Blurred lines: Reduced discrimination of gray white junctions observed on CT in out-of-hospital cardiac arrest (OHCA) portends poor prognosis

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

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.

Gray matter to white matter ratio for predicting neurological outcomes in patients treated with target temperature management after cardiac arrest: A systematic review and meta-analysis

AIMS

This study aimed to evaluate the prognostic accuracy of the gray matter to white matter ratio (GWR) in predicting neurological outcomes in post-cardiac arrest patients treated with target temperature management.

DATA SOURCES

We systematically searched MEDLINE and EMBASE (Search date: 09/13/2017). Included studies were those evaluating neurological outcomes using the cerebral performance categories scale. We performed a subgroup analysis based on the location of the measurement. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to assess the risk of bias.

RESULTS

In total, 1150 patients from 10 observational studies were included. GWR of the basal ganglia (BG) average showed the highest value (area under the curve [AUC] 0.96, SE 0.02, Q 0.90) compared with the putamen/posterior limb of internal capsule (AUC 0.93, SE 0.05, Q 0.87), overall average (AUC 0.91, SE 0.02, Q 0.85), and cerebrum (AUC 0.89, SE 0.05, Q 0.82) for prognostic accuracy. Furthermore, the highest pooled diagnostic odd ratio of GWR for predicting poor neurological outcomes was shown for the BG average (21.00, 95% CI 6.85-64.40) followed by the overall average (20.71, 95% CI 9.53-44.98), putamen/posterior limb of internal capsule (16.08, 95% CI 4.36-59.23), and cerebrum (13.96, 95% CI 4.26-45.76).

CONCLUSIONS

GWR in the early cranial computed tomography scan had high prognostic value in predicting poor neurological outcomes in post-cardiac arrest patients. The BG GWR had the highest prognostic accuracy when compared to other locations of the brain.