scholarly journals Differences in the gray-to-white matter ratio according to different computed tomography scanners for outcome prediction in post-cardiac arrest patients receiving target temperature management

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258480
Author(s):  
Jae Hun Oh ◽  
Seung Pill Choi ◽  
Jong Ho Zhu ◽  
Soo Hyun Kim ◽  
Kyu Nam Park ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cardiac Arrest ◽  
White Matter ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Internal Capsule ◽  
Temperature Management ◽  
Target Temperature Management ◽  
Ct Scanners ◽  
The Difference

The gray-to-white matter ratio (GWR) has been used to identify brain damage in comatose patients after cardiac arrest. However, Hounsfield units (HUs), the measurement of brain density on computed tomography (CT) images, may vary depending on the machine type or parameter. Therefore, differences in CT scanners may affect the GWR in post-cardiac arrest patients. We performed a retrospective study on comatose post-cardiac arrest patients who visited the hospital from 2007 to 2017. Two CT, Lightspeed and SOMATOM, scanners were used. Two observers independently measured the HUs of the caudate nucleus, putamen, posterior internal capsule, and corpus callosum using regions of interest. We compared the GWR calculated from the HUs measured at different CT scanners. The analysis of different scanners showed statistically significant differences in the measured HUs and GWR. The HUs and GWR of Lightspeed were measured lower than SOMATOM. The difference between the two CT scanners was also evident in groups divided by neurological prognosis. The area under the curve of the receiver operating characteristic curve to predict poor outcomes of Lightspeed was 0.798, and the cut-off value for 100% specificity was 1.172. The SOMATOM was 0.855, and the cut-off value was 1.269. The difference in scanners affects measurements and performance characteristics of the GWR in post-cardiac arrest patients. Therefore, when applying the results of the GWR study to clinical practice, reference values for each device should be presented, and an integrated plan should be prepared.

scholarly journals Does Combining Biomarkers and Brain Images Provide Improved Prognostic Predictive Performance for Out-Of-Hospital Cardiac Arrest Survivors before Target Temperature Management?

2020 ◽  
Vol 9 (3) ◽  
pp. 744 ◽  
Author(s):  
Seung Ha Son ◽  
In Ho Lee ◽  
Jung Soo Park ◽  
In Sool Yoo ◽  
Seung Whan Kim ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Neuron Specific Enolase ◽  
Area Under The Curve ◽  
Temperature Management ◽  
Target Temperature Management ◽  
High Signal ◽  
Target Temperature ◽  
Brain Images ◽  
Prognostic Performance ◽  
Hospital Cardiac Arrest

We examined whether combining biomarkers measurements and brain images early after the return of spontaneous circulation improves prognostic performance compared with the use of either biomarkers or brain images for patients with cardiac arrest following target temperature management (TTM). This retrospective observational study involved comatose out-of-hospital cardiac arrest survivors. We analyzed neuron-specific enolase levels in serum (NSE) or cerebrospinal fluid (CSF), grey-to-white matter ratio by brain computed tomography, presence of high signal intensity (HSI) in diffusion-weighted imaging (DWI), and voxel-based apparent diffusion coefficient (ADC). Of the 58 patients, 33 (56.9%) had poor neurologic outcomes. CSF NSE levels showed better prognostic performance (area under the curve (AUC) 0.873, 95% confidence interval (CI) 0.749–0.950) than serum NSE levels (AUC 0.792, 95% CI 0.644–0.888). HSI in DWI showed the best prognostic performance (AUC 0.833, 95% CI 0.711–0.919). Combining CSF NSE levels and HSI in DWI had better prognostic performance (AUC 0.925, 95% CI 0.813–0.981) than each individual method, followed by the combination of serum NSE levels and HSI on DWI and that of CSF NSE levels and the percentage of voxels of ADC (AUC 0.901, 95% CI 0.792–0.965; AUC 0.849, 95% CI 0.717–0.935, respectively). Combining CSF/serum NSE levels and HSI in DWI before TTM improved the prognostic performance compared to either each individual method or other combinations.

