The new classification announced by the World Health Organization in 2016 recognized five molecular subtypes of diffuse gliomas based on isocitrate dehydrogenase (IDH) and 1p/19q genotypes in addition to histologic phenotypes. We aim to determine whether clinical MRI can stratify these molecular subtypes to benefit the diagnosis and monitoring of gliomas. The data from 456 subjects with gliomas were obtained from The Cancer Imaging Archive. Overall, 214 subjects, including 106 cases of glioblastomas and 108 cases of lower grade gliomas with preoperative MRI, survival data, histology, IDH, and 1p/19q status were included. We proposed a three-level machine-learning model based on multimodal MR radiomics to classify glioma subtypes. An independent dataset with 70 glioma subjects was further collected to verify the model performance. The IDH and 1p/19q status of gliomas can be classified by radiomics and machine-learning approaches, with areas under ROC curves between 0.922 and 0.975 and accuracies between 87.7% and 96.1% estimated on the training dataset. The test on the validation dataset showed a comparable model performance with that on the training dataset, suggesting the efficacy of the trained classifiers. The classification of 5 molecular subtypes solely based on the MR phenotypes achieved an 81.8% accuracy, and a higher accuracy of 89.2% could be achieved if the histology diagnosis is available. The MR radiomics-based method provides a reliable alternative to determine the histology and molecular subtypes of gliomas. .

Several neuropsychiatric conditions, such as addiction and schizophrenia, may arise in part from dysregulated activity of ventral tegmental area dopaminergic (TH) neurons, as well as from more global maladaptation in neurocircuit function. However, whether TH activity affects large-scale brain-wide function remains unknown. Here we selectively activated TH neurons in transgenic rats and measured resulting changes in whole-brain activity using stimulus-evoked functional magnetic resonance imaging. Applying a standard generalized linear model analysis approach, our results indicate that selective optogenetic stimulation of TH neurons enhanced cerebral blood volume signals in striatal target regions in a dopamine receptor-dependent manner. However, brain-wide voxel-based principal component analysis of the same data set revealed that dopaminergic modulation activates several additional anatomically distinct regions throughout the brain, not typically associated with dopamine release events. Furthermore, explicit pairing of TH neuronal activation with a forepaw stimulus of a particular frequency expanded the sensory representation of that stimulus, not exclusively within the somatosensory cortices, but brain-wide. These data suggest that modulation of TH neurons can impact brain dynamics across many distributed anatomically distinct regions, even those that receive little to no direct TH input.

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