocyte aging analysis.

Main Methods:

• Applied statistical image processing to Nomarski differential interference contrast microscopy images of *C. elegans* oocytes.
• Quantified age-related cytoplasmic texture differences using Max-min value and Gray Level Co-occurrence Matrix (GLCM)-based Correlation (COR).
• Validated findings by manipulating synthetic images and performing manual measurements of cytoplasmic granule size.

Main Results:

• Max-min value quantitatively distinguished between 1-day-old and 3-day-old oocytes.
• COR demonstrated higher sensitivity than Max-min value in characterizing age-related texture differences.
• Synthetic image analysis confirmed that increasing granule size recapitulated age-associated COR changes, validated by manual measurements.

Conclusions:

• Max-min value and COR objectively quantify age-related changes in *C. elegans* oocyte appearance from microscopy images.
• These quantitative methods offer new avenues for investigating the mechanisms of oocyte aging.