1,721,079 research outputs found

    5-aminolevulinic Acid fluorescence in high grade glioma surgery: surgical outcome, intraoperative findings, and fluorescence patterns.

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    Background. 5-Aminolevulinic acid (5-ALA) fluorescence is a validated technique for resection of high grade gliomas (HGG); the aim of this study was to evaluate the surgical outcome and the intraoperative findings in a consecutive series of patients. Methods. Clinical and surgical data from patients affected by HGG who underwent surgery guided by 5-ALA fluorescence at our Department between June 2011 and February 2014 were retrospectively evaluated. Surgical outcome was evaluated by assessing the resection rate as gross total resection (GTR) > 98 % and GTR > 90 %. We finally stratified data for recurrent surgery, tumor location, tumor size, and tumor grade (IV versus III grade sec. WHO). Results. 94 patients were finally enrolled. Overall GTR > 98 % and GTR > 90 % was achieved in 93% and 100% of patients. Extent of resection (GTR > 98 %) was dependent on tumor location, tumor grade (P < 0.05), and tumor size (P < 0.05). In 43% of patients the boundaries of fluorescent tissue exceeded those of tumoral tissue detected by neuronavigation, more frequently in larger (57%) (P < 0.01) and recurrent (60%) tumors. Conclusions. 5-ALA fluorescence in HGG surgery enables a GTR in 100% of cases even if selection of patients remains a main bias. Recurrent surgery, and location, size, and tumor grade can predict both the surgical outcome and the intraoperative findings

    Mental Time Line Distortion in Right-Brain-Damaged Patients: Evidence From a Dynamic Spatiotemporal Task

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    Time is an elusive phenomenon that is difficult to grasp with our senses. Recent work has shown how spatial representations often lie beneath temporal ones, as shown by a family of spatiotemporal congruency effects. For instance, individuals who have been exposed to left-to-right orthographic systems are better at judging short durations with their left effector and long durations with their right effector than vice versa, a phenomenon known as the spatial-temporal association of response codes (STEARC) effect. In the present neuropsychological study, we aimed to provide evidence that spatial attention mechanisms play a crucial role in generating this spatially organized mental time line

    An overview of fotemustine in high-grade gliomas: from single agent to association with bevacizumab.

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    Fotemustine is a third-generation nitrosourea showing efficacy in various types of tumors such as melanoma and glioma. We reviewed the most important studies on fotemustine treatment in glioma patients analyzing its pharmacological profile and its activity and safety. Fotemustine was used as single agent or in association with new targeted drugs such as bevacizumab; fotemustine was used both as first-line chemotherapy before temozolomide era and in refractory-temozolomide patients during temozolomide era. Finally, analyzing and comparing the activity and safety of fotemustine alone or in combination with bevacizumab versus other nitrosoureas such as lomustine, we may suggest that the combination treatment with bevacizumab and fotemustine may be active and tolerable in patients with high grade glioma

    Accuracy of deep learning to differentiate the histopathological grading of meningiomas on MR images: a preliminary study

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    Background: Grading of meningiomas is important in the choice of the most effective treatment for each patient. Purpose: To determine the diagnostic accuracy of a deep convolutional neural network (DCNN) in the differentiation of the histopathological grading of meningiomas from MR images. Study Type: Retrospective. Population: In all, 117 meningioma-affected patients, 79 World Health Organization [WHO] Grade I, 32 WHO Grade II, and 6 WHO Grade III. Field Strength/Sequence: 1.5 T, 3.0 T postcontrast enhanced T1 W (PCT1W), apparent diffusion coefficient (ADC) maps (b values of 0, 500, and 1000 s/mm2). Assessment: WHO Grade II and WHO Grade III meningiomas were considered a single category. The diagnostic accuracy of the pretrained Inception-V3 and AlexNet DCNNs was tested on ADC maps and PCT1W images separately. Receiver operating characteristic curves (ROC) and area under the curve (AUC) were used to asses DCNN performance. Statistical Test: Leave-one-out cross-validation. Results: The application of the Inception-V3 DCNN on ADC maps provided the best diagnostic accuracy results, with an AUC of 0.94 (95% confidence interval [CI], 0.88–0.98). Remarkably, only 1/38 WHO Grade II–III and 7/79 WHO Grade I lesions were misclassified by this model. The application of AlexNet on ADC maps had a low discriminating accuracy, with an AUC of 0.68 (95% CI, 0.59–0.76) and a high misclassification rate on both WHO Grade I and WHO Grade II–III cases. The discriminating accuracy of both DCNNs on postcontrast T1W images was low, with Inception-V3 displaying an AUC of 0.68 (95% CI, 0.59–0.76) and AlexNet displaying an AUC of 0.55 (95% CI, 0.45–0.64). Data Conclusion: DCNNs can accurately discriminate between benign and atypical/anaplastic meningiomas from ADC maps but not from PCT1W images. Level of evidence: 2 Technical Efficacy: Stage
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