- Deep Transfer Learning and Radiomics Feature Prediction of Survival of Patients with High-Grade Gliomas
Fifty patients with high-grade gliomas from the authors’ hospital and 128 patients with high-grade gliomas from The Cancer Genome Atlas were included in this study. For each patient, the authors calculated 348 hand-crafted radiomics features and 8192 deep features generated by a pretrained convolutional neural network. They then applied feature selection and Elastic Net-Cox modeling to differentiate patients into long- and short-term survivors. In the 50 patients with high-grade gliomas from their institution, the combined feature analysis framework classified the patients into long- and short-term survivor groups with a log-rank test P value <.001. In the 128 patients from The Cancer Genome Atlas, the framework classified patients into long- and short-term survivors with a log-rank test P value of .014. In conclusion, the authors report successful production and initial validation of a deep transfer learning model combining radiomics and deep features to predict overall survival of patients with glioblastoma from postcontrast T1-weighed brain MR imaging.
- Flow-Diversion Treatment for Unruptured Nonsaccular Intracranial Aneurysms of the Posterior and Distal Anterior Circulation: A Meta-Analysis
The authors’ aim was to analyze the outcomes after flow diversion among nonsaccular unruptured lesions. Fifteen studies (213 aneurysms) were included in the analysis. The long-term adequate occlusion rate was 85.3%. Treatment-related complications were 17.4%. Overall, 15% were ischemic events. They conclude that unruptured nonsaccular aneurysms located in the posterior and distal anterior circulations can be effectively treated with a flow-diversion strategy. Nevertheless, treatment-related complications are not negligible, with about 15% ischemic events and 8% morbidity. Larger size (>10 mm) significantly increased the risk of procedure-related adverse events among nonsaccular lesions.
- Prediction of Hemorrhage after Successful Recanalization in Patients with Acute Ischemic Stroke: Improved Risk Stratification Using Dual-Energy CT Parenchymal Iodine Concentration Ratio Relative to the Superior Sagittal Sinus
The authors evaluated whether, in acute ischemic stroke, iodine concentration within contrast-stained parenchyma compared with an internal reference in the superior sagittal sinus on dual-energy CT could predict subsequent intracerebral hemorrhage in 71 patients. Forty-three of 71 patients had parenchymal hyperdensity on initial dual-energy CT. The median relative iodine concentration compared with the superior sagittal sinus was significantly higher in those with subsequent intracerebral hemorrhage (137.9% versus 109.2%). They conclude that in dual-energy CT performed within 1 hour following thrombectomy that the relative iodine concentration within contrast-stained brain parenchyma compared with that in the superior sagittal sinus was a more reliable predictor of ICH compared with the absolute maximum iodine concentration.
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