Gated metabolic myocardial imaging, a surrogate for dual perfusion-metabolism imaging by positron emission tomography.

OBJECTIVE: Perfusion-metabolism mismatch pattern on positron emission tomography (PET) predicts hibernating myocardium. We assess the ECG-gated metabolic PET as a surrogate for the perfusion-metabolism mismatch pattern on PET imaging. METHODS: 13N-Ammonia (NH3) and 18F-fluorodeoxyglucose (FDG) are respectively perfusion and metabolism PET tracers. We used ECG gating to acquire FDG-PET to collect wall thickening (mechanical) data. These allow detection of metabolic activity in regions with reduced contraction (metabolism-mechanical mismatch pattern). We had two data sets on each patient: perfusion-metabolism and metabolism-mechanical data sets. We tested the hypothesis that metabolism-mechanical pattern on PET could predict perfusion-metabolism mismatch pattern. RESULTS: We studied 55 patients (48 males), mean age 62 years. All were in sinus rhythm, and had impaired left ventricular contraction. Perfusion-metabolism mismatch pattern was found in 26 patients. Metabolism-mechanical mismatch pattern was found in 25 patients. The results were concordant in 52 patients (95%). As a surrogate for perfusion-metabolism mismatch pattern, demonstration of metabolism-mechanical mismatch pattern is highly sensitive (92%) and specific (97%). In this cohort, the positive and negative predictive accuracy of the new method are 96% and 93%, respectively. CONCLUSION: Metabolism-mechanical mismatch pattern could predict perfusion-metabolism mismatch pattern in patients with myocardial viability criteria on PET. Prospective validation against the gold standard of improved myocardial contraction after revascularisation is needed.

Spectral imaging technique for retinal perfusion detection using confocal scanning laser ophthalmoscopy.

To evaluate retinal perfusion in the human eye, a dual-wavelength confocal scanning laser ophthalmoscope (cSLO) was developed that provides spectral imaging of the fundus using a combination of red (670 nm) and near-infrared (810 nm) wavelengths. The image of the ocular fundus was analyzed to find out if quantitative measurements of the reflectivity of tissue permit assessment of the oxygen perfusion of tissue. We explored problems that affect the reproducibility of patient measurements such as non-uniformity errors on the image. For the first time, an image processing technique was designed and used to minimize the errors of oxygen saturation measurements by illumination correction in retina wide field by increasing SNR. Retinal images were taken from healthy and diabetic retinopathy eyes using the cSLO with a confocal aperture of 100 µm. The ratio image (RI) of red/IR, as oxygen saturation (SO2) index, was calculated for normal eyes. The image correction technique improved the reproducibility of the measurements. Average RI intensity variation of healthy retina tissue was determined within a range of about 5.5%. The capability of the new technique to discriminate oxygenation levels of retinal artery and vein was successfully demonstrated and showed good promise in the diagnosis of the perfused retina.

Improvement in DMSA imaging using adaptive noise reduction: an ROC analysis.

Dimercaptosuccinic acid imaging is the 'gold standard' for the detection of cortical defects and diagnosis of scarring of the kidneys. The Siemens planar processing package, which implements adaptive noise reduction using the Pixon algorithm, is designed to allow a reduction in image noise, enabling improved image quality and reduced acquisition time/injected activity. This study aimed to establish the level of improvement in image quality achievable using this algorithm. Images were acquired of a phantom simulating a single kidney with a range of defects of varying sizes, positions and contrasts. These images were processed using the Pixon processing software and shown to 12 observers (six experienced and six novices) who were asked to rate the images on a six-point scale depending on their confidence that a defect was present. The data were analysed using a receiver operating characteristic approach. Results showed that processed images significantly improved the performance of the experienced observers in terms of their sensitivity and specificity. Although novice observers showed significant increase in sensitivity when using the software, a significant decrease in specificity was also seen. This study concludes that the Pixon software can be used to improve the assessment of cortical defects in dimercaptosuccinic acid imaging by suitably trained observers.

Automated clarity assessment of retinal images using regionally based structural and statistical measures.

