Nuclear-labeling index analysis (NLIA), a software package used to performaccurate automation of cell nuclear-labeling index analysis on immunohistochemically stained rat liver samples

The nuclear labeling index (labeled nuclei/100 nuclei) and the apoptotic in dex (apoptotic cells/100 cells) are important parameters of cell growth and death. Automatic counting of labeled nuclei is desirable since manual coun ting is tedious, time-consuming, and with a greater potential for inaccurac ies. A nuclear-labeling index analysis (NLIA) software package was develope d in this laboratory to perform the counting process automatically and accu rately. This software package consists of an application program NLIA and a set of macros for obtaining nuclear data that is used in Scion Image. It i s designed to work cooperatively with Scion Image. Adobe Photoshop, and Mic rosoft Office. NLIA has two basic functions: building nuclear data files an d analyzing nuclear data. A color image captured from an immunohistochemica lly stained or autoradiographic sample is loaded into NLIA. Nuclear data ca n be entered into the program manually, automatically, or in combination. I n the manual data entering mode, NLIA acts as an object-counting tool, whil e in the automatic mode it acts as a data picker: picking up the data gener ated by Scion Image into memory. A method to enter nuclear data (both label ed nuclei and unlabeled nuclei) in the automatic mode is described. The col or image is processed in Adobe Photoshop, where the interested color ranges are selected and separated. These are then analyzed in Scion image with th e help of the macros for obtaining nuclear data. Since the advanced particl e analysis function is used, the counting process is automatic and rapid. D ata from thousands of nuclei can be obtained within seconds. To ensure the accuracy of the analysis, a nuclear data checking and edit feature is emplo yed in NLIA: results of computer-generated counting can be compared with th e original color image by overlaying the plot of counting results onto the original color image. In this way any computer counting mistakes can be eas ily discovered and corrected by the operator. Corrected nuclear data (inclu ding nuclear size, location, shape) are then stored in data files. These da ta files can be used in NLIA to obtain cell density and nuclear labeling in dices. Because criteria for obtaining nuclear data (truncation diameter, sh ape factor) can be set by the operator in NLIA, nuclear size distribution a nd shape variation can be analyzed. This method provides a fast and accurat e way to determine cell nuclear-labeling indices. Currently, Scion Image is a freeware on the internet, and NLIA software package is available from ou r lab home page. Methods presented here expand the Scion Image ability to a nalyze color images by using color separation techniques in a commercial gr aphic application. The instrumentation required can be relatively inexpensi ve, and the methods described may be useful in studies of cell kinetics, le sion growth, and tumor therapy. (C) 263 Elsevier Science Ireland Ltd. All r ights reserved.