Magnetic resonance elastography resolving all gross anatomical segments of the kidney during controlled hydration.

Introduction: Magnetic resonance elastography (MRE) is a non-invasive method to quantify biomechanical properties of human tissues. It has potential in diagnosis and monitoring of kidney disease, if established in clinical practice. The interplay of flow and volume changes in renal vessels, tubule, urinary collection system and interstitium is complex, but physiological ranges of in vivo viscoelastic properties during fasting and hydration have never been investigated in all gross anatomical segments simultaneously. Method: Ten healthy volunteers underwent two imaging sessions, one following a 12-hour fasting period and the second after a drinking challenge of >10 mL per kg body weight (60-75 min before the second examination). High-resolution renal MRE was performed using a novel driver with rotating eccentric mass placed at the posterior-lateral wall to couple waves (50 Hz) to the kidney. The biomechanical parameters, shear wave speed (cs in m/s), storage modulus (Gd in kPa), loss modulus (Gl in kPa), phase angle (Υ=2πatanGlGd) and attenuation (α in 1/mm) were derived. Accurate separation of gross anatomical segments was applied in post-processing (whole kidney, cortex, medulla, sinus, vessel). Results: High-quality shear waves coupled into all gross anatomical segments of the kidney (mean shear wave displacement: 163 ± 47 µm, mean contamination of second upper harmonics <23%, curl/divergence: 4.3 ± 0.8). Regardless of the hydration state, median Gd of the cortex and medulla (0.68 ± 0.11 kPa) was significantly higher than that of the sinus and vessels (0.48 ± 0.06 kPa), and consistently, significant differences were found in cs, Υ, and Gl (all p < 0.001). The viscoelastic parameters of cortex and medulla were not significantly different. After hydration sinus exhibited a small but significant reduction in median Gd by -0.02 ± 0.04 kPa (p = 0.01), and, consequently, the cortico-sinusoidal-difference in Gd increased by 0.04 ± 0.07 kPa (p = 0.05). Only upon hydration, the attenuation in vessels became lower (0.084 ± 0.013 1/mm) and differed significantly from the whole kidney (0.095 ± 0.007 1/mm, p = 0.01). Conclusion: High-resolution renal MRE with an innovative driver and well-defined 3D segmentation can resolve all renal segments, especially when including the sinus in the analysis. Even after a prolonged hydration period the approach is sensitive to small hydration-related changes in the sinus and in the cortico-sinusoidal-difference.

Differentiation of Glioblastoma and Brain Metastases by MRI-Based Oxygen Metabolomic Radiomics and Deep Learning.

Glioblastoma (GB) and brain metastasis (BM) are the most frequent types of brain tumors in adults. Their therapeutic management is quite different and a quick and reliable initial characterization has a significant impact on clinical outcomes. However, the differentiation of GB and BM remains a major challenge in today's clinical neurooncology due to their very similar appearance in conventional magnetic resonance imaging (MRI). Novel metabolic neuroimaging has proven useful for improving diagnostic performance but requires artificial intelligence for implementation in clinical routines. Here; we investigated whether the combination of radiomic features from MR-based oxygen metabolism ("oxygen metabolic radiomics") and deep convolutional neural networks (CNNs) can support reliably pre-therapeutic differentiation of GB and BM in a clinical setting. A self-developed one-dimensional CNN combined with radiomic features from the cerebral metabolic rate of oxygen (CMRO2) was clearly superior to human reading in all parameters for classification performance. The radiomic features for tissue oxygen saturation (mitoPO2; i.e., tissue hypoxia) also showed better diagnostic performance compared to the radiologists. Interestingly, both the mean and median values for quantitative CMRO2 and mitoPO2 values did not differ significantly between GB and BM. This demonstrates that the combination of radiomic features and DL algorithms is more efficient for class differentiation than the comparison of mean or median values. Oxygen metabolic radiomics and deep neural networks provide insights into brain tumor phenotype that may have important diagnostic implications and helpful in clinical routine diagnosis.

Radiophysiomics: Brain Tumors Classification by Machine Learning and Physiological MRI Data.

