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A comparative mathematical evaluation of contour irregularity using form factor and PERBAS, a new analytical shape
C M Payne1, C G Bjore, D W Cromey
1Department of Pathology, University Medical Center, Tucson, Arizona.
Analytical and Quantitative Cytology and Histology
|October 1, 1989
Summary
Two shape factors, form factor (FF) and PErimeter Ratio Before and After Smoothing (PERBAS), were used to analyze nuclear contour irregularity. PERBAS effectively distinguished between Burkitt's lymphoma and Burkitt's-like lymphoma, showing potential for cancer diagnosis.
Area of Science:
- * Quantitative morphology
- * Biophysical analysis of cell shape
- * Computational pathology
Background:
- * Assessing cellular and nuclear contour irregularity is crucial for cancer diagnosis and prognosis.
- * Traditional shape analysis methods may not fully capture complex contour features like concavities.
- * Developing robust mathematical tools for shape analysis is essential for objective pathological assessment.
Purpose of the Study:
- * To mathematically evaluate contour irregularity using two distinct shape factors: form factor (FF) and PErimeter Ratio Before and After Smoothing (PERBAS).
- * To compare the sensitivity and specificity of FF and PERBAS in characterizing shape deformations and surface roughness.
- * To apply these shape factors in distinguishing between Burkitt's lymphoma (BL) and Burkitt's-like lymphoma (BLL) and assess their diagnostic potential.
Main Methods:
- * Calculation of form factor (FF) using the formula 4πA/P².
- * Determination of PERBAS by comparing the perimeter of a smoothed, convex contour to the original contour, utilizing a MOP-3 computerized image analyzer.
- * Analysis of computer-generated images to assess FF and PERBAS sensitivity to shape deformations and roughness.
Main Results:
- * Form factor (FF) was more sensitive to simple shape deformations without concavities, while PERBAS was more specific for surface roughness (concavities).
- * The PErimeter Ratio Before and After Smoothing (PERBAS) values significantly distinguished Burkitt's-like lymphoma (BLL) from Burkitt's lymphoma (BL) (P = .029), unlike form factor (FF) (P = .093).
- * Bivariate plotting of FF and PERBAS values revealed distinct morphometric shape domains, with BL cases showing less heterogeneity than BLL cases.
Conclusions:
- * The PERBAS method is a valuable tool for quantifying nuclear contour roughness and holds significant potential for cancer diagnosis.
- * Combining FF and PERBAS enhances shape discrimination, offering improved capabilities for cancer diagnosis and patient prognosis.
- * Quantitative analysis of nuclear shape heterogeneity can aid in differentiating between lymphoma subtypes and predicting outcomes.