Deep learning segmentation algorithms can produce reproducible results in a matter of seconds. However, their application to more complex datasets is uncertain and may fail in the presence of severe structural abnormalities-such as those commonly seen in stroke patients. In this investigation, six recent, deep learning-based hippocampal segmentation algorithms were tested on 641 stroke patients of a multicentric, open-source dataset ATLAS 2.0. The comparisons of the volumes showed that the methods are not interchangeable with concordance correlation coefficients from 0.266 to 0.816. While the segmentation algorithms demonstrated an overall good performance (volumetric similarity [VS] 0.816 to 0.972, DICE score 0.786 to 0.921, and Hausdorff distance [HD] 2.69 to 6.34), no single out-performing algorithm was identified: FastSurfer performed best in VS, QuickNat in DICE and average HD, and Hippodeep in HD. Segmentation performance was significantly lower for ipsilesional segmentation, with a decrease in performance as a function of lesion size due to the pathology-based domain shift. Only QuickNat showed a more robust performance in volumetric similarity. Even though there are many pre-trained segmentation methods, it is important to be aware of the possible decrease in performance for the segmentation results on the lesion side due to the pathology-based domain shift. The segmentation algorithm should be selected based on the research question and the evaluation parameter needed. More research is needed to improve current hippocampal segmentation methods.

Glioblastoma multiforme alters healthy tissue vasculature by inducing angiogenesis and vascular remodeling. To fully comprehend the structural and functional properties of the resulting vascular network, it needs to be studied collectively by considering both geometric and topological properties. Utilizing Single Plane Illumination Microscopy (SPIM), the detailed capillary structure in entire healthy and tumor-bearing mouse brains could be resolved in three dimensions. At the scale of the smallest capillaries, the entire vascular systems of bulk U87- and GL261-glioblastoma xenografts, their respective cores, and healthy brain hemispheres were modeled as complex networks and quantified with fundamental topological measures. All individual vessel segments were further quantified geometrically and modular clusters were uncovered and characterized as meta-networks, facilitating an analysis of large-scale connectivity. An inclusive comparison of large tissue sections revealed that geometric properties of individual vessels were altered in glioblastoma in a relatively subtle way, with high intra- and inter-tumor heterogeneity, compared to the impact on the vessel connectivity. A network topology analysis revealed a clear decomposition of large modular structures and hierarchical network organization, while preserving most fundamental topological classifications, in both tumor models with distinct growth patterns. These results augment our understanding of cerebrovascular networks and offer a topological assessment of glioma-induced vascular remodeling. The findings may help understand the emergence of hypoxia and necrosis, and prove valuable for therapeutic interventions such as radiation or antiangiogenic therapy.

Redox switches are important mediators in neoplastic, cardiovascular and neurological disorders. We recently identified spontaneous redox signals in neurons at the single mitochondrion level where transients of glutathione oxidation go along with shortening and re-elongation of the organelle. We now have developed advanced image and signal-processing methods to re-assess and extend previously obtained data. Here we analyze redox and pH signals of entire mitochondrial populations. In total, we quantified the effects of 628 redox and pH events in 1797 mitochondria from intercostal axons and neuromuscular synapses using optical sensors (mito-Grx1-roGFP2; mito-SypHer). We show that neuronal mitochondria can undergo multiple redox cycles exhibiting markedly different signal characteristics compared to single redox events. Redox and pH events occur more often in mitochondrial clusters (medium cluster size: 34.1 ± 4.8 μm(2)). Local clusters possess higher mitochondrial densities than the rest of the axon, suggesting morphological and functional inter-mitochondrial coupling. We find that cluster formation is redox sensitive and can be blocked by the antioxidant MitoQ. In a nerve crush paradigm, mitochondrial clusters form sequentially adjacent to the lesion site and oxidation spreads between mitochondria. Our methodology combines optical bioenergetics and advanced signal processing and allows quantitative assessment of entire mitochondrial populations.

Volumetric measurements in radiologic images are important for monitoring tumor growth and treatment response. To make these more reproducible and objective we introduce the concept of virtual raters (VRs). A virtual rater is obtained by combining knowledge of machine-learning algorithms trained with past annotations of multiple human raters with the instantaneous rating of one human expert. Thus, he is virtually guided by several experts. To evaluate the approach we perform experiments with multi-channel magnetic resonance imaging (MRI) data sets. Next to gross tumor volume (GTV) we also investigate subcategories like edema, contrast-enhancing and non-enhancing tumor. The first data set consists of N = 71 longitudinal follow-up scans of 15 patients suffering from glioblastoma (GB). The second data set comprises N = 30 scans of low- and high-grade gliomas. For comparison we computed Pearson Correlation, Intra-class Correlation Coefficient (ICC) and Dice score. Virtual raters always lead to an improvement w.r.t. inter- and intra-rater agreement. Comparing the 2D Response Assessment in Neuro-Oncology (RANO) measurements to the volumetric measurements of the virtual raters results in one-third of the cases in a deviating rating. Hence, we believe that our approach will have an impact on the evaluation of clinical studies as well as on routine imaging diagnostics.