The precise initial characterization of contrast-enhancing brain tumors has significant consequences for clinical outcomes. Various novel neuroimaging methods have been developed to increase the specificity of conventional magnetic resonance imaging (cMRI) but also the increased complexity of data analysis. Artificial intelligence offers new options to manage this challenge in clinical settings. Here, we investigated whether multiclass machine learning (ML) algorithms applied to a high-dimensional panel of radiomic features from advanced MRI (advMRI) and physiological MRI (phyMRI; thus, radiophysiomics) could reliably classify contrast-enhancing brain tumors. The recently developed phyMRI technique enables the quantitative assessment of microvascular architecture, neovascularization, oxygen metabolism, and tissue hypoxia. A training cohort of 167 patients suffering from one of the five most common brain tumor entities (glioblastoma, anaplastic glioma, meningioma, primary CNS lymphoma, or brain metastasis), combined with nine common ML algorithms, was used to develop overall 135 classifiers. Multiclass classification performance was investigated using tenfold cross-validation and an independent test cohort. Adaptive boosting and random forest in combination with advMRI and phyMRI data were superior to human reading in accuracy (0.875 vs. 0.850), precision (0.862 vs. 0.798), F-score (0.774 vs. 0.740), AUROC (0.886 vs. 0.813), and classification error (5 vs. 6). The radiologists, however, showed a higher sensitivity (0.767 vs. 0.750) and specificity (0.925 vs. 0.902). We demonstrated that ML-based radiophysiomics could be helpful in the clinical routine diagnosis of contrast-enhancing brain tumors; however, a high expenditure of time and work for data preprocessing requires the inclusion of deep neural networks.

Physiological MRI of microvascular architecture, neovascularization activity, and oxygen metabolism facilitate early recurrence detection in patients with IDH-mutant WHO grade 3 glioma.

PURPOSE: This study aimed to determine the diagnostic performance of physiological MRI biomarkers including microvascular perfusion and architecture, neovascularization activity, tissue oxygen metabolism, and tension for recurrence detection of IDH-mutant WHO grade 3 glioma. METHODS: Sixty patients with IDH-mutant WHO grade 3 glioma who received overall 288 follow-up MRI examinations at 3 Tesla after standard treatment were retrospectively evaluated. A conventional MRI protocol was extended with a physiological MRI approach including vascular architecture mapping and quantitative blood-oxygen-level-dependent imaging which required 7 min extra data acquisition time. Custom-made MATLAB software was used for the calculation of MRI biomarker maps of microvascular perfusion and architecture, neovascularization activity, tissue oxygen metabolism, and tension. Statistical procedures included receiver operating characteristic analysis. RESULTS: Overall, 34 patients showed recurrence of the WHO grade 3 glioma; of these, in 15 patients, recurrence was detected one follow-up examination (averaged 160 days) earlier by physiological MRI data than by conventional MRI. During this time period, the tumor volume increased significantly (P = 0.001) on average 7.4-fold from 1.5 to 11.1 cm3. Quantitative analysis of MRI biomarkers demonstrated microvascular but no macrovascular hyperperfusion in early recurrence. Neovascularization activity (AUC = 0.833), microvascular perfusion (0.682), and oxygen metabolism (0.661) showed higher diagnostic performance for early recurrence detection of WHO grade 3 glioma compared to conventional MRI including cerebral blood volume (0.649). CONCLUSION: This study demonstrated that the targeted assessment of microvascular features and tissue oxygen tension as an early sign of neovascularization activity provided valuable information for recurrence diagnostic of WHO grade 3 glioma.

Metabolic Tumor Microenvironment Characterization of Contrast Enhancing Brain Tumors Using Physiologic MRI.

