Clinical monitoring of ocular physiology using digital image analysis

Aim: To examine the use of image analysis to quantify changes in ocular physiology. Method: A purpose designed computer program was written to objectively quantify bulbar hyperaemia, tarsal redness, corneal staining and tarsal staining. Thresholding, colour extraction and edge detection paradigms were investigated. The repeatability (stability) of each technique to changes in image luminance was assessed. A clinical pictorial grading scale was analysed to examine the repeatability and validity of the chosen image analysis technique. Results: Edge detection using a 3 × 3 kernel was found to be the most stable to changes in image luminance (2.6% over a +60 to -90% luminance range) and correlated well with the CCLRU scale images of bulbar hyperaemia (r = 0.96), corneal staining (r = 0.85) and the staining of palpebral roughness (r = 0.96). Extraction of the red colour plane demonstrated the best correlation-sensitivity combination for palpebral hyperaemia (r = 0.96). Repeatability variability was <0.5%. Conclusions: Digital imaging, in conjunction with computerised image analysis, allows objective, clinically valid and repeatable quantification of ocular features. It offers the possibility of improved diagnosis and monitoring of changes in ocular physiology in clinical practice. © 2003 British Contact Lens Association. Published by Elsevier Science Ltd. All rights reserved.

Digital pathology and image analysis in tissue biomarker research

Digital pathology and the adoption of image analysis have grown rapidly in the last few years. This is largely due to the implementation of whole slide scanning, advances in software and computer processing capacity and the increasing importance of tissue-based research for biomarker discovery and stratified medicine. This review sets out the key application areas for digital pathology and image analysis, with a particular focus on research and biomarker discovery. A variety of image analysis applications are reviewed including nuclear morphometry and tissue architecture analysis, but with emphasis on immunohistochemistry and fluorescence analysis of tissue biomarkers. Digital pathology and image analysis have important roles across the drug/companion diagnostic development pipeline including biobanking, molecular pathology, tissue microarray analysis, molecular profiling of tissue and these important developments are reviewed. Underpinning all of these important developments is the need for high quality tissue samples and the impact of pre-analytical variables on tissue research is discussed. This requirement is combined with practical advice on setting up and running a digital pathology laboratory. Finally, we discuss the need to integrate digital image analysis data with epidemiological, clinical and genomic data in order to fully understand the relationship between genotype and phenotype and to drive discovery and the delivery of personalized medicine.

Computer-assisted image analysis of liver collagen: relationship to Ishak scoring and hepatic venous pressure gradient

Histopathological scoring of disease stage uses descriptive categories without measuring the amount of fibrosis. Collagen, the major component of fibrous tissue, can be quantified by computer-assisted digital image analysis (DIA) using histological sections. We determined relationships between DIA, Ishak stage, and hepatic venous pressure gradient (HVPG) reflecting severity of fibrosis. One hundred fifteen patients with hepatitis C virus (HCV) who had undergone transplantation had 250 consecutive transjugular liver biopsies combined with HVPG (median length, 22 mm; median total portal tracts, 12), evaluated using the Ishak system and stained with Sirus red for DIA. Liver collagen was expressed as collagen proportionate area (CPA). Median CPA was 6% (0.2-45), correlating with Ishak stage (stage 6 range, 13%-45%), and with HVPG (r = 0.62; P < 0.001). Median CPA was 4.1% when HVPG was less than 6 mm Hg and 13.8% when HVPG was 6 mm Hg or more (P < 0.0001) and 6% when HVPG was less than 10 mm Hg and 17.3% when HVPG was 10 mm Hg or higher (P < 0.0001). Only CPA, not Ishak stage/grade, was independently associated by logistic regression, with HVPG of 6 mm Hg or more [odds ratio, 1.206; 95% confidence interval (CI), 1.094-1.331; P < 0.001], or HVPG of 10 mm Hg or more (odds ratio, 1.105; 95% CI, 1.026-1.191; P = 0.009). CPA increased by 50% (3.6%) compared with 20% in HVPG (1 mm Hg) in 38 patients with repeated biopsies. Conclusion: CPA assessed by DIA correlated with Ishak stage scores and HVPG measured contemporaneously. CPA was a better histological correlate with HVPG than Ishak stage, had a greater numerical change when HVPG was low, and resulted in further quantitation of fibrosis in cirrhosis.