An automated image analysis system for application in mass medical screening must assess the clarity of the images before analysing their content. This is the case in grading for diabetic retinopathy screening where the failure to assess clarity could result in retinal images of people with retinopathy being erroneously classed as normal. This paper compares methods of clarity assessment based on the degradation of visible structures and based on the deviation of image properties outside expected norms caused by clarity loss. Vessel visibility measures and statistical measures were determined at locations in the image which have high saliency and these were used to obtain an image clarity assessment using supervised classification. The usefulness of the measures as indicators of image clarity was assessed. Tests were performed on 987 disc-centred and macula-centred retinal photographs (347 with inadequate clarity) obtained from the English National Screening Programme. Images with inadequate clarity were detected with 92.6% sensitivity at 90% specificity. In a set of 2000 macula-centred images (200 with inadequate clarity) from the Scottish Screening Programme, inadequate clarity was detected with 96.7% sensitivity at 90% specificity. This study has shown that structural and statistical measures are equally useful for retinal image clarity assessment.

The evidence for automated grading in diabetic retinopathy screening.

Systematic screening for diabetic retinopathy using retinal photography has been shown to reduce the incidence of blindness among people with diabetes. The implementation of diabetic retinopathy screening programmes faces several challenges. Consequently, methods for improving the efficiency of screening are being sought, one of which is the automation of image grading involving detection of images with either disease or of inadequate quality using computer software. This review aims to bring together the available evidence that is suitable for making a judgement about whether automated grading systems could be used effectively in diabetic retinopathy screening. To do this, it focuses on studies made by the few centres who have presented results tests of automated grading software on large sets of patients or screening episodes. It also considers economic model analyses and papers describing the effectiveness of manual grading in order that the effect of replacing stages of manual grading by automated grading can be judged. In conclusion, the review shows that there is sufficient evidence to suggest that automated grading, operating as a disease / no disease grader, is safe and could reduce the workload of manual grading in diabetic retinopathy screening.

Detection of new vessels on the optic disc using retinal photographs.

Proliferative diabetic retinopathy is a rare condition likely to lead to severe visual impairment. It is characterized by the development of abnormal new retinal vessels. We describe a method for automatically detecting new vessels on the optic disc using retinal photography. Vessel-like candidate segments are first detected using a method based on watershed lines and ridge strength measurement. Fifteen feature parameters, associated with shape, position, orientation, brightness, contrast and line density are calculated for each candidate segment. Based on these features, each segment is categorized as normal or abnormal using a support vector machine (SVM) classifier. The system was trained and tested by cross-validation using 38 images with new vessels and 71 normal images from two diabetic retinal screening centers and one hospital eye clinic. The discrimination performance of the fifteen features was tested against a clinical reference standard. Fourteen features were found to be effective and used in the final test. The area under the receiver operator characteristic curve was 0.911 for detecting images with new vessels on the disc. This accuracy may be sufficient for it to play a useful clinical role in an automated retinopathy analysis system.

Automated grading for diabetic retinopathy: a large-scale audit using arbitration by clinical experts.

BACKGROUND/AIMS: Automated grading software has the potential to reduce the manual grading workload within diabetic retinopathy screening programmes. This audit was undertaken at the request of Scotland's National Diabetic Retinopathy Screening Collaborative to assess whether the introduction of automated grading software into the national screening programme would be safe, robust and effective. METHODS: Automated grading, performed by software for image quality assessment and for microaneurysm/dot haemorrhage detection, was carried out on 78,601 images, obtained from 33,535 consecutive patients, which had been manually graded at one of two regional diabetic retinopathy screening programmes. Cases where the automated grading software assessment indicated gradable images with no disease but the screening programme indicated ungradable images or disease more severe than mild retinopathy were arbitrated by seven senior ophthalmologists. RESULTS: 100% (180/180) of patients with proliferative retinopathy, 100% (324/324) with referable background retinopathy, 100% (193/193) with observable background retinopathy, 97.3% (1099/1130) with referable maculopathy, 99.2% (384/387) with observable maculopathy and 99.8% (1824/1827) with ungradable images were detected by the software. CONCLUSION: The automated grading software operated to previously published results when applied to a large, unselected population attending two regional screening programmes. Manual grading workload reduction would be 36.3%.

