The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia

Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at × 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 × 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.

Development of a modified flyash as a permeable reactive barrier media for a former manufactured gas plant site Northern Ireland

A sequential biological permeable reactive barrier (PRB) was determined to be the best option for remediating groundwater that has become contaminated with a wide range of organic contaminants (i.e., benzene, toluene, ethylbenzene, xylene and polyaromatic hydrocarbons), heavy metals (i.e., lead and arsenic), and cyanide at a former manufactured gas plant after 150 years of operation in Portadown, Northern Ireland. The objective of this study was to develop a modified flyash that could be used in the initial cell within a sequential biological PRB to filter complex contaminated groundwater containing ammonium. Flyash modified with lime (CaOH) and alum was subjected to a series of batch tests which investigated the modified cation exchange capacity (CEC) and rate of removal of anions and cations from the solution. These tests showed that a high flyash composition medium (80%) could remove 8.65 mol of ammonium contaminant for every kilogram of medium. The modified CEC procedure ruled out the possibility of cation exchange as the major removal mechanism. The medium could also adsorb anions as well as cations (i.e., Pb and Cr), but not with the same capacity. The initial mechanism for Pb and Cr removal is probably precipitation. This is followed by sorption, which is possibly the only mechanism for the removal of dichromate anions. Scanning electron microscopic analysis revealed very small (