Quantification of intratumoural heterogeneity in mice and patients via machine-learning models trained on PET-MRI data.

In oncology, intratumoural heterogeneity is closely linked with the efficacy of therapy, and can be partially characterized via tumour biopsies. Here we show that intratumoural heterogeneity can be characterized spatially via phenotype-specific, multi-view learning classifiers trained with data from dynamic positron emission tomography (PET) and multiparametric magnetic resonance imaging (MRI). Classifiers trained with PET-MRI data from mice with subcutaneous colon cancer quantified phenotypic changes resulting from an apoptosis-inducing targeted therapeutic and provided biologically relevant probability maps of tumour-tissue subtypes. When applied to retrospective PET-MRI data of patients with liver metastases from colorectal cancer, the trained classifiers characterized intratumoural tissue subregions in agreement with tumour histology. The spatial characterization of intratumoural heterogeneity in mice and patients via multimodal, multiparametric imaging aided by machine-learning may facilitate applications in precision oncology.

In vivo interrogation of regulatory genomes reveals extensive quasi-insufficiency in cancer evolution.

In contrast to mono- or biallelic loss of tumor-suppressor function, effects of discrete gene dysregulations, as caused by non-coding (epi)genome alterations, are poorly understood. Here, by perturbing the regulatory genome in mice, we uncover pervasive roles of subtle gene expression variation in cancer evolution. Genome-wide screens characterizing 1,450 tumors revealed that such quasi-insufficiency is extensive across entities and displays diverse context dependencies, such as distinct cell-of-origin associations in T-ALL subtypes. We compile catalogs of non-coding regions linked to quasi-insufficiency, show their enrichment with human cancer risk variants, and provide functional insights by engineering regulatory alterations in mice. As such, kilo-/megabase deletions in a Bcl11b-linked non-coding region triggered aggressive malignancies, with allele-specific tumor spectra reflecting gradual gene dysregulations through modular and cell-type-specific enhancer activities. Our study constitutes a first survey toward a systems-level understanding of quasi-insufficiency in cancer and gives multifaceted insights into tumor evolution and the tissue-specific effects of non-coding mutations.

Cerebrovascular Gi Proteins Protect Against Brain Hypoperfusion and Collateral Failure in Cerebral Ischemia.

Cerebral hypoperfusion and vascular dysfunction are closely related to common risk factors for ischemic stroke such as hypertension, dyslipidemia, diabetes, and smoking. The role of inhibitory G protein-dependent receptor (GiPCR) signaling in regulating cerebrovascular functions remains largely elusive. We examined the importance of GiPCR signaling in cerebral blood flow (CBF) and its stability after sudden interruption using various in vivo high-resolution magnetic resonance imaging techniques. To this end, we induced a functional knockout of GiPCR signaling in the brain vasculature by injection of pertussis toxin (PTX). Our results show that PTX induced global brain hypoperfusion and microvascular collapse. When PTX-pretreated animals underwent transient unilateral occlusion of one common carotid artery, CBF was disrupted in the ipsilateral hemisphere resulting in the collapse of the cortically penetrating microvessels. In addition, pronounced stroke features in the affected brain regions appeared in both MRI and histological examination. Our findings suggest an impact of cerebrovascular GiPCR signaling in the maintenance of CBF, which may be useful for novel pharmacotherapeutic approaches to prevent and treat cerebrovascular dysfunction and stroke.

CD147 a direct target of miR-146a supports energy metabolism and promotes tumor growth in ALK+ ALCL.