White Matter High Signals Interfere with Noncontrast Computed Tomography in the Early Identification of Cerebral Infarction

2020 ◽  
Vol 49 (2) ◽  
pp. 135-143
Author(s):  
Jixian Lin ◽  
Xutong Li ◽  
Guoqing Wu ◽  
Xi Chen ◽  
Yingfeng Weng ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Ischemic Stroke ◽  
White Matter ◽  
Cerebral Infarction ◽  
Lateral Ventricle ◽  
Clinical Symptoms ◽  
Image Data ◽  
Internal Capsule ◽  
The Difference ◽  
Noncontrast Computed Tomography

Background: We developed an image patch classification-based method to detect early ischemic stroke. The accuracy of this method was >75%. We aimed to analyze patients’ image data to identify interference factors that would affect its accuracy. Methods: We conducted a retrospective analysis of 162 patients who were hospitalized with acute ischemic stroke. Factors related to the noncontrast computed tomography (ncCT) determination results were analyzed according to the patient’s sex, age, clinical symptoms, cerebral infarction volume, cerebral infarction location, and whether or not the white matter high (WMH) signal was combined. Results: The volume of cerebral infarction was positively correlated with the predicted results. The correct percentages of patients with volumes >1 and <1 mL were 59.18 and 83.19%, respectively, and the difference was statistically significant (p = 0.001). The correct percentage of the internal capsule region (47.1%) was significantly lower than that of the other groups (p = 0.011). The correct percentage of lateral ventricular paraventricular infarction was significantly lower than that of non-lateral ventricle patients (70.8 vs. 85.7%). In patients with lateral ventricular paraventricular infarction, if the WMH was combined, the correct percentage will decreased further as the Fazekas level increased. The correct percentage of lateral ventricle infarction combined with Fazekas 3 was 40.0%, which was statistically significant compared with the patient having Fazekas 0 with lateral ventricular infarction (p = 0.01). Conclusions: WMH had a similar computed tomography appearance to cerebral infarction and could interfere with the prediction of the cerebral infarction region by ncCT. This result provides a reference for clinicians to choose imaging methods for identifying acute cerebral infarction areas.

scholarly journals Multimodal Long-Term Predictors of Outcome in Out of Hospital Cardiac Arrest Patients Treated with Targeted Temperature Management at 36 °C

2021 ◽  
Vol 10 (6) ◽  
pp. 1331
Author(s):  
Erik Roman-Pognuz ◽  
Jonathan Elmer ◽  
Frank X. Guyette ◽  
Gabriele Poillucci ◽  
Umberto Lucangelo ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cardiac Arrest ◽  
White Matter ◽  
Temperature Management ◽  
Single Test ◽  
Brain Computed Tomography ◽  
Good Outcome ◽  
Eeg Reactivity ◽  
Single Predictor

Introduction: Early prediction of long-term outcomes in patients resuscitated after cardiac arrest (CA) is still challenging. Guidelines suggested a multimodal approach combining multiple predictors. We evaluated whether the combination of the electroencephalography (EEG) reactivity, somatosensory evoked potentials (SSEPs) cortical complex and Gray to White matter ratio (GWR) on brain computed tomography (CT) at different temperatures could predict survival and good outcome at hospital discharge and six months after the event. Methods: We performed a retrospective cohort study including consecutive adult, non-traumatic patients resuscitated from out-of-hospital CA who remained comatose on admission to our intensive care unit from 2013 to 2017. We acquired SSEPs and EEGs during the treatment at 36 °C and after rewarming at 37 °C, Gray to white matter ratio (GWR) was calculated on the brain computed tomography scan performed within six hours of the hospital admission. We primarily hypothesized that SSEP was associated with favor-able functional outcome at distance and secondarily that SSEP provides independent information from EEG and CT. Outcomes were evaluated using the Cerebral Performance Category (CPC) scale at six months from discharge. Results: Of 171 resuscitated patients, 75 were excluded due to missing data or uninterpretable neurophysiological findings. EEG reactivity at 37 °C has been shown the best single predictor of good out-come (AUC 0.803) while N20P25 was the best single predictor for survival at each time point. (AUC 0.775 at discharge and AUC 0.747 at six months follow up). The predictive value of a model including EEG reactivity, average GWR, and SSEP N20P25 amplitude was superior (AUC 0.841 for survival and 0.920 for good out-come) to any combination of two tests or any single test. Conclusions: Our study, in which life-sustaining treatments were never suspended, suggests SSEP cortical complex N20P25, after normothermia and off sedation, is a reliable predictor for survival at any time. When SSEP cortical complex N20P25 is added into a model with GWR average and EEG reactivity, the predictivity for good outcome and survival at distance is superior than each single test alone.

scholarly journals Multimodal Long Term Predictors of Outcome in Out of Hospital Cardiac Arrest Patients Treated with Targeted Temperature Management at 36°C

2021 ◽  
Author(s):  
Erik Roman-Pognuz ◽  
Jonathan Elmer ◽  
Frank X Guyette ◽  
gabriele poillucci ◽  
umberto lucangelo ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cardiac Arrest ◽  
White Matter ◽  
Temperature Management ◽  
Single Test ◽  
Brain Computed Tomography ◽  
Good Outcome ◽  
Eeg Reactivity ◽  
Single Predictor

