Machine Learning-Based Prediction of Glioma IDH Gene Mutation Status Using Physio-Metabolic MRI of Oxygen Metabolism and Neovascularization (A Bicenter Study).

The mutational status of the isocitrate dehydrogenase (IDH) gene plays a key role in the treatment of glioma patients because it is known to affect energy metabolism pathways relevant to glioma. Physio-metabolic magnetic resonance imaging (MRI) enables the non-invasive analysis of oxygen metabolism and tissue hypoxia as well as associated neovascularization and microvascular architecture. However, evaluating such complex neuroimaging data requires computational support. Traditional machine learning algorithms and simple deep learning models were trained with radiomic features from clinical MRI (cMRI) or physio-metabolic MRI data. A total of 215 patients (first center: 166 participants + 16 participants for independent internal testing of the algorithms versus second site: 33 participants for independent external testing) were enrolled using two different physio-metabolic MRI protocols. The algorithms trained with physio-metabolic data demonstrated the best classification performance in independent internal testing: precision, 91.7%; accuracy, 87.5%; area under the receiver operating curve (AUROC), 0.979. In external testing, traditional machine learning models trained with cMRI data exhibited the best IDH classification results: precision, 84.9%; accuracy, 81.8%; and AUROC, 0.879. The poor performance for the physio-metabolic MRI approach appears to be explainable by site-dependent differences in data acquisition methodologies. The physio-metabolic MRI approach potentially supports reliable classification of IDH gene status in the presurgical stage of glioma patients. However, non-standardized protocols limit the level of evidence and underlie the need for a reproducible framework of data acquisition techniques.

Immunometabolic Profiling of Chronic Subdural Hematoma through Untargeted Mass Spectrometry Analysis: Preliminary Findings of a Novel Approach.

Objective: Metabolomics has growing importance in the research of inflammatory processes. Chronic subdural hematoma (cSDH) is considered to be, at least in part, of inflammatory nature, but no metabolic analyses yet exist. Therefore, a mass spectrometry untargeted metabolic analysis was performed on hematoma samples from patients with cSDH. Methods: A prospective analytical cross-sectional study on the efficacy of subperiosteal drains in cSDH was performed. Newly diagnosed patients had the option of granting permission for the collection of a hematoma sample upon its removal. The samples were analyzed using liquid chromatography-mass spectrometry to obtain different types of metabolites from diverse biochemical classes. The statistical analysis included data cleaning, imputation, and log transformation, followed by PCA, PLS-DA, HCA, and ANOVA. The postoperative course of the disease was followed for 3 months. The metabolite concentrations in the hematoma fluid were compared based on whether a recurrence of the disease was recorded within this time frame. Results: Fifty-nine samples from patients who were operated on because of a cSDH were gathered. Among those, 8 samples were eliminated because of missing metabolites, and only 51 samples were analyzed further. Additionally, 39 samples were from patients who showed no recurrence over the course of a 3-month follow-up, and 12 samples were from a group with later recurrence. We recorded a noticeable drop (35%) in the concentration of acylcarnitines in the "recurrence group", where 10 of the 22 tested metabolites showed a significant reduction (p < 0.05). Furthermore, a noticeable reduction in different Acyl-CoA-dehydrogenases was detected (VLCAD-deficiency p < 0.05, MCAD-deficiency p = 0.07). No further changes were detected between both populations. Conclusions: The current study presents a new approach to the research of cSDH. The measurements presented us with new data, which, to date, are without any reference values. Therefore, it is difficult to interpret the information, and our conclusions should be considered to be only speculative. The results do, however, point in the direction of impaired fatty acid oxidation for cases with later recurrence. As fatty acid oxidation plays an important role in inflammatory energy metabolism, the results suggest that inflammatory processes could be aggravated in cases with recurrence. Because our findings are neither proven through further analyses nor offer an obvious therapy option, their implications would not change everyday practice in the management of cSDH. They do, however, present a further possibility of research that might, in the future, be relevant to the therapy.

Controllability and Robustness of Functional and Structural Connectomic Networks in Glioma Patients.