The tumor microenvironment is a critical regulator of cancer development and progression as well as treatment response and resistance in brain neoplasms. The available techniques for investigation, however, are not well suited for noninvasive in vivo characterization in humans. A total of 120 patients (59 females; 61 males) with newly diagnosed contrast-enhancing brain tumors (64 glioblastoma, 20 brain metastases, 15 primary central nervous system (CNS) lymphomas (PCNSLs), and 21 meningiomas) were examined with a previously established physiological MRI protocol including quantitative blood-oxygen-level-dependent imaging and vascular architecture mapping. Six MRI biomarker maps for oxygen metabolism and neovascularization were fused for classification of five different tumor microenvironments: glycolysis, oxidative phosphorylation (OxPhos), hypoxia with/without neovascularization, and necrosis. Glioblastoma showed the highest metabolic heterogeneity followed by brain metastasis with a glycolysis-to-OxPhos ratio of approximately 2:1 in both tumor entities. In addition, glioblastoma revealed a significant higher percentage of hypoxia (24%) compared to all three other brain tumor entities: brain metastasis (7%; p < 0.001), PCNSL (8%; p = 0.001), and meningioma (8%; p = 0.003). A more aggressive biological brain tumor behavior was associated with a higher percentage of hypoxia and necrosis and a lower percentage of remaining vital tumor tissue and aerobic glycolysis. The proportion of oxidative phosphorylation, however, was rather similar (17-26%) for all four brain tumor entities. Tumor microenvironment (TME) mapping provides insights into neurobiological differences of contrast-enhancing brain tumors and deserves further clinical cancer research attention. Although there is a long roadmap ahead, TME mapping may become useful in order to develop new diagnostic and therapeutic approaches.

Hypoxia and Microvascular Alterations Are Early Predictors of IDH-Mutated Anaplastic Glioma Recurrence.

Anaplastic gliomas (AG) represents aggressive brain tumors that often affect young adults. Although isocitrate-dehydrogenase (IDH) gene mutation has been identified as a more favorable prognostic factor, most IDH-mutated AG patients are confronted with tumor recurrence. Hence, increased knowledge about pathophysiological precursors of AG recurrence is urgently needed in order to develop precise diagnostic monitoring and tailored therapeutic approaches. In this study, 142 physiological magnetic resonance imaging (phyMRI) follow-up examinations in 60 AG patients after standard therapy were evaluated and magnetic resonance imaging (MRI) biomarker maps for microvascular architecture and perfusion, neovascularization activity, oxygen metabolism, and hypoxia calculated. From these 60 patients, 34 patients developed recurrence of the AG, and 26 patients showed no signs for AG recurrence during the study period. The time courses of MRI biomarker changes were analyzed regarding early pathophysiological alterations over a one-year period before radiological AG recurrence or a one-year period of stable disease for patients without recurrence, respectively. We detected intensifying local tissue hypoxia 250 days prior to radiological recurrence which initiated upregulation of neovascularization activity 50 to 70 days later. These changes were associated with a switch from an avascular infiltrative to a vascularized proliferative phenotype of the tumor cells another 30 days later. The dynamic changes of blood perfusion, microvessel density, neovascularization activity, and oxygen metabolism showed a close physiological interplay in the one-year period prior to radiological recurrence of IDH-mutated AG. These findings may path the wave for implementing both new MR-based imaging modalities for routine follow-up monitoring of AG patients after standard therapy and furthermore may support the development of novel, tailored therapy options in recurrent AG.

Multimodal assessment of disease activity in glioblastoma : A single center experience.

BACKGROUND: Assessment of disease activity in glioblastoma (GBM) can be challenging due to several clinical and radiological pitfalls. Besides MRI, FET-PET and neurocognitive assessment (NA) are used in several neuro-oncological centers in order to improve the specificity of response assessment. We performed a retrospective study to investigate whether the assessment by RANO (Response Assessment in NeuroOncology) corresponds to FET-PET imaging and NA results. Moreover, the concordance of RANO with a final recommendation of an interdisciplinary neuro-oncological tumor board recommendation (TBR) was analyzed. METHODS: We enrolled 25 consecutive patients with newly diagnosed histologically confirmed GBM in a pilot study, accounting for 81 multimodal test results. All patients were selected after undergoing consecutive follow-up comprising MRI, FET-PET, and NA with a subsequent TBR. Results were analyzed for correlations between RANO, FET-PET and NA. An additional consistency analysis was performed to elucidate the impact of RANO on decision making. RESULTS: A highly statistically significant correlation was found between RANO and FET-PET and NA results (all P < 0.01); however, 26% of follow-up tests exhibited inconsistent results in multimodal assessment, among which RANO was only 48% in accordance with the final TBR. The concordance of NA and FET-PET with the final TBR was 67% and 86%, respectively. CONCLUSION: The RANO proved its value in the context of multimodal assessment of disease activity in GBM; however, because the implementation of multimodal assessment showed a considerably high percentage of inconsistent results, further studies are required to investigate the relationship between different assessment techniques, in addition to their overall significance to response rating.

