Background: The purpose of this study was to build radiogenomics models from texture signatures derived from computed tomography (CT) and 18F-FDG PET-CT (FDG PET-CT) images of non-small cell lung cancer (NSCLC) with and without epidermal growth factor receptor ( EGFR) mutations. Methods: Fifty patients diagnosed with NSCLC between 2011 and 2015 and with known EGFR mutation status were retrospectively identified. Texture features extracted from pretreatment CT and FDG PET-CT images by manual contouring of the primary tumor were used to develop multivariate logistic regression (LR) models to predict EGFR mutations in exon 19 and exon 20. Results: An LR model evaluating FDG PET-texture features was able to differentiate EGFR mutant from wild type with an area under the curve (AUC), sensitivity, specificity, and accuracy of 0.87, 0.76, 0.66, and 0.71, respectively. The model derived from CT texture features had an AUC, sensitivity, specificity, and accuracy of 0.83, 0.84, 0.73, and 0.78, respectively. FDG PET-texture features that could discriminate between mutations in EGFR exon 19 and 21 demonstrated AUC, sensitivity, specificity, and accuracy of 0.86, 0.84, 0.73, and 0.78, respectively. Based on CT texture features, the AUC, sensitivity, specificity, and accuracy were 0.75, 0.81, 0.69, and 0.75, respectively. Conclusion: Non-small cell lung cancer texture analysis using FGD-PET and CT images can identify tumors with mutations in EGFR. Imaging signatures could be valuable for pretreatment assessment and prognosis in precision therapy.

Background and Purpose-Intracerebral hemorrhage is a feared complication of intravenous alteplase therapy in patients with acute ischemic stroke. We explore the use of multimodal computed tomography in predicting this complication. Methods-All patients were administered intravenous alteplase with/without intra-arterial therapy. An age-and sex-matched case-control design with classic and conditional logistic regression techniques was chosen for analyses. Outcome was parenchymal hemorrhage on 24-to 48-hour imaging. Exposure variables were imaging (noncontrast computed tomography hypoattenuation degree, relative volume of very low cerebral blood volume, relative volume of cerebral blood flow ≤7 mL/min•per 100 g, relative volume of T max ≥16 s with all volumes standardized to z axis coverage, mean permeability surface area product values within T max ≥8 s volume, and mean permeability surface area product values within ipsilesional hemisphere) and clinical variables (NIHSS [National Institutes of Health Stroke Scale], onset to imaging time, baseline systolic blood pressure, blood glucose, serum creatinine, treatment type, and reperfusion status). Results-One-hundred eighteen subjects (22 patients with parenchymal hemorrhage versus 96 without, median baseline NIHSS score of 15) were included in the final analysis. In multivariable regression, noncontrast computed tomography hypoattenuation grade (P<0.006) and computerized tomography perfusion white matter relative volume of very low cerebral blood volume (P=0.04) were the only significant variables associated with parenchymal hemorrhage on follow-up imaging (area under the curve, 0.73; 95% confidence interval, 0.63-0.83). Interrater reliability for noncontrast computed tomography hypoattenuation grade was moderate (κ=0.6). Conclusions-Baseline hypoattenuation on noncontrast computed tomography and very low cerebral blood volume on computerized tomography perfusion are associated with development of parenchymal hemorrhage in patients with acute ischemic stroke receiving intravenous alteplase.

