Liver fat accumulation measured by high-speed T2-corrected multi-echo magnetic resonance spectroscopy can predict risk of cholelithiasis

High-Speed T2 -Corrected Multiecho Magnetic Resonance Spectroscopy for Quantitatively Detecting Skeletal Muscle Fatty Infiltration and Predicting the Loss of Ambulation in Patients With Duchenne Muscular Dystrophy

BACKGROUND

High-speed T2 -corrected multiecho MRS (HISTO-MRS) is emerging as a quantitative modality for detecting muscle fat infiltration (MFF). However, the predictive value of HISTO-MRS for the loss of ambulation (LoA) in Duchenne muscular dystrophy (DMD) is unknown.

PURPOSE

To determine the feasibility of HISTO-MRS for assessing MFF in DMD and further identify the predictive value of HISTO-MRS for the LoA.

STUDY TYPE

Prospective.

SUBJECTS

A total of 134 DMD boys (9.20 ± 2.43 years old) and 21 healthy boys (9.25 ± 2.10 years old).

FIELD STRENGTH/SEQUENCE

A 3 T, fast spin echo T1 -weighted imaging (T1 WI), two-point-Dixon gradient echo sequence (2-pt-Dixon) and HISTO-MRS.

ASSESSMENT

Subjective T1 WI fat grades by three radiologists, ROI analysis for MFF on 2 pt-Dixon (Dixon MFF) and MFF on HISTO-MRS (HISTO MFF) by two radiologists. Clinical motor function: North Star Ambulatory Assessment, 10-m run/walk time, Gowers maneuver, and time to four-stairs climb and descend.

STATISTICAL TESTS

Spearman rank correlation was used to assess the relation of fat filtration assessments and motor ability. Bland-Altman plots was performed to determine the agreement of HISTO MFF and Dixon MFF. Receiver operating characteristic (ROC) curves were analyzed to determine the discriminating ability of above MRI modalities for ambulatory and nonambulatory DMD. Logistic regression was used to identify the predictor of LoA. Variables with P < 0.05 in univariate logistic regression analysis were entered into the multivariate logistic regression model.

RESULTS

HISTO MFF was significantly correlated with Dixon MFF. Bland-Altman plots show good agreement of HISTO MFF and Dixon MFF. ROC curves indicated that HISTO MFF show similar discrimination of LoA for DMD with Dixon MFF but better value than T1WI fat grades. Logistic regression showed that HISTO MFF was an independent predictor for LoA.

DATA CONCLUSION

HISTO-MRS is a potential quantitative method for assessing fat infiltration and shows predictive value for LoA in DMD patients.

LEVEL OF EVIDENCE: 1

TECHNICAL EFFICACY

Stage 5.

Relationship of Iron Intake, Ferritin, and Hepcidin with the Transverse Relaxation Rate of Water Protons in the Pancreas

(1) Background: There is a paucity of markers of iron metabolism in health and disease. The aim was to investigate the associations of iron metabolism with pancreas transverse water proton relaxation rate (R2water) in healthy individuals and people after an attack of pancreatitis. (2) Methods: All participants underwent a 3.0 T magnetic resonance imaging of the abdomen on the same scanner. High-speed T2-corrected multi-echo (HISTO) acquisition at single-voxel magnetic resonance spectroscopy and inline processing were used to quantify pancreas R2water. Habitual dietary intake of iron was determined using the EPIC-Norfolk food frequency questionnaire. Circulating levels of ferritin and hepcidin were measured. Generalised additive models were used, adjusting for age, sex, body mass index, and haemoglobin A1c. (3) Results: A total of 139 individuals (47 healthy individuals, 54 individuals after acute pancreatitis, and 38 individuals after chronic pancreatitis) were included. Total dietary intake of iron was significantly associated with pancreas R2water, consistently in healthy individuals (p < 0.001), individuals after acute pancreatitis (p < 0.001), and individuals after chronic pancreatitis (p < 0.001) across all the statistical models. Ferritin was significantly associated with pancreas R2water, consistently in healthy individuals (p < 0.001), individuals after acute pancreatitis (p < 0.001), and individuals after chronic pancreatitis (p = 0.01) across all adjusted models. Hepcidin was significantly associated with pancreas R2water in individuals after acute pancreatitis (p < 0.001) and individuals after chronic pancreatitis (p = 0.04) in the most adjusted model. (4) Conclusions: Pancreas R2water, corrected for T2, is related to iron metabolism in both health and pancreatitis. This non-invasive marker could be used for automated in vivo identification of intra-pancreatic iron deposition.

Non-invasive evaluation of NAFLD and the contribution of genes: an MRI-PDFF-based cross-sectional study

OBJECTIVE

To investigate the clinical, laboratory and genetic features of NAFLD patients based on MRI-PDFF in China.

DESIGN

Patients with high ALT and with a diagnosis of fatty liver were included in this cross-sectional study. Fasting blood was collected to test biomarkers and SNPs. A total of 266 patients underwent MRI-PDFF and FibroScan examinations, and 38 underwent liver biopsy. Diagnostic models (decision tree, LASSO, and elastic net) were developed based on the diagnosis from MRI-PDFF reports.

RESULTS

Approximately, 1/3 of the patients were found to have NASH and fibrosis. After quantifying liver steatosis by MRI-PDFF (healthy: n = 47; mild NAFLD: n = 136; moderate/severe NAFLD: n = 83; liver fat content (LFC): 3.6% vs. 8.7% vs. 19.0%), most biomarkers showed significant differences among the three groups, and patients without obesity were found to have a similar LFC as those with obesity (11.1% vs. 12.3%). Models including biomarkers showed strong diagnostic ability (accuracy: 0.80-0.91). Variant alleles of PNPLA3, HSD17B13 and MBOAT7 were identified as genetic risk factors causing higher LFC (8.7% vs. 12.3%; 11.0% vs. 14.5%; 8.5% vs. 10.2%, p < 0.05); those with the UQCC1 rs878639 variant allele showed lower LFC (10.4% vs. 8.4%; OR = 0.58, p < 0.05). Patients with more risk alleles had higher LFCs (8.1% vs. 10.7% vs. 11.6% vs. 14.5%).

CONCLUSIONS

Based on MRI-PDFF, a combination of several specific biomarkers can accurately predict disease status. When the effects of genes on liver steatosis were first quantified by MRI-PDFF, the UQCC1 rs878639 G allele was identified as a protective factor, and the MBOAT7 T allele was identified as a risk only among nonobese individuals.