The role of haemorrhage and exudate detection in automated grading of diabetic retinopathy.

BACKGROUND/AIMS: Automated grading has the potential to improve the efficiency of diabetic retinopathy screening services. While disease/no disease grading can be performed using only microaneurysm detection and image-quality assessment, automated recognition of other types of lesions may be advantageous. This study investigated whether inclusion of automated recognition of exudates and haemorrhages improves the detection of observable/referable diabetic retinopathy. METHODS: Images from 1253 patients with observable/referable retinopathy and 6333 patients with non-referable retinopathy were obtained from three grading centres. All images were reference-graded, and automated disease/no disease assessments were made based on microaneurysm detection and combined microaneurysm, exudate and haemorrhage detection. RESULTS: Introduction of algorithms for exudates and haemorrhages resulted in a statistically significant increase in the sensitivity for detection of observable/referable retinopathy from 94.9% (95% CI 93.5 to 96.0) to 96.6% (95.4 to 97.4) without affecting manual grading workload. CONCLUSION: Automated detection of exudates and haemorrhages improved the detection of observable/referable retinopathy.

Automated detection of exudates for diabetic retinopathy screening.

Automated image analysis is being widely sought to reduce the workload required for grading images resulting from diabetic retinopathy screening programmes. The recognition of exudates in retinal images is an important goal for automated analysis since these are one of the indicators that the disease has progressed to a stage requiring referral to an ophthalmologist. Candidate exudates were detected using a multi-scale morphological process. Based on local properties, the likelihoods of a candidate being a member of classes exudate, drusen or background were determined. This leads to a likelihood of the image containing exudates which can be thresholded to create a binary decision. Compared to a clinical reference standard, images containing exudates were detected with sensitivity 95.0% and specificity 84.6% in a test set of 13,219 images of which 300 contained exudates. Depending on requirements, this method could form part of an automated system to detect images showing either any diabetic retinopathy or referable diabetic retinopathy.

Automatic detection of retinal anatomy to assist diabetic retinopathy screening.

Screening programmes for diabetic retinopathy are being introduced in the United Kingdom and elsewhere. These require large numbers of retinal images to be manually graded for the presence of disease. Automation of image grading would have a number of benefits. However, an important prerequisite for automation is the accurate location of the main anatomical features in the image, notably the optic disc and the fovea. The locations of these features are necessary so that lesion significance, image field of view and image clarity can be assessed. This paper describes methods for the robust location of the optic disc and fovea. The elliptical form of the major retinal blood vessels is used to obtain approximate locations, which are refined based on the circular edge of the optic disc and the local darkening at the fovea. The methods have been tested on 1056 sequential images from a retinal screening programme. Positional accuracy was better than 0.5 of a disc diameter in 98.4% of cases for optic disc location, and in 96.5% of cases for fovea location. The methods are sufficiently accurate to form an important and effective component of an automated image grading system for diabetic retinopathy screening.

Automated microaneurysm detection using local contrast normalization and local vessel detection.

Screening programs using retinal photography for the detection of diabetic eye disease are being introduced in the UK and elsewhere. Automatic grading of the images is being considered by health boards so that the human grading task is reduced. Microaneurysms (MAs) are the earliest sign of this disease and so are very important for classifying whether images show signs of retinopathy. This paper describes automatic methods for MA detection and shows how image contrast normalization can improve the ability to distinguish between MAs and other dots that occur on the retina. Various methods for contrast normalization are compared. Best results were obtained with a method that uses the watershed transform to derive a region that contains no vessels or other lesions. Dots within vessels are handled successfully using a local vessel detection technique. Results are presented for detection of individual MAs and for detection of images containing MAs. Images containing MAs are detected with sensitivity 85.4% and specificity 83.1%.

Automated assessment of diabetic retinal image quality based on clarity and field definition.

