BACKGROUND: A definitive diagnosis of urothelial carcinoma in urine cytology is often challenging and subjective. Many urine cytology samples receive an indeterminate diagnosis. Ancillary techniques such as fluorescence in situ hybridization (FISH) have been used to improve the diagnostic sensitivity, but FISH is not approved as a routine screening test, and the complex fluorescent staining protocol also limits its widespread clinical use. Quantitative phase imaging (QPI) is an emerging technology allowing accurate measurements of the single-cell dry mass. This study was undertaken to explore the ability of QPI to improve the diagnostic accuracy of urine cytology for malignancy. METHODS: QPI was performed on unstained, ThinPrep-prepared urine cytology slides from 28 patients with 4 categories of cytological diagnoses (negative, atypical, suspicious, and positive for malignancy). The nuclear/cell dry mass, the entropy, and the nucleus-to-cell mass ratio were calculated for several hundred cells for each patient, and they were then correlated with the follow-up diagnoses. RESULTS: The nuclear mass and nuclear mass entropy of urothelial cells showed significant differences between negative and positive groups. These data showed a progressive increase from patients with negative diagnosis, to patients with atypical/suspicious and positive cytologic diagnosis. Most importantly, among the patients in the atypical and suspicious diagnosis, the nuclear mass and its entropy were significantly higher for those patients with a follow-up diagnosis of malignancy than those patients without a subsequent follow-up diagnosis of malignancy. CONCLUSIONS: QPI shows potential for improving the diagnostic accuracy of urine cytology, especially for indeterminate cases, and should be further evaluated as an ancillary test for urine cytology. Cancer Cytopathol 2016;124:641–50. © 2016 American Cancer Society.
CITATION STYLE
Pham, H. V., Pantanowitz, L., & Liu, Y. (2016). Quantitative phase imaging to improve the diagnostic accuracy of urine cytology. Cancer Cytopathology, 124(9), 641–650. https://doi.org/10.1002/cncy.21734
Mendeley helps you to discover research relevant for your work.