We recently reported that miR-146a is differentially expressed in ALK+ and ALK- anaplastic large cell lymphoma (ALCL). In this study, the downstream targets of miR-146a in ALK+ ALCL were investigated by transcriptome analysis, identifying CD147 as potential target gene. Because CD147 is differentially expressed in ALK+ ALCL versus ALK- ALCL and normal T cells, this gene emerged as a strong candidate for the pathogenesis of this tumor. Here we demonstrate that CD147 is a direct target of miR-146 and contributes to the survival and proliferation of ALK+ ALCL cells in vitro and to the engraftment and tumor growth in vivo in an ALK+ ALCL-xenotransplant mouse model. CD147 knockdown in ALK+ ALCL cells resulted in loss of monocarboxylate transporter 1 (MCT1) expression, reduced glucose consumption and tumor growth retardation, as demonstrated by [18F]FDG-PET/MRI analysis. Investigation of metabolism in vitro and in vivo supported these findings, revealing reduced aerobic glycolysis and increased basal respiration in CD147 knockdown. In conclusion, our findings indicate that CD147 is of vital importance for ALK+ ALCL to maintain the high energy demand of rapid cell proliferation, promoting lactate export, and tumor growth. Furthermore, CD147 has the potential to serve as a novel therapeutic target in ALK+ ALCL, and warrants further investigation.

Intratumoral in vivo staging of breast cancer by multi-tracer PET and advanced analysis.

The staging and local management of breast cancer involves the evaluation of the extent and completeness of excision of both the invasive carcinoma component and also the intraductal component or ductal carcinoma in situ. When both invasive ductal carcinoma and coincident ductal carcinoma in situ are present, assessment of the extent and localization of both components is required for optimal therapeutic planning. We have used a mouse model of breast cancer to evaluate the feasibility of applying molecular imaging to assess the local status of cancers in vivo. Multi-tracer positron emission tomography (PET) and magnetic resonance imaging (MRI) characterize the transition from premalignancy to invasive carcinoma. PET tracers for glucose consumption, membrane synthesis, and neoangiogenesis in combination with a Gaussian mixture model-based analysis reveal image-derived thresholds to separate the different stages within the whole-lesion. Autoradiography, histology, and quantitative image analysis of immunohistochemistry further corroborate our in vivo findings. Finally, clinical data further support our conclusions and demonstrate translational potential. In summary, this preclinical model provides a platform for characterizing multistep tumor progression and provides proof of concept that supports the utilization of advanced protocols for PET/MRI in clinical breast cancer imaging.

TET3 promotes AML growth and epigenetically regulates glucose metabolism and leukemic stem cell associated pathways.

Acute myeloid leukemia (AML) is considered a poor prognosis malignancy where patients exhibit altered glucose metabolism and stem cell signatures that contribute to AML growth and maintenance. Here, we report that the epigenetic factor, Ten-Eleven Translocation 3 (TET3) dioxygenase is overexpressed in AML patients and functionally validated human leukemic stem cells (LSCs), is required for leukemic growth by virtue of its regulation of glucose metabolism in AML cells. In human AML cells, TET3 maintains 5-hydroxymethylcytosine (5hmC) epigenetic marks and expression of early myeloid progenitor program, critical glucose metabolism and STAT5A signaling pathway genes, which also positively correlate with TET3 expression in AML patients. Consequently, TET3 depletion impedes hexokinase activity and L-Lactate production in AML cells. Conversely, overexpression of TET3 in healthy human hematopoietic stem progenitors (HSPCs) upregulates the expression of glucose metabolism, STAT5A signaling and AML associated genes, and impairs normal HSPC lineage differentiation in vitro. Finally, TET3 depletion renders AML cells highly sensitive to blockage of the TET3 downstream pathways glycolysis and STAT5 signaling via the combination of 2-Deoxy-D-glucose and STAT5 inhibitor which preferentially targets AML cells but spares healthy CD34+ HSPCs.

Machine learning identifies stroke features between species.

