Assessment of the Prognostic Value of Radiomic Features in 18F-FMISO PET Imaging of Hypoxia in Postsurgery Brain Cancer Patients: Secondary Analysis of Imaging Data from a Single-Center Study and the Multicenter ACRIN 6684 Trial.

Hypoxia is associated with resistance to radiotherapy and chemotherapy in malignant gliomas, and it can be imaged by positron emission tomography with 18F-fluoromisonidazole (18F-FMISO). Previous results for patients with brain cancer imaged with 18F-FMISO at a single center before conventional chemoradiotherapy showed that tumor uptake via T/Bmax (tissue SUVmax/blood SUV) and hypoxic volume (HV) was associated with poor survival. However, in a multicenter clinical trial (ACRIN 6684), traditional uptake parameters were not found to be prognostically significant, but tumor SUVpeak did predict survival at 1 year. The present analysis considered both study cohorts to reconcile key differences and examine the potential utility of adding radiomic features as prognostic variables for outcome prediction on the combined cohort of 72 patients with brain cancer (30 University of Washington and 42 ACRIN 6684). We used both 18F-FMISO intensity metrics (T/Bmax, HV, SUV, SUVmax, SUVpeak) and assessed radiomic measures that determined first-order (histogram), second-order, and higher-order radiomic features of 18F-FMISO uptake distributions. A multivariate model was developed that included age, HV, and the intensity of 18F-FMISO uptake. HV and SUVpeak were both independent predictors of outcome for the combined data set (P < .001) and were also found significant in multivariate prognostic models (P < .002 and P < .001, respectively). Further model selection that included radiomic features showed the additional prognostic value for overall survival of specific higher order texture features, leading to an increase in relative risk prediction performance by a further 5%, when added to the multivariate clinical model..

ACRIN 6684: Assessment of Tumor Hypoxia in Newly Diagnosed Glioblastoma Using 18F-FMISO PET and MRI.

PURPOSE: Structural and functional alterations in tumor vasculature are thought to contribute to tumor hypoxia which is a primary driver of malignancy through its negative impact on the efficacy of radiation, immune surveillance, apoptosis, genomic stability, and accelerated angiogenesis. We performed a prospective, multicenter study to test the hypothesis that abnormal tumor vasculature and hypoxia, as measured with MRI and PET, will negatively impact survival in patients with newly diagnosed glioblastoma. EXPERIMENTAL DESIGN: Prior to the start of chemoradiation, patients with glioblastoma underwent MRI scans that included dynamic contrast enhanced and dynamic susceptibility contrast perfusion sequences to quantitate tumor cerebral blood volume/flow (CBV/CBF) and vascular permeability (ktrans) as well as 18F-Fluoromisonidazole (18F-FMISO) PET to quantitate tumor hypoxia. ROC analysis and Cox regression models were used to determine the association of imaging variables with progression-free and overall survival. RESULTS: Fifty patients were enrolled of which 42 had evaluable imaging data. Higher pretreatment 18F-FMISO SUVpeak (P = 0.048), mean ktrans (P = 0.024), and median ktrans (P = 0.045) were significantly associated with shorter overall survival. Higher pretreatment median ktrans (P = 0.021), normalized RCBV (P = 0.0096), and nCBF (P = 0.038) were significantly associated with shorter progression-free survival. SUVpeak [AUC = 0.75; 95% confidence interval (CI), 0.59-0.91], nRCBV (AUC = 0.72; 95% CI, 0.56-0.89), and nCBF (AUC = 0.72; 95% CI, 0.56-0.89) were predictive of survival at 1 year. CONCLUSIONS: Increased tumor perfusion, vascular volume, vascular permeability, and hypoxia are negative prognostic markers in newly diagnosed patients with gioblastoma, and these important physiologic markers can be measured safely and reliably using MRI and 18F-FMISO PET. Clin Cancer Res; 22(20); 5079-86. ©2016 AACR.

Imaging of cerebellopontine angle masses: self-assessment module.

The educational objectives for this self-assessment module are for the participant to exercise, self-assess, and improve his or her understanding of the imaging features of cerebellopontine angle (CPA) masses and the role of advanced MRI in the differential diagnosis of CPA masses.

Sonographic NASCET index: a new doppler parameter for assessment of internal carotid artery stenosis.

BACKGROUND AND PURPOSE: Established Doppler parameters for carotid stenosis assessment do not reflect North American Symptomatic Carotid Endarterectomy Trial (NASCET)-style methodology. We derived a Doppler parameter, termed sonographic NASCET index (SNI), and hypothesized that the SNI would provide greater angiographic correlation and better accuracy in predicting stenosis of 70% or greater than that of currently used peak systolic velocity (PSV) measurements. METHODS: Inclusion criteria of angiographically proved carotid stenoses of 40-95% and measured proximal and distal internal carotid artery Doppler PSV values were established. Occlusions and near occlusions were specifically excluded. Doppler and angiographic data meeting the inclusion criteria from 32 carotid bifurcations were identified; actual angiographic stenoses ranged 40-89%. SNI values were calculated for each vessel. PSV and SNI were correlated with angiography by using linear regression analysis. Accuracies of SNI and PSV in predicting stenosis of 70% or greater were compared at two thresholds. RESULTS: Correlation between SNI and angiography was superior to that between PSV and angiography (r2=0.64 vs 0.38). PSV and SNI values that corresponded to 70% angiographic stenosis were 345 cm/s and 45.5, respectively. Accuracy of PSV of 345 cm/s or greater in predicting stenosis of 70% or greater was 78%, compared with 88% for SNI of 45.5 or greater. The SNI value that corresponded to a PSV threshold of 250 cm/s was 33. Accuracy of PSV of 250 cm/s or greater in predicting stenosis of 70% or greater was 81%, compared with 88% for SNI of 33 or greater. CONCLUSION: Correlation between SNI and angiography was greater than that between PSV and angiography. Accuracy of SNI in predicting stenosis of 70% or greater was also superior to that of PSV at two thresholds. These results suggest that SNI may be a better predictor of high-grade carotid stenosis than is PSV.