The development of morphological biosignatures to precisely characterize preneoplastic progression necessitates high-resolution three-dimensional (3D) cell imagery and robust image processing algorithms. We report on the quantitative characterization of nuclear structure alterations associated with preneoplastic progression in human esophageal epithelial cells using single-cell optical tomography and fully automated 3D karyometry. We stained cultured cells with hematoxylin and generated 3D images of individual cells by mathematically reconstructing 500 projection images acquired using optical absorption tomographic imaging. For 3D karyometry, we developed novel, fully automated algorithms to robustly segment the cellular, nuclear, and subnuclear components in the acquired cell images, and computed 41 quantitative morphological descriptors from these segmented volumes. In addition, we developed algorithms to quantify the spatial distribution and texture of the nuclear DNA. We applied our methods to normal, metaplastic, and dysplastic human esophageal epithelial cell lines, analyzing 100 cells per line. The 3D karyometric descriptors elucidated quantitative differences in morphology and enabled robust discrimination between cell lines on the basis of extracted morphological features. The morphometric hallmarks of cancer progression such as increased nuclear size, elevated nuclear content, and anomalous chromatin texture and distribution correlated with this preneoplastic progression model, pointing to the clinical use of our method for early cancer detection. ' 2010 International Society for
Advancement of CytometryKey terms preneoplastic progression; Barrett's esophagus; esophageal cancer; single cell; computed tomography; 3D karyometry; image processing NUCLEAR architecture is a key factor in cell functioning and pathogenesis (1). The functional relevance of nuclear structure in many core cell processes necessitates detailed studies on the interplay between nuclear architecture and functions like gene expression. One of the most important applications of three-dimensional (3D) karyometric studies is the quantitative characterization of the morphological changes associated with malignancy. Alterations in nuclear structure hold high clinical and research relevance, especially in the context of early cancer detection (2,3). Although much remains to be learned about the molecular mechanisms that drive cancerrelated alterations in nuclear structure and the higher-order spatial organization of chromatin, accurate quantification of structural parameters could be beneficial for developing robust biosignatures for early cancer detection.Rapid advances in automation sciences and imaging technologies have facilitated the use of computer-aided karyometry, where sets of morphological descriptors (referred to as morphometric signatures) are extracted from microscopy images using digital image processing algorithms. Morphometric signatures generated from a statistically significant number of cells may then be used to p...