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Non-alcoholic steatohepatitis (NASH) is characterized from its early stages by a profound remodeling of the liver microenvironment, encompassing changes in the composition and activities of multiple cell types and associated gene expression patterns. Hyperpolarized (HP) 13 C MRI provides a unique view of the metabolic microenvironment, with potential relevance for early diagnosis of liver disease. Previous studies have detected changes in HP 13 C pyruvate to lactate conversion, catalyzed by lactate dehydrogenase (LDH), with experimental liver injury. HP ∝ -ketobutyrate ( ∝ KB) is a close molecular analog of pyruvate with modified specificity for LDH isoforms, specifically attenuated activity with their LDHA-expressed subunits that dominate liver parenchyma. Building on recent results with pyruvate, we investigated HP ∝ KB in methionine-choline deficient (MCD) diet as a model of early-stage NASH. Similarity of results between this new agent and pyruvate (~ 50% drop in cytoplasmic reducing capacity), interpreted together with gene expression data from the model, suggests that changes are mediated through broad effects on intermediary metabolism. Plausible mechanisms are depletion of the lactate pool by upregulation of gluconeogenesis (GNG) and pentose phosphate pathway (PPP) flux, and a possible shift toward increased lactate oxidation. These changes may reflect high levels of oxidative stress and/or shifting macrophage populations in NASH., (© 2024. The Author(s).)

The aim of this study was to use texture analysis to establish quantitative CT-based imaging features to predict clinical severity in patients with acute alcohol-associated hepatitis (AAH). A secondary aim was to compare the performance of texture analysis to deep learning. In this study, mathematical texture features were extracted from CT slices of the liver for 34 patients with a diagnosis of AAH and 35 control patients. Recursive feature elimination using random forest (RFE-RF) was used to identify the best combination of features to distinguish AAH from controls. These features were subsequently used as predictors to determine associated clinical values. To compare machine learning with deep learning approaches, a 2D dense convolutional neural network (CNN) was implemented and trained for the classification task of AAH. RFE-RF identified 23 top features used to classify AAH images, and the subsequent model demonstrated an accuracy of 82.4% in the test set. The deep learning CNN demonstrated an accuracy of 70% in the test set. We show that texture features of the liver are unique in AAH and are candidate quantitative biomarkers that can be used in prospective studies to predict the severity and outcomes of patients with AAH.

The type 2 diabetic phenotype results from mixed effects of insulin deficiency and insulin resistance, but the relative contributions of these two distinct factors remain poorly characterized, as do the respective roles of the gluconeogenic organs. The purpose of this study was to investigate localized in vivo metabolic changes in liver and kidneys of contrasting models of diabetes mellitus (DM): streptozotocin (STZ)-treated wild-type Zucker rats (T1DM) and Zucker diabetic fatty (ZDF) rats (T2DM). Intermediary metabolism was probed using hyperpolarized (HP) [1- 13 C]pyruvate MRI of the liver and kidneys. These data were correlated with gene expression data for key mediators, assessed using rtPCR. Increased HP [1- 13 C]lactate was detected in both models, in association with elevated gluconeogenesis as reflected by increased expression of phosphoenolpyruvate carboxykinase. In contrast, HP [1- 13 C]alanine diverged between the two models, increasing in ZDF rats, while decreasing in the STZ-treated rats. The differences in liver alanine paralleled differences in key lipogenic mediators. Thus, HP [1- 13 C]alanine is a marker that can identify phenotypic differences in kidneys and liver of rats with T1DM vs. T2DM, non-invasively in vivo. This approach could provide a powerful diagnostic tool for characterizing tissue metabolic defects and responses to treatment in diabetic patients with ambiguous systemic manifestations.

Occult bacterial infections represent a worldwide health problem. Differentiating active bacterial infection from sterile inflammation can be difficult using current imaging tools. Present clinically viable methodologies either detect morphologic changes (CT/ MR), recruitment of immune cells ( 111 In-WBC SPECT), or enhanced glycolytic flux seen in inflammatory cells ( 18 F-FDG PET). However, these strategies are often inadequate to detect bacterial infection and are not specific for living bacteria. Recent approaches have taken advantage of key metabolic differences between prokaryotic and eukaryotic organisms, allowing easier distinction between bacteria and their host. In this report, we exploited one key difference, bacterial cell wall biosynthesis, to detect living bacteria using a positron-labeled D-amino acid. After screening several 14 C D-amino acids for their incorporation into E. coli in culture, we identified D-methionine as a probe with outstanding radiopharmaceutical potential. Based on an analogous procedure to that used for L-[methyl- 11 C]methionine ([ 11 C] L-Met), we developed an enhanced asymmetric synthesis of D-[methyl- 11 C]methionine ([ 11 C] D-Met), and showed that it can rapidly and selectively differentiate both E. coli and S. aureus infections from sterile inflammation in vivo. We believe that the ease of [ 11 C] D-Met radiosynthesis, coupled with its rapid and specific in vivo bacterial accumulation, make it an attractive radiotracer for infection imaging in clinical practice.

Nonalcoholic fatty liver disease (NAFLD) has become highly prevalent, now considered the most common liver disease in the western world. Approximately one-third of patients with NASH develop non-alchoholic steatohepatitis (NASH), histologically defined by lobular and portal inflammation, and accompanied by marked oxidative stress. Patients with NASH are at increased risk for cirrhosis and hepatocellular carcinoma, and diagnosis currently requires invasive biopsy. In animal models of NASH, particularly the methionine-choline deficient (MCD) model, profound changes are seen in redox enzymes and key intracellular antioxidants. To study antioxidant status in NASH non-invasively, we applied the redox probe hyperpolarized [1- 13 C] dehydroascorbic acid (HP DHA), which is reduced to Vitamin C (VitC) rapidly in the normal liver. In MCD mice, we observed a significant decrease in HP DHA to VitC conversion that accompanied hepatic fat deposition. When these animals were subsequently placed on a normal diet, resonance ratios reverted to those seen in control mice. These findings suggest that HP DHA, a potentially clinically translatable imaging agent, holds special promise in imaging NASH and other metabolic syndromes, to monitor disease progression and response to targeted therapies.