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ADC Values from brain MRI may Predict Neurological Outcomes in OHCA Survivors: Study
Recently published study conducted a quantitative analysis of apparent diffusion coefficient (ADC) values obtained from brain magnetic resonance imaging (MRI) to predict poor neurological outcomes in out-of-hospital cardiac arrest (OHCA) survivors. The observational study used data from two tertiary academic hospitals, with a derivation cohort of 70% of the patients randomly selected from one hospital and internal/external validation cohorts comprising the remaining 30% and data from another hospital, respectively. A total of 448 brain MRI scans were evaluated, and the proportion of brain volume with specific ADC values below 450, 500, 550, 600, and 650 × 10–6 mm2/s demonstrated good to excellent performance in predicting poor neurological outcomes. The study observed high reproducibility and sensitivity at a 0% false-positive rate (FPR) when maintaining consistent specifications for the MRI type (3 T) and timing of image acquisition (72–96 h after OHCA). The proportion of brain volume with an ADC below 600 × 10–6 mm2/s predicted a poor outcome with high sensitivity (76%) and 0% FPR in the derivation cohort, with similar performance in the internal and external validation cohorts.
The study overcame the limitations associated with qualitative analysis of MRI scans and identified specific ADC thresholds that differentiate between good and poor neurological outcomes in OHCA survivors. The researchers also highlighted the need for prospective multicentre studies to validate these findings and suggested that consistent specifications for MRI types and imaging timing could lead to improved predictive performance. The study showed that maintaining a specific MRI type (3 T) and timing of image acquisition (72–96 h after OHCA) resulted in high reproducibility and sensitivity, and the identified cut-off values showed consistent performance across derivation, internal validation, and external validation cohorts. The study emphasized the potential of MRI-based quantitative analysis as a significant predictor in a multimodal approach for prognostic prediction in OHCA survivors.
Key Points
1. The study conducted a quantitative analysis of apparent diffusion coefficient (ADC) values obtained from brain magnetic resonance imaging (MRI) to predict poor neurological outcomes in out-of-hospital cardiac arrest (OHCA) survivors. The study used data from two tertiary academic hospitals, with a total of 448 brain MRI scans evaluated. The proportion of brain volume with specific ADC values below certain thresholds demonstrated good to excellent performance in predicting poor neurological outcomes, with a high reproducibility and sensitivity at a 0% false-positive rate (FPR) when maintaining consistent specifications for the MRI type (3 T) and timing of image acquisition (72–96 h after OHCA).
2. The study identified specific ADC thresholds that differentiate between good and poor neurological outcomes in OHCA survivors, overcoming the limitations associated with qualitative analysis of MRI scans. The researchers emphasized the need for prospective multicentre studies to validate these findings and suggested that consistent specifications for MRI types and imaging timing could lead to improved predictive performance. The study also highlighted the potential of MRI-based quantitative analysis as a significant predictor in a multimodal approach for prognostic prediction in OHCA survivors.
3. The proportion of brain volume with an ADC below 600 × 10–6 mm2/s predicted a poor outcome with high sensitivity (76%) and 0% false-positive rate in the derivation cohort, with similar performance in the internal and external validation cohorts. The identified cut-off values showed consistent performance across derivation, internal validation, and external validation cohorts. This suggests that MRI-based quantitative analysis of ADC values has the potential to be an important tool in predicting neurological outcomes in OHCA survivors, particularly when specific MRI types and imaging timing are consistently maintained.
Reference –
Yoon, J.A., Kang, C., Park, J.S. et al. Quantitative analysis of apparent diffusion coefficients to predict neurological prognosis in cardiac arrest survivors: an observational derivation and internal–external validation study. Crit Care 28, 138 (2024). https://doi.org/10.1186/s13054-024-04909-z
MBBS, MD (Anaesthesiology), FNB (Cardiac Anaesthesiology)
Dr Monish Raut is a practicing Cardiac Anesthesiologist. He completed his MBBS at Government Medical College, Nagpur, and pursued his MD in Anesthesiology at BJ Medical College, Pune. Further specializing in Cardiac Anesthesiology, Dr Raut earned his FNB in Cardiac Anesthesiology from Sir Ganga Ram Hospital, Delhi.