In vivo 1 H MRS of human gallbladder bile in understanding the pathophysiology of primary sclerosing cholangitis (PSC): Immune-mediated disease versus bile acid-induced injury.

Primary sclerosing cholangitis (PSC) has been considered to be either an "autoimmune disease" or a "bile acid-induced injury." In vitro MRS studies on PSC patients have limitations due to the contamination of bile with contrast agent (commonly administered during endoscopic retrograde cholangiopancreatography) and/or the use of patient cohorts with other diseases as controls. The objective of this study was to quantify biliary metabolites using in vivo 1 H MRS and gain insight into the pathogenesis of PSC. Biliary metabolites in 10 PSC patients and 14 healthy controls were quantified in vivo using 1 H MRS on a 3 T MR scanner. The concentrations of total bile acids plus cholesterol, glycine-conjugated bile acids, taurine-conjugated bile acids, and choline-containing phospholipids (chol-PLs) were compared between the two groups. There were statistically significant decreases in the levels of the above mentioned biliary metabolites in the PSC patients compared with controls. The reduction in bile acid secretion in bile of PSC patients indicates accumulation of bile acids in hepatocytes. Moreover, reduction in the levels of chol-PLs in bile may increase the toxic effects of bile acids. Our findings suggest that the bile duct injury in PSC patients is most likely due to "bile acid-induced injury."

Pro-inflammatory cytokines are raised in extrahepatic portal venous obstruction, with minimal hepatic encephalopathy.

BACKGROUND AND AIMS: Minimal hepatic encephalopathy (MHE) and hyperammonemia are seen in patients with extrahepatic portal venous obstruction (EHPVO). Inflammation has been shown to play an important role in the pathogenesis of hepatic encephalopathy in cirrhotics. This study assessed serum pro-inflammatory cytokines and their correlation with hyperammonemia, (1)H-magnetic resonance (MR) spectroscopy-derived brain glutamine, and diffusion tensor imaging (DTI)-derived metrics in patients with EPHVO, with and without MHE. METHODS: Neuropsychological tests, DTI, (1)H-MR spectroscopy, and estimation of blood ammonia and pro-inflammatory cytokines (tumor necrosis factor-α[TNF-α] and interleukin-6 [IL-6]) were done in 20 patients with EHPVO and eight healthy controls. RESULTS: Pro-inflammatory cytokines (TNF-α and IL-6), blood ammonia, brain glutamine, and mean diffusivity were increased in both patient groups, as compared to controls. Patients with MHE (n-12) had significantly higher TNF-α, IL-6, blood ammonia, brain glutamine, and mean diffusivity, signifying brain edema, than controls. A significant, positive correlation was seen between TNF-α and IL-6 and between blood ammonia and TNF-α, IL-6, and brain glutamine. Significant, positive correlations of TNF-α, IL-6, and blood ammonia with mean diffusivity values were seen in various brain regions, including spectroscopy voxel-derived mean diffusivity. CONCLUSION: Patients with extrahepatic portal vein obstruction have inflammation and hyperammonemia made evident by higher blood TNF-α, IL-6, ammonia, and brain glutamine levels. A significant correlation between hyperammonemia, pro-inflammatory cytokines, and cerebral edema on DTI in various brain regions suggests that both these factors play a role in the pathogenesis of MHE in these patients.

Deep learning can accelerate and quantify simulated localized correlated spectroscopy.

Nuclear magnetic resonance spectroscopy (MRS) allows for the determination of atomic structures and concentrations of different chemicals in a biochemical sample of interest. MRS is used in vivo clinically to aid in the diagnosis of several pathologies that affect metabolic pathways in the body. Typically, this experiment produces a one dimensional (1D) 1H spectrum containing several peaks that are well associated with biochemicals, or metabolites. However, since many of these peaks overlap, distinguishing chemicals with similar atomic structures becomes much more challenging. One technique capable of overcoming this issue is the localized correlated spectroscopy (L-COSY) experiment, which acquires a second spectral dimension and spreads overlapping signal across this second dimension. Unfortunately, the acquisition of a two dimensional (2D) spectroscopy experiment is extremely time consuming. Furthermore, quantitation of a 2D spectrum is more complex. Recently, artificial intelligence has emerged in the field of medicine as a powerful force capable of diagnosing disease, aiding in treatment, and even predicting treatment outcome. In this study, we utilize deep learning to: (1) accelerate the L-COSY experiment and (2) quantify L-COSY spectra. All training and testing samples were produced using simulated metabolite spectra for chemicals found in the human body. We demonstrate that our deep learning model greatly outperforms compressed sensing based reconstruction of L-COSY spectra at higher acceleration factors. Specifically, at four-fold acceleration, our method has less than 5% normalized mean squared error, whereas compressed sensing yields 20% normalized mean squared error. We also show that at low SNR (25% noise compared to maximum signal), our deep learning model has less than 8% normalized mean squared error for quantitation of L-COSY spectra. These pilot simulation results appear promising and may help improve the efficiency and accuracy of L-COSY experiments in the future.

