Software for computerised analysis of cardiotocographic traces. Issue 124 (February 2016) - Romano, M.; Bifulco, P.; Ruffo, M.; Improta, G.; Clemente, F.; Cesarelli, M.
Highlights: A software for automatic CTG analysis which could be a useful clinical tool is shown. The software provides important classical and nonlinear parameters. Simulated and real CTG traces were analysed to test software reliability. The software showed good performance, in fact all simulated events were detected. On real CTG: sensitivity equal to 93%, positive predictive value 82%, accuracy 77%. Abstract: Despite the widespread use of cardiotocography in foetal monitoring, the evaluation of foetal status suffers from a considerable inter and intra-observer variability. In order to overcome the main limitations of visual cardiotocographic assessment, computerised methods to analyse cardiotocographic recordings have been recently developed. In this study, a new software for automated analysis of foetal heart rate is presented. It allows an automatic procedure for measuring the most relevant parameters derivable from cardiotocographic traces. Simulated and real cardiotocographic traces were analysed to test software reliability. In artificial traces, we simulated a set number of events (accelerations, decelerations and contractions) to be recognised. In the case of real signals, instead, results of the computerised analysis were compared with the visual assessment performed by 18 expert clinicians and three performance indexes were computed to gain information about performances of the proposed software. The software showed preliminary performance we judged satisfactory in that the results matched completely the requirements, as proved by tests on artificial signals in which all simulated events were detected from the software. Performance indexes computed in comparison with obstetricians' evaluations are, on the contrary, not so satisfactory; in fact they led to obtain the following values of the statistical parameters: sensitivity equal to 93%, positive predictive value equal to 82% and accuracy equal to 77%. Very probably this arises from the high variability of trace annotation carried out by clinicians.