Previous studies suggest that the topological properties of structural and functional neural networks in glioma patients are altered beyond the tumor location. These alterations are due to the dynamic interactions with large-scale neural circuits. Understanding and describing these interactions may be an important step towards deciphering glioma disease evolution. In this study, we analyze structural and functional brain networks in terms of determining the correlation between network robustness and topological features regarding the default-mode network (DMN), comparing prognostically differing patient groups to healthy controls. We determine the driver nodes of these networks, which are receptive to outside signals, and the critical nodes as the most important elements for controllability since their removal will dramatically affect network controllability. Our results suggest that network controllability and robustness of the DMN is decreased in glioma patients. We found losses of driver and critical nodes in patients, especially in the prognostically less favorable IDH wildtype (IDHwt) patients, which might reflect lesion-induced network disintegration. On the other hand, topological shifts of driver and critical nodes, and even increases in the number of critical nodes, were observed mainly in IDH mutated (IDHmut) patients, which might relate to varying degrees of network plasticity accompanying the chronic disease course in some of the patients, depending on tumor growth dynamics. We hereby implement a novel approach for further exploring disease evolution in brain cancer under the aspects of neural network controllability and robustness in glioma patients.

Prediction of the Topography of the Corticospinal Tract on T1-Weighted MR Images Using Deep-Learning-Based Segmentation.

INTRODUCTION: Tractography is an invaluable tool in the planning of tumor surgery in the vicinity of functionally eloquent areas of the brain as well as in the research of normal development or of various diseases. The aim of our study was to compare the performance of a deep-learning-based image segmentation for the prediction of the topography of white matter tracts on T1-weighted MR images to the performance of a manual segmentation. METHODS: T1-weighted MR images of 190 healthy subjects from 6 different datasets were utilized in this study. Using deterministic diffusion tensor imaging, we first reconstructed the corticospinal tract on both sides. After training a segmentation model on 90 subjects of the PIOP2 dataset using the nnU-Net in a cloud-based environment with graphical processing unit (Google Colab), we evaluated its performance using 100 subjects from 6 different datasets. RESULTS: Our algorithm created a segmentation model that predicted the topography of the corticospinal pathway on T1-weighted images in healthy subjects. The average dice score was 0.5479 (0.3513-0.7184) on the validation dataset. CONCLUSIONS: Deep-learning-based segmentation could be applicable in the future to predict the location of white matter pathways in T1-weighted scans.

Artificial Intelligence in Oncology: A Topical Collection in 2022.

Artificial intelligence (AI) is considered one of the core technologies of the Fourth Industrial Revolution that is currently taking place [...].

Emerging roles of leptin in Parkinson's disease: Chronic inflammation, neuroprotection and more?

An increasing body of experimental evidence implicates a relationship between immunometabolic deterioration and the progression of Parkinson's disease (PD) with a dysregulation of central and peripheral neuroinflammatory networks mediated by circulating adipokines, in particular leptin. We screened the current literature on the role of adipokines in PD. Hence, we searched known databases (PubMed, MEDLINE/OVID) and reviewed original and review articles using the following terms: "leptin/ObR", "Parkinson's disease", "immune-metabolism", "biomarkers" and "neuroinflammation". Focusing on leptin, we summarize and discuss the existing in vivo and in vitro evidence on how adipokines may be protective against neurodegeneration, but at the same time contribute to the progression of PD. These components of the adipose brain axis represent a hitherto underestimated pathway to study systemic influences on dopaminergic degeneration. In addition, we give a comprehensive update on the potential of adjunctive therapeutics in PD targeting leptin, leptin-receptors, and associated pathways. Further experimental and clinical trials are needed to elucidate the mechanisms of action and the value of central and peripheral adipose-immune-metabolism molecular phenotyping in order to develop and validate the differential roles of different adipokines as potential therapeutic target for PD patients.

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.

Deep brain stimulation and stereotactic-assisted brain graft injection targeting fronto-striatal circuits for Huntington's disease: an update.

