Early CT changes and outcome of ischemic stroke

Prediction model of early biomarkers of massive cerebral infarction caused by anterior circulation occlusion: Establishment and evaluation

Objective

The purpose of this study is to establish and evaluate an early biomarker prediction model of massive cerebral infarction caused by anterior circulation occlusion.

Methods

One hundred thirty-four patients with acute cerebral infarction from January 2018 to October 2020 were selected to establish the development cohort for the internal test of the nomogram. Ninety-one patients with acute cerebral infarction hospitalized in our hospital from December 2020 to December 2021 were constituted the validation cohort for the external validation. All patients underwent baseline computed tomography (CT) scans within 12 h of onset and early imaging signs (hyperdense middle cerebral artery sign, obscuration of the lentiform nucleus, insular ribbon sign) of acute cerebral infarction were identified on CT by two neurologists. Based on follow-up CT images, patients were then divided into a massive cerebral infarction group and a non-massive cerebral infarction group. The nomogram model was constructed based on logistic regression analysis with R language. The nomogram was subsequently validated in an independent external validation cohort. Accuracy and discrimination of the prediction model were evaluated by a calibration chart, receiver operating characteristic (ROC) curve, and decision curve.

Results

The indicators, including insular ribbon sign, reperfusion therapy, National Institutes of Health Stroke Scale (NHISS) score, previous cerebral infarction, and atrial fibrillation, were entered into the prediction model through binary logistic regression analysis. The prediction model showed good predictive ability. The area under the ROC curve of the prediction model was 0.848. The specificity, sensitivity, and Youden index were 0.864, 0.733, and 0.597, respectively. This nomogram to the validation cohort also showed good discrimination (AUC = 0.940, 95% CI 0.894–0.985) and calibration.

Conclusion

Demonstrating favorable predictive efficacy and reproducibility, this study successfully established a prediction model of CT imaging signs and clinical data as early biomarkers of massive cerebral infarction caused by anterior circulation occlusion.

Does radiological conjugate eye deviation sign play a role in acute stroke imaging? A meta-analysis

BACKGROUND AND PURPOSE

The diagnostic value of non-contrast CT (NCCT) in acute stroke imaging remains indispensable, especially under emergency conditions with limited resources. The radiological conjugate eye deviation (RCED) has been demonstrated as a NCCT sign to predict acute ischemic stroke (AIS) or AIS secondary to large vessel occlusion (LVO) in recent studies. We performed a meta-analysis to gain a better understanding into the predictive role of RCED for AISs and LVO-AISs.

METHODS

We conducted a systematic literature search using PubMed, Embase, and Cochrane. The search focused on studies published between January 2000 and August 2020 that reported the predictive value of RCED for the diagnosis of AIS or LVO-AIS. Principal measurements of the meta-analysis were the overall sensitivity, specificity, the positive likelihood ratio (PLR), and the negative likelihood ratio (NLR) of RCED in predicting AIS and LVO-AIS.

RESULTS

We included 11 studies (n = 2304). For AIS, RCED had a sensitivity of 0.37 (95% CI 0.27-0.47), a specificity of 0.86 (95% CI 0.73-0.93), the area under the receiver operating characteristic curve (AUC) was 0.58 (95% CI 0.53-0.62), PLR was 2.5 (95% CI 1.5-4.4), and NLR was 0.74 (95% CI 0.65-0.84). For LVO-AIS, RCED had a sensitivity of 0.63 (95% CI 0.46-0.77), a specificity of 0.77 (95% CI 0.71-0.82), AUC was 0.63 (95% CI 0.46-0.77), PLR was 2.7 (95% CI 1.7-4.3), and NLR was 0.49 (95% CI 0.3-0.78).

CONCLUSION

RCED can be used to predict LVO-AIS. It is expected that this method will be extensively used and validated in acute stroke imaging, especially under emergency conditions with limited resources.

Early signs of middle cerebral artery infarction on multidetector computed tomography: Review of 20 cases

OBJECTIVE

This study intended to assess the occurrence of early signs of middle cerebral artery (MCA) on multidetector computed tomography (MDCT) in correlation with duration of the clinical features of stroke.

PATIENTS AND METHODS

This retrospective study analyzed the electronic records of 20 patients with MCA infarction. The detected signs studied according to the onset of the clinical features of stroke to the time of CT imaging.

RESULTS

Out of 20 patients with MCA infarction included in this study, the results revealed a significant relationship between the presence of insular ribbon sign and/or subtle hypodensity and hyperacute infarction (P < 0.001 and 0.003, respectively). Results revealed significant relationship between the occurrence of hypodense area, effacement of the cortical sulci, and compression of the ipsilateral lateral ventricle with acute infarction (6-72 h), (P = 0.006, 0.007, and 0.002) (odds ratio = 0.047, 0.050 and 0.028) and (95% confidence interval = 0.004-0.552, 0.004-0.597 and 0.002-0.367) respectively.

CONCLUSION

MDCT can detect nearly half of MCA infarctions in the first 6 h. Insular ribbon sign and subtle hypodensity were the most significant findings in the first 6 h of stroke. Hypodense area was a significant sign after 6 h. Diabetes mellitus and ischemic heart disease were the most common risk factors. Hemiparesis was the most common clinical finding in MCA infarction.

Identification by CT scan of ischemic stroke patients with high risk of brain death

The identification of patients with high risk of evolution to brain death is one of the more important tasks of transplant coordination teams. Although most of pool of potential donors come from the group of patients who suffer a head injury or hemorrhagic stroke, the procurement of organs from brain-dead patients suffering an ischemic stroke as the cause of brain damage must also be considered. The main objective of this study was to investigate the radiological signs that in the CT scan of admission to a neurological ICU are more frequently associated with progression to brain death. We studied the CT scans of 15 brain-dead patients after an ischemic stroke versus the scans of 15 recovered patients admitted to ICU with the same diagnosis. The radiological signs included: insular ribbon sign, hyperintensities inside the big arteries of the base of the skull, hemispheric hypodensities, midline shift, and compression of the cerebrospinal fluid spaces. There were two signs significantly associated with brain death: midline shifts and the compression of the ambiens cistern. It may be concluded that analysis of the CT scan at admission of patients with an ischemic stroke in the ICU can predict the risk of evolution to brain death.