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To determine whether noncontrast computed tomography (NCCT) models based on multivariable, radiomics features, and machine learning (ML) algorithms could further improve the discrimination of early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (sICH).
We retrospectively reviewed 261 patients with sICH who underwent initial NCCT within 6 hours of ictus and follow-up CT within 24 hours after initial NCCT, between April 2011 and March 2019. The clinical characteristics, imaging signs and radiomics features extracted from the initial NCCT images were used to construct models to discriminate early HE. A clinical-radiologic model was constructed using a multivariate logistic regression (LR) analysis. Radiomics models, a radiomics-radiologic model, and a combined model were constructed in the training cohort (n = 182) and independently verified in the validation cohort (n = 79). Receiver operating characteristic analysis and the area under the curve (AUC) were used to evaluate the discriminative power.
The AUC of the clinical-radiologic model for discriminating early HE was 0.766. The AUCs of the radiomics model for discriminating early HE built using the LR algorithm in the training and validation cohorts were 0.926 and 0.850, respectively. The AUCs of the radiomics-radiologic model in the training and validation cohorts were 0.946 and 0.867, respectively. The AUCs of the combined model in the training and validation cohorts were 0.960 and 0.867, respectively.
NCCT models based on multivariable, radiomics features and ML algorithm could improve the discrimination of early HE. The combined model was the best recommended model to identify sICH patients at risk of early HE.
NCCT models based on multivariable, radiomics features and ML algorithm could improve the discrimination of early HE. 10-Deacetylbaccatin-III price The combined model was the best recommended model to identify sICH patients at risk of early HE.
The mitotic count of gastrointestinal stromal tumors (GIST) is closely associated with the risk of planting and metastasis. The purpose of this study was to develop a predictive model for the mitotic index of local primary GIST, based on deep learning algorithm.
Abdominal contrast-enhanced CT images of 148 pathologically confirmed GIST cases were retrospectively collected for the development of a deep learning classification algorithm. The areas of GIST masses on the CT images were retrospectively labelled by an experienced radiologist. The postoperative pathological mitotic count was considered as the gold standard (high mitotic count, > 5/50 high-power fields [HPFs]; low mitotic count, ≤ 5/50 HPFs). A binary classification model was trained on the basis of the VGG16 convolutional neural network, using the CT images with the training set (n = 108), validation set (n = 20), and the test set (n = 20). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) wereVGG convolutional neural network. The model displayed a good predictive performance.
We developed and preliminarily verified the GIST mitotic count binary prediction model, based on the VGG convolutional neural network. The model displayed a good predictive performance.Artificial nerve conduits capable of adequately releasing neurotrophic factors are extensively studied to bridge nerve defects. However, the lack of neurotrophic factors in the proximal area and their visible effects in axonal retrograde transport following nerve injury is one of the factors causing an incomplete nerve regeneration. Herein, an advanced conduit made of silk fibroin is produced, which can incorporate growth factors and promote an effective regeneration after injury. For that, enzymatically crosslinked silk fibroin-based conduits are developed to be used as a platform for the controlled delivery of neurotrophic factors. Nerve growth factor and glial-cell line derived neurotrophic factor (GDNF) are incorporated using two different methodologies i) crosslinking and ii) absorption method. The release profile is measured by ELISA technique. The bioactivity of the neurotrophic factors is evaluated in vitro by using primary dorsal root ganglia. When implanted in a 10 mm sciatic nerve defect in rats, GDNF-loaded silk fibroin conduits reveal retrograde neuroprotection as compared to autografts and plain silk fibroin conduit. Therefore, the novel design presents a substantial improvement of retrograde trafficking, neurons' protection, and motor nerve reinnervation.
This clinical randomized study aimed to evaluate the early plaque formation on nonresorbable polytetrafluoroethylene (PTFE) membranes having either a dense (d-PTFE) or an expanded (e-PTFE) microstructure and exposed to the oral cavity.
Twelve individuals were enrolled in this study. In a split-mouth design, five test membranes (e-PTFE) with a dual-layer configuration and five control membranes (d-PTFE) were bonded on the buccal surfaces of posterior teeth of each subject. All study subjects refrained from toothbrushing during the study period. Specimens were detached from the teeth at 4 and 24 hr and subjected to viability counting, confocal microscopy, and scanning electron microscopy. Plaque samples were harvested from neighboring teeth at baseline, 4, and 24 hr, as control. Wilcoxon signed rank test was applied.
No bond failure of the membranes was reported. Between the early and late time points, viable bacterial counts increased on all membranes, with no difference between the test and control. The number of Staphylococcus spp. decreased on the tooth surfaces and increased on both membranes overtime, with a significant difference compared to teeth. The total biomass and average biofilm thickness of live and dead cells were significantly greater at the d-PTFE barriers after 4 hr.
This study demonstrated that the e-PTFE membrane was associated with a lesser degree of biofilm accumulation during the initial exposure compared to the d-PTFE membrane. The present experimental setup provides a valuable toolbox to study the in vivo behavior of different membranes used in guided bone regeneration (GBR).
This study demonstrated that the e-PTFE membrane was associated with a lesser degree of biofilm accumulation during the initial exposure compared to the d-PTFE membrane. The present experimental setup provides a valuable toolbox to study the in vivo behavior of different membranes used in guided bone regeneration (GBR).