Identification and localization of ischemic stroke (IS) lesions is routinely performed to confirm diagnosis, assess stroke severity, predict disability and plan rehabilitation strategies using magnetic resonance imaging (MRI). In basic research, stroke lesion segmentation is necessary to study complex peri-infarction tissue changes. Moreover, final stroke volume is a critical outcome evaluated in clinical and preclinical experiments to determine therapy or intervention success. Manual segmentations are performed but they require a specialized skill set, are prone to inter-observer variation, are not entirely objective and are often not supported by histology. The task is even more challenging when dealing with large multi-center datasets, multiple experimenters or large animal cohorts. On the other hand, current automatized segmentation approaches often lack histological validation, are not entirely user independent, are often based on single parameters, or in the case of complex machine learning methods, require vast training datasets and are prone to a lack of model interpretation. Methods: We induced IS using the middle cerebral artery occlusion model on two rat cohorts. We acquired apparent diffusion coefficient (ADC) and T2-weighted (T2W) images at 24 h and 1-week after IS induction. Subsets of the animals at 24 h and 1-week post IS were evaluated using histology and immunohistochemistry. Using a Gaussian mixture model, we segmented voxel-wise interactions between ADC and T2W parameters at 24 h using one of the rat cohorts. We then used these segmentation results to train a random forest classifier, which we applied to the second rat cohort. The algorithms' stroke segmentations were compared to manual stroke delineations, T2W and ADC thresholding methods and the final stroke segmentation at 1-week. Volume correlations to histology were also performed for every segmentation method. Metrics of success were calculated with respect to the final stroke volume. Finally, the trained random forest classifier was tested on a human dataset with a similar temporal stroke on-set. Manual segmentations, ADC and T2W thresholds were again used to evaluate and perform comparisons with the proposed algorithms' output. Results: In preclinical rat data our framework significantly outperformed commonly applied automatized thresholding approaches and segmented stroke regions similarly to manual delineation. The framework predicted the localization of final stroke regions in 1-week post-stroke MRI with a median Dice similarity coefficient of 0.86, Matthew's correlation coefficient of 0.80 and false positive rate of 0.04. The predicted stroke volumes also strongly correlated with final histological stroke regions (Pearson correlation = 0.88, P < 0.0001). Lastly, the stroke region characteristics identified by our framework in rats also identified stroke lesions in human brains, largely outperforming thresholding approaches in stroke volume prediction (P<0.01). Conclusion: Our findings reveal that the segmentation produced by our proposed framework using 24 h MRI rat data strongly correlated with the final stroke volume, denoting a predictive effect. In addition, we show for the first time that the stroke imaging features can be directly translated between species, allowing identification of acute stroke in humans using the model trained on animal data. This discovery reduces the gap between the clinical and preclinical fields, unveiling a novel approach to directly co-analyze clinical and preclinical data. Such methods can provide further biological insights into human stroke and highlight the differences between species in order to help improve the experimental setups and animal models of the disease.

Enriched Environmental Conditions Modify the Gut Microbiome Composition and Fecal Markers of Inflammation in Parkinson's Disease.

Recent findings suggest an implication of the gut microbiome in Parkinson's disease (PD) patients. PD onset and progression has also been linked with various environmental factors such as physical activity, exposure to pesticides, head injury, nicotine, and dietary factors. In this study, we used a mouse model, overexpressing the complete human SNCA gene (SNCA-TG mice) modeling familial and sporadic forms of PD to study whether environmental conditions such as standard vs. enriched environment changes the gut microbiome and influences disease progression. We performed 16S rRNA DNA sequencing on fecal samples for microbiome analysis and studied fecal inflammatory calprotectin from the colon of control and SNCA-TG mice kept under standard environment (SE) and enriched environment (EE) conditions. The overall composition of the gut microbiota was not changed in SNCA-TG mice compared with WT in EE with respect to SE. However, individual gut bacteria at genus level such as Lactobacillus sp. was a significant changed in the SNCA-TG mice. EE significantly reduced colon fecal inflammatory calprotectin protein in WT and SNCA-TG EE compared to SE. Moreover, EE reduces the pro-inflammatory cytokines in the feces and inflammation inducing genes in the colon. Our data suggest that an enriched social environment has a positive effect on the induction of SNCA mediated inflammation in the intestine and by modulating anti-inflammatory gut bacteria.

