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Chan WP, Nguyen C, Kim N, Tripodis Y, Gilmore EJ, Greer DM, Beekman R. A practical magnetic-resonance imaging score for outcome prediction in comatose cardiac arrest survivors. Resuscitation 2024; 202:110370. [PMID: 39178939 DOI: 10.1016/j.resuscitation.2024.110370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Revised: 08/04/2024] [Accepted: 08/16/2024] [Indexed: 08/26/2024]
Abstract
AIM Magnetic Resonance Imaging (MRI) is an important prognostic tool in cardiac arrest (CA) survivors given its sensitivity for detecting hypoxic-ischemic brain injury (HIBI), however, it is limited by poorly defined objective thresholds. To address this limitation, we evaluated a qualitative MRI score for predicting neurological outcome in CA survivors. METHODS Adult comatose CA survivors who underwent MRI were retrospectively identified at a single academic medical center. Two blinded neurointensivists qualitatively scored HIBI amongst 12 MRI brain regions. Scores were summated to form four distinct score groups: cortex, deep grey nuclei (DGN), cortex-DGN combined, and total (cortex, DGN, brainstem, and cerebellum). Poor neurological outcome was defined as Cerebral Performance Category (CPC) score 3-5 at hospital discharge. Inter-rater reliability was tested using intra-class correlation (ICC) and discrimination of poor neurological outcome assessed using area under the receiver operating curve (AUC). RESULTS Our cohort included 219 patients with median time to MRI of 96 (IQR 81-110) hours. ICC (95% CI) was good to excellent across all MRI scores: cortex 0.92 (0.89-0.94), DGN 0.88 (0.80-0.92), cortex-DGN 0.94 (0.92-0.95), and total 0.93 (0.91-0.95). AUC (95% CI) for poor outcome was good across all MRI scores: cortex 0.84 (0.78-0.90), DGN 0.83 (0.77-0.89), cortex-DGN 0.83 (0.77-0.89), and total 0.83 (0.77-0.88). CONCLUSION A simplified, qualitative MRI score had excellent reliability and good discrimination for poor neurologic outcome. Further work is necessary to externally validate our findings in an independent, ideally prospective, cohort.
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Affiliation(s)
- Wang Pong Chan
- Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
| | - Christine Nguyen
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA.
| | - Noah Kim
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA.
| | - Yorghos Tripodis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
| | - Emily J Gilmore
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA.
| | - David M Greer
- Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA.
| | - Rachel Beekman
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA.
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Yoon JA, Kang C, Park JS, You Y, Min JH, In YN, Jeong W, Ahn HJ, Jeong HS, Kim YH, Lee BK, Kim D. Quantitative analysis of apparent diffusion coefficients to predict neurological prognosis in cardiac arrest survivors: an observational derivation and internal-external validation study. Crit Care 2024; 28:138. [PMID: 38664807 PMCID: PMC11044301 DOI: 10.1186/s13054-024-04909-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Accepted: 04/11/2024] [Indexed: 04/29/2024] Open
Abstract
BACKGROUND This study aimed to validate apparent diffusion coefficient (ADC) values and thresholds to predict poor neurological outcomes in out-of-hospital cardiac arrest (OHCA) survivors by quantitatively analysing the ADC values via brain magnetic resonance imaging (MRI). METHODS This observational study used prospectively collected data from two tertiary academic hospitals. The derivation cohort comprised 70% of the patients randomly selected from one hospital, whereas the internal validation cohort comprised the remaining 30%. The external validation cohort used the data from another hospital, and the MRI data were restricted to scans conducted at 3 T within 72-96 h after an OHCA experience. We analysed the percentage of brain volume below a specific ADC value at 50-step intervals ranging from 200 to 1200 × 10-6 mm2/s, identifying thresholds that differentiate between good and poor outcomes. Poor neurological outcomes were defined as cerebral performance categories 3-5, 6 months after experiencing an OHCA. RESULTS A total of 448 brain MRI scans were evaluated, including a derivation cohort (n = 224) and internal/external validation cohorts (n = 96/128, respectively). The proportion of brain volume with ADC values below 450, 500, 550, 600, and 650 × 10-6 mm2/s demonstrated good to excellent performance in predicting poor neurological outcomes in the derivation group (area under the curve [AUC] 0.89-0.91), and there were no statistically significant differences in performances among the derivation, internal validation, and external validation groups (all P > 0.5). Among these, the proportion of brain volume with an ADC below 600 × 10-6 mm2/s predicted a poor outcome with a 0% false-positive rate (FPR) and 76% (95% confidence interval [CI] 68-83) sensitivity at a threshold of > 13.2% in the derivation cohort. In both the internal and external validation cohorts, when using the same threshold, a specificity of 100% corresponded to sensitivities of 71% (95% CI 58-81) and 78% (95% CI 66-87), respectively. CONCLUSIONS In this validation study, by consistently restricting the MRI types and timing during quantitative analysis of ADC values in brain MRI, we observed high reproducibility and sensitivity at a 0% FPR. Prospective multicentre studies are necessary to validate these findings.