Tissue Hypoxia and Alterations in Microvascular Architecture Predict Glioblastoma Recurrence in Humans.

PURPOSE: Insufficient control of infiltrative glioblastoma (GBM) cells is a major cause of treatment failure and tumor recurrence. Hence, detailed insights into pathophysiologic changes that precede GBM recurrence are needed to develop more precise neuroimaging modalities for tailored diagnostic monitoring and therapeutic approaches. EXPERIMENTAL DESIGN: Overall, 168 physiologic MRI follow-up examinations of 56 patients with GBM who developed recurrence after standard therapy were retrospectively evaluated, that is, two post-standard-therapeutic follow-ups before and one at radiological recurrence. MRI biomarkers for microvascular architecture and perfusion, neovascularization activity, oxygen metabolism, and hypoxia were determined for brain areas that developed in the further course into recurrence and for the recurrent GBM itself. The temporal pattern of biomarker changes was fitted with locally estimated scatterplot smoothing functions and analyzed for pathophysiologic changes preceding radiological GBM recurrence. RESULTS: Our MRI approach demonstrated early pathophysiologic changes prior to radiological GBM recurrence in all patients. Analysis of the time courses revealed a model for the pathophysiology of GBM recurrence: 190 days prior to radiological recurrence, vascular cooption by GBM cells induced vessel regression, detected as decreasing vessel density/perfusion and increasing hypoxia. Seventy days later, neovascularization activity was upregulated, which reincreased vessel density and perfusion. Hypoxia, however, continued to intensify for 30 days and peaked 90 days before radiological recurrence. CONCLUSIONS: Hypoxia may represent an early sign for GBM recurrence. This might become useful in the development of new combined diagnostic-therapeutic approaches for tailored clinical management of recurrent GBM. Further preclinical and in-human studies are required for validation and evaluation.

Physiologic MR imaging of the tumor microenvironment revealed switching of metabolic phenotype upon recurrence of glioblastoma in humans.

Treating recurrent glioblastoma (GB) is one of the challenges in modern neurooncology. Hypoxia, neovascularization, and energy metabolism are of crucial importance for therapy failure and recurrence. Twenty-one patients with initially untreated GB who developed recurrence were examined with a novel MRI approach for noninvasive visualization of the tumor microenvironment (TME). Imaging biomarker information about oxygen metabolism (mitochondrial oxygen tension) and neovascularization (microvascular density and type) were fused for classification of five different TME compartments: necrosis, hypoxia with/without neovascularization, oxidative phosphorylation, and glycolysis. Volume percentages of these TME compartments were compared between untreated and recurrent GB. At initial diagnosis, all 21 GB showed either the features of a glycolytic dominant phenotype with a high percentage of functional neovasculature (N = 12) or those of a necrotic/hypoxic dominant phenotype with a high percentage of defective tumor neovasculature (N = 9). At recurrence, all 21 GB revealed switching of the initial metabolic phenotype: either from the glycolytic to the necrotic/hypoxic dominant phenotype or vice-versa. A necrotic/hypoxic phenotype at recurrence was associated with a higher rate of multifocality of the recurrent lesions. Our MRI approach may be helpful for a better understanding of treatment-induced metabolic phenotype switching and for future studies developing targeted therapeutic strategies for recurrent GB.

Vascular architecture mapping for early detection of glioblastoma recurrence.

