The 3D EdgeRunner Pipeline: A Novel Shape-Based Analysis for Neoplasms Characterization

Area of Science:

• Medical Imaging
• Computational Pathology
• Oncology

Background:

• Current tumor characterization relies on qualitative assessments by experts.
• Quantitative shape analysis can improve diagnostic accuracy and efficiency.
• Distinguishing between benign and malignant tumors is crucial for treatment decisions.

Purpose of the Study:

• To introduce and describe the 3D EdgeRunner Pipeline for tumor shape characterization.
• To enable quantitative comparison of tumor shapes for improved classification.
• To explore shape features as non-invasive diagnostic markers.

Main Methods:

• The 3D EdgeRunner Pipeline analyzes tumor shape by measuring distances from edge points to a central field of view.
• A second derivative via five-point differentiation identifies rapid changes (peaks) in these distances.
• These peak coordinates serve as quantitative data for statistical tumor comparison.

Main Results:

• The pipeline successfully captures significant shape features (peaks) in kidney tumor samples.
• Quantitative shape data provides a novel approach to tumor characterization.
• Identified peaks correlate with tumor morphology, offering diagnostic insights.

Conclusions:

• The 3D EdgeRunner Pipeline offers a robust method for quantitative tumor shape analysis.
• This approach has the potential to enhance diagnostic accuracy and reduce invasive procedures.
• Further validation on diverse tumor types could establish its clinical utility.