INTRODUCTION: Huntington's Disease as progressive neurological disorders associated with motor, behavioral, and cognitive impairment poses a therapeutic challenge in case of limited responsiveness to established therapeutics. Pallidal deep brain stimulation and neurorestorative strategies (brain grafts) scoping to modulate fronto-striatal circuits have gained increased recognition for the treatment of refractory Huntington's disease (HD). AREAS COVERED: A review (2000-2022) was performed in PubMed, Embase, and Cochrane Library covering clinical trials conceptualized to determine the efficacy and safety of invasive, stereotactic-guided deep-brain stimulation and intracranial brain-graft injection targeting the globus pallidus and adjunct structures (striatum). EXPERT OPINION: Stereotactic brain-grafting strategies were performed in few HD patients with inconsistent findings and mild-to-moderate clinical responsiveness with a recently published large, randomized-controlled trial (NCT00190450) yielding negative results. We identified 19 in-human DBS trials (uncontrolled) targeting the globus pallidus internus/externus along with randomized-controlled trial pending report (NCT02535884). We did not detect any significant changes in the UHDRS total score after restorative injections, while in contrast, the use of deep-brain stimulation resulted in a significant reduction of chorea. GPi-DBS should be considered in cases where selective chorea is present. However, both invasive therapies remain experimental and are not ready for the implementation in clinical use.

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.

Deep Brain Stimulation, Stereotactic Radiosurgery and High-Intensity Focused Ultrasound Targeting the Limbic Pain Matrix: A Comprehensive Review.

Chronic pain (CP) represents a socio-economic burden for affected patients along with therapeutic challenges for currently available therapies. When conventional therapies fail, modulation of the affective pain matrix using reversible deep brain stimulation (DBS) or targeted irreversible thalamotomy by stereotactic radiosurgery (SRS) and magnetic resonance (MR)-guided focused ultrasound (MRgFUS) appear to be considerable treatment options. We performed a literature search for clinical trials targeting the affective pain circuits (thalamus, anterior cingulate cortex [ACC], ventral striatum [VS]/internal capsule [IC]). PubMed, Ovid, MEDLINE and Scopus were searched (1990-2021) using the terms "chronic pain", "deep brain stimulation", "stereotactic radiosurgery", "radioneuromodulation", "MR-guided focused ultrasound", "affective pain modulation", "pain attention". In patients with CP treated with DBS, SRS or MRgFUS the somatosensory thalamus and periventricular/periaquaeductal grey was the target of choice in most treated subjects, while affective pain transmission was targeted in a considerably lower number (DBS, SRS) consisting of the following nodi of the limbic pain matrix: the anterior cingulate cortex; centromedian-parafascicularis of the thalamus, pars posterior of the central lateral nucleus and internal capsule/ventral striatum. Although DBS, SRS and MRgFUS promoted a meaningful and sustained pain relief, an effective, evidence-based comparative analysis is biased by heterogeneity of the observation period varying between 3 months and 5 years with different stimulation patterns (monopolar/bipolar contact configuration; frequency 10-130 Hz; intensity 0.8-5 V; amplitude 90-330 µs), source and occurrence of lesioning (radiation versus ultrasound) and chronic pain ethology (poststroke pain, plexus injury, facial pain, phantom limb pain, back pain). The advancement of neurotherapeutics (MRgFUS) and novel DBS targets (ACC, IC/VS), along with established and effective stereotactic therapies (DBS-SRS), increases therapeutic options to impact CP by modulating affective, pain-attentional neural transmission. Differences in trial concept, outcome measures, targets and applied technique promote conflicting findings and limited evidence. Hence, we advocate to raise awareness of the potential therapeutic usefulness of each approach covering their advantages and disadvantages, including such parameters as invasiveness, risk-benefit ratio, reversibility and responsiveness.

Real-time imaging of glutamate transients in the extracellular space of acute human brain slices using a single-wavelength glutamate fluorescence nanosensor.