OBJECTIVE: Treatment failure and inevitable tumor recurrence are the main reasons for the poor prognosis of glioblastoma (GB). Gross-total resection at repeat craniotomy for GB recurrence improves patient overall survival but requires early and reliable detection. It is known, however, that even advanced MRI approaches have limited diagnostic performance for distinguishing tumor progression from pseudoprogression. The novel MRI technique of vascular architectural mapping (VAM) provides deeper insight into tumor microvascularity and neovascularization. In this study the authors evaluated the usefulness of VAM for the monitoring of GB patients and quantitatively analyzed the features of neovascularization of early- and progressed-stage GB recurrence. METHODS: In total, a group of 115 GB patients who received overall 374 follow-up MRI examinations after standard treatment were retrospectively evaluated in this study. The clinical routine MRI (cMRI) protocol at 3 Tesla was extended with the authors' experimental VAM approach, requiring 2 minutes of extra time for data acquisition. Custom-made MATLAB software was used for calculation of imaging biomarker maps of macrovascular perfusion from perfusion cMRI as well as of microvascular perfusion and architecture from VAM data. Additionally, cMRI data were analyzed by two board-certified radiologists in consensus. Statistical procedures included receiver operating characteristic (ROC) analysis to determine diagnostic performances for GB recurrence detection. RESULTS: Overall, cMRI showed GB recurrence in 89 patients, and in 28 of these patients recurrence was detected earlier with VAM data, by 1 (20 patients) or 2 (8 patients) follow-up examinations, than with cMRI data. The mean time difference between recurrence detection with VAM and cMRI data was 147 days. During this time period the mean tumor volume increased significantly (p < 0.001) from 9.7 to 26.8 cm3. Quantitative analysis of imaging biomarkers demonstrated microvascular but no macrovascular hyperperfusion in early GB recurrence. Therefore, ROC analysis revealed superior diagnostic performance for VAM compared with cMRI. CONCLUSIONS: This study demonstrated that the targeted assessment of microvascular features using the VAM technique provided valuable information about early neovascularization activity in recurrent GB that is complementary to perfusion cMRI and may be helpful for earlier and more precise monitoring of patients suffering from GB. This VAM approach is compatible with existing cMRI protocols. Prospective clinical trials are necessary to investigate the clinical usefulness and potential benefit of increased overall survival with the use of VAM in patients with recurrent GB.

Predicting Glioblastoma Response to Bevacizumab Through MRI Biomarkers of the Tumor Microenvironment.

PURPOSE: Glioblastoma (GB) is one of the most vascularized of all solid tumors and, therefore, represents an attractive target for antiangiogenic therapies. Many lesions, however, quickly develop escape mechanisms associated with changes in the tumor microenvironment (TME) resulting in rapid treatment failure. To prevent patients from adverse effects of ineffective therapy, there is a strong need to better predict and monitor antiangiogenic treatment response. PROCEDURES: We utilized a novel physiological magnetic resonance imaging (MRI) method combining the visualization of oxygen metabolism and neovascularization for classification of five different TME compartments: necrosis, hypoxia with/without neovascularization, oxidative phosphorylation, and aerobic glycolysis. This approach, termed TME mapping, was used to monitor changes in tumor biology and pathophysiology within the TME in response to bevacizumab treatment in 18 patients with recurrent GB. RESULTS: We detected dramatic changes in the TME by rearrangement of its compartments after the onset of bevacizumab treatment. All patients showed a decrease in active tumor volume and neovascularization as well as an increase in hypoxia and necrosis in the first follow-up after 3 months. We found that recurrent GB with a high percentage of neovascularization and active tumor before bevacizumab onset showed a poor or no treatment response. CONCLUSIONS: TME mapping might be useful to develop strategies for patient stratification and response prediction before bevacizumab onset.

Recurrence of glioblastoma is associated with elevated microvascular transit time heterogeneity and increased hypoxia.

Dynamic susceptibility contrast (DSC) perfusion MRI provide information about differences in macro- and microvasculature when executed with gradient-echo (GE; sensitive to macrovasculature) and spin-echo (SE; sensitive to microvasculature) contrast. This study investigated whether there are differences between macro- and microvascular transit time heterogeneity (MVTH and µVTH) and tissue oxygen tension (PO2mit) in newly-diagnosed and recurrent glioblastoma. Fifty-seven patients with glioblastoma (25 newly-diagnosed/32 recurrent) were examined with GE- and SE-DSC perfusion sequences, and a quantitative blood-oxygen-level-dependent (qBOLD) approach. Maps of MVTH, µVTH and coefficient of variation (MCOV and µCOV) were calculated from GE- and SE-DSC data, respectively, using an extended flow-diffusion equation. PO2mit maps were calculated from qBOLD data. Newly-diagnosed and recurrent glioblastoma showed significantly lower ( P ≤ 0.001) µCOV values compared to both normal brain and macrovasculature (MCOV) of the lesions. Recurrent glioblastoma had significantly higher µVTH ( P = 0.014) and µCOV ( P = 0.039) as well as significantly lower PO2mit values ( P = 0.008) compared to newly-diagnosed glioblastoma. The macrovasculature, however, showed no significant differences. Our findings provide evidence of microvascular adaption in the disorganized tumor vasculature for retaining the metabolic demands in stress response of therapeutically-uncontrolled glioblastomas. Thus, µVTH and PO2mit mapping gives insight into the tumor microenvironment (vascular and hypoxic niches) responsible for therapy resistance.