Imaging fibrosis in inflammatory diseases: targeting the exposed extracellular matrix.

In a variety of diseases, from benign to life-threatening ones, inflammation plays a major role. Monitoring the intensity and extent of a multifaceted inflammatory process has become a cornerstone in diagnostics and therapy monitoring. However, the current tools lack the ability to provide insight into one of its most crucial aspects, namely, the alteration of the extracellular matrix (ECM). Using a radiolabeled platelet glycoprotein VI-based ECM-targeting fusion protein (GPVI-Fc), we investigated how binding of GPVI-Fc on fibrous tissue could uncover the progression of several inflammatory disease models at different stages (rheumatoid arthritis, cutaneous delayed-type hypersensitivity, lung inflammation and experimental autoimmune encephalomyelitis). Methods: The fusion protein GPVI-Fc was covalently linked to 1,4,7-triazacyclononane-1,4,7-triacetic acid (NOTA) and subsequently labeled with 64Cu. We analyzed noninvasively in vivo64Cu-GPVI-Fc accumulation in murine cutaneous delayed-type hypersensitivity, anti-glucose-6-phosphate isomerase serum-induced rheumatoid arthritis, lipopolysaccharide-induced lung inflammation and an experimental autoimmune encephalomyelitis model. Static and dynamic Positron Emission Tomography (PET) of the radiotracer distribution was performed in vivo, with ex vivo autoradiography confirmation, yielding quantitative accumulation and a distribution map of 64Cu-GPVI-Fc. Ex vivo tissue histological staining was performed on harvested samples to highlight the fusion protein binding to collagen I, II and III, fibronectin and fibrinogen as well as the morphology of excised tissue. Results:64Cu-GPVI-Fc showed a several-fold increased uptake in inflamed tissue compared to control tissue, particularly in the RA model, with a peak 24 h after radiotracer injection of up to half the injected dose. Blocking and isotype control experiments indicated a target-driven accumulation of the radiotracer in the case of chronic inflammation. Histological analysis confirmed a prolonged accumulation at the inflammation site, with a pronounced colocalization with the different components of the ECM (collagen III and fibronectin notably). Binding of the fusion protein appeared to be specific to the ECM but unspecific to particular components. Conclusion: Imaging of 64Cu-GPVI-Fc accumulation in the ECM matrix appears to be a promising candidate for monitoring chronic inflammation. By binding to exposed fibrous tissue (collagen, fibronectin, etc.) after extravasation, a new insight is provided into the fibrotic events resulting from a prolonged inflammatory state.

PiggyBac transposon tools for recessive screening identify B-cell lymphoma drivers in mice.

B-cell lymphoma (BCL) is the most common hematologic malignancy. While sequencing studies gave insights into BCL genetics, identification of non-mutated cancer genes remains challenging. Here, we describe PiggyBac transposon tools and mouse models for recessive screening and show their application to study clonal B-cell lymphomagenesis. In a genome-wide screen, we discover BCL genes related to diverse molecular processes, including signaling, transcriptional regulation, chromatin regulation, or RNA metabolism. Cross-species analyses show the efficiency of the screen to pinpoint human cancer drivers altered by non-genetic mechanisms, including clinically relevant genes dysregulated epigenetically, transcriptionally, or post-transcriptionally in human BCL. We also describe a CRISPR/Cas9-based in vivo platform for BCL functional genomics, and validate discovered genes, such as Rfx7, a transcription factor, and Phip, a chromatin regulator, which suppress lymphomagenesis in mice. Our study gives comprehensive insights into the molecular landscapes of BCL and underlines the power of genome-scale screening to inform biology.

The administration route of tumor-antigen-specific T-helper cells differentially modulates the tumor microenvironment and senescence.