Glutamate is the most important excitatory neurotransmitter in the brain. The ability to assess glutamate release and re-uptake with high spatial and temporal resolution is crucial to understand the involvement of this primary excitatory neurotransmitter in both normal brain function and different neurological disorders. Real-time imaging of glutamate transients by fluorescent nanosensors has been accomplished in rat brain slices. We performed for the first time single-wavelength glutamate nanosensor imaging in human cortical brain slices obtained from patients who underwent epilepsy surgery. The glutamate fluorescence nanosensor signals of the electrically stimulated human cortical brain slices showed steep intensity increase followed by an exponential decrease. The spatial distribution and the time course of the signal were in good agreement with the position of the stimulation electrode and the dynamics of the electrical stimulation, respectively. Pharmacological manipulation of glutamate release and reuptake was associated with corresponding changes in the glutamate fluorescence nanosensor signals. We demonstrated that the recently developed fluorescent nanosensors for glutamate allow to detect neuronal activity in acute human cortical brain slices with high spatiotemporal precision. Future application to tissue samples from different pathologies may provide new insights into pathophysiology without the limitations of an animal model.

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.

Association between tissue hypoxia, perfusion restrictions, and microvascular architecture alterations with lesion-induced impairment of neurovascular coupling.

Functional magnetic resonance imaging (fMRI) has been mainly utilized for the preoperative localization of eloquent cortical areas. However, lesion-induced impairment of neurovascular coupling (NVC) in the lesion border zone may lead to false-negative fMRI results. The purpose of this study was to determine physiological factors impacting the NVC. Twenty patients suffering from brain lesions were preoperatively examined using multimodal neuroimaging including fMRI, magnetoencephalography (MEG) during language or sensorimotor tasks (depending on lesion location), and a novel physiologic MRI approach for the combined quantification of oxygen metabolism, perfusion state, and microvascular architecture. Congruence of brain activity patterns between fMRI and MEG were found in 13 patients. In contrast, we observed missing fMRI activity in perilesional cortex that demonstrated MEG activity in seven patients, which was interpreted as lesion-induced impairment of NVC. In these brain regions with impaired NVC, physiologic MRI revealed significant brain tissue hypoxia, as well as significantly decreased macro- and microvascular perfusion and microvascular architecture. We demonstrated that perilesional hypoxia with reduced vascular perfusion and architecture is associated with lesion-induced impairment of NVC. Our physiologic MRI approach is a clinically applicable method for preoperative risk assessment for the presence of false-negative fMRI results and may prevent severe postoperative functional deficits.

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.

Melatonin Moderates the Triangle of Chronic Pain, Sleep Architecture and Immunometabolic Traffic.

Preclinical as well as human studies indicate that melatonin is essential for a physiological sleep state, promotes analgesia and is involved in immunometabolic signaling by regulating neuroinflammatory pathways. Experimental and clinical neuromodulation studies for chronic pain treatment suggest that neurostimulation therapies such as spinal cord stimulation, vagus nerve stimulation and dorsal root ganglion stimulation have an impact on circulating inflammatory mediators in blood, cerebrospinal fluid and saliva. Herein, we provide an overview of current literature relevant for the shared pathways of sleep, pain and immunometabolism and elaborate the impact of melatonin on the crossroad of sleep, chronic pain and immunometabolism. Furthermore, we discuss the potential of melatonin as an adjunct to neurostimulation therapies. In this narrative review, we addressed these questions using the following search terms: melatonin, sleep, immunometabolism, obesity, chronic pain, neuromodulation, neurostimulation, neuroinflammation, molecular inflammatory phenotyping. So far, the majority of the published literature is derived from experimental studies and studies specifically assessing these relationships in context to neurostimulation are sparse. Thus, the adjunct potential of melatonin in clinical neurostimulation has not been evaluated under the umbrella of randomized-controlled trials and deserves increased attention as melatonin interacts and shares pathways relevant for noninvasive and invasive neurostimulation therapies.

JunB is a key regulator of multiple myeloma bone marrow angiogenesis.