Neurofilament light chain (NfL), released during central nervous injury, has evolved as a powerful serum marker of disease severity in many neurological disorders, including infectious diseases. So far NfL has not been assessed in cerebral malaria in human or its rodent model experimental cerebral malaria (ECM), a disease that can lead to fatal brain edema or reversible brain edema. In this study we assessed if NfL serum levels can also grade disease severity in an ECM mouse model with reversible (n = 11) and irreversible edema (n = 10). Blood-brain-barrier disruption and brain volume were determined by magnetic resonance imaging. Neurofilament density volume as well as structural integrity were examined by electron microscopy in regions of most severe brain damage (olfactory bulb (OB), cortex and brainstem). NfL plasma levels in mice with irreversible edema (317.0 ± 45.01 pg/ml) or reversible edema (528.3 ± 125.4 pg/ml) were significantly increased compared to controls (103.4 ± 25.78 pg/ml) by three to five fold, but did not differ significantly in mice with reversible or irreversible edema. In both reversible and irreversible edema, the brain region most affected was the OB with highest level of blood-brain-barrier disruption and most pronounced decrease in neurofilament density volume, which correlated with NfL plasma levels (r = - 0.68, p = 0.045). In cortical and brainstem regions neurofilament density was only decreased in mice with irreversible edema and strongest in the brainstem. In reversible edema NfL plasma levels, MRI findings and neurofilament volume density normalized at 3 months' follow-up. In conclusion, NfL plasma levels are elevated during ECM confirming brain damage. However, NfL plasma levels fail short on reliably indicating on the final outcomes in the acute disease stage that could be either fatal or reversible. Increased levels of plasma NfL during the acute disease stage are thus likely driven by the anatomical location of brain damage, the olfactory bulb, a region that serves as cerebral draining pathway into the nasal lymphatics.

High-precision radiotherapy (HPR) of recurrent high grade glioma (HGG) requires accurate spatial allocation of these infiltrative tumors. We investigated the impact of 18F-FET PET on tumor delineation and progression of recurrent HGG after HPR with carbon ions. T1 contrast enhanced MRI and 18F-FET-PET scans of 26 HGG patients were fused with radiotherapy planning volumes. PET-positive (PET+) tumor volumes using different isocontours (I%) were systematically investigated and compared with MRI-derived gross tumor volumes (GTV). Standardized uptake ratios (SUR) were further correlated with GTV and tumor progression patterns. In grade IV glioma, SUR > 2.92 significantly correlated with poor median overall survival (6.5 vs 13.1 months, p = 0.00016). We found no reliable SUR cut-off criteria for definition of PET+ volumes. Overall conformity between PET and MRI-based contours was low, with maximum conformities between 0.42-0.51 at I40%. The maximum sensitivity and specificity for PET+ volumes outside of GTV predicting tumor progression were 0.16 (I40%) and 0.52 (I50%), respectively. In 75% of cases, FLAIR hyperintense area covered over 80% of PET+ volumes. 18F-FET-PET derived SUR has a prognostic impact in grade IV glioma. The value of substantial mismatches between MRI-based GTV and PET+ volumes to improve tumor delineation in radiotherapy awaits further validation in randomized prospective trials.

The recent identification of IDH mutations in gliomas and several other cancers suggests that this pathway is involved in oncogenesis; however effector functions are complex and yet incompletely understood. To study the regulatory effects of IDH on hypoxia-inducible-factor 1-alpha (HIF1A), a driving force in hypoxia-initiated angiogenesis, we analyzed mRNA expression profiles of 288 glioma patients and show decreased expression of HIF1A targets on a single-gene and pathway level, strong inhibition of upstream regulators such as HIF1A and downstream biological functions such as angio- and vasculogenesis in IDH mutant tumors. Genotype/imaging phenotype correlation analysis with relative cerebral blood volume (rCBV) MRI - a robust and non-invasive estimate of tumor angiogenesis - in 73 treatment-naive patients with low-grade and anaplastic gliomas showed that a one-unit increase in rCBV corresponded to a two-third decrease in the odds for an IDH mutation and correctly predicted IDH mutation status in 88% of patients. Together, these findings (1) show that IDH mutation status is associated with a distinct angiogenesis transcriptome signature which is non-invasively predictable with rCBV imaging and (2) highlight the potential future of radiogenomics (i.e. the correlation between cancer imaging and genomic features) towards a more accurate diagnostic workup of brain tumors.

