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

Competing risk and heterogeneity of treatment effect in clinical trials

It has been demonstrated that patients enrolled in clinical trials frequently have a large degree of variation in their baseline risk for the outcome of interest. Thus, some have suggested that clinical trial results should routinely be stratified by outcome risk using risk models, since the summary results may otherwise be misleading. However, variation in competing risk is another dimension of risk heterogeneity that may also underlie treatment effect heterogeneity. Understanding the effects of competing risk heterogeneity may be especially important for pragmatic comparative effectiveness trials, which seek to include traditionally excluded patients, such as the elderly or complex patients with multiple comorbidities. Indeed, the observed effect of an intervention is dependent on the ratio of outcome risk to competing risk, and these risks – which may or may not be correlated – may vary considerably in patients enrolled in a trial. Further, the effects of competing risk on treatment effect heterogeneity can be amplified by even a small degree of treatment related harm. Stratification of trial results along both the competing and the outcome risk dimensions may be necessary if pragmatic comparative effectiveness trials are to provide the clinically useful information their advocates intend

Quality of Life After Sentinel Lymph Node Biopsy or Axillary Lymph Node Dissection in Stage I/II Breast Cancer Patients: A Prospective Longitudinal Study

Background:\ud Breast cancer patients’ quality of life (QoL) after surgery has been reported to improve significantly over time. Little is known about QoL recovery after sentinel lymph node biopsy (SLNB) in comparison to axillary lymph node dissection (ALND).\ud \ud Methods:\ud 175 of 195 stage I/II breast cancer patients completed the EORTC QLQ-C30: one day before surgery (T0) and after 6 (T1), 26 (T2), 52 (T3) and 104 (T4) weeks. Of these, 54 patients underwent SLNB, 56 SLNB+ALND and 65 ALND. General linear models and paired T-tests between T0–T4 and T1–T4 were computed. Complications, radiotherapy and systemic therapy were added to the model.\ud \ud Results:\ud Significant time effects were found on physical, role and emotional functioning. Physical and role functioning decreased between T0 and T1. At T4, SLNB patients’ functioning had increased to their T0 level; ALND (+/– SLNB) patients’ functioning had increased, but had not improved to T0 level. Emotional functioning increased linearly between T0 and T4. At T4, emotional functioning was significantly higher in all groups as compared with T0. No significant group or interaction (time × group) effects were found. Complications and chemotherapy had a significant negative effect on role, emotional and cognitive functioning. Complications had a significant effect on social functioning also. Effect sizes varied between 0.00 and 0.06.\ud \ud Conclusion:\ud Two years post surgery, breast cancer patients’ QoL is comparable to that shortly before surgery. Women rated their emotional functioning as even better. SLNB is not associated with a better QoL than ALND. However, undergoing systemic therapy and/or experiencing complications affects QoL negatively

An international comparison of Retinopathy of Prematurity grading performance within the Benefits of Oxygen Saturation Targeting (BOOST) II trials. International variation in ROP grading.

PurposeTo investigate whether the observed international differences in retinopathy of prematurity (ROP) treatment rates within the Benefits of Oxygen Saturation Targeting (BOOST) II trials might have been caused by international variation in ROP disease grading.MethodsGroups of BOOST II trial ophthalmologists in UK, Australia, and New Zealand (ANZ), and an international reference group (INT) used a web based system to grade a selection of RetCam images of ROP acquired during the BOOST II UK trial. Rates of decisions to treat, plus disease grading, ROP stage grading, ROP zone grading, inter-observer variation within groups and intra-observer variation within groups were measured.ResultsForty-two eye examinations were graded. UK ophthalmologists diagnosed treat-requiring ROP more frequently than ANZ ophthalmologists, 13.9 (3.49) compared to 9.4 (4.46) eye examinations, P=0.038. UK ophthalmologists diagnosed plus disease more frequently than ANZ ophthalmologists, 14.1 (6.23) compared to 8.5 (3.24) eye examinations, P=0.021. ANZ ophthalmologists diagnosed stage 2 ROP more frequently than UK ophthalmologists, 20.2 (5.8) compared to 12.7 (7.1) eye examinations, P=0.026. There were no other significant differences in the grading of ROP stage or zone. Inter-observer variation was higher within the UK group than within the ANZ group. Intra-observer variation was low in both groups.ConclusionsWe have found evidence of international variation in the diagnosis of treatment-requiring ROP. Improved standardisation of the diagnosis of treatment-requiring ROP is required. Measures might include improved training in the grading of ROP, using an international approach, and further development of ROP image analysis software.Eye advance online publication, 28 July 2017; doi:10.1038/eye.2017.150

