Diabet. Med. 29, 776783 (2012) Abstract Aims To develop and evaluate an image grading external quality assurance system for the Scottish Diabetic Retinopathy Screening Programme. Method A web-based image grading system was developed which closely matches the current Scottish national screening software. Two rounds of external quality assurance were run in autumn 2008 and spring 2010, each time using the same 100 images. Graders were compared with a consensus standard derived from the top-level graders results. After the first round, the centre lead clinicians and top-level graders reviewed the results and drew up guidance notes for the second round. Results Grader sensitivities ranged from 60.0 to 100% (median 92.5%) in 2008, and from 62.5 to 100% (median 92.5%) in 2010. Specificities ranged from 34.0 to 98.0% (median 86%) in 2008, and 54.0 to 100% (median 88%) in 2010. There was no difference in sensitivity between grader levels, but first-level graders had a significantly lower specificity than level-two and level-three graders. In 2008, one centre had a lower sensitivity but higher specificity than the majority of centres. Following the feedback from the first round, overall agreement improved in 2010 and there were no longer any significant differences between centres. Conclusions A useful educational tool has been developed for image grading external quality assurance.

The development of new vessels on the retina of people with diabetes is rare, but is likely to lead to severe visual impairment. This paper investigates the selection of suitable image features for the automatic detection of new vessels on the optic disc. The features are chosen based on their discrimination capability (tested using the non-parametric Wilcoxon rank sum and Ansari-Bradley dispersion tests) and absence of correlation with other features (tested using the Kendall Tau coefficient). Classification was performed using a support vector machine. The system was trained and tested by cross-validation using 38 images with new vessels and 71 normal images without new vessels. Fourteen features were selected, giving an area under the receiver operator characteristic curve of 0.911 for detecting images with new vessels on the disc. The method could have a useful role as part of an automated retinopathy analysis system.

Aims To assess the cost-effectiveness of an improved automated grading algorithm for diabetic retinopathy against a previously described algorithm, and in comparison with manual grading.Methods Efficacy of the alternative algorithms was assessed using a reference graded set of images from three screening centres in Scotland (1253 cases with observable/referable retinopathy and 6333 individuals with mild or no retinopathy). Screening outcomes and grading and diagnosis costs were modelled for a cohort of 180 000 people, with prevalence of referable retinopathy at 4%. Algorithm (b), which combines image quality assessment with detection algorithms for microaneurysms (MA), blot haemorrhages and exudates, was compared with a simpler algorithm (a) (using image quality assessment and MA/dot haemorrhage (DH) detection), and the current practice of manual grading.Results Compared with algorithm (a), algorithm (b) would identify an additional 113 cases of referable retinopathy for an incremental cost of 68 pound per additional case. Compared with manual grading, automated grading would be expected to identify between 54 and 123 fewer referable cases, for a grading cost saving between 3834 pound and 1727 pound per case missed. Extrapolation modelling over a 20-year time horizon suggests manual grading would cost between 25 pound 676 and 267 pound 115 per additional quality adjusted life year gained.Conclusions Algorithm (b) is more cost-effective than the algorithm based on quality assessment and MA/DH detection. With respect to the value of introducing automated detection systems into screening programmes, automated grading operates within the recommended national standards in Scotland and is likely to be considered a cost-effective alternative to manual disease/no disease grading.

Aims: National screening programmes for diabetic retinopathy using digital photography and multi-level manual grading systems are currently being implemented in the UK. Here, we assess the cost-effectiveness of replacing first level manual grading in the National Screening Programme in Scotland with an automated system developed to assess image quality and detect the presence of any retinopathy.Methods: A decision tree model was developed and populated using sensitivity/specificity and cost data based on a study of 6722 patients in the Grampian region. Costs to the NHS, and the number of appropriate screening outcomes and true referable cases detected in 1 year were assessed.Results: For the diabetic population of Scotland (approximately 160 000), with prevalence of referable retinopathy at 4% (6400 true cases), the automated strategy would be expected to identify 5560 cases (86.9%) and the manual strategy 5610 cases (87.7%). However, the automated system led to savings in grading and quality assurance costs to the NHS of 201 pound 600 per year. The additional cost per additional referable case detected (manual vs automated) totalled 4088 pound and the additional cost per additional appropriate screening outcome (manual vs automated) was 1990 pound.Conclusions: Given that automated grading is less costly and of similar effectiveness, it is likely to be considered a cost-effective alternative to manual grading.

