CT‐Based Classification of Acute Cerebral Edema: Association with Intracranial Pressure and Outcome

Zausinger, Stefan; Patzig, Maximilian; Kunz, Mathias

doi:10.1111/jon.12736

Cited by 20 publications

(11 citation statements)

References 47 publications

(58 reference statements)

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“… 10 Repeated computed tomography (CT) scanning is not practical to monitor the radiologic features of ND due to the patients’ clinical state and the risk of radiation overexposure. 11 Transcranial Doppler (TCD) provides a measurement of the cerebral blood flow velocities non-invasively and has become one of the most commonly utilized tools to estimate ICP changes and identify patients requiring invasive monitoring. 12 Studies have confirmed that elevated ICP will lead to a decrease in end-diastolic flow velocity (Vd) and an increase in pulsatility index (PI).…”

Section: Introductionmentioning

confidence: 99%

Nomogram Prediction of Short-Term Outcome After Intracerebral Hemorrhage

Kang

Cai

Gong

et al. 2021

IJGM

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Background:The early symptoms of patients with elevated intracranial pressure (ICP) after intracerebral hemorrhage (ICH) are easily overlooked, which will result in missing the optimal opportunity for clinical intervention. However, it is difficult for ICH patients admitted to the neurology department to receive invasive ICP monitoring, although it is crucial for the early identification of neurologic deterioration (ND). Objective: The aim of this study is to investigate the association between the changes of transcranial Doppler (TCD) variables and ND after onset and establish a nomogram for predicting the short-term outcome of ICH. Methods: A total of 297 patients were recruited and their clinical characteristics and the changes of TCD variables were recorded. The independent prognostic factors for the ND after onset in the ICH patients were screened from multivariate Logistic regression analysis, which were served as inputs for the nomogram construction. Discrimination and calibration validations were performed to assess the performance of the nomogram [concordance index (C-index) for discrimination and Hosmer-Lemeshow (HL) test for calibration] and the decision curve analysis was applied to assess the clinical suitability. Results: ΔaPI [defined as the change of pulsatility index (PI) between the 1st and 3rd day after onset for affected hemisphere] was independently associated with the ND after onset. Moreover, hematoma volume, presence of intraventricular hemorrhage, and Glasgow coma scale were also the independent prognostic factors of ND. The developed nomogram incorporating ΔaPI showed good discrimination (C-index: 0.916 after 1000 bootstrapping) and calibration (P=0.412, HL test) and yielded net benefits. Conclusion:The nomogram incorporating ΔaPI might be useful in predicting the risk of ND within 14 days after onset, which might help identify patients in the neurology department in need of further care.

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Section: Introductionmentioning

confidence: 99%

Nomogram Prediction of Short-Term Outcome After Intracerebral Hemorrhage

Kang

Cai

Gong

et al. 2021

IJGM

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“…Despite these advantages, the interpretation of CT images, especially in the detection of CE, has been questioned because it relies heavily on the radiologist’s subjective judgment of subtle differences in the attenuation of CE [ 11 ]. Recently, Lietke et al [ 6 ] proposed the CT grading method for CE for the first time. According to the A5(+ 1) point scale, we extracted the head CT examination data on the third day of hospitalization and scored the edema on the head CT data of each patient.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, after craniocerebral injury, CE gradually worsened. Lietke et al [ 6 ] found that the grade of BE was significantly correlated with ICP and prognosis through the statistics of continuous monitoring values of ICP on the third day after admission. In our study,although our results were significant, our results did not show a particularly good correlation with the original study.…”

Section: Discussionmentioning

confidence: 99%

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Establishment and validation of prognosis model for patients with cerebral contusion

