Spinal hematomas are a frequent indication for radiologic evaluation and can be a diagnostic dilemma for many radiologists and surgeons. There are four types of spinal hematomas: epidural, subdural, subarachnoid, and intramedullary (spinal cord) hematomas. Because they differ by their location in relationship to the meningeal membranes and spinal cord, unique radiologic appearances can be recognized to distinguish these types of spinal hemorrhage. Anatomic knowledge of the spinal compartments is essential to the radiologist for confident imaging diagnosis of spinal hematomas and to specify correct locations. MRI is the modality of choice to diagnose the location of the hematoma, characterize important features such as age of the hemorrhage, and detect associated injury or disease. Each type of spinal hematoma has imaging patterns and characteristics that distinguish it from the others, as these specific spinal compartments displace and affect the adjacent anatomic structures. Early detection and accurate localization of spinal hematomas is critical for the surgeon to address the proper treatment and surgical decompression, when necessary, as neurologic deficits may otherwise become permanent. Online supplemental material is available for this article. RSNA, 2018.
BACKGROUND AND PURPOSE: Isocitrate dehydrogenase (IDH)-mutant lower grade gliomas are classified as oligodendrogliomas or diffuse astrocytomas based on 1p/19q-codeletion status. We aimed to test and validate neuroradiologists' performances in predicting the codeletion status of IDH-mutant lower grade gliomas based on simple neuroimaging metrics. MATERIALS AND METHODS: One hundred two IDH-mutant lower grade gliomas with preoperative MR imaging and known 1p/19q status from The Cancer Genome Atlas composed a training dataset. Two neuroradiologists in consensus analyzed the training dataset for various imaging features: tumor texture, margins, cortical infiltration, T2-FLAIR mismatch, tumor cyst, T2* susceptibility, hydrocephalus, midline shift, maximum dimension, primary lobe, necrosis, enhancement, edema, and gliomatosis. Statistical analysis of the training data produced a multivariate classification model for codeletion prediction based on a subset of MR imaging features and patient age. To validate the classification model, 2 different independent neuroradiologists analyzed a separate cohort of 106 institutional IDH-mutant lower grade gliomas. RESULTS: Training dataset analysis produced a 2-step classification algorithm with 86.3% codeletion prediction accuracy, based on the following: 1) the presence of the T2-FLAIR mismatch sign, which was 100% predictive of noncodeleted lower grade gliomas, (n ϭ 21); and 2) a logistic regression model based on texture, patient age, T2* susceptibility, primary lobe, and hydrocephalus. Independent validation of the classification algorithm rendered codeletion prediction accuracies of 81.1% and 79.2% in 2 independent readers. The metrics used in the algorithm were associated with moderate-substantial interreader agreement (ϭ 0.56-0.79). CONCLUSIONS: We have validated a classification algorithm based on simple, reproducible neuroimaging metrics and patient age that demonstrates a moderate prediction accuracy of 1p/19q-codeletion status among IDH-mutant lower grade gliomas.
INTRODUCTION Immune checkpoint inhibitors (ICIs) improve survival in patients with advanced non-small cell lung cancer (NSCLC). Clinical trials examining the efficacy of ICI in patients with NSCLC excluded patients with untreated brain metastases (BM). As stereotactic radiosurgery (SRS) is commonly employed for NSCLC-BMs, we sought to define the safety, radiologic/clinical outcomes for patients with NSCLC-BM treated with concurrent ICI/SRS. METHODS A retrospective, matched cohort study was performed on patients who underwent SRS to one or more NSCLC-derived BM. Two matched cohorts were identified: one who received ICI within 3-mo of SRS (concurrent-ICI) and one who did not (ICI-naive). Locoregional tumor control, peritumoral edema, and central nervous system adverse events were compared. RESULTS A total of 17 patients (45-BMs) and 34 patients (92-BMs) comprised the concurrent-ICI and ICI-naive cohorts, respectively. Per RANO criteria, there was no difference in overall-survival (HR 0.99, 95% CI: 0.39-2.52) or CNS progression-free-survival (HR 2.18, 95% CI 0.72-6.62) between both groups. Similarly, the 12-mo local tumor control rate was 84.9% and 76.3% for tumors in the concurrent-ICI and ICI-naive cohorts, respectively (P = .94). Nevertheless, patients receiving concurrent-ICI had increased rates of complete response for BMs treated with SRS (50% vs 15.6%; P = .012) per RANO criteria. There was a shorter median time to BM regression in the concurrent-ICI cohort (2.5-mo vs 3.1-mo, P < .001). There was no increased rate of radiation necrosis or intratumoral hemorrhage in patients receiving concurrent-ICI (concurrent-ICI: 5.9%; ICI-naive: 2.9%, P = .99). There was no difference in the rate of peritumoral edema progression across both groups (concurrent-ICI: 11.1%, ICI-naive: 21.7%; P = .162). CONCLUSION The use of ICI/SRS to treat NSCLC-BM was well tolerated while providing more rapid BM regression. Concurrent-ICI did not increase rates of peritumoral edema, radiation necrosis, or intratumoral hemorrhage. Further studies are needed to evaluate whether concurrent ICI/SRS improves PFS/OS for patients with metastatic NSCLC.
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