Yupeng Zhang
Capital Medical University
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Publication
Featured researches published by Yupeng Zhang.
Interventional Neuroradiology | 2018
Baorui Zhang; Xin Feng; Fei Peng; Luyao Wang; Er Kang Guo; Yupeng Zhang; Peng Liu; Zhongxue Wu; Aihua Liu
Background Brain arteriovenous malformation (bAVM)-related epilepsy can significantly affect patient quality of life. We aimed to identify the factors associated with seizures occurrence and evaluate the long-term outcome following Onyx embolization in bAVM patients. Methods Between July 2014 and July 2016, 239 consecutive patients underwent treatment for bAVMs in our institute and were respectively analyzed. Demographics, seizure status and bAVM morphologic characteristics were recorded. Modified Engel classification was used to evaluate the long-term seizure outcomes. Results Of 239 bAVM patients, 68 (28.5%) initially presented with seizures. Seizure occurrence was associated with cerebral hemorrhage history, frontal-temporal location and arterial borderzone location. Of the 37 patients who presented with initial seizures and were treated with Onyx embolization, 23 (62.2%) were treated with antiepileptic drugs (AEDs) before Onyx embolization. At the last follow-up visit, 19 (51.4%) of the 37 patients reached modified Engel class I outcome. Of the 23 patients who had ever been treated with AEDs, 12 (52.2%) were still taking AEDs at the last follow-up visit. Single-factor analysis showed that arterial borderzone location was significantly correlated with higher modified Engel class outcome (p = 0.046). Conclusion Patients with bAVM hemorrhage history, frontal-temporal location and arterial borderzone location were associated with seizure occurrence. Seizure-free status was not obtained in AVM patients with arterial borderzone after embolization, though it may have benefits in other ways. The seizure-free mechanism of bAVM with Onyx embolization is worth further study.
European Radiology | 2018
Yupeng Zhang; Baorui Zhang; Fei Liang; Shikai Liang; Yuxiang Zhang; Peng Yan; Chao Ma; Aihua Liu; Feng Guo; Chuhan Jiang
ObjectiveTo investigate the classification ability of quantitative radiomics features extracted on non-contrast-enhanced CT (NECT) image for discrimination of AVM-related hematomas from those caused by other etiologies.MethodsTwo hundred sixty-one cases with intraparenchymal hematomas underwent baseline CT scan between 2012 and 2017 in our center. Cases were split into a training dataset (n = 180) and a test dataset (n = 81). Hematoma types were dichotomized into two classes, namely, AVM-related hematomas (AVM-H) and hematomas caused by other etiologies. A total of 576 radiomics features of 6 feature groups were extracted from NECT. We applied 11 feature selection methods to select informative features from each feature group. Selected radiomics features and the clinical feature age were then used to fit machine learning classifiers. In combination of the 11 feature selection methods and 8 classifiers, we constructed 88 predictive models. Predictive models were evaluated and the optimal one was selected and evaluated.ResultsThe selected radiomics model was RELF_Ada, which was trained with Adaboost classifier and features selected by Relief method. Cross-validated area under the curve (AUC) on training dataset was 0.988 and the relative standard deviation (RSD%) was 0.062. AUC on the test dataset was 0.957. Accuracy (ACC), sensitivity, specificity, positive prediction value (PPV), and negative predictive value (NPV) were 0.926, 0.889, 0.937, 0.800, and 0.967, respectively.ConclusionsMachine learning models with radiomics features extracted from NECT scan accurately discriminated AVM-related intraparenchymal hematomas from those caused by other etiologies. This technique provided a fast, non-invasive approach without use of contrast to diagnose this disease.Key Points• Radiomics features from non-contrast-enhanced CT accurately discriminated AVM-related hematomas from those caused by other etiologies.• AVM-related hematomas tended to be larger in diameter, coarser in texture, and more heterogeneous in composition.• Adaboost classifier is an efficient approach for analyzing radiomics features.
Interventional Neuroradiology | 2017
Yupeng Zhang; Shikai Liang; Chuhan Jiang
Unruptured vertebral arteries dissecting aneurysms have a benign clinical course. The most common symptoms compromise headache, neck pain, dizziness and vomiting. The optimal endovascular treatment option remains controversial. Reconstructive techniques have many advantages over deconstructive ones since the advent of flow diverters such as the Pipeline embolization device (PED). Here, we present a case successfully treated with a PED through a combination of the radial access and advancement of the Marksman catheter into the contralateral vertebral artery due to the special angio-architecture of the patient.
Frontiers in Neurology | 2017
Yuxiang Zhang; Yupeng Zhang; Fei Liang; Chuhan Jiang
The use of Willis covered stent (WCS) for intracranial aneurysms has increased based on the promising results of previous studies about its safety and effectiveness. With the accumulation of cases, reports about peri-procedural complications are emerging. In our department, 25 patients were treated with WCS during December 2015 to March 2017. We here reported an unexpected technical complication occurred in the treatment with the WCS for a blood blister-like aneurysm (BBA). During the procedure, the distal end of the stents detached from the dilating balloon partially or as a whole. This was attributed to the tortuosity of the access route and the extracorporeal gas exhaust maneuver. Then we applied a half-dilating technique to retrieve the detached stent. The procedures were detailed in this report and the possible reasons and approaches to avoid it were explored.
World Neurosurgery | 2018
X. Lv; Yupeng Zhang; Weijian Jiang
World Neurosurgery | 2018
Feng Guo; Yupeng Zhang; Shikai Liang; Fei Liang; Peng Yan; Chuhan Jiang
World Neurosurgery | 2018
Yupeng Zhang; Chao Ma; Shikai Liang; Peng Yan; Fei Liang; Feng Guo; Chuhan Jiang
World Neurosurgery | 2018
Fei Liang; Yupeng Zhang; Feng Guo; Yuxiang Zhang; Peng Yan; Shikai Liang; Yuhua Jiang; Peng Jiang; Chuhan Jiang
World Neurosurgery | 2018
Yuxiang Zhang; Yupeng Zhang; Feng Guo; Fei Liang; Peng Yan; Shikai Liang; Chuhan Jiang
Chinese Neurosurgical Journal | 2018
Fei Liang; Yupeng Zhang; Yuntao Di; Feng Guo; Chuhan Jiang