Serum proinflammatory cytokines correlate with diffusion tensor imaging derived metrics and 1H-MR spectroscopy in patients with acute liver failure.

Hyperammonemia and inflammation are major contributing factors in the development of cerebral edema (CE) in acute liver failure (ALF). Aim of this study was to look for the relationship between proinflammatory cytokines with diffusion tensor imaging (DTI) derived metrics and (1)H-MR spectroscopy ((1)H-MRS) derived Glutamate/Glutamine (Glx). Fourteen patients with ALF and 14 age/sex matched controls were included in this study. All subjects had undergone clinical, biochemical, MR imaging and (1)H-MRS studies. Serum proinflammatory cytokines (IL-6 and TNF-α), blood ammonia level and Glx were computed for independent t-test and Pearson correlation. Serum proinflammatory cytokines, blood ammonia level and brain Glx were significantly increased in ALF patients as compared to controls. Blood ammonia level and Glx showed significant positive correlation with proinflammatory cytokines. Spectroscopy voxel derived spherical anisotropy (CS) showed positive correlation with Glx while mean diffusivity (MD) showed negative correlation. Proinflammatory cytokines showed positive correlation with CS and negative correlation with MD in various brain regions including spectroscopy voxel. Significant correlation of Glx, CS and MD with proinflammatory cytokines suggests that both DTI derived metrics and (1)H-MRS measure the synergistic effect of hyperammonemia and proinflammatory cytokines and may be used as non-invasive tools for understanding the pathogenesis of CE in ALF.

Noninvasive assessment of abdominal adipose tissues and quantification of hepatic and pancreatic fat fractions in type 2 diabetes mellitus.

The purpose of this study was to evaluate adipose tissue distributions and hepatic and pancreatic fat contents using a 6-point Dixon MRI technique in type 2 diabetes mellitus (T2DM), and to assess associations between fat distributions and biochemical markers of insulin resistance. Intra-abdominal MRI was investigated in 14 T2DM patients, 13 age- and sex-matched healthy controls (HC) and 11 young HC using a 3 T Prisma MRI scanner. All T2DM subjects completed a fasting comprehensive metabolic panel, and demographic measurements were taken according to standardized methodologies. We observed excellent correlation (R2 = 0.94) between hepatic fat fraction quantified using 6-point Dixon MRI and gold standard MRS, establishing the accuracy and reliability of the Dixon technique. Significantly increased visceral adipose tissue (VAT) volumes were found in T2DM patients compared to age-matched HC (1569.81 ± 670.62 cm3 vs. 1106.60 ± 566.85 cm3, p = .04). We also observed a trend of increasing subcutaneous adipose tissues (SAT), and total abdominal fat (TAT) volumes in T2DM compared to age-matched HC. Hepatic fat fraction percentage (HFF%) was 44.6% higher in T2DM compared to age-matched HC and 64.4% higher compared to young HC. Pancreatic fat fractions in the head and body/tail were higher in T2DM patients compared to both healthy cohorts. We also observed correlations between fat contents of the liver and pancreas in T2DM patients, and association between biochemical markers of T2DM with HFF, indicating a risk for non-alcoholic fatty liver disease among T2DM. In summary, this study provides evidence of T2DM patients having increased liver and pancreatic fat, as well as increased adipose tissues.

Metabolite-cycled density-weighted concentric rings k-space trajectory (DW-CRT) enables high-resolution 1 H magnetic resonance spectroscopic imaging at 3-Tesla.

Magnetic resonance spectroscopic imaging (MRSI) is a promising technique in both experimental and clinical settings. However, to date, MRSI has been hampered by prohibitively long acquisition times and artifacts caused by subject motion and hardware-related frequency drift. In the present study, we demonstrate that density weighted concentric ring trajectory (DW-CRT) k-space sampling in combination with semi-LASER excitation and metabolite-cycling enables high-resolution MRSI data to be rapidly acquired at 3 Tesla. Single-slice full-intensity MRSI data (short echo time (TE) semi-LASER TE = 32 ms) were acquired from 6 healthy volunteers with an in-plane resolution of 5 × 5 mm in 13 min 30 sec using this approach. Using LCModel analysis, we found that the acquired spectra allowed for the mapping of total N-acetylaspartate (median Cramer-Rao Lower Bound [CRLB] = 3%), glutamate+glutamine (8%), and glutathione (13%). In addition, we demonstrate potential clinical utility of this technique by optimizing the TE to detect 2-hydroxyglutarate (long TE semi-LASER, TE = 110 ms), to produce relevant high-resolution metabolite maps of grade III IDH-mutant oligodendroglioma in a single patient. This study demonstrates the potential utility of MRSI in the clinical setting at 3 Tesla.