The Accuracy and Clinical Relevance of the Multi-echo Dixon Technique for Evaluating Changes to Hepatic Steatosis in Patients with Non-alcoholic Fatty Liver Disease Treated with Formulated Food

Association of changes in the type 2 diabetes and MASLD/related SLD status with risk of developing cardiovascular disease

BACKGROUND & AIMS

This study assessed the association of remission of type 2 diabetes mellitus (DM) or metabolic dysfunction-associated steatotic liver disease (MASLD)/related SLD (r-SLD; MASLD with excessive alcohol intake) as defined by the fatty liver index with the risk of cardiovascular disease (CVD).

METHODS

Health examination data at baseline and after 2 years (2-Years) were extracted from a nationwide claims database in Japan. Among participants aged 18-72 years with at least 3 years of follow-up, 9345 participants with DM-associated MASLD/r-SLD and 71 932 participants with non-DM MASLD/r-SLD at baseline were included in the study. The participants were stratified by the achievement of remission of MASLD/r-SLD or DM at 2-Years. In each group after stratification, the risk of new-onset CVD during the observation period was analysed using multivariate Cox proportional hazards models.

RESULTS

During a median follow-up of 4.9 years (starting from 2-Years), 1368 cases of CVD were observed. The hazard ratio (95% confidence interval) for CVD was 0.50 (0.31-0.80) for participants with remission of DM, 0.65 (0.47-0.91) for participants with remission of MASLD/r-SLD, and 0.34 (0.15-0.77) for participants with remission of both DM and MASLD/r-SLD. Conversely, remission of MASLD/r-SLD was not linked to a reduced risk of CVD in participants with non-DM MASLD/r-SLD.

CONCLUSION

The association of MASLD/r-SLD remission with CVD risk differs greatly in the presence and absence of DM. In patients with DM-MASLD/r-SLD, MASLD/r-SLD remission can significantly reduce CVD risk similarly as remission of DM.

Fat fraction quantification with MRI estimates tumor proliferation of hepatocellular carcinoma

Purpose

To assess the utility of fat fraction quantification using quantitative multi-echo Dixon for evaluating tumor proliferation and microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Methods

A total of 66 patients with resection and histopathologic confirmed HCC were enrolled. Preoperative MRI with proton density fat fraction and R2* mapping was analyzed. Intratumoral and peritumoral regions were delineated with manually placed regions of interest at the maximum level of intratumoral fat. Correlation analysis explored the relationship between fat fraction and Ki67. The fat fraction and R2* were compared between high Ki67(>30%) and low Ki67 nodules, and between MVI negative and positive groups. Receiver operating characteristic (ROC) analysis was used for further analysis if statistically different.

Results

The median fat fraction of tumor (tFF) was higher than peritumor liver (5.24% vs 3.51%, P=0.012). The tFF was negatively correlated with Ki67 (r=-0.306, P=0.012), and tFF of high Ki67 nodules was lower than that of low Ki67 nodules (2.10% vs 4.90%, P=0.001). The tFF was a good estimator for low proliferation nodules (AUC 0.747, cut-off 3.39%, sensitivity 0.778, specificity 0.692). There was no significant difference in tFF and R2* between MVI positive and negative nodules (3.00% vs 2.90%, P=0.784; 55.80s-1 vs 49.15s-1, P=0.227).

Conclusion

We infer that intratumor fat can be identified in HCC and fat fraction quantification using quantitative multi-echo Dixon can distinguish low proliferative HCCs.

Accelerated four-dimensional free-breathing whole-liver water-fat magnetic resonance imaging with deep dictionary learning and chemical shift modeling

Background

Multi-echo chemical-shift-encoded magnetic resonance imaging (MRI) has been widely used for fat quantification and fat suppression in clinical liver examinations. Clinical liver water-fat imaging typically requires breath-hold acquisitions, with the free-breathing acquisition method being more desirable for patient comfort. However, the acquisition for free-breathing imaging could take up to several minutes. The purpose of this study is to accelerate four-dimensional free-breathing whole-liver water-fat MRI by jointly using high-dimensional deep dictionary learning and model-guided (MG) reconstruction.

Methods

A high-dimensional model-guided deep dictionary learning (HMDDL) algorithm is proposed for the acceleration. The HMDDL combines the powers of the high-dimensional dictionary learning neural network (hdDLNN) and the chemical shift model. The neural network utilizes the prior information of the dynamic multi-echo data in spatial respiratory motion, and echo dimensions to exploit the features of images. The chemical shift model is used to guide the reconstruction of field maps, R 2 ∗ maps, water images, and fat images. Data acquired from ten healthy subjects and ten subjects with clinically diagnosed nonalcoholic fatty liver disease (NAFLD) were selected for training. Data acquired from one healthy subject and two NAFLD subjects were selected for validation. Data acquired from five healthy subjects and five NAFLD subjects were selected for testing. A three-dimensional (3D) blipped golden-angle stack-of-stars multi-gradient-echo pulse sequence was designed to accelerate the data acquisition. The retrospectively undersampled data were used for training, and the prospectively undersampled data were used for testing. The performance of the HMDDL was evaluated in comparison with the compressed sensing-based water-fat separation (CS-WF) algorithm and a parallel non-Cartesian recurrent neural network (PNCRNN) algorithm.