BACKGROUND AND PURPOSE: Infarct core volume measurement using CTP (CT perfusion) is a mainstay paradigm for stroke treatment decision-making. Yet, there are several downfalls with cine CTP technology that can be overcome by adopting the simple perfusion reconstruction algorithm (SPIRAL) derived from multiphase CTA. We compare SPIRAL with CTP parameters for the prediction of 24-hour infarction.MATERIALS AND METHODS: Seventy-two patients had admission NCCT, multiphase CTA, CTP, and 24-hour DWI. All patients had successful/quality reperfusion. Patient-level and cohort-level receiver operator characteristic curves were generated to determine accuracy. A 10-fold cross-validation was performed on the cohort-level data. Infarct core volume was compared for SPIRAL, CTPtime-to-maximum, and final DWI by Bland-Altman analysis.RESULTS: When we compared the accuracy in patients with early and late reperfusion for cortical GM and WM, there was no significant difference at the patient level (0.83 versus 0.84, respectively), cohort level (0.82 versus 0.81, respectively), or the cross-validation (0.77 versus 0.74, respectively). In the patient-level receiver operating characteristic analysis, the SPIRAL map had a slightly higher, though nonsignificant (P , .05), average receiver operating characteristic area under the curve (cortical GM/WM, r ¼ 0.82; basal ganglia ¼ 0.79, respectively) than both the CTP-time-to-maximum (cortical GM/WM ¼ 0.82; basal ganglia ¼ 0.78, respectively) and CTP-CBF (cortical GM/WM ¼ 0.74; basal ganglia ¼ 0.78, respectively) parameter maps. The same relationship was observed at the cohort level. The Bland-Altman plot limits of agreement for SPIRAL and time-to-maximum infarct volume were similar compared with 24-hour DWI. CONCLUSIONS:We have shown that perfusion maps generated from a temporally sampled helical CTA are an accurate surrogate for infarct core. ABBREVIATIONS: AUC ¼ area under the curve; EVT ¼ endovascular therapy; mCTA ¼ multiphase CTA; ROC ¼ receiver operating characteristic; SPIRAL ¼ simple perfusion reconstruction algorithm; Tmax ¼ time-to-maximum E ndovascular therapy (EVT) for acute ischemic stroke can lead to remarkable results for improving stroke outcome. [1][2][3] The emphasis on fast treatment decisions for patients with acute ischemic stroke requires simple, quick, and accurate neuroimaging of patients for detection of early ischemic changes. Additionally, image-processing software that can provide this information should be preferably inexpensive and easily accessible to all stroke centers, both primary and comprehensive, around the world. CT is the most commonly used and practical imaging technique for assessing patients with acute stroke, but sensitivity and reliability are only modest, even in the hands of stroke specialists. Software systems, including perfusion analysis, to identify ischemic tissue using advanced imaging paradigms are now recommended by the American Stroke Association and have been used successfully in several clinical trials, including selection of patients fo...

Treatment with endovascular therapy in the extended time window for acute ischaemic stroke with large vessel occlusion involves stringent selection criteria based on the two landmark studies DAWN and DEFUSE3. Current protocols typically include the requirement of advanced perfusion imaging which may exclude a substantial proportion of patients from receiving a potentially effective therapy. Efforts to offer endovascular reperfusion therapies to all appropriate candidates may be facilitated by the use of simplified imaging selection paradigms with widely available basic imaging techniques, such as non-contrast CT and CT angiography. Currently available evidence from our literature review suggests that patients meeting simplified imaging selection criteria may benefit as much as those patients selected using advanced imaging techniques (CT perfusion or MRI) from endovascular therapy in the extended time window. A comprehensive understanding of the role of imaging in patient selection is critical to optimising access to endovascular therapy in the extended time window and improving outcomes in acute stroke. This article provides an overview on current developments and future directions in this emerging area.

The hyperdense sign is a marker of thrombus in non-contrast computed tomography (NCCT) datasets. The aim of this work was to determine optimal Hounsfield unit (HU) thresholds for thrombus segmentation in thin-slice non-contrast CT (NCCT) and use these thresholds to generate 3D thrombus models. Patients with thin-slice baseline NCCT (≤2.5 mm) and MCA-M1 occlusions were included. CTA was registered to NCCT, and three regions of interest (ROIs) were placed in the NCCT, including: the thrombus, contralateral brain tissue, and contralateral patent MCA-M1 artery. Optimal HU thresholds differentiating the thrombus from non-thrombus tissue voxels were calculated using receiver operating characteristic analysis. Linear regression analysis was used to predict the optimal HU threshold for discriminating the clot only based on the average contralateral vessel HU or contralateral parenchyma HU. Three-dimensional models from 70 participants using standard (45 HU) and patient-specific thresholds were generated and compared to CTA clot characteristics. The optimal HU threshold discriminating thrombus in NCCT from other structures varied with a median of 51 (IQR: 49–55). Experts chose 3D models derived using patient-specific HU models as corresponding better to the thrombus seen in CTA in 83.8% (31/37) of cases. Patient-specific HU thresholds for segmenting the thrombus in NCCT can be derived using normal parenchyma. Thrombus segmentation using patient-specific HU thresholds is superior to conventional 45 HU thresholds.