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Standardised and automated assessment of head computed tomography reliably predicts poor functional outcome after cardiac arrest: a prospective multicentre study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2024年6月20日

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  • Margareta Lang,
  • Martin Kenda,
  • Michael Scheel,
  • Juha Martola,
  • Matthew Wheeler,
  • Stephanie Owen,
  • Mikael Johnsson,
  • Martin Annborn,
  • Josef Dankiewicz,
  • Nicolas Deye,
  • Joachim Düring,
  • Hans Friberg,
  • Thomas Halliday,
  • Janus Christian Jakobsen,
  • Jean-Baptiste Lascarrou,
  • Helena Levin,
  • Gisela Lilja,
  • Anna Lybeck,
  • Peter McGuigan,
  • Christian Rylander,
  • Victoria Sem,
  • Matthew Thomas,
  • Susann Ullén,
  • Johan Undén,
  • Matt P. Wise,
  • Tobias Cronberg,
  • Johan Wassélius,
  • Niklas Nielsen,
  • Christoph Leithner,
  • Marion Moseby-Knappe

摘要

Purpose

Application of standardised and automated assessments of head computed tomography (CT) for neuroprognostication after out-of-hospital cardiac arrest.

Methods

Prospective, international, multicentre, observational study within the Targeted Hypothermia versus Targeted Normothermia after out-of-hospital cardiac arrest (TTM2) trial. Routine CTs from adult unconscious patients obtained > 48 h ≤ 7 days post-arrest were assessed qualitatively and quantitatively by seven international raters blinded to clinical information using a pre-published protocol. Grey–white-matter ratio (GWR) was calculated from four (GWR-4) and eight (GWR-8) regions of interest manually placed at the basal ganglia level. Additionally, GWR was obtained using an automated atlas-based approach. Prognostic accuracies for prediction of poor functional outcome (modified Rankin Scale 4–6) for the qualitative assessment and for the pre-defined GWR cutoff < 1.10 were calculated.

Results

140 unconscious patients were included; median age was 68 years (interquartile range [IQR] 59–76), 76% were male, and 75% had poor outcome. Standardised qualitative assessment and all GWR models predicted poor outcome with 100% specificity (95% confidence interval [CI] 90–100). Sensitivity in median was 37% for the standardised qualitative assessment, 39% for GWR-8, 30% for GWR-4 and 41% for automated GWR. GWR-8 was superior to GWR-4 regarding prognostic accuracies, intra- and interrater agreement. Overall prognostic accuracy for automated GWR (area under the curve [AUC] 0.84, 95% CI 0.77–0.91) did not significantly differ from manually obtained GWR.

Conclusion

Standardised qualitative and quantitative assessments of CT are reliable and feasible methods to predict poor functional outcome after cardiac arrest. Automated GWR has the potential to make CT quantification for neuroprognostication accessible to all centres treating cardiac arrest patients.