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.

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.

Quantitative sensory phenotyping in chronic neuropathic pain patients treated with unilateral L4-dorsal root ganglion stimulation.

BACKGROUND: In a previous study, we reported that selective dorsal root ganglion stimulation (DRGSTIM) at DRG level L4 promoted a favorable outcome for complex regional pain syndrome (CRPS) patients along with DRGSTIM-related changes of inflammatory biomarkers in blood and saliva. The impact on somatosensation is largely unknown. Herein, we assessed the quantitative sensory profile to quantify L4-DRGSTIM effects in CRPS patients. METHODS: Twelve refractory CRPS patients (4 female; 8 male; mean age 69 ± 9 years) received standardized quantitative sensory testing (QST) protocol at baseline and after 3 months of unilateral L4-DRGSTIM assessing nociceptive and non-nociceptive thermal and mechanical sensitivity of the knee affected by CRPS and the contralateral non-painful knee area. RESULTS: At baseline, CRPS subjects showed significantly increased thresholds for warmth, tactile and vibration detection (WDT, MDT and VDT) and exaggerated pain summation (WUR). After 3 months of unilateral L4-DRGSTIM all pain parameters exhibited trends towards normalization of sensitivity accumulating to a significant overall normalization for pain sensitivity (effect size: 0.91, p < 0.01), while with the one exception of WDT all non-nociceptive QST parameters remained unchanged. Overall change of non-nociceptive detection was negligible (effect size: 0.25, p > 0.40). Notably, reduction of pain summation (WUR) correlated significantly with pain reduction after 3 months of L4-DRGSTIM. CONCLUSIONS: Selective L4-DRGSTIM lowered ongoing pain in CRPS patients and evoked significant normalization in the pain domain of the somatosensory profile. Thermoreception and mechanoreception remained unchanged. However, larger randomized, sham-controlled trials are highly warranted to shed more light on effects and mechanisms of dorsal root ganglion stimulation on quantitative sensory characteristics. The study protocol was registered at the 15.11.2016 on German Register for Clinical Trials (DRKS ID 00011267). https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00011267.

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.

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.

Spatiotemporal Pattern of Human Cortical and Subcortical Activity during Early-Stage Odor Processing.

The dynamics of early-stage cortical and subcortical responses in the human brain to odor stimulation are currently unknown. The objective of the present study was to analyze spatiotemporal patterns of human brain activity during odor perception using magnetoencephalography (MEG). In 12 normosmic healthy subjects, we investigated the onset of brain activity in relation to ipsilateral and contralateral stimulation with 2 odorants. Olfactory stimuli (200ms duration) were applied using an olfactometer, and brain activity was recorded with a 248-magnetometer whole-head MEG system. Olfactory responses were identified shortly (within 150ms) after stimulus onset in both hemispheres. Stimulation on the ipsilateral side yielded signals earlier (starting at 90ms) compared with contralateral stimulation in the primary olfactory cortex, hippocampus, parahippocampal gyrus, amygdala, and orbitofrontal cortex ( P < 0.001). The duration and peak amplitude of olfactory evoked magnetic fields were found to increase with increasing poststimulus time in the majority of the investigated cortical structures ( P ≤ 0.019 and P ≤ 0.021). The study showed the locations of early olfactory brain activity in humans within 150ms after the onset of stimuli. Olfactory activation is processed on the ipsilateral side of stimulation in early stages. After a short delay of 34ms a corresponding pattern of activation was also seen in the contralateral hemisphere, indicating the functional connectivity between the 2 hemispheres in the anterior commissure.

Physiological effects of cigarette smoking in the limbic system revealed by 3 tesla magnetic resonance spectroscopy.

