Search

Objectives In utero Magnetic Resonance (iuMR) imaging to diagnose fetal brain abnormalities has been established and is supported by meta-analyses of retrospective and prospective studies. In this paper we describe and classify the iuMR errors made in the largest diagnostic accuracy study to date (MERIDIAN). We also correlate the error rates and types with the prior experience of the reporting radiologists in order to inform how to provide a national programme with the best diagnostic accuracy achievable. Methods The MERIDIAN cohort of 570 fetuses formed the basis of this study and included 40 cases with a confirmed diagnostic error, compared with the Outcome Reference Diagnosis. Analysis included the potential clinical effect of the error and classification of error type through an Expert Neuroradiological Panel re-reporting the study. Assessments were made regarding radiologists experience prior to MERIDIAN. Results The overall confirmed error rate for iuMR was 7·0% and it was considered that there would have been an adverse effect on prognostic information in 22/40 cases if the iuMR had informed counselling. The experienced central reporter made statistically significant fewer errors than the less experienced non-central reporters (3·8% v 11·0%) and the central reporter made fewer clinically significant errors. Furthermore, the type of cognitive errors differed between central and non-central reporters. Conclusions Although iuMR imaging improves the diagnostic accuracy of detecting fetal brain abnormalities there remains a substantial error rate, which can have major clinical significance. We have shown that error rates are lower for more experienced reporting radiologists with fewer potential deleterious clinical implications. We discuss the implications of these findings in terms of providing a uniform national service.

Background Birth-related acute profound hypoxic–ischaemic\ud brain injury has specific patterns of damage including the\ud paracentral lobules.\ud Objective To test the hypothesis that there is anatomically coherent\ud regional volume loss of the corpus callosum as a result of\ud this hemispheric abnormality.\ud Materials and methods Study subjects included 13 children\ud with proven acute profound hypoxic–ischaemic brain injury\ud and 13 children with developmental delay but no brain abnormalities.\ud A computerised system divided the corpus callosum\ud into 100 segments, measuring each width. Principal component\ud analysis grouped the widths into contiguous anatomical regions.\ud We conducted analysis of variance of corpus callosum widths as\ud well as support vector machine stratification into patient groups.\ud Results There was statistically significant narrowing of the\ud mid–posterior body and genu of the corpus callosum in children\ud with hypoxic–ischaemic brain injury. Support vector machine\ud analysis yielded over 95% accuracy in patient group stratification\ud using the corpus callosum centile widths.\ud Conclusion Focal volume loss is seen in the corpus callosum\ud of children with hypoxic–ischaemic brain injury secondary to\ud loss of commissural fibres arising in the paracentral lobules.\ud Support vector machine stratification into the hypoxic–ischaemic\ud brain injury group or the control group on the basis of\ud corpus callosum width is highly accurate and points towards\ud rapid clinical translation of this technique as a potential biomarker\ud of hypoxic–ischaemic brain injury

This work concerns a review of the state of the art of current and practical experience on environmental assessment (including monitoring) in order to set the path to be followed for future ocean energy schemes. It includes a revision of the work done so far in some test sites and deployment sites and discusses the use of several tools considering project phases (installation, deployment and decommissioning) and environmental impact assessment steps (screening, scoping, baseline studies for reference condition characterization, impact identification and evaluation, mitigation measures and monitoring). Within the list of such tools the applicability of checklists, matrices, mathematical modelling, Geographic Information Systems are considered as well as other shared and integrative methods: Environmental Risk Assessment and Life Cycle Analysis.