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Affiliation(s)
- Jung A Yoon
- Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea
| | - Changshin Kang
- Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea
| | - Jung Soo Park
- Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea.
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea.
| | - Yeonho You
- Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea
| | - Jin Hong Min
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea
- Department of Emergency Medicine, Chungnam National University Sejong Hospital, Daejoen, Republic of Korea
| | - Yong Nam In
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea
- Department of Emergency Medicine, Chungnam National University Sejong Hospital, Daejoen, Republic of Korea
| | - Wonjoon Jeong
- Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea
| | - Hong Jun Ahn
- Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea
| | - Hye Seon Jeong
- Department of Neurology, Chungnam National University Hospital, Daejoen, Republic of Korea
| | - Yong Hwan Kim
- Department of Emergency Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Gyeongsangnam-do, Republic of Korea
| | - Byung Kook Lee
- Department of Emergency Medicine, Chonnam National University Medical School, Chonnam National University Hospital, Gwangju, Republic of Korea
| | - Dongha Kim
- Department of Statistics, Sungshin Women's University, Seoul, Republic of Korea
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Park JS, Kim EY, You Y, Min JH, Jeong W, Ahn HJ, In YN, Lee IH, Kim JM, Kang C. Combination strategy for prognostication in patients undergoing post-resuscitation care after cardiac arrest. Sci Rep 2023; 13:21880. [PMID: 38072906 PMCID: PMC10711008 DOI: 10.1038/s41598-023-49345-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 12/07/2023] [Indexed: 12/18/2023] Open
Abstract
This study investigated the prognostic performance of combination strategies using a multimodal approach in patients treated after cardiac arrest. Prospectively collected registry data were used for this retrospective analysis. Poor outcome was defined as a cerebral performance category of 3-5 at 6 months. Predictors of poor outcome were absence of ocular reflexes (PR/CR) without confounding factors, a highly malignant pattern on the most recent electroencephalography, defined as suppressed background with or without periodic discharges and burst-suppression, high neuron-specific enolase (NSE) after 48 h, and diffuse injury on imaging studies (computed tomography or diffusion-weighted imaging [DWI]) at 72-96 h. The prognostic performances for poor outcomes were analyzed for sensitivity and specificity. A total of 130 patients were included in the analysis. Of these, 68 (52.3%) patients had poor outcomes. The best prognostic performance was observed with the combination of absent PR/CR, high NSE, and diffuse injury on DWI [91.2%, 95% confidence interval (CI) 80.7-97.1], whereas the combination strategy of all available predictors did not improve prognostic performance (87.8%, 95% CI 73.8-95.9). Combining three of the predictors may improve prognostic performance and be more efficient than adding all tests indiscriminately, given limited medical resources.
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Affiliation(s)
- Jung Soo Park
- Department of Emergency Medicine, Chungnam National University Hospital, 282 Munhwa-ro, Jung-gu, Daejeon, Republic of Korea
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 282 Mokdong-ro, Jung-gu, Daejeon, Republic of Korea
| | - Eun Young Kim
- Department of Neurology, Chungnam National University Sejong Hospital, 20, Bodeum 7-ro, Sejong, Republic of Korea
| | - Yeonho You
- Department of Emergency Medicine, Chungnam National University Hospital, 282 Munhwa-ro, Jung-gu, Daejeon, Republic of Korea
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 282 Mokdong-ro, Jung-gu, Daejeon, Republic of Korea
| | - Jin Hong Min
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 282 Mokdong-ro, Jung-gu, Daejeon, Republic of Korea
| | - Wonjoon Jeong
- Department of Emergency Medicine, Chungnam National University Hospital, 282 Munhwa-ro, Jung-gu, Daejeon, Republic of Korea
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 282 Mokdong-ro, Jung-gu, Daejeon, Republic of Korea
| | - Hong Joon Ahn
- Department of Emergency Medicine, Chungnam National University Hospital, 282 Munhwa-ro, Jung-gu, Daejeon, Republic of Korea
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 282 Mokdong-ro, Jung-gu, Daejeon, Republic of Korea
| | - Yong Nam In
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 282 Mokdong-ro, Jung-gu, Daejeon, Republic of Korea
| | - In Ho Lee
- Department of Radiology, Chungnam National University Hospital, 282 Munhwa-ro, Jung-gu, Daejeon, Republic of Korea
- Department of Radiology, College of Medicine, Chungnam National University, 282 Mokdong-ro, Jung-gu, Daejeon, Republic of Korea
| | - Jae Moon Kim
- Department of Neurology, College of Medicine, Chungnam National University, 282 Mokdong-ro, Jung-gu, Daejeon, Republic of Korea
| | - Changshin Kang
- Department of Emergency Medicine, Chungnam National University Hospital, 282 Munhwa-ro, Jung-gu, Daejeon, Republic of Korea.
