Isocitrate dehydrogenase () mutations in glioma patients confer longer survival and may guide treatment decision making. We aimed to predict the status of gliomas from MR imaging by applying a residual convolutional neural network to preoperative radiographic data. Preoperative imaging was acquired for 201 patients from the Hospital of University of Pennsylvania (HUP), 157 patients from Brigham and Women's Hospital (BWH), and 138 patients from The Cancer Imaging Archive (TCIA) and divided into training, validation, and testing sets. We trained a residual convolutional neural network for each MR sequence (FLAIR, T2, T1 precontrast, and T1 postcontrast) and built a predictive model from the outputs. To increase the size of the training set and prevent overfitting, we augmented the training set images by introducing random rotations, translations, flips, shearing, and zooming. With our neural network model, we achieved IDH prediction accuracies of 82.8% (AUC = 0.90), 83.0% (AUC = 0.93), and 85.7% (AUC = 0.94) within training, validation, and testing sets, respectively. When age at diagnosis was incorporated into the model, the training, validation, and testing accuracies increased to 87.3% (AUC = 0.93), 87.6% (AUC = 0.95), and 89.1% (AUC = 0.95), respectively. We developed a deep learning technique to noninvasively predict genotype in grade II-IV glioma using conventional MR imaging using a multi-institutional data set. .

No enhancement and a smooth non-enhancing margin on MRI were predictive of longer PFS, while a smooth non-enhancing margin was a significant predictor of longer OS in LGGs. Textural analyses of MR imaging data predicted IDH1 mutation, 1p/19q codeletion, histological grade, and tumor progression with high accuracy.

ObjectiveTo measure the frequency, persistence, isoform specificity, and clinical correlates of neurofascin antibodies in patients with peripheral neuropathies.MethodsWe studied cohorts of patients with Guillain-Barre syndrome (GBS) or chronic inflammatory demyelinating polyneuropathy (CIDP) (n = 59), genetic neuropathy (n = 111), and idiopathic neuropathy (n = 43) for immunoglobulin (Ig) G and IgM responses to 3 neurofascin (NF) isoforms (NF140, NF155, and NF186) using cell-based assays.ResultsNeurofascin antibodies were more common in patients with GBS/CIDP (14%, 8 of 59) compared to genetic neuropathy controls (3%, 3 of 111, p = 0.01). Seven percent (3 of 43) of patients with idiopathic neuropathy also had neurofascin antibodies. NF155 IgG4 antibodies were associated with CIDP refractory to IV immunoglobulin but responsive to rituximab, and some of these patients had an acute onset resembling GBS. NF186 IgG and IgM to either isoform were less specific. A severe form of CIDP, approaching a locked-in state, was seen in a patient with antibodies recognizing all 3 neurofascin isoforms.ConclusionsNeurofascin antibodies were 4 times more frequent in autoimmune neuropathy samples compared to genetic neuropathy controls. Persistent IgG4 responses to NF155 correlated with severe CIDP resistant to usual treatments but responsive to rituximab. IgG4 antibodies against the common domains shared by glial and axonal isoforms may portend a particularly severe but treatable neuropathy. The prognostic implications of neurofascin antibodies in a subset of idiopathic neuropathy patients and transient IgM responses in GBS require further investigation.