Oliver Eidel

Gadolinium Retention in the Dentate Nucleus and Globus Pallidus Is Dependent on the Class of Contrast Agent

PURPOSE To compare changes in signal intensity (SI) ratios of the dentate nucleus (DN) and the globus pallidus (GP) to those of other structures on unenhanced T1-weighted magnetic resonance (MR) images between linear and macrocyclic gadolinium-based contrast agents (GBCAs). MATERIALS AND METHODS The study was approved by the ethical committee of the University of Heidelberg (reference no. S-324/2014). Owing to the retrospective character of the study, the ethical committee did not require any written informed consent. Two groups of 50 patients who underwent at least six consecutive MR imaging examinations with the exclusive use of either a linear GBCA (gadopentetate dimeglumine) or a macrocyclic GBCA (gadoterate meglumine) were analyzed retrospectively. The difference in mean SI ratios of DN to pons and GP to thalamus on unenhanced T1-weighted images from the last and first examinations was calculated. One-sample and independent-sample t tests were used to assess the difference in SI ratios for both groups, and regression analysis was performed to account for potential confounders. RESULTS The SI ratio difference in the linear group was greater than 0 (mean DN difference ± standard deviation, 0.0407 ± 0.0398 [P < .001]; GP, 0.0287 ± 0.0275 [P < .001]) and significantly larger (DN, P < .001 and standardized difference of 1.16; GP, P < .001 and standardized difference of 0.81) than that in the macrocyclic group, which did not differ from 0 (DN, 0.0016 ± 0.0266 [P = .680]; GP, 0.0031 ± 0.0354 [P = .538]). The SI ratio difference between the last and first examinations for the DN remained significantly different between the two groups in the regression analysis (P < .001). CONCLUSION This study indicates that an SI increase in the DN and GP on T1-weighted images is caused by serial application of the linear GBCA gadopentetate dimeglumine but not by the macrocyclic GBCA gadoterate meglumine. Clinical implications of this observation remain unclear.

Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models

Purpose To evaluate whether radiomic feature-based magnetic resonance (MR) imaging signatures allow prediction of survival and stratification of patients with newly diagnosed glioblastoma with improved accuracy compared with that of established clinical and radiologic risk models. Materials and Methods Retrospective evaluation of data was approved by the local ethics committee and informed consent was waived. A total of 119 patients (allocated in a 2:1 ratio to a discovery [n = 79] or validation [n = 40] set) with newly diagnosed glioblastoma were subjected to radiomic feature extraction (12 190 features extracted, including first-order, volume, shape, and texture features) from the multiparametric (contrast material-enhanced T1-weighted and fluid-attenuated inversion-recovery imaging sequences) and multiregional (contrast-enhanced and unenhanced) tumor volumes. Radiomic features of patients in the discovery set were subjected to a supervised principal component (SPC) analysis to predict progression-free survival (PFS) and overall survival (OS) and were validated in the validation set. The performance of a Cox proportional hazards model with the SPC analysis predictor was assessed with C index and integrated Brier scores (IBS, lower scores indicating higher accuracy) and compared with Cox models based on clinical (age and Karnofsky performance score) and radiologic (Gaussian normalized relative cerebral blood volume and apparent diffusion coefficient) parameters. Results SPC analysis allowed stratification based on 11 features of patients in the discovery set into a low- or high-risk group for PFS (hazard ratio [HR], 2.43; P = .002) and OS (HR, 4.33; P < .001), and the results were validated successfully in the validation set for PFS (HR, 2.28; P = .032) and OS (HR, 3.45; P = .004). The performance of the SPC analysis (OS: IBS, 0.149; C index, 0.654; PFS: IBS, 0.138; C index, 0.611) was higher compared with that of the radiologic (OS: IBS, 0.175; C index, 0.603; PFS: IBS, 0.149; C index, 0.554) and clinical risk models (OS: IBS, 0.161, C index, 0.640; PFS: IBS, 0.139; C index, 0.599). The performance of the SPC analysis model was further improved when combined with clinical data (OS: IBS, 0.142; C index, 0.696; PFS: IBS, 0.132; C index, 0.637). Conclusion An 11-feature radiomic signature that allows prediction of survival and stratification of patients with newly diagnosed glioblastoma was identified, and improved performance compared with that of established clinical and radiologic risk models was demonstrated. (©) RSNA, 2016 Online supplemental material is available for this article.