Cancer treatment with adoptively transferred tumor-associated antigen-specific CD4+ T-helper cells is a promising immunotherapeutic approach. In the pancreatic cancer model RIP-Tag2, the intraperitoneal (i.p.) application of Tag-specific TH1 cells exhibited a profound antitumoral efficiency. We investigated, whether an intravenous (i.v.) application of Tag-TH1 cells induces an equivalent therapeutic effect. Adoptively transferred fluorescent Tag-TH1 cells revealed a pronounced homing to the tumors after either i.p. or i.v. transfer, and both routes induced an almost equivalent therapeutic effect as demonstrated by magnetic resonance imaging, blood glucose level course and histology. The i.v. administration of Tag-TH1 cells induced p16INK4-positive/Ki67-negative tumor senescence more efficiently than i.p. administration. Both routes replenish host CD4+ T cells by transferred T cells and recruitment of B and dendritic cells to the tumors while reducing CD8+ T cells and depleting macrophages. Both administration routes efficiently induced a similar antitumoral efficiency despite the pronounced senescence induction after i.v. administration. Thus, a combinatory i.v./i.p. injection of therapeutic cells might overcome limitations of the individual routes and improve therapeutic efficacy in solid tumors.

Loss of Endometrial Sodium Glucose Cotransporter SGLT1 is Detrimental to Embryo Survival and Fetal Growth in Pregnancy.

Embryo implantation requires a hospitable uterine environment. A key metabolic change that occurs during the peri-implantation period, and throughout early pregnancy, is the rise in endometrial glycogen content. Glycogen accumulation requires prior cellular uptake of glucose. Here we show that both human and murine endometrial epithelial cells express the high affinity Na+-coupled glucose carrier SGLT1. Ussing chamber experiments revealed electrogenic glucose transport across the endometrium in wild type (Slc5a1 +/+) but not in SGLT1 deficient (Slc5a1 -/-) mice. Endometrial glycogen content, litter size and weight of offspring at birth were significantly lower in Slc5a1 -/- mice. In humans, SLC5A1 expression was upregulated upon decidualization of primary endometrial stromal cells. Endometrial SLC5A1 expression during the implantation window was attenuated in patients with recurrent pregnancy loss when compared with control subjects. Our findings reveal a novel mechanism establishing adequate endometrial glycogen stores for pregnancy. Disruption of this histiotrophic pathway leads to adverse pregnancy outcome.

NFAT2 is a critical regulator of the anergic phenotype in chronic lymphocytic leukaemia.

Chronic lymphocytic leukaemia (CLL) is a clonal disorder of mature B cells. Most patients are characterised by an indolent disease course and an anergic phenotype of their leukaemia cells, which refers to a state of unresponsiveness to B cell receptor stimulation. Up to 10% of CLL patients transform from an indolent subtype to an aggressive form of B cell lymphoma over time (Richter´s syndrome) and show a significantly worse treatment outcome. Here we show that B cell-specific ablation of Nfat2 leads to the loss of the anergic phenotype culminating in a significantly compromised life expectancy and transformation to aggressive disease. We further define a gene expression signature of anergic CLL cells consisting of several NFAT2-dependent genes including Cbl-b, Grail, Egr2 and Lck. In summary, this study identifies NFAT2 as a crucial regulator of the anergic phenotype in CLL.NFAT2 is a transcription factor that has been linked with chronic lymphocytic leukaemia (CLL), but its functions in CLL manifestation are still unclear. Here the authors show, by analysing mouse CLL models and characterising biopsies from CLL patients, that NFAT2 is an important regulator for the anergic phenotype of CLL.

Cre/lox-assisted non-invasive in vivo tracking of specific cell populations by positron emission tomography.

