Prognostic value of automatically extracted nuclear morphometric features in whole slide images of male breast cancer

Abstract

Numerous studies have shown the prognostic significance of nuclear morphometry in breast cancer patients. Wide acceptance of morphometric methods has, however, been hampered by the tedious and time consuming nature of the manual segmentation of nuclei and the lack of equipment for high throughput digitization of slides. Recently, whole slide imaging became more affordable and widely available, making fully digital pathology archives feasible. In this study, we employ an automatic nuclei segmentation algorithm to extract nuclear morphometry features related to size and we analyze their prognostic value in male breast cancer. The study population comprised 101 male breast cancer patients for whom survival data was available (median follow-up of 5.7 years). Automatic segmentation was performed on digitized tissue microarray slides, and for each patient, the mean nuclear area and the standard deviation of the nuclear area were calculated. In univariate survival analysis, a significant difference was found between patients with low and high mean nuclear area (P ¼ 0.022), while nuclear atypia score did not provide prognostic value. In Cox regression, mean nuclear area had independent additional prognostic value (P ¼ 0.032) to tumor size and tubule formation. In conclusion, we present an automatic method for nuclear morphometry and its application in male breast cancer prognosis. The automatically extracted mean nuclear area proved to be a significant prognostic indicator. With the increasing availability of slide scanning equipment in pathology labs, these kinds of quantitative approaches can be easily integrated in the workflow of routine pathology practice.

A nuclear circularity-based classifier for diagnostic distinction of desmoplastic from spindle cell melanoma in digitized histological images

“…[43] With respect to automated quantification of microscopic information, nuclear morphometry is clearly a useful diagnostic tool in several settings. [1617181920212627] Automated quantification of microscopic information can uncover differences not necessarily captured visually;[44] and in reverse, qualitative morphological impressions are hard to compare or quantify. Here, we applied a nuclear circularity-based classifier to confirm a morphological impression of the variation in nuclear shapes between SM and DM.…”

“…human epidermal growth factor receptor 2-immunolabeling intensity) has become part of the repertoire for many diagnostic pathologists. [11131415] Despite various studies reporting on classification of morphometric[3] and in particular nuclear features,[161718192021] these shape-based quantification tools are not widely established in routine surgical pathology. In contrast, there are several recent basic-science examples of clever combinations of computational morphometry, molecular-genetic, and functional methods.…”

“…[12022232425] The lack of adoption in the routine diagnostic setting is particularly surprising given that morphometry can provide clinically relevant information[8172026] and is able to solve diagnostic problems. [1617181920212627] Due to the drastically increasing performance and adoption of imaging solutions in pathology, one key opportunity of digital pathology quantitative shape-assessment, is largely unexplored.…”

Computer-aided prognosis on breast cancer with hematoxylin and eosin histopathology images: A review

“…For instance, size and shape features ( Figure 5(c)) can be utilized to quantify nuclei pleomorphism. 69 Spatial-arrangement-level features can describe biological domain-specific information between cells that are inextricably linked up with one another in histopathology images. For example, Voronoi f) and (i)) were used to grade the lymphocyte infiltration.…”

“…For examples, shape features could measure deviation in nuclei appearance, 94 and the mean nuclear area was an independent prognostic factor for male BC. 69 Texture features could describe the variation in chromatin distribution, which is generally more heterogeneous in higher grade BC cells. 89 And nuclear densitometric features were significantly associated with nuclear grading.…”