Quantification of Tumor Vessels in Glioblastoma Patients Using Time-of-Flight Angiography at 7 Tesla: A Feasibility Study

Purpose To analyze if tumor vessels can be visualized, segmented and quantified in glioblastoma patients with time of flight (ToF) angiography at 7 Tesla and multiscale vessel enhancement filtering. Materials and Methods Twelve patients with newly diagnosed glioblastoma were examined with ToF angiography (TR = 15 ms, TE = 4.8 ms, flip angle = 15°, FOV = 160×210 mm2, voxel size: 0.31×0.31×0.40 mm3) on a whole-body 7 T MR system. A volume of interest (VOI) was placed within the border of the contrast enhancing part on T1-weighted images of the glioblastoma and a reference VOI was placed in the non-affected contralateral white matter. Automated segmentation and quantification of vessels within the two VOIs was achieved using multiscale vessel enhancement filtering in ImageJ. Results Tumor vessels were clearly visible in all patients. When comparing tumor and the reference VOI, total vessel surface (45.3±13.9 mm2 vs. 29.0±21.0 mm2 (p<0.035)) and number of branches (3.5±1.8 vs. 1.0±0.6 (p<0.001) per cubic centimeter were significantly higher, while mean vessel branch length was significantly lower (3.8±1.5 mm vs 7.2±2.8 mm (p<0.001)) in the tumor. Discussion ToF angiography at 7-Tesla MRI enables characterization and quantification of the internal vascular morphology of glioblastoma and may be used for the evaluation of therapy response within future studies.

Nuclear Overhauser Enhancement imaging of glioblastoma at 7 Tesla: region specific correlation with apparent diffusion coefficient and histology.

Objective To explore the correlation between Nuclear Overhauser Enhancement (NOE)-mediated signals and tumor cellularity in glioblastoma utilizing the apparent diffusion coefficient (ADC) and cell density from histologic specimens. NOE is one type of chemical exchange saturation transfer (CEST) that originates from mobile macromolecules such as proteins and might be associated with tumor cellularity via altered protein synthesis in proliferating cells. Patients and Methods For 15 patients with newly diagnosed glioblastoma, NOE-mediated CEST-contrast was acquired at 7 Tesla (asymmetric magnetization transfer ratio (MTRasym) at 3.3ppm, B1 = 0.7 μT). Contrast enhanced T1 (CE-T1), T2 and diffusion-weighted MRI (DWI) were acquired at 3 Tesla and coregistered. The T2 edema and the CE-T1 tumor were segmented. ADC and MTRasym values within both regions of interest were correlated voxelwise yielding the correlation coefficient rSpearman (rSp). In three patients who underwent stereotactic biopsy, cell density of 12 specimens per patient was correlated with corresponding MTRasym and ADC values of the biopsy site. Results Eight of 15 patients showed a weak or moderate positive correlation of MTRasym and ADC within the T2 edema (0.16≤rSp≤0.53, p<0.05). Seven correlations were statistically insignificant (p>0.05, n = 4) or yielded rSp≈0 (p<0.05, n = 3). No trend towards a correlation between MTRasym and ADC was found in CE-T1 tumor (-0.310.05, n = 6). The biopsy-analysis within CE-T1 tumor revealed a strong positive correlation between tumor cellularity and MTRasym values in two of the three patients (rSp patient3 = 0.69 and rSp patient15 = 0.87, p<0.05), while the correlation of ADC and cellularity was heterogeneous (rSp patient3 = 0.545 (p = 0.067), rSp patient4 = -0.021 (p = 0.948), rSp patient15 = -0.755 (p = 0.005)). Discussion NOE-imaging is a new contrast promising insight into pathophysiologic processes in glioblastoma regarding cell density and protein content, setting itself apart from DWI. Future studies might be based on the assumption that NOE-mediated CEST visualizes cellularity more accurately than ADC, especially in the CE-T1 tumor region.

