An automated machine vision system for the histological grading of cervical intraepithelial neoplasia (CIN)

The histological grading of cervical intraepithelial neoplasia (CIN) remains subjective, resulting in inter- and intra-observer variation and poor reproducibility in the grading of cervical lesions. This study has attempted to develop an objective grading system using automated machine vision. The architectural features of cervical squamous epithelium are quantitatively analysed using a combination of computerized digital image processing and Delaunay triangulation analysis; 230 images digitally captured from cases previously classified by a gynaecological pathologist included normal cervical squamous epithelium (n = 30), koilocytosis (n = 46), CIN 1 (n = 52), CIN 2 (n = 56), and CIN 3 (n=46). Intra- and inter-observer variation had kappa values of 0.502 and 0.415, respectively. A machine vision system was developed in KS400 macro programming language to segment and mark the centres of all nuclei within the epithelium. By object-oriented analysis of image components, the positional information of nuclei was used to construct a Delaunay triangulation mesh. Each mesh was analysed to compute triangle dimensions including the mean triangle area, the mean triangle edge length, and the number of triangles per unit area, giving an individual quantitative profile of measurements for each case. Discriminant analysis of the geometric data revealed the significant discriminatory variables from which a classification score was derived. The scoring system distinguished between normal and CIN 3 in 98.7% of cases and between koilocytosis and CIN 1 in 76.5% of cases, but only 62.3% of the CIN cases were classified into the correct group, with the CIN 2 group showing the highest rate of misclassification. Graphical plots of triangulation data demonstrated the continuum of morphological change from normal squamous epithelium to the highest grade of CIN, with overlapping of the groups originally defined by the pathologists. This study shows that automated location of nuclei in cervical biopsies using computerized image analysis is possible. Analysis of positional information enables quantitative evaluation of architectural features in CIN using Delaunay triangulation meshes, which is effective in the objective classification of CIN. This demonstrates the future potential of automated machine vision systems in diagnostic histopathology. Copyright (C) 2000 John Wiley and Sons, Ltd.

Measles virus minigenomes encoding two autofluorescent proteins reveal cell-to-cell variation in reporter expression dependent on viral sequences between the transcription units.

Transcription from morbillivirus genomes commences at a single promoter in the 3' non-coding terminus, with the six genes being transcribed sequentially. The 3' and 5' untranslated regions (UTRs) of the genes (mRNA sense), together with the intergenic trinucleotide spacer, comprise the non-coding sequences (NCS) of the virus and contain the conserved gene end and gene start signals, respectively. Bicistronic minigenomes containing transcription units (TUs) encoding autofluorescent reporter proteins separated by measles virus (MV) NCS were used to give a direct estimation of gene expression in single, living cells by assessing the relative amounts of each fluorescent protein in each cell. Initially, five minigenomes containing each of the MV NCS were generated. Assays were developed to determine the amount of each fluorescent protein in cells at both cell population and single-cell levels. This revealed significant variations in gene expression between cells expressing the same NCS-containing minigenome. The minigenome containing the M/F NCS produced significantly lower amounts of fluorescent protein from the second TU (TU2), compared with the other minigenomes. A minigenome with a truncated F 5' UTR had increased expression from TU2. This UTR is 524 nt longer than the other MV 5' UTRs. Insertions into the 5' UTR of the enhanced green fluorescent protein gene in the minigenome containing the N/P NCS showed that specific sequences, rather than just the additional length of F 5' UTR, govern this decreased expression from TU2.