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Mr. Skakel was released from prison after spending approximately 17 years behind bars. It has been roughly 11 years since he has been out of jail. Mr. Skakel apologized to his mother the morning of his release.
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OBJECTIVE A growing body of evidence suggests that low-grade gliomas (LGGs) are more heterogeneous in vivo than previously thought. The purpose of this study was to develop and validate a methodology for the analysis and classification of LGGs in vivo using dynamic susceptibility contrast-enhanced (DSC) MRI. METHODS Patients with LGGs (WHO grade II, n = 67) and healthy control subjects (n = 26) were studied. An image analysis and classification algorithm (IAC) to identify LGGs in vivo was developed using standard image processing techniques. The use of the proposed method was investigated using three-dimensional (3D) T2-weighted (T2W) gradient echo (GRE) MRI acquired prior to and following DSC perfusion-weighted imaging. Histograms of relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) were computed to identify rCBV and rCBF thresholds, which were then used to train and classify LGGs in vivo. The performance of the IAC was assessed via internal cross-validation and comparison with a current clinical practice-based classification algorithm developed by the authors (the algorithm presented on the WHO website). RESULTS The mean rCBV and rCBF of LGGs were found to be significantly higher than healthy controls (p < 0.05). LGG classification via the IAC had a test sensitivity and specificity of 79.5% and 92.9%, respectively, when trained and tested on a subset of data from healthy subjects. When trained and tested on all data from patients with LGGs, the IAC had a test sensitivity and specificity of 77.6% and 87.
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