Ultrasound Based Analysis- A

Master thesis in medicine, Programme of medicine, Sahlgrenska Academy, Gothenburg, Sweden Title: Ultrasound Based Analysis – a Non-invasive Method to Predict Respiratory Morbidity in the Newborn. Author, Year: Patricia Johansson, 2014 Institution: Institution of Clinical Science, Department of Obstetrics and Gynaecology Background: Approximately 11% of all live births globally are premature, meaning birth before 37 weeks of gestation. Preterms are affected by higher rates of mortality and morbidity, especially respiratory complications due to the late development of the fetal lungs. One of the most common disorders is RDS, Respiratory Distress Syndrome, which is a potentially fatal condition and associated with surfactant deficiency. Today the only way of assessing fetal lung maturity is through amniocentesis and the amount of surfactant in the amniotic fluid. It is an invasive procedure entailing risks such as infection and miscarriage. The possibilities to assess fetal lung maturity through ultrasound based quantitative texture analysis have been greatly explored during the last years. A Spanish research team has developed an algorithm, QuantUS-FLM with the intention to be able to predict respiratory morbidity by quantitative texture analysis of ultrasound images of fetal lungs. A similar master thesis project evaluating the predecessor to the current algorithm, AQUA,was recently conducted at Sahlgrenska Hospital Östra by medical student Lars Cedergren. During this study difficulties for an inexperienced student to obtain ultrasound images of sufficient quality to be analysed in the algorithm were discovered. Because of this a quality assurance model to raise the number of approved images was developed. Aims: To explore if ultrasound based quantitative texture analysis is a practicable way of predicting neonatal respiratory morbidity. A secondary aim was to evaluate the previous developed quality assurance model of ultrasound image acquisition. Method: 41 ultrasound images of fetal lungs from pregnant women admitted to the delivery wards at Sahlgrenska Hospital Östra were obtained during October 2013 to Mars 2014. Inclusion criteria were gestational weeks 25+0 to 40+0, maternal BMI below 35, no antenatal steroids administrated between the image acquisition and the parturition, delivery occurring within 48 hours from the image acquisition and no malformations that could potentially affect the respiratory function. An additional 37 images obtained by medical student Lars Cedergren were added to the study. The images were then analysed with the QuantUS-FLM software online application developed by the Spanish research team. A review of both the mother’s and the child’s medical records was done in regards to maternal age, maternal conditions and neonatal data. Statistical descriptive analysis was performed using SPSS. Results: QuantUS-FLM analysed a total of 71 images and predicted 16 as high risk of developing a neonatal respiratory morbidity. Among these 16, five neonates developed RDS and two developed another respiratory morbidity. None of the 55 neonates that were classified as low risk of developing a respiratory morbidity eventually did so. Using the quality assurance model developed by a previous master thesis student raised the initial approval rate of the first collection phase from 50% in the previously carried out study, to 87% in this study. Discussion: This study might indicate some optimism of the ability of QuantUS-FLM algorithm to predict respiratory morbidity through quantitative texture analysis. Due to low incidence of RDS, the formation of the study and the student’s pre-requisites for this study a sufficient amount of included patients to achieve a moderately strong indication was not achieved. As this is only a local study within a larger multicentre study such a number of included patients was, on the other hand, never the essential goal. A test that could predict neonatal respiratory morbidity is of special clinical importance in the group of neonates born in gestational week 28 to 36 where the obstetrician is facing the dilemmas of delivery planning and antenatal steroid administration. Conclusions: Any conclusions regarding QuantUS-FLM and its ability to predict respiratory morbidity in the newborn cannot be made due to lack of power in this study. The quality assurance model of image acquisition will likely have contributed to increase the number of ultrasound images approved for analysis with the algorithm by the Spanish research team. More education and practical training of the student and clearer guidelines concerning optimal image features would possibly increase it even more