Qualitative assessment of bubble behaviour for central and asymmetric injection in 2D gas-solid fluidized bed using image analysis technique and CFD modelling

Bubble characteristics such as shape, size, and trajectory control the hydrodynamics and therefore heat transfer in fluidized bed reactors. Thus understanding these characteristics is very important for the design and scaleup of fluidized beds. An earlier developed Eulerian-Eulerian two-fluid model for simulating dense gas–solid two-phase flow has been used to compare the experimental data in a pseudo-two-dimensional (2-D) bed. Bubbles are injected asymmetrically by locating the nozzle at proximity to the wall, thus presenting the effect wall has on asymmetrical injection as compared to symmetrical injection. In this work, a digital image analysis technique was developed to study the bubble behaviour in a two-dimensional bubbling bed. The high-speed photography reveals an asymmetric wake formation during detachment indicating an early onset of mixing process. The wall forces acts tangentially on thebubble and has a significant impact on the bubble shape, neck formation during detachment and its trajectory through the bed. Larger bubbles drifting away from the centre with longer paths are observed. This qualitative behaviour is well predicted by CFD modelling. Asymmetric injection can significantly influence the heat and mass transfer characteristics.

An image analysis study of pit formation on Ti-6Al-4V

Metallographic techniques and digital image processing have been used to investigate heat-treated Ti-6Al-4V pitting corrosion, often used as aircraft components. LM and SEM metallography of 'as received', annealed (heating up to 800 degreesC/30 min and cooling furnace) and aged (heating up to 900 degreesC/30 min, quenching in water, heating up to 540 degreesC/240 min and again water-quenched) microstructures reveal pitting sites at primary and secondary alpha/beta interfaces. Microstructural arrangements influence and corrosive environment association on pit morphology could be demonstrated by digital image analysis and results statistical treatment. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Image analysis of immunohistochemistry is superior to visual scoring as shown for patient outcome of esophageal adenocarcinoma.

Quantification of protein expression based on immunohistochemistry (IHC) is an important step in clinical diagnoses and translational tissue-based research. Manual scoring systems are used in order to evaluate protein expression based on staining intensities and distribution patterns. However, visual scoring remains an inherently subjective approach. The aim of our study was to explore whether digital image analysis proves to be an alternative or even superior tool to quantify expression of membrane-bound proteins. We analyzed five membrane-binding biomarkers (HER2, EGFR, pEGFR, β-catenin, and E-cadherin) and performed IHC on tumor tissue microarrays from 153 esophageal adenocarcinomas patients from a single center study. The tissue cores were scored visually applying an established routine scoring system as well as by using digital image analysis obtaining a continuous spectrum of average staining intensity. Subsequently, we compared both assessments by survival analysis as an end point. There were no significant correlations with patient survival using visual scoring of β-catenin, E-cadherin, pEGFR, or HER2. In contrast, the results for digital image analysis approach indicated that there were significant associations with disease-free survival for β-catenin, E-cadherin, pEGFR, and HER2 (P = 0.0125, P = 0.0014, P = 0.0299, and P = 0.0096, respectively). For EGFR, there was a greater association with patient survival when digital image analysis was used compared to when visual scoring was (visual: P = 0.0045, image analysis: P < 0.0001). The results of this study indicated that digital image analysis was superior to visual scoring. Digital image analysis is more sensitive and, therefore, better able to detect biological differences within the tissues with greater accuracy. This increased sensitivity improves the quality of quantification.

A low cost and widely applicable methodology of digital imagen analysis of ores for mineral and envirommental engineering

Technological and environmental problems related to ore processing are a serious limitation for sustainable development of mineral resources, particularly for countries / companies rich in ores, but with little access to sophisticated technology, e.g. in Latin America. Digital image analysis (DIA) can provide a simple, unexpensive and broadly applicable methodology to assess these problems, but this methodology has to be carefully defined, to produce reproducible and relevant information.