Many pathophysiological processes are associated with proliferation, migration or death of distinct cell populations. Monitoring specific cell types and their progeny in a non-invasive, longitudinal and quantitative manner is still challenging. Here we show a novel cell-tracking system that combines Cre/lox-assisted cell fate mapping with a thymidine kinase (sr39tk) reporter gene for cell detection by positron emission tomography (PET). We generate Rosa26-mT/sr39tk PET reporter mice and induce sr39tk expression in platelets, T lymphocytes or cardiomyocytes. As proof of concept, we demonstrate that our mouse model permits longitudinal PET imaging and quantification of T-cell homing during inflammation and cardiomyocyte viability after myocardial infarction. Moreover, Rosa26-mT/sr39tk mice are useful for whole-body characterization of transgenic Cre mice and to detect previously unknown Cre activity. We anticipate that the Cre-switchable PET reporter mice will be broadly applicable for non-invasive long-term tracking of selected cell populations in vivo.Non-invasive cell tracking is a powerful method to visualize cells in vivo under physiological and pathophysiological conditions. Here Thunemann et al. generate a mouse model for in vivo tracking and quantification of specific cell types by combining a PET reporter gene with Cre-dependent activation that can be exploited for any cell population for which a Cre mouse line is available.

11-Keto-ß-Boswellic Acid Inhibits Lymphocyte (CD3) Infiltration Into Pancreatic Islets of Young None Obese Diabetic (NOD) Mice.

11-Keto-ß-Boswellic acid (KBA) has been shown to prevent infiltration of lymphocytes into pancreatic islets and appearance of peri-insular apoptotic cells in an animal model of autoimmune diabetes caused by injection of Multiple Low Doses of Streptozotocin (MLD-STZ), which is a chemical compound belonging to the class of nitrososureas. The aim of this work was to study whether or not KBA can also prevent/attenuate infiltration of lymphocytes into pancreatic islets and appearance of peri-insular apoptotic cells in an animal model of autoimmune diabetes caused by genetic dysfunction resembling human type 1 diabetes in several important features. Four weeks old female NOD mice received daily i.p. injections of 7.5 mg/kg of KBA over a period of 3 weeks. Compared to 4 weeks old animals there was significant infiltration of lymphocytes (CD3) into pancreatic islets and appearance of peri-insular apoptotic cells in the period between 4 and 7 weeks. During this time plasma glucose dropped significantly and body weight did not increase. As far as pro-inflammatory cytokines are concerned, except a small increase of IFN-γ, there was no change in the blood. In mice that had been treated with KBA between 4 and 7 weeks after birth no significant infiltration of lymphocytes into pancreatic islets and appearance of peri-insular apoptotic cells was observed, when compared to 4 weeks old mice. Moreover, there was no drop of blood glucose and the animals gained body weight. It is concluded that - similar to the model of MLD-STZ-diabetes - also in the NOD mouse model KBA is able to attenuate or even prevent development of insulitis, suggesting that KBA protects islets from autoimmune reaction regardless whether the signal is provided by a chemical compound or by genetic dysfunction. Whether this also holds for human type 1 diabetes remains to be established.

Characterization of a novel murine model for spontaneous hemorrhagic stroke using in vivo PET and MR multiparametric imaging.

The clinical use of Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) has proven to be a strong diagnostic tool in the field of neurology. The reliability of these methods to confirm clinical diagnoses has guided preclinical research to utilize these techniques for the characterization of animal disease models. Previously, we demonstrated that an endothelial cell-specific ablation of the murine Serum Response Factor (SrfiECKO) results in blood brain barrier (BBB) breakdown and hemorrhagic stroke. Taking advantage of this mouse model we here perform a comprehensive longitudinal, multiparametric and in vivo imaging approach to reveal pathophysiological processes occurring before and during the appearance of cerebral microbleeds using combined PET and MRI. We complement our imaging results with data regarding animal behavior and immunohistochemistry. Our results demonstrate diffusion abnormalities in the cortical brain tissue prior to the onset of cerebral microbleeds. Diffusion reductions were accompanied by significant increments of [18F]FAZA uptake before the onset of the lesions in T2WI. The Open Field behavioral tests revealed reduced activity of SrfiECKO animals, whereas histology confirmed the presence of hemorrhages in cortical regions of the mouse brain and iron deposition at lesion sites with increased hypoxia inducible factor 1α, CD31 and glial fibrillary acidic protein expression. For the first time, we performed a thorough evaluation of the prodromal period before the occurrence of spontaneous cerebral microbleeds. Using in vivo PET and MRI, we show the pathological tissue changes that occur previous to gross blood brain barrier (BBB) disruption and breakage. In addition, our results show that apparent diffusion coefficient (ADC) reduction may be an early biomarker of BBB disruption proposing an alternate clinical interpretation. Furthermore, our findings remark the usefulness of this novel SrfiECKO mouse model to study underlying mechanisms of hemorrhagic stroke.

