Fractal analysis for assessing tumour grade in microscopic images of breast tissue

Abstract

In 2006, breast cancer is expected to continue as the leading form of cancer diagnosed in women, and the second leading cause of cancer mortality in this group. A method that has proven useful for guiding the choice of treatment strategy is the assessment of histological tumor grade. The grading is based upon the mitosis count, nuclear pleomorphism, and tubular formation, and is known to be subject to inter-observer variability. Since cancer grade is one of the most significant predictors of prognosis, errors in grading can affect patient management and outcome. Hence, there is a need to develop a breast cancer-grading tool that is minimally operator dependent to reduce variability associated with the current grading system, and thereby reduce uncertainty that may impact patient outcome. In this work, we explored the potential of a computer-based approach using fractal analysis as a quantitative measure of cancer grade for breast specimens. More specifically, we developed and optimized computational tools to compute the fractal dimension of low-versus high-grade breast sections and found them to be significantly different,These results indicate that fractal dimension (a measure of morphologic complexity) may be a useful tool for demarcating low-versus high-grade cancer specimens, and has potential as an objective measure of breast cancer grade. Such prognostic value could provide more sensitive and specific information that would reduce inter-observer variability by aiding the pathologist in grading cancers.

Quantifying the architectural complexity of microscopic images of histology specimens

“…In recent studies, we employed fractal analysis on segmented histological structures of breast tissue sections that were stained with pan-keratin to highlight the epithelial components (Tambasco et al, 2007;Tambasco and Magliocco, 2008). These epithelial components comprised the multi-cellular structures (gland formations), cellular structures (individual cell shapes), and subcellular structures (distribution of keratin within the cells and nuclear shape).…”

Relationship between tumor grade and computed architectural complexity in breast cancer specimens

“…However, to our knowledge, there have been no studies performed to assess the degree of tumor differentiation in histologic breast specimens. We have recently developed a fractal analysis technique for the examination of histologic breast specimens [13]. As a preliminary assessment of this technique and to test the hypothesis that architectural complexity of epithelial structures increases with decreasing degree of tumor differentiation, we apply it to specimens of grades 1, 2, and 3 ductal carcinoma of the breast.…”

“…The original pan-keratin-stained image of a representative grade 1 tumor (left) is converted to binary (center) from which an outline image containing the architectural features of interest is created (right) (from Tambasco et al[13] with permission).…”

“…Diagrammatic representation of the box counting method (from Tambasco et al[13] with permission): the outline image (containing the structures of interest) is divided into boxes of differing sizes, and the number of boxes containing an outline is counted.…”