Results

Four-dimensional water-fat images with ten motion states for whole-liver are demonstrated at several R values. In comparison with the CS-WF and PNCRNN, the HMDDL improved the mean peak signal-to-noise ratio (PSNR) of images by 9.93 and 2.20 dB, respectively, and improved the mean structure similarity (SSIM) of images by 0.058 and 0.009, respectively, at R=10. The paired t-test shows that there was no significant difference between HMDDL and ground truth for proton-density fat fraction (PDFF) and R 2 ∗ values at R up to 10.

Conclusions

The proposed HMDDL enables features of water images and fat images from the highly undersampled multi-echo data along spatial, respiratory motion, and echo dimensions, to improve the performance of accelerated four-dimensional (4D) free-breathing water-fat imaging.

Outcomes of Various Classes of Oral Antidiabetic Drugs on Nonalcoholic Fatty Liver Disease

Importance

Several oral antidiabetic drug (OAD) classes can potentially improve patient outcomes in nonalcoholic fatty liver disease (NAFLD) to varying degrees, but clinical data on which class is favored are lacking.

Objective

To investigate which OAD is associated with the best patient outcomes in NAFLD and type 2 diabetes (T2D).

Design, Setting, and Participants

This retrospective nonrandomized interventional cohort study used the National Health Information Database, which provided population-level data for Korea. This study involved patients with T2D and concomitant NAFLD.

Exposures

Receiving either sodium-glucose cotransporter 2 (SGLT2) inhibitors, thiazolidinediones, dipeptidyl peptidase-4 (DPP-4) inhibitors, or sulfonylureas, each combined with metformin for 80% or more of 90 consecutive days.

Main Outcomes and Measures

The main outcomes were NAFLD regression assessed by the fatty liver index and composite liver-related outcome (defined as liver-related hospitalization, liver-related mortality, liver transplant, and hepatocellular carcinoma) using the Fine-Gray model regarding competing risks.

Results

In total, 80 178 patients (mean [SD] age, 58.5 [11.9] years; 43 007 [53.6%] male) were followed up for 219 941 person-years, with 4102 patients experiencing NAFLD regression. When compared with sulfonylureas, SGLT2 inhibitors (adjusted subdistribution hazard ratio [ASHR], 1.99 [95% CI, 1.75-2.27]), thiazolidinediones (ASHR, 1.70 [95% CI, 1.41-2.05]), and DPP-4 inhibitors (ASHR, 1.45 [95% CI, 1.31-1.59]) were associated with NAFLD regression. SGLT2 inhibitors were associated with a higher likelihood of NAFLD regression when compared with thiazolidinediones (ASHR, 1.40 [95% CI, 1.12-1.75]) and DPP-4 inhibitors (ASHR, 1.45 [95% CI, 1.30-1.62]). Only SGLT2 inhibitors (ASHR, 0.37 [95% CI, 0.17-0.82]), not thiazolidinediones or DPP-4 inhibitors, were significantly associated with lower incidence rates of adverse liver-related outcomes when compared with sulfonylureas.

Conclusions and Relevance

The results of this cohort study suggest that physicians may lean towards prescribing SGLT2 inhibitors as the preferred OAD for individuals with NAFLD and T2D, considering their potential benefits in NAFLD regression and lower incidences of adverse liver-related outcomes. This observational study should prompt future research to determine whether prescribing practices might merit reexamination.

Systemic immune-inflammatory biomarkers (SII, NLR, PLR and LMR) linked to non-alcoholic fatty liver disease risk

Background

Systemic immune-inflammatory biomarkers including systemic immune inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) have been demonstrated to be associated with the risk and severity of various liver diseases. However, studies on their role and clinical significance in metabolic diseases, especially in nonalcoholic fatty liver disease (NAFLD), are limited and results are inconsistent.

Methods

10821 adults aged 20 years or older were enrolled in this cross-sectional study, sourced from six cycles of the National Health and Nutrition Examination Survey (NHANES). Survey-weighted logistic regression was employed to investigate the correlation between systemic immune-inflammatory biomarkers (SII, NLR, PLR, and LMR) and NAFLD risk. Restricted cubic spline regression models and segmented regression models were used to describe nonlinear relationships and threshold effects. Subgroup and sensitivity analyses were also conducted.

Results

After adjusting for all confounding variables, there was a significant positive association observed between ln-transformed SII (OR= 1.46, 95% CI: 1.27-1.69, P <0.001), NLR (OR= 1.25, 95% CI: 1.05-1.49, P =0.015), LMR (OR= 1.39, 95% CI: 1.14-1.69, P = 0.002) with NAFLD. A nonlinear dose-response relationship with an inverted "U"-shaped threshold of 4.64 was observed between ln(PLR) and NAFLD risk. When ln(PLR) was below 4.64, each unit increase in ln(PLR) was associated with a 0.55-fold increase in the risk of NAFLD (OR= 1.55, 95% CI: 1.05-2.31, P <0.05). Conversely, when ln(PLR) exceeded 4.64, each unit increase in ln(PLR) was associated with a 0.40-fold decrease in the risk of NAFLD (OR= 0.60, 95% CI. 0.44-0.81, P <0.05).

Conclusion

ln-transformed SII, NLR, and LMR were linearly associated with NAFLD risk. ln(PLR) showed an inverted "U"-shaped nonlinear dose-response relationship with the risk of NAFLD.