In Vivo Hypoxia PET Imaging Quantifies the Severity of Arthritic Joint Inflammation in Line with Overexpression of Hypoxia-Inducible Factor and Enhanced Reactive Oxygen Species Generation.

Hypoxia is essential for the development of autoimmune diseases such as rheumatoid arthritis (RA) and is associated with the expression of reactive oxygen species (ROS), because of the enhanced infiltration of immune cells. The aim of this study was to demonstrate the feasibility of measuring hypoxia noninvasively in vivo in arthritic ankles with PET/MRI using the hypoxia tracers 18F-fluoromisonidazole (18F-FMISO) and 18F-fluoroazomycinarabinoside (18F-FAZA). Additionally, we quantified the temporal dynamics of hypoxia and ROS stress using L-012, an ROS-sensitive chemiluminescence optical imaging probe, and analyzed the expression of hypoxia-inducible factors (HIFs). Methods: Mice underwent noninvasive in vivo PET/MRI to measure hypoxia or optical imaging to analyze ROS expression. Additionally, we performed ex vivo pimonidazole-/HIF-1α immunohistochemistry and HIF-1α/2α Western blot/messenger RNA analysis of inflamed and healthy ankles to confirm our in vivo results. Results: Mice diseased from experimental RA exhibited a 3-fold enhancement in hypoxia tracer uptake, even in the early disease stages, and a 45-fold elevation in ROS expression in inflamed ankles compared with the ankles of healthy controls. We further found strong correlations of our noninvasive in vivo hypoxia PET data with pimonidazole and expression of HIF-1α in arthritic ankles. The strongest hypoxia tracer uptake was observed as soon as day 3, whereas the most pronounced ROS stress was evident on day 6 after the onset of experimental RA, indicating that tissue hypoxia can precede ROS stress in RA. Conclusion: Collectively, for the first time to our knowledge, we have demonstrated that the noninvasive measurement of hypoxia in inflammation using 18F-FAZA and 18F-FMISO PET imaging represents a promising new tool for uncovering and monitoring rheumatic inflammation in vivo. Further, because hypoxic inflamed tissues are associated with the overexpression of HIFs, specific inhibition of HIFs might represent a new powerful treatment strategy.

A Novel Unsupervised Segmentation Approach Quantifies Tumor Tissue Populations Using Multiparametric MRI: First Results with Histological Validation.

PURPOSE: We aimed to precisely estimate intra-tumoral heterogeneity using spatially regularized spectral clustering (SRSC) on multiparametric MRI data and compare the efficacy of SRSC with the previously reported segmentation techniques in MRI studies. PROCEDURES: Six NMRI nu/nu mice bearing subcutaneous human glioblastoma U87 MG tumors were scanned using a dedicated small animal 7T magnetic resonance imaging (MRI) scanner. The data consisted of T2 weighted images, apparent diffusion coefficient maps, and pre- and post-contrast T2 and T2* maps. Following each scan, the tumors were excised into 2-3-mm thin slices parallel to the axial field of view and processed for histological staining. The MRI data were segmented using SRSC, K-means, fuzzy C-means, and Gaussian mixture modeling to estimate the fractional population of necrotic, peri-necrotic, and viable regions and validated with the fractional population obtained from histology. RESULTS: While the aforementioned methods overestimated peri-necrotic and underestimated viable fractions, SRSC accurately predicted the fractional population of all three tumor tissue types and exhibited strong correlations (rnecrotic = 0.92, rperi-necrotic = 0.82 and rviable = 0.98) with the histology. CONCLUSIONS: The precise identification of necrotic, peri-necrotic and viable areas using SRSC may greatly assist in cancer treatment planning and add a new dimension to MRI-guided tumor biopsy procedures.