Vascular Hysteresis Loops and Vascular Architecture Mapping in Patients with Glioblastoma treated with Antiangiogenic Therapy.

In this study, we investigated the variability of vascular hysteresis loop (VHL) shapes and the spatial heterogeneity of neovascularization and microvascular alterations using vascular architecture mapping (VAM) in patients with recurrent glioblastoma during bevacizumab mono-therapy. VAM data were acquired in 13 patients suffering from recurrent glioblastoma prior to and 3 months after bevacizumab treatment onset using a dual contrast agent injections approach as part of routine MRI. Two patients were additionally examined after the first cycle of bevacizumab to check for early treatment response. VHLs were evaluated as biomarker maps of neovascularization activity: microvessel type indicator (MTI) and curvature (Curv) of the VHL-long-axis. Early response to bevacizumab was dominated by reduction of smaller microvasculature (around 10 µm). In the 3-month follow-up, responding tumors additionally showed a reduction in larger microvasculature (>20 µm). VAM biomarker images revealed spatially heterogeneous microvascular alterations during bevacizumab treatment. Responding, non-responding, progressive, and remote-progressive tumor areas were observed. MTI may be useful to predict responding and non-responding tumor regions, and Curv to assess severity of vasogenic edema. Analysis of VHLs in combination with VAM biomarkers may lead to a new perspective on investigating the spatial heterogeneity of neovascularization and microvascular alterations in glioblastoma during antiangiogenic therapy.

Magnetic resonance imaging biomarkers for clinical routine assessment of microvascular architecture in glioma.

Knowledge about the topological and structural heterogeneity of the microvasculature is important for diagnosis and monitoring of glioma. A vessel caliber and type-dependent temporal shift in the magnetic resonance imaging signal forms the basis for vascular architecture mapping. This study introduced a clinically feasible approach for assessment of vascular pathologies in gliomas using vascular architecture mapping. Sixty consecutive patients with known or suspected gliomas were examined using vascular architecture mapping as part of the routine magnetic resonance imaging protocol. Maps of microvessel radius and density, which adapted to the vasculature-dependent temporal shift phenomenon, were calculated using a costume-made software tool. Microvessel radius and density were moderately to severely elevated in a heterogeneous, inversely correlated pattern within high-grade gliomas. Additionally, three new imaging biomarkers were introduced: Microvessel type indicator allowing differentiation between supplying arterial and draining venous microvasculature in high-grade gliomas. Vascular-induced bolus peak time shift may presumably be sensitive for early neovascularization in the infiltration zone. Surprisingly, curvature showed significant changes in peritumoral vasogenic edema which correlated with neovascularization in the tumor core of high-grade gliomas. These new magnetic resonance imaging biomarkers give insights into complexity and heterogeneity of vascular changes in glioma; however, histological validations in more well-defined patient populations are required.

MR Imaging-derived Oxygen Metabolism and Neovascularization Characterization for Grading and IDH Gene Mutation Detection of Gliomas.