PURPOSE: To evaluate the performance of an automated retinal image quality assessment system for use in automated diabetic retinopathy grading. METHODS: Algorithmic methods have been developed for assessing the quality of 45 degrees single field retinal images for use in diabetic retinopathy screening. For this purpose, image quality was defined by two aspects: image clarity and field definition. An image with adequate clarity was defined as one that shows sufficient detail for automated retinopathy grading. The visibility of the macular vessels was used as an indicator of image clarity, since these vessels are known to be narrow and become less visible with any image degradation. An image with adequate field definition was defined as one that shows the desired field of view for retinopathy grading, including the full 45 degrees field of view, the optic disc, and at least two optic disc diameters of visible retina around the fovea. From 489 patients attending a diabetic retinopathy screening program, 1039 retinal images were obtained. The images were graded by a clinician for image clarity and field definition, with a comprehensive image-quality grading scheme. RESULTS: The sensitivity and specificity were, respectively, 100% and 90.9% for inadequate clarity detection, 95.3% and 96.4% for inadequate field definition detection, and 99.1% and 89.4% for inadequate overall quality detection. CONCLUSIONS: The automated system performs with sufficient accuracy to form part of an automated diabetic retinopathy grading system.

Involvement of CCR5 in the passage of Th1-type cells across the blood-retina barrier in experimental autoimmune uveitis.

Although the recruitment of T helper cell type 1 (Th1)/Th2 cells into peripheral tissues is essential for inflammation and the host response to infection, the traffic signals that enable the distinct positioning of Th1/Th2 cells are unclear. We have determined the role of CC chemokine receptor 5 (CCR5) in this using experimental autoimmune uveitis (EAU) as a model system. In EAU, Th1-like cells are preferentially recruited into the retina across the blood-retina barrier, partly as a result of expression of the adhesion molecules P-selectin glycoprotein ligand 1 and lymphocyte function-associated antigen-1 on these cells. CD3+ T cells, infiltrating the retina, also expressed the chemokine receptor CCR5, and CCR5 ligands, macrophage-inflammatory protein-1alpha (MIP-1alpha), MIP-1beta, and regulated on activation, normal T expressed and secreted (RANTES), were strongly expressed in the retina at peak EAU. Th1-like cells, polarized in vitro, expressed high levels of CCR5. The trafficking of these CCR5+ cells was examined by tracking them after adoptive transfer in real time in vivo at an early disease stage using scanning laser ophthalmoscopy. Treatment of the cells with antibody against CCR5 prior to transfer resulted in a reduction in their infiltration into the retina. However, rolling velocity, rolling efficiency, and adherence of the cells to retinal endothelium were not reduced. CCR5 is clearly important for Th1 cell recruitment, and this study demonstrates for the first time in vivo that CCR5 may act at the level of transendothelial migration rather than at the earlier stage of rolling on the endothelium.

Ultra-wide-field fluorescein angiography of the ocular fundus.

PURPOSE: To evaluate the clinical applicability of a novel scanning laser ophthalmoscopy imaging system for ultra-wide-field fluorescein angiography. DESIGN: Observational case report. METHODS: Wide-field fluorescein angiography images were captured in normal volunteers and in patients with a variety of clinical disorders with a newly developed scanning laser ophthalmoscope (Optomap; Optos PLC., Dunfermline, Scotland, United Kingdom) that produces high-resolution images of the fundus up to a 200-degree field. Fluorescein angiograms were performed using standard sequence times. RESULTS: Peripheral vascular perfusion of all four quadrants of a normal fundus was observed with good detail of the capillary architecture. Patients with diabetes and ocular inflammatory eye disease showed evidence of peripheral retinal nonperfusion. The relative degrees of retinal perfusion and nonperfusion could be compared in single images. CONCLUSIONS: Ultra-wide-field fundus fluorescein angiography offers the possibility of evaluating and quantitating peripheral retinal perfusion and vascular pathology in fundus disease.

Recruitment of IFN-gamma-producing (Th1-like) cells into the inflamed retina in vivo is preferentially regulated by P-selectin glycoprotein ligand 1:P/E-selectin interactions.

