Correlation between stress drop and applied strain as a biomarker for tumor detection

Area of Science:

• Biomedical Engineering
• Biophysics
• Materials Science

Background:

• Assessing tumor viscoelasticity is crucial for diagnosis.
• Existing methods for quantifying viscoelasticity can be time-consuming.
• A need exists for efficient and accurate biomarkers for tumor detection.

Purpose of the Study:

• To develop and validate a time-efficient method for measuring tumor viscoelastic behavior.
• To investigate the stress drop-strain (Δσ-ε) relation as a potential biomarker for tumor detection.
• To differentiate between tumor and normal tissues based on viscoelastic properties.

Main Methods:

• Stepwise compression-relaxation testing using a 2D tactile sensor.
• Quantification of the Δσ-ε relation using Pearson correlation analysis (slope and R²).
• Measurement of ex vivo breast tumor (BT) tissues, in vivo pancreatic tumor (PT) tissues, and normal tissues.

Main Results:

• The coefficient of determination (R²) showed significant differences between tumor sites and normal tissues.
• R² distinguished between pre- and post-treatment PT tissues, with post-treatment tissues resembling normal tissues.
• The slope parameter failed to differentiate between PT and BT tissues, highlighting the importance of R².

Conclusions:

• The Δσ-ε relation, particularly R², serves as a sensitive biomarker for tumor detection and treatment monitoring.
• This method provides a time-efficient alternative to traditional viscoelastic modeling for tumor analysis.
• The findings support the potential of tactile sensing for non-invasive tumor characterization.