Purpose To explore the diagnostic performance of physiological magnetic resonance (MR) imaging of oxygen metabolism and neovascularization activity for grading and characterization of isocitrate dehydrogenase (IDH) gene mutation status of gliomas. Materials and Methods This retrospective study had institutional review board approval; written informed consent was obtained from all patients. Eighty-three patients with histopathologically proven glioma (World Health Organization [WHO] grade II-IV) were examined with quantitative blood oxygen level-dependent imaging and vascular architecture mapping. Biomarker maps of neovascularization activity (microvessel radius, microvessel density, and microvessel type indicator [MTI]) and oxygen metabolism (oxygen extraction fraction [OEF] and cerebral metabolic rate of oxygen [CMRO2]) were calculated. Receiver operating characteristic analysis was used to determine diagnostic performance for grading and detection of IDH gene mutation status. Results Low-grade (WHO grade II) glioma showed areas with increased OEF (+18%, P < .001, n = 20), whereas anaplastic glioma (WHO grade III) and glioblastoma (WHO grade IV) showed decreased OEF when compared with normal brain tissue (-54% [P < .001, n = 21] and -49% [P < .001, n = 41], respectively). This allowed clear differentiation between low- and high-grade glioma (area under the receiver operating characteristic curve [AUC], 1) for the patient cohort. MTI had the highest diagnostic performance (AUC, 0.782) for differentiation between gliomas of grades III and IV among all biomarkers. CMRO2 was decreased (P = .037) in low-grade glioma with a mutated IDH gene, and MTI was significantly increased in glioma grade III with IDH mutation (P = .013) when compared with the IDH wild-type counterparts. CMRO2 showed the highest diagnostic performance for IDH gene mutation detection in low-grade glioma (AUC, 0.818) and MTI in high-grade glioma (AUC, 0.854) and for all WHO grades (AUC, 0.899) among all biomarkers. Conclusion MR imaging-derived oxygen metabolism and neovascularization characterization may be useful for grading and IDH mutation detection of gliomas and requires only 7 minutes of extra imaging time. © RSNA, 2016 Online supplemental material is available for this article.

Malignancy rates and diagnostic performance of the Bosniak classification for the diagnosis of cystic renal lesions in computed tomography - a systematic review and meta-analysis.

OBJECTIVE: To systematically review the literature on the Bosniak classification system in CT to determine its diagnostic performance to diagnose malignant cystic lesions and the prevalence of malignancy in Bosniak categories. METHODS: A predefined database search was performed from 1 January 1986 to 18 January 2016. Two independent reviewers extracted data on malignancy rates in Bosniak categories and several covariates using predefined criteria. Study quality was assessed using QUADAS-2. Meta-analysis included data pooling, subgroup analyses, meta-regression and investigation of publication bias. RESULTS: A total of 35 studies, which included 2,578 lesions, were investigated. Data on observer experience, inter-observer variation and technical CT standards were insufficiently reported. The pooled rate of malignancy increased from Bosniak I (3.2 %, 95 % CI 0-6.8, I2 = 5 %) to Bosniak II (6 %, 95 % CI 2.7-9.3, I2 = 32 %), IIF (6.7 %, 95 % CI 5-8.4, I2 = 0 %), III (55.1 %, 95 % CI 45.7-64.5, I2 = 89 %) and IV (91 %, 95 % CI 87.7-94.2, I2 = 36). Several study design-related influences on malignancy rates and subsequent diagnostic performance indices were identified. CONCLUSION: The Bosniak classification is an accurate tool with which to stratify the risk of malignancy in renal cystic lesions. KEY POINTS: • The Bosniak classification can accurately rule out malignancy. • Specificity remains moderate at 74 % (95 % CI 64-82). • Follow-up examinations should be considered in Bosniak IIF and Bosniak II cysts. • Data on the influence of reader experience and inter-reader variability are insufficient. • Technical CT standards and publication year did not influence diagnostic performance.

Magnetic Resonance Imaging Compatibility of a New Generation of Active Middle Ear Implant: A Clinically Relevant Temporal Bone Laboratory Study.

OBJECTIVE: Magnetic resonance imaging (MRI) has become an essential tool of modern medical imaging and disease diagnosis. In November 2014, a new MRI-conditional (up to 1.5 T) generation of an active middle ear implant (AMEI) was released to the market.The aim of the study was to test the MRI compatibility of the new implant system in a clinical-anatomical study. DESIGN: Experimental cadaver head model. SETTING: Temporal bone laboratory. PARTICIPANTS: AMEIs were implanted in 28 fixed temporal bones at three different floating mass transducer (FMT)-coupling positions (N = 8 short process of the incus, N = 16 long process of the incus, N = 4 round window). MAIN OUTCOME MEASURES: The position of the FMT and the integrity of the ossicular chain was monitored through microscopy, microendoscopy, and computed tomography (CT) scans before and after the MRI (1.5 T) was conducted. Proper function of the implant was tested with reverse transfer function (RTF) measurements. RESULTS: Neither positional nor functional changes after MRI were observed. CONCLUSION: The new generation of the AMEI is a MRI-compatible system, which features an easier and quicker implant fixation method. The option of MRI in patients with AMEI should be taken into consideration during the preoperative discussion with potential candidates.