Bone marrow (BM) angiogenesis significantly influences disease progression in multiple myeloma (MM) patients and correlates with adverse prognosis. The present study shows a statistically significant correlation of the AP-1 family member JunB with VEGF, VEGFB, and IGF1 expression levels in MM. In contrast to the angiogenic master regulator Hif-1α, JunB protein levels were independent of hypoxia. Results in tumor-cell models that allow the induction of JunB knockdown or JunB activation, respectively, corroborated the functional role of JunB in the production and secretion of these angiogenic factors (AFs). Consequently, conditioned media derived from MM cells after JunB knockdown or JunB activation either inhibited or stimulated in vitro angiogenesis. The impact of JunB on MM BM angiogenesis was finally confirmed in a dynamic 3D model of the BM microenvironment, a xenograft mouse model as well as in patient-derived BM sections. In summary, in continuation of our previous study (Fan et al., 2017), the present report reveals for the first time that JunB is not only a mediator of MM cell survival, proliferation, and drug resistance, but also a promoter of AF transcription and consequently of MM BM angiogenesis. Our results thereby underscore worldwide efforts to target AP-1 transcription factors such as JunB as a promising strategy in MM therapy.

Treatment with Cyclic AMP Activators Reduces Glioblastoma Growth and Invasion as Assessed by Two-Photon Microscopy.

(1) Background: Despite progress in surgery and radio-chemotherapy of glioblastoma (GB), the prognosis remains very poor. GB cells exhibit a preference for hypoxia to maintain their tumor-forming capacity. Enhancing oxidative phosphorylation-known as the anti-Warburg effect-with cyclic AMP activators has been demonstrated to drive GB cells from proliferation to differentiation thereby reducing tumor growth in a cell culture approach. Here we re-evaluate this treatment in a more clinically relevant model. (2) Methods: The effect of treatment with dibutyryl cyclic AMP (dbcAMP, 1 mM) and the cAMP activator forskolin (50µM) was assessed in a GB cell line (U87GFP+, 104 cells) co-cultured with mouse organotypic brain slices providing architecture and biochemical properties of normal brain tissue. Cell viability was determined by propidium-iodide, and gross metabolic effects were excluded in the extracellular medium. Tumor growth was quantified in terms of area, volume, and invasion at the start of culture, 48 h, 7 days, and 14 days after treatment. (3) Results: The tumor area was significantly reduced following dbcAMP or forskolin treatment (F2,249 = 5.968, p = 0.0029). 3D volumetric quantification utilizing two-photon fluorescence microscopy revealed that the treated tumors maintained a spheric shape while the untreated controls exhibited the GB typical invasive growth pattern. (4) Conclusions: Our data demonstrate that treatment with a cAMP analog/activator reduces GB growth and invasion.

Physiological MRI Biomarkers in the Differentiation Between Glioblastomas and Solitary Brain Metastases.

PURPOSE: Glioblastomas (GB) and solitary brain metastases (BM) are the most common brain tumors in adults. GB and BM may appear similar in conventional magnetic resonance imaging (cMRI). Their management strategies, however, are quite different with significant consequences on clinical outcome. The aim of this study was to evaluate the usefulness of a previously presented physiological MRI approach scoping to obtain quantitative information about microvascular architecture and perfusion, neovascularization activity, and oxygen metabolism to differentiate GB from BM. PROCEDURES: Thirty-three consecutive patients with newly diagnosed, untreated, and histopathologically confirmed GB or BM were preoperatively examined with our physiological MRI approach as part of the cMRI protocol. RESULTS: Physiological MRI biomarker maps revealed several significant differences in the pathophysiology of GB and BM: Central necrosis was more hypoxic in GB than in BM (30 %; P = 0.036), which was associated with higher neovascularization activity (65 %; P = 0.043) and metabolic rate of oxygen (48 %; P = 0.004) in the adjacent contrast-enhancing viable tumor parts of GB. In peritumoral edema, GB infiltration caused neovascularization activity (93 %; P = 0.018) and higher microvascular perfusion (30 %; P = 0.022) associated with higher tissue oxygen tension (33 %; P = 0.020) and lower oxygen extraction from vasculature (32 %; P = 0.040). CONCLUSION: Our physiological MRI approach, which requires only 7 min of extra data acquisition time, might be helpful to noninvasively distinguish GB and BM based on pathophysiological differences. However, further studies including more patients are required.

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.