Tumor infiltration in enhancing and non-enhancing parts of glioblastoma: A correlation with histopathology

Purpose To correlate histopathologic findings from biopsy specimens with their corresponding location within enhancing areas, non-enhancing areas and necrotic areas on contrast enhanced T1-weighted MRI scans (cT1). Materials and Methods In 37 patients with newly diagnosed glioblastoma who underwent stereotactic biopsy, we obtained a correlation of 561 1mm3 biopsy specimens with their corresponding position on the intraoperative cT1 image at 1.5 Tesla. Biopsy points were categorized as enhancing (CE), non-enhancing (NE) or necrotic (NEC) on cT1 and tissue samples were categorized as “viable tumor cells”, “blood” or “necrotic tissue (with or without cellular component)”. Cell counting was done semi-automatically. Results NE had the highest content of tissue categorized as viable tumor cells (89% vs. 60% in CE and 30% NEC, respectively). Besides, the average cell density for NE (3764 ± 2893 cells/mm2) was comparable to CE (3506 ± 3116 cells/mm2), while NEC had a lower cell density with 2713 ± 3239 cells/mm2. If necrotic parts and bleeds were excluded, cell density in biopsies categorized as “viable tumor tissue” decreased from the center of the tumor (NEC, 5804 ± 3480 cells/mm2) to CE (4495 ± 3209 cells/mm2) and NE (4130 ± 2817 cells/mm2). Discussion The appearance of a glioblastoma on a cT1 image (circular enhancement, central necrosis, peritumoral edema) does not correspond to its diffuse histopathological composition. Cell density is elevated in both CE and NE parts. Hence, our study suggests that NE contains considerable amounts of infiltrative tumor with a high cellularity which might be considered in resection planning.

Assessment of tumor oxygenation and its impact on treatment response in bevacizumab-treated recurrent glioblastoma.

Antiantiogenic therapy with bevacizumab in recurrent glioblastoma is currently understood to both reduce microvascular density and to prune abnormal tumor microvessels. Microvascular pruning and the resulting vascular normalization are hypothesized to reduce tumor hypoxia and increase supply of systemic therapy to the tumor; however, the underlying pathophysiological changes and their timing after treatment initiation remain controversial. Here, we use a novel dynamic susceptibility contrast MRI-based method, which allows simultaneous assessment of tumor net oxygenation changes reflected by the tumor metabolic rate of oxygen and vascular normalization represented by the capillary transit time heterogeneity. We find that capillary transit time heterogeneity, and hence the oxygen extraction fraction combine with the tumoral blood flow (cerebral blood flow) in such a way that the overall tumor oxygenation appears to be worsened despite vascular normalization. Accordingly, hazards for both progression and death are found elevated in patients with a greater reduction of tumor metabolic rate of oxygen in response to bevacizumab and patients with higher intratumoral tumor metabolic rate of oxygen at baseline. This implies that tumors with a higher degree of angiogenesis prior to bevacizumab-treatment retain a higher level of angiogenesis during therapy despite a greater antiangiogenic effect of bevacizumab, hinting at evasive mechanisms limiting bevacizumab efficacy in that a reversal of their biological behavior and relative prognosis does not occur.

Automatic analysis of cellularity in glioblastoma and correlation with ADC using trajectory analysis and automatic nuclei counting

Objective Several studies have analyzed a correlation between the apparent diffusion coefficient (ADC) derived from diffusion-weighted MRI and the tumor cellularity of corresponding histopathological specimens in brain tumors with inconclusive findings. Here, we compared a large dataset of ADC and cellularity values of stereotactic biopsies of glioblastoma patients using a new postprocessing approach including trajectory analysis and automatic nuclei counting. Materials and Methods Thirty-seven patients with newly diagnosed glioblastomas were enrolled in this study. ADC maps were acquired preoperatively at 3T and coregistered to the intraoperative MRI that contained the coordinates of the biopsy trajectory. 561 biopsy specimens were obtained; corresponding cellularity was calculated by semi-automatic nuclei counting and correlated to the respective preoperative ADC values along the stereotactic biopsy trajectory which included areas of T1-contrast-enhancement and necrosis. Results There was a weak to moderate inverse correlation between ADC and cellularity in glioblastomas that varied depending on the approach towards statistical analysis: for mean values per patient, Spearman’s ρ = -0.48 (p = 0.002), for all trajectory values in one joint analysis Spearman’s ρ = -0.32 (p < 0.001). The inverse correlation was additionally verified by a linear mixed model. Conclusions Our data confirms a previously reported inverse correlation between ADC and tumor cellularity. However, the correlation in the current article is weaker than the pooled correlation of comparable previous studies. Hence, besides cell density, other factors, such as necrosis and edema might influence ADC values in glioblastomas.