Introduction Early prediction of long term outcomes in patients resuscitated after cardiac arrest (CA) is still challenging. Guidelines suggested a multimodal approach combining multiple predictors. We evaluated whether the combination of the electroencephalography (EEG) reactivity, somatosensory evoked potentials (SSEPs) cortical complex and Gray to White matter ratio (GWR) on brain computed tomography (CT) at different temperatures could predict survival and good outcome at hospital discharge and after six months. Methods We performed a retrospective cohort study including consecutive adult, non-traumatic patients resuscitated from out-of-hospital CA who remained comatose on admission to our intensive care unit from 2013 to 2017. We acquired SSEPs and EEGs during the treatment at 36&deg;C and after rewarming at 37&deg;C, Gray to white matter ratio (GWR) was calculated on the brain computed tomography scan performed within six hours of the hospital admission. We primarily hypothesized that SSEP was associated with favorable functional outcome at distance and secondarily that SSEP provides independent information from EEG and CT. Outcomes were evaluated using the Cerebral Performance Category (CPC) scale at six months from discharge. Results Of 171 resuscitated patients, 75 were excluded due to missing of data or uninterpretable neurophysiological findings. EEG reactivity at 37 &deg;C has been shown the best single predictor of good outcome (AUC 0.803) while N20P25 was the best single predictor for survival at each time point. (AUC 0.775 at discharge and AUC 0.747 at six months follow up) Predictive value of a model including EEG reactivity, average GWR, and SSEP N20P25 amplitude was superior (AUC 0.841 for survival and 0.920 for good outcome) to any combination of two tests or any single test. Conclusion Our study, in which life-sustaining treatments were never suspended, suggests SSEP cortical complex N20P25, after normothermia ad off sedation, is a reliable predictor for survival at any time. When SSEP cortical complex N20P25 is added into a model with GWR average and EEG reactivity, the predictivity for good outcome and survival at distance is superior than each single test alone.

Abstract 407: Utility of Abnormal Head Computed Tomography in Predicting Outcome in Out of Hospital Cardiac Arrest Victims Resuscitated and Subsequently Placed on Targeted Temperature Management

Circulation ◽  
2019 ◽  
Vol 140 (Suppl_2) ◽  
Author(s):  
Michael Bernett ◽  
Robert A Swor
Keyword(s):  
Computed Tomography ◽  
Cardiac Arrest ◽  
Survival Analysis ◽  
Interrater Reliability ◽  
Targeted Temperature Management ◽  
Neurologic Outcome ◽  
Temperature Management ◽  
Radiology Reports ◽  
Head Computed Tomography ◽  
Hospital Cardiac Arrest

Introduction: Head computed tomography (HCT) is often performed to assess for hypoxic-ischemic brain injury in resuscitated out of hospital cardiac arrest (OHCA) patients. Our primary objective was to assess whether cerebral edema (CE) on early HCT is associated with poor survival and neurologic outcome post OHCA. Methods: We included subjects from a prospectively collected cardiac arrest database of OHCA adult patients who received targeted temperature management (TTM) at two academic suburban hospitals from 2009-Sept-2018. Cases were included if a HCT was performed in the emergency department (ED). Patient demographics and cardiac arrest variables were collected. HCT results were abstracted by study authors from radiology reports. HCT findings were categorized as no acute disease, evidence of CE, or excluded (bleed, tumor, stroke). Outcomes were survival to discharge or cerebral performance scores (CPC) at discharge of three or four (poor neurologic outcome). Descriptive statistics, univariate, multivariate, survival, and interrater reliability analysis were performed. Results: During the study period, there were 425 OHCA, 277 cases had ED HCTs performed; 254 cases were included in the final survival analysis. Patients were predominately male, 189 (65.0%), average age 60.9 years, average BMI of 30.5. Of all cases, 44 (15.9%) showed CE on CT. Univariate analysis demonstrated that CE was associated with 9.2-fold greater odds of poor outcome (OR: 9.23; 95% CI 1.73, 49.2), and 9.1-fold greater odds of death (OR: 9.09: 95% CI 2.4 33.9). In adjusted analysis, CE was associated with 14.9-fold greater odds of poor CPC outcome (AOR: 14.9, 95% CI, 2.49, 88.4), and 13.7-fold greater odds of death (AOR: 13.7, 95% CI, 3.26, 57.4). Adjusted survival analysis demonstrated that patients with CE on HCT had 3.6-fold greater hazard of death than those without CE (HR: 3.56: 95% CI 2.34, 5.41). Interrater reliability demonstrated excellent agreement between reviewers for CE on HCT (κ = 0.86). Conclusion: The results identify that abnormal HCTs early in the post-arrest period in OHCA patients are associated with poor rates of survival and neurologic outcome. Prospective work is needed to confirm whether selection bias or other variables confound this association.

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