Basal lamina visualization using color image processing and pattern recognition.

Abstract

In histologic assessment, the absence of basal lamina is a useful feature for distinguishing invasive malignancy from benign and in situ lesions. As this feature is not possible to assess in routine H&E sections, pathologists have instead relied on histochemical and immunohistochemical stains to show components of the basal lamina such as laminin or type IV collagen. Standard image-processing software with the necessary image-processing toolbox (Matlab v5, Mathworks, Natick, MA) was used in a unique combination of color image processing and pattern recognition techniques to accentuate the collagenous stroma surrounding glands, which approximates basal lamina, in a series of benign, in situ, and invasive breast proliferations. Distinct differences in pattern were found between benign and invasive lesions, and also between in situ and malignant lesions, corresponding to that observed with type IV collagen immunostaining. Compared with immunostaining, this computer-generated method had a sensitivity of 0.96, specificity of 0.89, positive predictive value of 0.92, negative predictive value of 0.89, positive likelihood ratio of 9.1, and negative likelihood ratio of 0.042. Digital image processing serves as a less expensive and faster way of visualizing basal lamina and represents a useful adjunct to identify invasive malignancy in routinely stained sections. In addition, digital visualization of basal lamina is readily amenable to quantitative assessment, and the method provides a basis for the development of computer-based cancer diagnosis.