Edge Contrast of the FLAIR Hyperintense Region Predicts Survival in Patients with High-Grade Gliomas following Treatment with Bevacizumab.

BACKGROUND AND PURPOSE: Treatment with bevacizumab is standard of care for recurrent high-grade gliomas; however, monitoring response to treatment following bevacizumab remains a challenge. The purpose of this study was to determine whether quantifying the sharpness of the fluid-attenuated inversion recovery hyperintense border using a measure derived from texture analysis-edge contrast-improves the evaluation of response to bevacizumab in patients with high-grade gliomas. MATERIALS AND METHODS: MRIs were evaluated in 33 patients with high-grade gliomas before and after the initiation of bevacizumab. Volumes of interest within the FLAIR hyperintense region were segmented. Edge contrast magnitude for each VOI was extracted using gradients of the 3D FLAIR images. Cox proportional hazards models were generated to determine the relationship between edge contrast and progression-free survival/overall survival using age and the extent of surgical resection as covariates. RESULTS: After bevacizumab, lower edge contrast of the FLAIR hyperintense region was associated with poorer progression-free survival (P = .009) and overall survival (P = .022) among patients with high-grade gliomas. Kaplan-Meier curves revealed that edge contrast cutoff significantly stratified patients for both progression-free survival (log-rank χ2 = 8.3, P = .003) and overall survival (log-rank χ2 = 5.5, P = .019). CONCLUSIONS: Texture analysis using edge contrast of the FLAIR hyperintense region may be an important predictive indicator in patients with high-grade gliomas following treatment with bevacizumab. Specifically, low FLAIR edge contrast may partially reflect areas of early tumor infiltration. This study adds to a growing body of literature proposing that quantifying features may be important for determining outcomes in patients with high-grade gliomas.

Restriction Spectrum Imaging Improves Risk Stratification in Patients with Glioblastoma.

BACKGROUND AND PURPOSE: ADC as a marker of tumor cellularity has been promising for evaluating the response to therapy in patients with glioblastoma but does not successfully stratify patients according to outcomes, especially in the upfront setting. Here we investigate whether restriction spectrum imaging, an advanced diffusion imaging model, performed after an operation but before radiation therapy, could improve risk stratification in patients with newly diagnosed glioblastoma relative to ADC. MATERIALS AND METHODS: Pre-radiation therapy diffusion-weighted and structural imaging of 40 patients with glioblastoma were examined retrospectively. Restriction spectrum imaging and ADC-based hypercellularity volume fraction (restriction spectrum imaging-FLAIR volume fraction, restriction spectrum imaging-contrast-enhanced volume fraction, ADC-FLAIR volume fraction, ADC-contrast-enhanced volume fraction) and intensities (restriction spectrum imaging-FLAIR 90th percentile, restriction spectrum imaging-contrast-enhanced 90th percentile, ADC-FLAIR 10th percentile, ADC-contrast-enhanced 10th percentile) within the contrast-enhanced and FLAIR hyperintensity VOIs were calculated. The association of diffusion imaging metrics, contrast-enhanced volume, and FLAIR hyperintensity volume with progression-free survival and overall survival was evaluated by using Cox proportional hazards models. RESULTS: Among the diffusion metrics, restriction spectrum imaging-FLAIR volume fraction was the strongest prognostic metric of progression-free survival (P = .036) and overall survival (P = .007) in a multivariate Cox proportional hazards analysis, with higher values indicating earlier progression and shorter survival. Restriction spectrum imaging-FLAIR 90th percentile was also associated with overall survival (P = .043), with higher intensities, indicating shorter survival. None of the ADC metrics were associated with progression-free survival/overall survival. Contrast-enhanced volume exhibited a trend toward significance for overall survival (P = .063). CONCLUSIONS: Restriction spectrum imaging-derived cellularity in FLAIR hyperintensity regions may be a more robust prognostic marker than ADC and conventional imaging for early progression and poorer survival in patients with glioblastoma. However, future studies with larger samples are needed to explore its predictive ability.

Search for novel contrast materials in dual-energy x-ray breast imaging using theoretical modeling of contrast-to-noise ratio.

Contrast-enhanced (CE) dual-energy (DE) x-ray breast imaging uses a low- and high-energy x-ray spectral pair to eliminate soft-tissue signal variation and thereby increase the detectability of exogenous imaging agents. Currently, CEDE breast imaging is performed with iodinated contrast agents. These compounds are limited by several deficiencies, including rapid clearance and poor tumor targeting ability. The purpose of this work is to identify novel contrast materials whose contrast-to-noise ratio (CNR) is comparable or superior to that of iodine in the mammographic energy range. A monoenergetic DE subtraction framework was developed to calculate the DE signal intensity resulting from the logarithmic subtraction of the low- and high-energy signal intensities. A weighting factor is calculated to remove the dependence of the DE signal on the glandularity of the breast tissue. Using the DE signal intensity and weighting factor, the CNR for materials with atomic numbers (Z) ranging from 1 to 79 are computed for energy pairs between 10 and 50 keV. A group of materials with atomic numbers ranging from 42 to 63 were identified to exhibit the highest levels of CNR in the mammographic energy range. Several of these materials have been formulated as nanoparticles for various applications but none, apart from iodine, have been investigated as CEDE breast imaging agents. Within this group of materials, the necessary dose fraction to the LE image decreases as the atomic number increases. By reducing the dose to the LE image, the DE subtraction technique will not provide an anatomical image of sufficient quality to accompany the contrast information. Therefore, materials with Z from 42 to 52 provide nearly optimal values of CNR with energy pairs and dose fractions that provide good anatomical images. This work is intended to inspire further research into new materials for optimized CEDE breast functional imaging.

Exploring silver as a contrast agent for contrast-enhanced dual-energy X-ray breast imaging.

OBJECTIVE: Through prior monoenergetic modelling, we have identified silver as a potential alternative to iodine in dual-energy (DE) X-ray breast imaging. The purpose of this study was to compare the performance of silver and iodine contrast agents in a commercially available DE imaging system through a quantitative analysis of signal difference-to-noise ratio (SDNR). METHODS: A polyenergetic simulation algorithm was developed to model the signal intensity and noise. The model identified the influence of various technique parameters on SDNR. The model was also used to identify the optimal imaging techniques for silver and iodine, so that the two contrast materials could be objectively compared. RESULTS: The major influences on the SDNR were the low-energy dose fraction and breast thickness. An increase in the value of either of these parameters resulted in a decrease in SDNR. The SDNR for silver was on average 43% higher than that for iodine when imaged at their respective optimal conditions, and 40% higher when both were imaged at the optimal conditions for iodine. CONCLUSION: A silver contrast agent should provide benefit over iodine, even when translated to the clinic without modification of imaging system or protocol. If the system were slightly modified to reflect the lower k-edge of silver, the difference in SDNR between the two materials would be increased. ADVANCES IN KNOWLEDGE: These data are the first to demonstrate the suitability of silver as a contrast material in a clinical contrast-enhanced DE image acquisition system.