Spectral Clustering Predicts Tumor Tissue Heterogeneity Using Dynamic 18F-FDG PET: A Complement to the Standard Compartmental Modeling Approach.

In this study, we described and validated an unsupervised segmentation algorithm for the assessment of tumor heterogeneity using dynamic 18F-FDG PET. The aim of our study was to objectively evaluate the proposed method and make comparisons with compartmental modeling parametric maps and SUV segmentations using simulations of clinically relevant tumor tissue types. Methods: An irreversible 2-tissue-compartmental model was implemented to simulate clinical and preclinical 18F-FDG PET time-activity curves using population-based arterial input functions (80 clinical and 12 preclinical) and the kinetic parameter values of 3 tumor tissue types. The simulated time-activity curves were corrupted with different levels of noise and used to calculate the tissue-type misclassification errors of spectral clustering (SC), parametric maps, and SUV segmentation. The utility of the inverse noise variance- and Laplacian score-derived frame weighting schemes before SC was also investigated. Finally, the SC scheme with the best results was tested on a dynamic 18F-FDG measurement of a mouse bearing subcutaneous colon cancer and validated using histology. Results: In the preclinical setup, the inverse noise variance-weighted SC exhibited the lowest misclassification errors (8.09%-28.53%) at all noise levels in contrast to the Laplacian score-weighted SC (16.12%-31.23%), unweighted SC (25.73%-40.03%), parametric maps (28.02%-61.45%), and SUV (45.49%-45.63%) segmentation. The classification efficacy of both weighted SC schemes in the clinical case was comparable to the unweighted SC. When applied to the dynamic 18F-FDG measurement of colon cancer, the proposed algorithm accurately identified densely vascularized regions from the rest of the tumor. In addition, the segmented regions and clusterwise average time-activity curves showed excellent correlation with the tumor histology. Conclusion: The promising results of SC mark its position as a robust tool for quantification of tumor heterogeneity using dynamic PET studies. Because SC tumor segmentation is based on the intrinsic structure of the underlying data, it can be easily applied to other cancer types as well.

The Positron Emission Tomography Tracer 3'-Deoxy-3'-[18F]Fluorothymidine ([18F]FLT) Is Not Suitable to Detect Tissue Proliferation Induced by Systemic Yersinia enterocolitica Infection in Mice.

Most frequently, gram-negative bacterial infections in humans are caused by Enterobacteriaceae and remain a major challenge in medical diagnostics. We non-invasively imaged moderate and severe systemic Yersinia enterocolitica infections in mice using the positron emission tomography (PET) tracer 3'-deoxy-3'-[18F]fluorothymidine ([18F]FLT), which is a marker of proliferation, and compared the in vivo results to the ex vivo biodistributions, bacterial loads, and histologies of the corresponding organs. Y. enterocolitica infection is detectable with histology using H&E staining and immunohistochemistry for Ki 67. [18F]FLT revealed only background uptake in the spleen, which is the main manifestation site of systemic Y. enterocolitica-infected mice. The uptake was independent of the infection dose. Antibody-based thymidine kinase 1 (Tk-1) staining confirmed the negative [18F]FLT-PET data. Histological alterations of spleen tissue, observed via Ki 67-antibody-based staining, can not be detected by [18F]FLT-PET in this model. Thus, the proliferation marker [18F]FLT is not a suitable tracer for the diagnosis of systemic Y. enterocolitica infection in the C57BL/6 animal model of yersiniosis.