The utility and predictive value of combinations of low penetrance genes for screening and risk prediction of colorectal cancer

Despite the fact that colorectal cancer (CRC) is a highly treatable form of cancer if detected early, a very low proportion of the eligible population undergoes screening for this form of cancer. Integrating a genomic screening profile as a component of existing screening programs for CRC could potentially improve the effectiveness of population screening by allowing the assignment of individuals to different types and intensities of screening and also by potentially increasing the uptake of existing screening programs. We evaluated the utility and predictive value of genomic profiling as applied to CRC, and as a potential component of a population-based cancer screening program. We generated simulated data representing a typical North American population including a variety of genetic profiles, with a range of relative risks and prevalences for individual risk genes. We then used these data to estimate parameters characterizing the predictive value of a logistic regression model built on genetic markers for CRC. Meta-analyses of genetic associations with CRC were used in building science to inform the simulation work, and to select genetic variants to include in logistic regression model-building using data from the ARCTIC study in Ontario, which included 1,200 CRC cases and a similar number of cancer-free population-based controls. Our simulations demonstrate that for reasonable assumptions involving modest relative risks for individual genetic variants, that substantial predictive power can be achieved when risk variants are common (e.g., prevalence > 20%) and data for enough risk variants are available (e.g., ~140–160). Pilot work in population data shows modest, but statistically significant predictive utility for a small collection of risk variants, smaller in effect than age and gender alone in predicting an individual’s CRC risk. Further genotyping and many more samples will be required, and indeed the discovery of many more risk loci associated with CRC before the question of the potential utility of germline genomic profiling can be definitively answered

Implementation of an educational intervention to improve hand washing in primary schools: process evaluation within a randomised controlled trial

Background: Process evaluations are useful for understanding how interventions are implemented in trial settings. This is important for interpreting main trial results and indicating how the intervention might function beyond the trial. The purpose of this study was to examine the reach, dose, fidelity, acceptability, and sustainability of the implementation of an educational hand washing intervention in primary schools, and to explore views regarding acceptability and sustainability of the intervention. Methods: Process evaluation within a cluster randomised controlled trial, including focus groups with pupils aged 6 to 11, semi-structured interviews with teachers and external staff who coordinated the intervention delivery, and school reports and direct observations of the intervention delivery. Results: The educational package was delivered in 61.4% of schools (85.2% of intervention schools, 37.8% of control schools following completion of the trial). Teachers and pupils reacted positively to the intervention, although concerns were raised about the age-appropriateness of the resources. Teachers adapted the resources to suit their school setting and pupils. Staff coordinating the intervention delivery had limited capacity to follow up and respond to schools. Conclusions: The hand washing intervention was acceptable to schools, but its reach outside of a randomised trial, evidenced in the low proportion of schools in the control arm who received it after the trial had ended, suggests that the model of delivery may not be sustainable.Catherine R Chittleborough, Alexandra L Nicholson, Elaine Young, Sarah Bell and Rona Campbel

Quantity and quality of childcare and children’s educational outcomes

Policy-makers wanting to support child development can choose to adjust the quantity or quality of publicly funded universal pre-school. To assess the impact of such changes, we estimate the effects of an increase in free pre-school education in England of about 3.5 months at age 3 on children’s school achievement at age 5. We exploit date-of-birth discontinuities that create variation in the length and starting age of free pre-school using administrative school records linked to nursery characteristics. Estimated effects are small overall, but the impact of the additional term is substantially larger in settings with the highest inspection quality rating but not in settings with highly qualified staff. Estimated effects fade out by age 7

Fall Armyworm (Spodoptera frugiperda)

The fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), originated from America but is reported recently from Africa and the Asia-Pacific. FAW has caused huge international concern since its outbreak in Africa since 2016 and in Asia since mid-2018. The chapter mainly reviews its global distribution, life cycle, identification characters, strains, host plants, nature of damage, economic damage, and integrated pest management strategies available. The pest completes its life cycle on maize in 30 days (in warm summer months); in cooler temperatures, it may extend up to 60–90 days. For effective management of fall armyworm, different tools, viz., cultural control, agronomic management, breeding for resistance, natural enemies, and eco-friendly insecticides, should be used in an integrated approach. As the insect is recently introduced to Africa and the Asia-Pacific, possible management strategies and future cases of action are discussed