Aim:To assess the efficacy of automated “disease/no disease” grading for diabetic retinopathy within a systematic screening programme.Methods:Anonymised images were obtained from consecutive patients attending a regional primary care based diabetic retinopathy screening programme. A training set of 1067 images was used to develop automated grading algorithms. The final software was tested using a separate set of 14 406 images from 6722 patients. The sensitivity and specificity of manual and automated systems operating as “disease/no disease” graders (detecting poor quality images and any diabetic retinopathy) were determined relative to a clinical reference standard.Results:The reference standard classified 8.2% of the patients as having ungradeable images (technical failures) and 62.5% as having no retinopathy. Detection of technical failures or any retinopathy was achieved by manual grading with 86.5% sensitivity (95% confidence interval 85.1 to 87.8) and 95.3% specificity (94.6 to 95.9) and by automated grading with 90.5% sensitivity (89.3 to 91.6) and 67.4% specificity (66.0 to 68.8). Manual and automated grading detected 99.1% and 97.9%, respectively, of patients with referable or observable retinopathy/maculopathy. Manual and automated grading detected 95.7% and 99.8%, respectively, of technical failures.Conclusion:Automated “disease/no disease” grading of diabetic retinopathy could safely reduce the burden of grading in diabetic retinopathy screening programmes.

Objectives. We sought to compare the myocardial velocity gradient (MVG) measured across the left ventricular (LV) posterior wall during the cardiac cycle between patients with hypertrophic cardiomyopathy (HCM), athletes and patients with LV hypertrophy due to systemic hypertension and to determine whether it might be used to discriminate these groups.Background. The MVG is a new ultrasound variable, based on the color Doppler technique, that quantifies the spatial distribution of transmyocardial velocities.Methods. A cohort of 158 subjects was subdivided by age into two groups: Group I (mean [+/-SD] 30 +/- 7 years) and Group II (58 +/- 8 years). Within each group there were three categories of subjects: Group la consisted of patients with HCM (n = 25), Group Ib consisted of athletes (n = 21), and Group Ic consisted of normal subjects; Group IIa consisted of patients with HCM (n = 19), Group IIb consisted of hypertensive patients (n = 27), and Group IIc consisted of normal subjects (n = 33).Results. The MVG (mean [+/-SD] s(-1)) measured in systole was lower (p < 0.01) in patients with HCM (Group Ia 3.2 +/- 1.1; Group IIa 2.9 +/- 1.2) compared with athletes (Group Ib 4.6 +/- 1.1), hypertensive patients (Group IIb 4.2 +/- 1.8) and normal subjects (Group Ic 4.4 +/- 0.8; Group Ile 4.8 +/- 0.8), In early diastole, the MVG was lower (p < 0.05) in patients with HCM (Group Ia 3.7 +/- 1.5; Group IIa 2.6 +/- 0.9) than in athletes (Group Ib 9.9 +/- 1.9) and normal subjects (Group Ic 9.2 +/- 2.0; Group IIc 3.6 +/- 1.5), but not hypertensive patients (Group IIb 3.3 +/- 1.3), In fate diastole, the MVG in patients with HCM (Group Ia 1.3 +/- 0.8; Group IIa 1.4 +/- 0.8) was lower (p < 0.01) than that in hypertensive patients (Group IIb 4.3 +/- 1.7) and normal subjects (Group IIc 3.5 +/- 0.9), An MVG less than or equal to 7 s(-1), as a single diagnostic approach, differentiated accurately (0.96 positive and 0.94 negative predictive value) between patients with HCM and athletes when the measurements were taken during early diastole.Conclusions. In both age groups, the MVG was lower in both systole and diastole in patients with HCM than in athletes, hypertensive patients or normal subjects, The MVG measured in early diastole in a group of subjects 18 to 45 years old would appear to be an accurate variable used to discriminate between HCM and hypertrophy in athletes. (C) 1997 by the American College of Cardiology.