Although there is evidence that altering the Th1/Th2 balance toward Th2 cells may be important in the resolution of Th1-type autoimmune disease, adoptive transfer of Th2 cells is not effective in protecting against Th1-type disease and may cause disease. Therefore, we examined the recruitment of Th1- and Th2-like cells into the retina in the murine autoimmune disease experimental autoimmune uveoretinitis. CD4 T cells were polarized in vitro to IFN-gamma-producing Th1-like cells and non-IFN-gamma-producing Th2-like cells, labeled, and adoptively transferred. Trafficking to the retina in vivo was evaluated by scanning laser ophthalmoscopy and infiltration by confocal microscopy. There were more rolling and adherent Th1-like cells and they rolled more slowly than did Th2-like cells. Th1-like cells were preferentially recruited into the retinal parenchyma at both initiation and resolution. Surface P-selectin glycoprotein ligand 1 (PSGL-1) and LFA-1 were up-regulated on both populations but were expressed at higher levels on Th1-like cells. Up-regulation of CD44 expression was higher on Th2-like cells. P-selectin, E-selectin, and ICAM-1 are up-regulated on postcapillary venules in the retina. Pretreatment of Th1-like cells with anti-PSGL-1 inhibited rolling and infiltration of Th1-like cells but not Th2-like cells, providing direct in vivo evidence for the inability of Th2 to respond to P/E-selectin despite increased expression of PSGL-1. Anti-LFA-1 pretreatment inhibited infiltration of both Th1- and Th2-like cells, but more so Th-1. We suggest that random trafficking of activated T cells (both Th1 and Th2) across the blood-retina barrier is mediated by CD44:CD44R and LFA-1:ICAM-1, whereas preferential recruitment of Th1 cells is mediated by PSGL-1:P/E-selectin.

Reduction in shear stress, activation of the endothelium, and leukocyte priming are all required for leukocyte passage across the blood--retina barrier.

The passage of leukocytes across the blood-retina barrier at the early stages of an inflammatory reaction is influenced by a complex series of interactions about which little is known. In particular, the relationship between hydrodynamic factors, such as shear stress and leukocyte velocity, to the adherence and subsequent extravasation of leukocytes into the retina is unclear. We have used a physiological method, scanning laser ophthalmoscopy, to track labeled leukocytes circulating in the retina, followed by confocal microscopy of retinal flatmounts to detect infiltrating cells at the early stage of experimental autoimmune uveitis. This has shown that retinal vessels are subjected to high shear stress under normal circumstances. During the inflammatory reaction, shear stress in retinal veins is reduced 24 h before leukocyte infiltration. This reduction is negatively correlated with leukocyte rolling and sticking in veins and postcapillary venules, the sites of leukocyte extravasation. Activation of vascular endothelial cells is also a prerequisite for leukocyte rolling and infiltration. In addition, antigen priming of leukocytes is influential at the early stage of inflammation, and this is seen clearly in the reduction in rolling velocity and adherence of the primed leukocytes in activated retinal venules, 9 days postimmunization.

Automated measurement of microaneurysm turnover.

PURPOSE: An automated system for the measurement of microaneurysm (MA) turnover was developed and compared with manual measurement. The system analyses serial fluorescein angiogram (FA) or red-free (RF) fundus images; fluorescein angiography was used in this study because it is the more sensitive test for MAs. Previous studies have shown that the absolute number of MAs observed does not reflect the dynamic temporal nature of the MA population. In this study, almost half of the MAs present at baseline had regressed after a year and been replaced by new lesions elsewhere. METHODS: Two clinical datasets were used to evaluate the performance of the automated turnover measurement system. The first consisted of 10 patients who had two fluorescein angiograms acquired a year apart. These data were analyzed, both manually and using the automated system, to investigate the inter- and intraobserver variations associated with manual measurement and to assess the performance of the automated system. The second dataset contained FAs from a further 25 patients. This dataset was analyzed only with the automated system to investigate some properties of microaneurysm turnover, in particular the differing detection sensitivities of new, static and regressed microaneurysms. RESULTS: Manual measurements exhibited large inter- and intraobserver variation. The sensitivity and specificity of the automated system were similar to those of the human observers. However, the automated measurements were more consistent-an important condition for accurate turnover quantification. Regressed MAs were more difficult to detect reliably than new MAs, which were themselves more difficult to detect reliably than static MAs. CONCLUSIONS: The automated system was shown to be fast, reliable, and repeatable, making it suitable for processing large numbers of images. Performance was similar to that of trained manual observers.