Several studies and recent models of effects of nicotine, the main addictive and psychoactive component in tobacco, point to action of the drug on the limbic system during maintenance of addiction, either direct or indirect via projections from the ventral tegmental area. The objective of this study was to demonstrate physiological effects of cigarette smoking on the hippocampus and the grey matter of the dorsal anterior cingulate cortex in the human brain with regard to addiction and withdrawal. This aim was achieved by group comparisons of results of magnetic resonance spectroscopy between non-smokers, smokers and smokers during withdrawal. 12 smokers and 12 non-smokers were measured with single voxel proton magnetic resonance spectroscopy for total N-acetyl aspartate, glutamate and glutamine, choline-containing compounds, myo-inositol and total creatine in the right and the left hippocampus and in the right and the left dorsal anterior cingulate cortex. Smokers were examined twice, first during regular cigarette smoking and second on the third day of nicotine withdrawal. The ratios to total creatine were used for better reliability. In our study, Glx/tCr was significantly increased and tCho/tCr was significantly decreased in the left cingulate cortex in smokers compared to non-smokers (p = 0.01, both). Six out of seven smokers showed normalization of the Glx/tCr in the left cingulate cortex during withdrawal. Although these results are preliminary due to the small sample size, our results confirm the assumption that cigarette smoking interferes directly or indirectly with the glutamate circuit in the dorsal anterior cingulate cortex.

Functional and quantitative magnetic resonance myelography of symptomatic stenoses of the lumbar spine.

INTRODUCTION: The objective of this study was to demonstrate that functional, quantitative magnetic resonance myelography (MRM) allows standardized diagnosis of symptomatic lumbar spinal stenoses which show at least equal detectability compared to functional myelography and postmyelographic CT (pmCT) based on intra- and postoperative findings. METHODS: We investigated 43 volunteers and 47 patients with symptomatic lumbar spinal stenoses using MRM in normal position as well as in flexion and extension in a standard whole-body MR scanner. Twenty volunteers were additionally examined under axial loading. All patients were investigated by functional myelography and pmCT and 10 patients had a functional lumbar MRM postoperatively. Range of motion and cerebrospinal fluid (CSF) volumes in normal position, flexion, extension, and under axial loading (volunteers) were assessed for each segment. Detectability was determined by using intraoperative findings, and postoperative freedom of symptoms was correlated with CSF volume changes in MRM. RESULTS: The ranges of motion in a standard whole-body MR scanner provide adequate scope for investigations into function (flexion and extension) in both volunteers and patients. Axial loading was associated with a mechanism of extension, albeit to a far smaller extent. Detectability of lumbar stenoses was 100% for MRM, 58% for conventional myelography, and 68% for pmCT. Postoperative changes in CSF volume of levels with stenoses in MRM strongly correlated with freedom of symptoms (R = 0.772). CONCLUSION: This MRM method allows for exact diagnosis and reproducible quantification of stenoses, motion-related changes, and spondylolistheses of the lumbar spine. It may be useful for early detection of alterations in order to avoid neuronal compression.

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.

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 [...].

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.

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.

Magnetic resonance velocity mapping of 3D cerebrospinal fluid flow dynamics in hydrocephalus: preliminary results.

OBJECTIVES: To investigate the detectability of CSF flow alterations in the ventricular system of patients with hydrocephalus using time-resolved 3D MR velocity mapping. METHODS: MR velocity mapping was performed in 21 consecutive hydrocephalus patients and 21 age-matched volunteers using a 3D phase-contrast (PC) sequence. Velocity vectors and particle path lines were calculated for visualisation of flow dynamics. CSF flow was classified as "hypomotile flow" if it showed attenuated dynamics and as "hypermotile flow" if it showed increased dynamics compared with volunteers. Diagnostic efficacy was compared with routine 2D cine PC-MRI. RESULTS: Seven patients showed hypomotile CSF flow: six had non-communicating hydrocephalus due to aqueductal stenosis. One showed oscillating flow between the lateral ventricles after craniotomy for intracranial haemorrhage. Seven patients showed normal flow: six had hydrocephalus ex vacuo due to brain atrophy. One patient who underwent ventriculostomy 10 years ago showed a flow path through the opening. Seven patients showed hypermotile flow: three had normal pressure hydrocephalus, three had dementia, and in one the diagnosis remained unclear. The diagnostic efficacy of velocity mapping was significantly higher except for that of aqueductal stenosis. CONCLUSIONS: Our approach may be useful for diagnosis, therapy planning, and follow-up of different kinds of hydrocephalus.

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 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.

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, 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.

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.