Doppler myocardial imaging is a new cardiac ultrasound technique based on the principles of colour Doppler imaging which can determine myocardial velocities by detecting the changes of phase-shift of the ultrasound signal returning directly from the myocardium. To determine the normal range of transmural velocities in healthy hearts a prospective study was carried out involving 42 normal subjects (age from 21 to 78, mean 47 +/- 16 years). Using M-mode Doppler myocardial imaging the peak values of the mean velocity and velocity gradient across the left ventricular posterior wall were measured during standardized phases of the cardiac cycle. Peak mean velocities had the following values during the cardiac cycle: isovolumic contraction - 1.3 +/- 1.2 cm. s-1, early ventricular ejection 4.2 +/- 1.2 cm. s-1, late ventricular ejection 1.8 +/- 1.1 cm. s-1, isovolumic relaxation -2.0 +/- 0.8 cm. s-1, rapid ventricular filling -6.6 +/- 2.2 cm. s-1, atrial contraction -2.8 +/- 1.8 cm. s-1, atrial relaxation 1.2 +/- 1.1 cm. s-1. Peak velocity gradients were: isovolumic contraction 1.3 +/- 1.9 s-1, early ventricular contraction 4.7 +/- 1.9 s-1, late ventricular contraction 1.1 +/- 1.0 s-1, isovolumic relaxation -0.6 +/- 0.5 s-1, rapid ventricular filling 6.1 +/- 3.4 s-1, atrial contraction 2.6 +/- 1.7 s-1, atrial relaxation 0.0 +/- 0.3 s-1. Linear regression analysis showed that with the increase of age, peak velocity gradient decreases during rapid ventricular filling (r = 0.83; P < 0.0001) and increases during atrial contraction (r = 0.86; P < 0.0001) while peak mean velocity increases only during atrial contraction (r = 0.80, P < 0.0001). Thus, there was no correlation between increasing age and systolic peak mean velocity and peak velocity gradient but both diastolic filling phases rapid ventricular filling and atrial contraction demonstrated age-related changes. In summary, this study has determined the age-related range of normal transmural myocardial velocities within the left ventricular posterior wall in healthy hearts during the cardiac cycle. We conclude that these measurements of peak mean velocities and peak velocity gradients, should form the baseline for subsequent Doppler myocardial imaging clinical studies on myocardial diseases processes.

Doppler tissue imaging (DTI) is a new ultrasonic technique that can be used to give quantified information about the motion of the myocardium. DTI M-mode recordings can be generated that display cardiac wall motion in great detail. In order to verify the motion as displayed in these images comparisons were made with simultaneously obtained grey-scale M-mode recordings. After capturing 135 simultaneous DTI and grey-scale M-mode recordings, those were selected in which wall motion could be accurately assessed from the grey-scale recording. Comparison with the DTI images shows: (1) that DTI accurately displays the direction of wall motion; and (2) that DTI displays whether the wall is thickening or thinning as a velocity distribution across the heart wall. This information is more reliably displayed and easier to interpret in the DTI M-mode recordings than in the grey-scale M-mode recordings.

An investigation has been carried out on the velocity resolution, spatial resolution and accuracy of Doppler images as part of a study into the Doppler display of cardiac tissue motion. Test-phantoms were designed to perform this work and images were captured on a computer. The characteristics of the phantom images and of the image capture process were studied. The smallest spatial detail that was observed in the Doppler image was 3 mm by 3 mm. Doppler receive gain and Doppler ensemble size both affected velocity resolution. Different target materials gave different measures for velocity resolution. This could be related to the different back-scatter intensities of the materials.

Using a scanner whose colour Doppler mode has been adapted to display tissue motion (instead of blood flow), velocity gradients have been detected across the myocardium. A velocity gradient is a gradual spatial change in the value of velocity estimates. Velocity gradients have potential for assessing regional myocardial contractility. 28 M-mode scans were performed on nine normal volunteers at different locations in the left-ventricle posterior wall. In each case simultaneous Doppler M-mode and pulse-echo M-mode images were obtained. Doppler velocity gradient (DVG) was calculated from Doppler M-mode images and rate of change of wall thickness (RCWT) was calculated from pulse-echo M-mode images. In all Doppler M-mode images statistically significant velocity gradients were observed. In all but one scan, cyclically consistent peaks in DVG occur relative to the electrocardiogram waveform. 99% of systolic and 89% of early diastolic peaks in RCWT have a corresponding peak in DVG. Velocity gradients are consistent with wall thickness changes, suggesting that they have potential for assessment of myocardial contractility.