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Pittsburgh Computational Pathology Interest Group is a special group formed to bring focus on developing basic computer vision and and machine learning algorithms for transmitted light and fluorescence microscopy imaging data from histopathology and highlight the translation role of computational pathology research in interfacing with genomics, personalized medicine and microbiomics.
Our goal is to promote a vibrant community of computational pathology research and education practices here in Pittsburgh by engaging researchers and clinicians across Pitt, CMU and Duquesne campuses, and the local industrial partners.
The complex structural network of the tissue system highlights the need for a systems biology approach to anatomic pathology, in which quantification of key system processes, including stromal component, is combined with informatics tools to produce actionable scores to aid clinical decision-making. Cernostics has developed a platform for quantitative, multiplexed biomarker assessment, termed TissueCypher trade;, which applies systems biology to anatomic pathology. TissueCypher™ employs multiplexed fluorescence labeling of key epithelial and stromal biomarkers in anatomic pathology specimens with whole slide fluorescence imaging, and automated image analysis to quantify biomarker expression and spatial relationships in the context of tissue morphology. This approach is coupled to classifier software to integrate multivariable biomarker and morphology feature data to produce actionable scores. Cernostics is applying the TissueCypher™ approach to tackle unmet needs in the management of patients with Barrett’s esophagus, which is a precursor to esophageal adenocarcinoma. The TissueCypher™ Barrett’s Esophagus Assay evaluates baseline/index esophageal biopsies, and integrates quantitative data from multiple epithelial and stromal biomarkers and morphometrics to produce an individualized risk score that is correlated with risk of malignant progression. The risk score is actionable, and can be used to guide surveillance frequencies and therapeutic interventions in patients with Barrett’s Esophagus, which has the potential to optimize use of care and to improve patient outcomes.
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