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 282 Mokdong-ro, Jung-gu, Daejeon, Republic of Korea.
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Yoon JA, Kang C, Park JS, You Y, Min JH, In YN, Jeong W, Ahn HJ, Lee IH, Jeong HS, Lee BK, Lee JK. Quantitative analysis of early apparent diffusion coefficient values from MRIs for predicting neurological prognosis in survivors of out-of-hospital cardiac arrest: an observational study. Crit Care 2023; 27:407. [PMID: 37880777 PMCID: PMC10599006 DOI: 10.1186/s13054-023-04696-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 10/19/2023] [Indexed: 10/27/2023] Open
Abstract
BACKGROUND This study aimed to quantitatively analyse ultra-early brain diffusion-weighted magnetic resonance imaging (DW-MRI) findings to determine the apparent diffusion coefficient (ADC) threshold associated with neurological outcomes in comatose survivors of out-of-hospital cardiac arrest (OHCA). METHODS This retrospective study included adult survivors of comatose OHCA who underwent DW-MRI imaging scans using a 3-T MRI scanner within 6 h of the return of spontaneous circulation (ROSC). We investigated the association between neurological outcomes and ADC values obtained through voxel-based analysis on DW-MRI. Additionally, we constructed multivariable logistic regression models with pupillary light reflex (PLR), serum neuron-specific enolase (NSE), and ADC values as independent variables to predict poor neurological outcomes. The primary outcome was poor neurological outcome 6 months after ROSC, determined by the Cerebral Performance Category 3-5. RESULTS Overall, 131 patients (26% female) were analysed, of whom 74 (57%) showed poor neurological outcomes. The group with a poor neurological outcome had lower mean whole brain ADC values (739.1 vs. 787.1 × 10-6 mm/s) and higher percentages of voxels with ADC below threshold in all ranges (250-1150) (all P < 0.001). The mean whole brain ADC values (area under the receiver operating characteristic curve [AUC] 0.83) and the percentage of voxels with ADC below 600 (AUC 0.81) had the highest sensitivity of 51% (95% confidence interval [CI] 39.4-63.1; cut-off value ≤ 739.2 × 10-6 mm2/s and > 17.2%, respectively) when the false positive rate (FPR) was 0%. In the multivariable model, which also included PLR, NSE, and mean whole brain ADC values, poor neurological outcome was predicted with the highest accuracy (AUC 0.91; 51% sensitivity). This model showed more accurate prediction and sensitivity at an FPR of 0% than did the combination of PLR and NSE (AUC 0.86; 30% sensitivity; P = 0.03). CONCLUSIONS In this cohort study, early voxel-based quantitative ADC analysis after ROSC was associated with poor neurological outcomes 6 months after cardiac arrest. The mean whole brain ADC value demonstrated the highest sensitivity when the FPR was 0%, and including it in the multivariable model improved the prediction of poor neurological outcomes.
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Affiliation(s)
- Jung A Yoon
- Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea
| | - Changshin Kang
- Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea
| | - Jung Soo Park
- Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea.
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea.
| | - Yeonho You
- Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea
| | - Jin Hong Min
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea
- Department of Emergency Medicine, Sejong Chungnam National University Hospital, Daejoen, Republic of Korea
| | - Yong Nam In
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea
- Department of Emergency Medicine, Sejong Chungnam National University Hospital, Daejoen, Republic of Korea
| | - Wonjoon Jeong
- Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea
| | - Hong Joon Ahn
- Department of Emergency Medicine, Chungnam National University Hospital, Daejoen, Republic of Korea
- Department of Emergency Medicine, College of Medicine, Chungnam National University, 266 Munwha-ro, Jung-gu, Daejeon, 35015, Republic of Korea
| | - In Ho Lee
- Department of Radiology, College of Medicine, Chungnam National University, 266, Munhwa-ro, Jung-gu, Daejeon, Republic of Korea
| | - Hye Seon Jeong
- Department of Neurology, Chungnam National University Hospital, Daejeon, Republic of Korea
| | - Byung Kook Lee
- Department of Emergency Medicine, Chonnam National University Medical School, Chonnam National University Hospital, Gwangju, Republic of Korea
| | - Jae Kwang Lee
- Department of Emergency Medicine, College of Medicine, Konyang University Hospital, Daejeon, Republic of Korea
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