NEUROlogical Prognosis After Cardiac Arrest in Kids (NEUROPACK) study: protocol for a prospective multicentre clinical prediction model derivation and validation study in children after cardiac arrest

Introduction Currently, we are unable to accurately predict mortality or neurological morbidity following resuscitation after paediatric out of hospital (OHCA) or in-hospital (IHCA) cardiac arrest. A clinical prediction model may improve communication with parents and families and risk stratification of patients for appropriate postcardiac arrest care. This study aims to the derive and validate a clinical prediction model to predict, within 1 hour of admission to the paediatric intensive care unit (PICU), neurodevelopmental outcome at 3 months after paediatric cardiac arrest. Methods and analysis A prospective study of children (age: >24 hours and <16 years), admitted to 1 of the 24 participating PICUs in the UK and Ireland, following an OHCA or IHCA. Patients are included if requiring more than 1 min of cardiopulmonary resuscitation and mechanical ventilation at PICU admission Children who had cardiac arrests in PICU or neonatal intensive care unit will be excluded. Candidate variables will be identified from data submitted to the Paediatric Intensive Care Audit Network registry. Primary outcome is neurodevelopmental status, assessed at 3 months by telephone interview using the Vineland Adaptive Behavioural Score II questionnaire. A clinical prediction model will be derived using logistic regression with model performance and accuracy assessment. External validation will be performed using the Therapeutic Hypothermia After Paediatric Cardiac Arrest trial dataset. We aim to identify 370 patients, with successful consent and follow-up of 150 patients. Patient inclusion started 1 January 2018 and inclusion will continue over 18 months. Ethics and dissemination Ethical review of this protocol was completed by 27 September 2017 at the Wales Research Ethics Committee 5, 17/WA/0306. The results of this study will be published in peer-reviewed journals and presented in conferences. Trial registration number NCT03574025

Challenge of prostate MRI segmentation on T2-weighted images: inter-observer variability and impact of prostate morphology

International audienc

Correction to: Prostate Volume Prediction on MRI: Tools, Accuracy and Variability

International audienceA reliable estimation of prostate volume (PV) is essential to prostate cancer management. The objective of our multi-rater study was to compare intra- and inter-rater variability of PV from manual planimetry and ellipsoid formulas

Prostate volume prediction on MRI: tools, accuracy and variability

The original publication is available at www.springerlink.com: https://link.springer.com/article/10.1007/s00330-022-08554-4International audienceOBJECTIVE: A reliable estimation of prostate volume (PV) is essential to prostate cancer management. Theobjective of our multi-rater study was to compare intra and inter-rater variability of PV frommanual planimetry and ellipsoid formulas.METHODS: Forty treatment-naive patients who underwent prostate MRI were selected from a localdatabase. PV and corresponding PSA density (PSAd) were estimated on 3D T2-weighted MRI(3T) by 7 independent radiologists using the traditional ellipsoid formula (TEF),the newerbiproximate ellipsoid formula (BPEF), and the manual planimetry method (MPM) used asground truth. Intra and inter-rater variability was calculated using the mixed model basedintraclass correlation coefficient (ICC).RESULTS: Mean volumes were 67.00 (±36.61), 66.07(±35.03), and 64.77(±38.27)cm 3 with the TEF,BPEF, and MPM methods respectively. Both TEF and BPEF overestimated PV relative toMPM, with the former presenting significant differences (+1.91cm3, IQ=[-0.33cm3, 5.07cm3],p-val=0.03). Both intra (ICC>0.90) and inter-rater (ICC>0.90) reproducibility were excellent. MPM had thehighest inter-rater reproducibility (ICC=0.999). Inter-rater PV variation led to discrepancies inclassification according to the clinical criterion of PSAd>0.15ng/mL for 2 patients (5%), 7patients (17.5%), and 9 patients (22.5%) when using MPM, TEF, and BPEF respectively.CONCLUSION: PV measurements using ellipsoid formulas and MPM are highly reproducible. MPM is a robustmethod for PV assessment and PSAd calculation, with the lowest variability. TEF showed ahigh degree of concordance with MPM but a slight overestimation of PV. Precise anatomiclandmarks as defined with the BPEF led to a more accurate PV estimation, but also to a highervariability

Reference standard for the evaluation of automatic segmentation algorithms: Quantification of inter observer variability of manual delineation of prostate contour on MRI

International audienceThe purpose of this study was to investigate the relationship between inter-reader variability in manual prostate contour segmentation on magnetic resonance imaging (MRI) examinations and determine the optimal number of readers required to establish a reliable reference standard. Materials and methods: Seven radiologists with various experiences independently performed manual segmentation of the prostate contour (whole-gland [WG] and transition zone [TZ]) on 40 prostate MRI examinations obtained in 40 patients. Inter-reader variability in prostate contour delineations was estimated using standard metrics (Dice similarity coefficient [DSC], Hausdorff distance and volume-based metrics). The impact of the number of readers (from two to seven) on segmentation variability was assessed using pairwise metrics (consistency) and metrics with respect to a reference segmentation (conformity), obtained either with majority voting or simultaneous truth and performance level estimation (STAPLE) algorithm. Results: The average segmentation DSC for two readers in pairwise comparison was 0.919 for WG and 0.876 for TZ. Variability decreased with the number of readers: the interquartile ranges of the DSC were 0.076 (WG) / 0.021 (TZ) for configurations with two readers, 0.005 (WG) / 0.012 (TZ) for configurations with three readers, and 0.002 (WG) / 0.0037 (TZ) for configurations with six readers. The interquartile range decreased slightly faster between two and three readers than between three and six readers. When using consensus methods, variability often reached its minimum with three readers (with STAPLE, DSC = 0.96 [range: 0.945 −0.971] for WG and DSC = 0.94 [range: 0.912−0.957] for TZ, and interquartile range was minimal for configurations with three readers. Conclusion: The number of readers affects the inter-reader variability, in terms of inter-reader consistency and conformity to a reference. Variability is minimal for three readers, or three readers represent a tipping point in the variability evolution, with both pairwise-based metrics or metrics with respect to a reference. Accordingly, three readers may represent an optimal number to determine references for artificial intelligence applications

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population.The aim of this study was to inform vaccination prioritization by modelling the impact of vaccination on elective inpatient surgery. The study found that patients aged at least 70 years needing elective surgery should be prioritized alongside other high-risk groups during early vaccination programmes. Once vaccines are rolled out to younger populations, prioritizing surgical patients is advantageous