Abstract
ABSTRACT The size distribution of adipocytes in fat tissue provides important information about metabolic status and overall health of patients. Histological measurements of biopsied adipose tissue can reveal cardiovascular and/or cancer risks, to complement typical prognosis parameters such as body mass index, hypertension or diabetes. Yet, current methods for adipocyte quantification are problematic and insufficient. Methods such as hand-tracing are tedious and time-consuming, ellipse approximation lacks precision, and fully automated methods have not proven reliable. A semi-automated method fills the gap in goal-directed computational algorithms, specifically for high-throughput adipocyte quantification. Here, we design and develop a tool, AdipoCyze, which incorporates a novel semi-automated tracing algorithm, along with benchmark methods, and use breast histological images from the Komen for the Cure Foundation to assess utility. Speed and precision of the new approach are superior to conventional methods and accuracy is comparable, suggesting a viable option to quantify adipocytes, while increasing user flexibility. This platform is the first to provide multiple methods of quantification in a single tool. Widespread laboratory and clinical use of this program may enhance productivity and performance, and yield insight into patient metabolism, which may help evaluate risks for breast cancer progression in patients with comorbidities of obesity. ABBREVIATIONS: BMI: body mass index.
Highlights
Breast cancer incidence, progression and mortality continue to pose a serious public health challenge, among underserved patients and in safety net hospitals [1,2,3], where the prevalence of comorbid obesity and metabolic disease are high [4]
We have investigated chronic metabolic disease, Type 2 diabetes in the context of obesity [15], which associates with increased adipocyte size [16] and increased incidence, progression and mortality in breast cancer [17,18]
The area enclosed in the long-dash border contains poorly defined adipocyte cells with deteriorated cell membranes, indicative of poor fixation or nonuniform slices that are too thin for adipose tissue
Summary
Progression and mortality continue to pose a serious public health challenge, among underserved patients and in safety net hospitals [1,2,3], where the prevalence of comorbid obesity and metabolic disease are high [4]. We have investigated chronic metabolic disease, Type 2 diabetes in the context of obesity [15], which associates with increased adipocyte size [16] and increased incidence, progression and mortality in breast cancer [17,18]. A recent analysis of race and clinical outcomes in this trial demonstrated inferior outcomes for Black patients despite similar recurrence scores and comparable systemic therapy [23] This result supports the contention that factors beyond the genomic landscape are critical in determining worse outcomes in Black women. New pathology tools to characterize adipocyte dysfunction in obesity may help identify and stratify the highest risk patients, and assist clinical decision-making to reduce mortality
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