Zhu

Jin

et al. 2021

BMC Neurol

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Background And Objective Cerebral Contusion (CC) is one of the most serious injury types in patients with traumatic brain injury (TBI). In this study, the baseline data, imaging features and laboratory examinations of patients with CC were summarized and analyzed to develop and validate a prediction model of nomogram to evaluate the clinical outcomes of patients. Methods A total of 426 patients with cerebral contusion (CC) admitted to the People’s Hospital of Qinghai Province and Affiliated Hospital of Qingdao University from January 2018 to January 2021 were included in this study, We randomly divided the cohort into a training cohort (n = 284) and a validation cohort (n = 142) with a ratio of 2:1.At Least absolute shrinkage and selection operator (Lasso) regression were used for screening high-risk factors affecting patient prognosis and development of the predictive model. The identification ability and clinical application value of the prediction model were analyzed through the analysis of receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). Results Twelve independent prognostic factors, including age, Glasgow Coma Score (GCS), Basal cistern status, Midline shift (MLS), Third ventricle status, intracranial pressure (ICP) and CT grade of cerebral edema,etc., were selected by Lasso regression analysis and included in the nomogram. The model showed good predictive performance, with a C index of (0.87, 95% CI, 0.026–0.952) in the training cohort and (0.93, 95% CI, 0.032–0.965) in the validation cohort. Clinical decision curve analysis (DCA) also showed that the model brought high clinical benefits to patients. Conclusion This study established a high accuracy of nomogram model to predict the prognosis of patients with CC, its low cost, easy to promote, is especially applicable in the acute environment, at the same time, CSF-glucose/lactate ratio(C-G/L), volume of contusion, and mean CT values of edema zone, which were included for the first time in this study, were independent predictors of poor prognosis in patients with CC. However, this model still has some limitations and deficiencies, which require large sample and multi-center prospective studies to verify and improve our results.

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“…Currently, the radiographic assessment of edema is mostly based on standard CT findings ( Fabritius et al, 2017 ; Muscari et al, 2019 ; Dhar et al, 2020 ; Foroushani et al, 2020 ; Lietke et al, 2020 ). This approach is insensitive to lesion or edema volume measurements, especially stroke within 12–24 h. In addition, edema was primarily seen in brain regions that flow pathways for cerebrospinal fluid (CSF)-interstitial fluid (ISF), and CSF is thought to be the primary source of early edema fluid after ischemic stroke ( Lempriere, 2020 ; Mestre et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

MRI Radiomics Features From Infarction and Cerebrospinal Fluid for Prediction of Cerebral Edema After Acute Ischemic Stroke

Jiang

Zhang

Wang

et al. 2022

Front. Aging Neurosci.

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Neuroimaging biomarkers that predict the edema after acute stroke may help clinicians provide targeted therapies and minimize the risk of secondary injury. In this study, we applied pretherapy MRI radiomics features from infarction and cerebrospinal fluid (CSF) to predict edema after acute ischemic stroke. MRI data were obtained from a prospective, endovascular thrombectomy (EVT) cohort that included 389 patients with acute stroke from two centers (dataset 1, n = 292; dataset 2, n = 97), respectively. Patients were divided into edema group (brain swelling and midline shift) and non-edema group according to CT within 36 h after therapy. We extracted the imaging features of infarct area on diffusion weighted imaging (DWI) (abbreviated as DWI), CSF on fluid-attenuated inversion recovery (FLAIR) (CSFFLAIR) and CSF on DWI (CSFDWI), and selected the optimum features associated with edema for developing models in two forms of feature sets (DWI + CSFFLAIR and DWI + CSFDWI) respectively. We developed seven ML models based on dataset 1 and identified the most stable model. External validations (dataset 2) of the developed stable model were performed. Prediction model performance was assessed using the area under the receiver operating characteristic curve (AUC). The Bayes model based on DWI + CSFFLAIR and the RF model based on DWI + CSFDWI had the best performances (DWI + CSFFLAIR: AUC, 0.86; accuracy, 0.85; recall, 0.88; DWI + CSFDWI: AUC, 0.86; accuracy, 0.84; recall, 0.84) and the most stability (RSD% in DWI + CSFFLAIR AUC: 0.07, RSD% in DWI + CSFDWI AUC: 0.09), respectively. External validation showed that the AUC of the Bayes model based on DWI + CSFFLAIR was 0.84 with accuracy of 0.77 and area under precision-recall curve (auPRC) of 0.75, and the AUC of the RF model based on DWI + CSFDWI was 0.83 with accuracy of 0.81 and the auPRC of 0.76. The MRI radiomics features from infarction and CSF may offer an effective imaging biomarker for predicting edema.

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CT‐Based Classification of Acute Cerebral Edema: Association with Intracranial Pressure and Outcome

Cited by 20 publications

References 47 publications

Nomogram Prediction of Short-Term Outcome After Intracerebral Hemorrhage

Nomogram Prediction of Short-Term Outcome After Intracerebral Hemorrhage

Establishment and validation of prognosis model for patients with cerebral contusion

MRI Radiomics Features From Infarction and Cerebrospinal Fluid for Prediction of Cerebral Edema After Acute Ischemic Stroke

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