The catabolism of tryptophan to immunosuppressive and neuroactive kynurenines is a key metabolic pathway regulating immune responses and neurotoxicity. The rate-limiting step is controlled by indoleamine-2,3-dioxygenase (IDO) and tryptophan-2,3-dioxygenase (TDO). IDO is expressed in antigen presenting cells during immune reactions, hepatic TDO regulates blood homeostasis of tryptophan and neuronal TDO influences neurogenesis. While the role of IDO has been described in multiple immunological settings, little is known about TDO's effects on the immune system. TDO-deficiency is neuroprotective in C. elegans and Drosophila by increasing tryptophan and specific kynurenines. Here we have determined the role of TDO in autoimmunity and neurodegeneration in experimental autoimmune encephalomyelitis (EAE), a model of multiple sclerosis. We created reporter-TDO mice for in vivo imaging to show that hepatic but not CNS TDO expression is activated during EAE. TDO deficiency did not influence myelin-specific T cells, leukocyte infiltration into the CNS, demyelination and disease activity. TDO-deficiency protected from neuronal loss in the spinal cord but not in the optic nerves. While this protection did not translate to an improved overt clinical outcome, our data suggest that spatially distinct neuroprotection is conserved in mammals and support TDO as a potential target for treatment of diseases associated with neurodegeneration.

Cerebral malaria is a life-threatening complication of Plasmodia infection and a major cause of child mortality in Sub-Saharan Africa. We report that protection from experimental cerebral malaria in the rodent model is obtained by a single intravenous or subcutaneous whole-parasite immunization. Whole-parasite immunization with radiation-attenuated sporozoites was equally protective as immunization with non-attenuated sporozoites under chemoprophylaxis. Both immunization regimens delayed the development of blood-stage parasites, but differences in cellular and humoral immune mechanisms were observed. Single-dose whole-parasite vaccination might serve as a relatively simple and feasible immunization approach to prevent life-threatening cerebral malaria.

In light of the limited treatment options of diabetic polyneuropathy (DPN) available, suitable animal models are essential to investigate pathophysiological mechanisms and to identify potential therapeutic targets. In vivo evaluation with current techniques, however, often provides only restricted information about disease evolution. In the study of patients with DPN, magnetic resonance neurography (MRN) has been introduced as an innovative diagnostic tool detecting characteristic lesions within peripheral nerves. We developed a novel multicontrast ultra high field MRN strategy to examine major peripheral nerve segments in diabetic mice non-invasively. It was first validated in a cross-platform approach on human nerve tissue and then applied to the popular streptozotocin(STZ)-induced mouse model of DPN. In the absence of gross morphologic alterations, a distinct MR-signature within the sciatic nerve was observed mirroring subtle changes of the nerves' fibre composition and ultrastructure, potentially indicating early re-arrangements of DPN. Interestingly, these signal alterations differed from previously reported typical nerve lesions of patients with DPN. The capacity of our approach to non-invasively assess sciatic nerve tissue structure and function within a given mouse model provides a powerful tool for direct translational comparison to human disease hallmarks not only in diabetes but also in other peripheral neuropathic conditions.

Cerebral organoids recapitulate the structure and function of the developing human brain in vitro, offering a large potential for personalized therapeutic strategies. The enormous growth of this research area over the past decade with its capability for clinical translation makes a non-invasive, automated analysis pipeline of organoids highly desirable. This work presents a novel non-invasive approach to monitor and analyze cerebral organoids over time using high-field magnetic resonance imaging and state-of-the-art tools for automated image analysis. Three specific objectives are addressed, (I) organoid segmentation to investigate organoid development over time, (II) global cysticity classification and (III) local cyst segmentation for organoid quality assessment. We show that organoid growth can be monitored reliably over time and cystic and non-cystic organoids can be separated with high accuracy, with on par or better performance compared to state-of-the-art tools applied to brightfield imaging. Local cyst segmentation is feasible but could be further improved in the future. Overall, these results highlight the potential of the pipeline for clinical application to larger-scale comparative organoid analysis.