Retinopathy of prematurity screening at ≥30 weeks: urinary NTpro-BNP performance

Aim: Urinary N-terminal B-type natriuretic peptide NTproBNP levels are associated with the development of retinopathy of prematurity (ROP) in infants <30 weeks of gestation. The incidence of ROP in more mature infants who meet other ROP screening criteria is very low. We therefore aimed to test whether urinary NTproBNP predicted ROP development in these infants. Methods: Prospective observational study in 151 UK infants ≥30 + 0 weeks of gestation but also <32 weeks of gestation and/or <1501 g, to test the hypothesis that urinary NTproBNP levels on day of life (DOL) 14 and 28 were able to predict ROP development. Results: Urinary NTproBNP concentrations on day 14 and day 28 of life did not differ between infants with and without ROP (medians 144 vs 128 mcg/mL, respectively, p = 0.86 on DOL 14 and medians 117 vs 94 mcg/mL, respectively, p = 0.64 on DOL28). Conclusion: The association previously shown for infants <30 completed weeks between urinary NTproBNP and the development of ROP was not seen in more mature infants. Urinary NTproBNP does not appear helpful in rationalising direct ophthalmoscopic screening for ROP in more mature infants, and may suggest a difference in pathophysiology of ROP in this population

Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging

Using medical images to evaluate disease severity and change over time is a routine and important task in clinical decision making. Grading systems are often used, but are unreliable as domain experts disagree on disease severity category thresholds. These discrete categories also do not reflect the underlying continuous spectrum of disease severity. To address these issues, we developed a convolutional Siamese neural network approach to evaluate disease severity at single time points and change between longitudinal patient visits on a continuous spectrum. We demonstrate this in two medical imaging domains: retinopathy of prematurity (ROP) in retinal photographs and osteoarthritis in knee radiographs. Our patient cohorts consist of 4861 images from 870 patients in the Imaging and Informatics in Retinopathy of Prematurity (i-ROP) cohort study and 10,012 images from 3021 patients in the Multicenter Osteoarthritis Study (MOST), both of which feature longitudinal imaging data. Multiple expert clinician raters ranked 100 retinal images and 100 knee radiographs from excluded test sets for severity of ROP and osteoarthritis, respectively. The Siamese neural network output for each image in comparison to a pool of normal reference images correlates with disease severity rank (ρ = 0.87 for ROP and ρ = 0.89 for osteoarthritis), both within and between the clinical grading categories. Thus, this output can represent the continuous spectrum of disease severity at any single time point. The difference in these outputs can be used to show change over time. Alternatively, paired images from the same patient at two time points can be directly compared using the Siamese neural network, resulting in an additional continuous measure of change between images. Importantly, our approach does not require manual localization of the pathology of interest and requires only a binary label for training (same versus different). The location of disease and site of change detected by the algorithm can be visualized using an occlusion sensitivity map-based approach. For a longitudinal binary change detection task, our Siamese neural networks achieve test set receiving operator characteristic area under the curves (AUCs) of up to 0.90 in evaluating ROP or knee osteoarthritis change, depending on the change detection strategy. The overall performance on this binary task is similar compared to a conventional convolutional deep-neural network trained for multi-class classification. Our results demonstrate that convolutional Siamese neural networks can be a powerful tool for evaluating the continuous spectrum of disease severity and change in medical imaging

A predictive score for retinopathy of prematurity in very low birth weight preterm infants

Aims This study describes the development of a score based on cumulative risk factors for the prediction of severe retinopathy of prematurity (ROP) comparing the performance of the score against the birth weight (BW) and gestational age (GA) in order to predict the onset of ROP.Methods A prospective cohort of preterm infants with BWp1500 g and/or GAp32 weeks was studied. the score was developed based on BW, GA, proportional weight gain from birth to the 6th week of life, use of oxygen in mechanical ventilation, and need for blood transfusions from birth to the 6th week of life. the score was established after linear regression, considering the impact of each variable on the occurrences of any stage and severe ROP. Receiver operating characteristic (ROC) curves were used to determine the best sensitivity and specificity values for the score. All variables were entered into an Excel spreadsheet (Microsoft) for practical use by ophthalmologists during screening sessions.Results the sample included 474 patients. the area under the ROC curve for the score was 0.77 and 0.88 to predict any stage and severe ROP, respectively. These values were significantly higher for the score than for BW (0.71) and GA (0.69) when measured separately.Conclusions ROPScore is an excellent index of neonatal risk factors for ROP, which is easy to record and more accurate than BW and GA to predict any stage ROP or severe ROP in preterm infants. the scoring system is simple enough to be routinely used by ophthalmologists during screening examination for detection of ROP. Eye (2012) 26, 400-406; doi: 10.1038/eye. 2011.334; published online 23 December 2011Hosp Clin Porto Alegre, Dept Ophthalmol, BR-90035903 Porto Alegre, RS, BrazilUniv Fed Rio Grande do Sul, Dept Ophthalmol, Sch Med, Porto Alegre, RS, BrazilUniversidade Federal de São Paulo, Dept Ophthalmol, Sch Med, São Paulo, BrazilUniv Fed Rio Grande do Sul, Dept Paediat, Newborn Sect, Sch Med, Porto Alegre, RS, BrazilUniversidade Federal de São Paulo, Dept Ophthalmol, Sch Med, São Paulo, BrazilWeb of Scienc

The Incidence and Course of Retinopathy of Prematurity: Findings From the Early Treatment for Retinopathy of Prematurity Study

Lai, WW is one of the member of the Early Treatment for Retinopathy of Prematurity Cooperative GroupObjectives. To estimate the incidence of retinopathy of prematurity (ROP) in the Early Treatment for Retinopathy of Prematurity (ETROP) Study and compare these results with those reported in the Cryotherapy for Retinopathy of Prematurity (CRYO-ROP) Study. Methods. The ETROP Study, as part of its protocol, screened 6998 infants at 26 centers throughout the United States. Serial eye examinations were conducted for infants born weighing <1251 g, making it possible to estimate the frequency of ROP in different birth weight and gestational age categories. ROP was categorized according to the International Classification for ROP. Results. The incidence of any ROP was 68% among infants of <1251 g. The findings were compared with those for infants born in 1986 and 1987 in the CRYO-ROP Study. The overall incidences of ROP were similar in the 2 studies, but there was more zone I ROP in the ETROP Study. Among infants with ROP, more-severe ROP (prethreshold) occurred for 36.9% of infants in the ETROP Study and 27.1% of infants in the CRYO-ROP Study. The gestational age of onset of ROP of different severities has changed very little since the CRYO-ROP Study was conducted. Conclusions. ROP remains a common important problem among infants with birth weights of <1251 g. The incidence of ROP, time of onset, rate of progression, and time of onset of prethreshold disease have changed little since the CRYO-ROP natural-history study