Association of Dietary Patterns with MRI Markers of Hepatic Inflammation and Fibrosis in the MAST4HEALTH Study

Whereas the etiology of non-alcoholic fatty liver disease (NAFLD) is complex, the role of nutrition as a causing and preventive factor is not fully explored. The aim of this study is to associate dietary patterns with magnetic resonance imaging (MRI) parameters in a European population (Greece, Italy, and Serbia) affected by NAFLD. For the first time, iron-corrected T1 (cT1), proton density fat fraction (PDFF), and the liver inflammation fibrosis score (LIF) were examined in relation to diet. A total of 97 obese patients with NAFLD from the MAST4HEALTH study were included in the analysis. A validated semi-quantitative food frequency questionnaire (FFQ) was used to assess the quality of diet and food combinations. Other variables investigated include anthropometric measurements, total type 2 diabetes risk, physical activity level (PAL), and smoking status. Principal component analysis (PCA) was performed to identify dietary patterns. Six dietary patterns were identified, namely “High-Sugar”, “Prudent”, “Western”, “High-Fat and Salt”, “Plant-Based”, and “Low-Fat Dairy and Poultry”. The “Western” pattern was positively associated with cT1 in the unadjusted model (beta: 0.020, p-value: 0.025) and even after adjusting for age, sex, body mass index (BMI), PAL, smoking, the center of the study, and the other five dietary patterns (beta: 0.024, p-value: 0.020). On the contrary, compared with low-intake patients, those with medium intake of the “Low-Fat Dairy and Poultry” pattern were associated with lower values of cT1, PDFF, and LIF. However, patients with a “Low-Fat Dairy and Poultry” dietary pattern were negatively associated with MRI parameters (cT1: beta: −0.052, p-value: 0.046, PDFF: beta: −0.448, p-value: 0.030, LIF: beta: −0.408, p-value: 0.025). Our findings indicate several associations between MRI parameters and dietary patterns in NAFLD patients, highlighting the importance of diet in NAFLD.

Error quantification in multi-parameter mapping facilitates robust estimation and enhanced group level sensitivity

Multi-Parameter Mapping (MPM) is a comprehensive quantitative neuroimaging protocol that enables estimation of four physical parameters (longitudinal and effective transverse relaxation rates R1 and R2*, proton density PD, and magnetization transfer saturation MTsat) that are sensitive to microstructural tissue properties such as iron and myelin content. Their capability to reveal microstructural brain differences, however, is tightly bound to controlling random noise and artefacts (e.g. caused by head motion) in the signal. Here, we introduced a method to estimate the local error of PD, R1, and MTsat maps that captures both noise and artefacts on a routine basis without requiring additional data. To investigate the method's sensitivity to random noise, we calculated the model-based signal-to-noise ratio (mSNR) and showed in measurements and simulations that it correlated linearly with an experimental raw-image-based SNR map. We found that the mSNR varied with MPM protocols, magnetic field strength (3T vs. 7T) and MPM parameters: it halved from PD to R1 and decreased from PD to MT_sat by a factor of 3-4. Exploring the artefact-sensitivity of the error maps, we generated robust MPM parameters using two successive acquisitions of each contrast and the acquisition-specific errors to down-weight erroneous regions. The resulting robust MPM parameters showed reduced variability at the group level as compared to their single-repeat or averaged counterparts. The error and mSNR maps may better inform power-calculations by accounting for local data quality variations across measurements. Code to compute the mSNR maps and robustly combined MPM maps is available in the open-source hMRI toolbox.

Magnetic Resonance Imaging-Proton Density Fat Fraction vs. Transient Elastography-Controlled Attenuation Parameter in Diagnosing Non-alcoholic Fatty Liver Disease in Children and Adolescents: A Meta-Analysis of Diagnostic Accuracy

Background and Aim: Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease in children and adolescents, and its prevalence increases with obesity. Magnetic resonance imaging (MRI) and transient elastography (TE) have been widely used to non-invasively evaluate NAFLD in adults. This study aimed to determine the efficacy and accuracy of MRI-proton density fat fraction (MRI-PDFF) and TE-controlled attenuation parameter (TE-CAP) in distinguishing hepatic steatosis in children and adolescents.Materials and Methods: In this meta-analysis, the PubMed, Cochrane Library, Embase, Medline, and Web of Science databases were searched for articles that reported studies on the accuracy of MRI-PDFF or TE-CAP in grading the steatosis in children and adolescents with NAFLD. This study compared the sensitivity, specificity, and hierarchical summary receiver operating characteristic curves (HSROCs) of MRI-PDFF and TE-CAP in distinguishing between steatosis grades S0 and S1–3.Results: A total of eight articles involving 874 children and adolescents with NAFLD were included in this study. The proportions of steatosis grades were 5 and 95% for S0 and S1–3, respectively. MRI-PDFF accurately diagnosed S1–3 steatosis, with a summary sensitivity of 0.95 (95% CI, 0.92–0.97), specificity of 0.92 (95% CI, 0.77–0.98), and HSROC of 0.96 (95% CI, 0.94–0.98). Likewise, TE-CAP accurately diagnosed S1–3 steatosis, with a summary sensitivity of 0.86 (95% CI, 0.70–0.94), specificity of 0.88 (95% CI, 0.71–0.96), and HSROC of 0.94 (95% CI, 0.91–0.95). Following a “positive” measurement (over the threshold value) for S1–3, the corresponding post-test probabilities of MRI-PDFF and TE-CAP for the presence of steatosis reached 92 and 88%, respectively, at the pretest probability of 50%. When the values were below the mentioned threshold values (“negative” results), the post-test probabilities of MRI-PDFF and TE-CAP became 5 and 13%, respectively.Conclusion: Both MRI-PDFF and TE-CAP are highly accurate non-invasive methods to grade the hepatic steatosis in children and adolescents with NAFLD. Furthermore, MRI-PDFF is significantly more accurate in assessing steatosis grade than TE-CAP.Systematic Review Registration: PROSPERO, identifier: CRD42021220422.

Texture Analysis Using CT and Chemical Shift Encoding-Based Water-Fat MRI Can Improve Differentiation Between Patients With and Without Osteoporotic Vertebral Fractures

PurposeOsteoporosis is a highly prevalent skeletal disease that frequently entails vertebral fractures. Areal bone mineral density (BMD) derived from dual-energy X-ray absorptiometry (DXA) is the reference standard, but has well-known limitations. Texture analysis can provide surrogate markers of tissue microstructure based on computed tomography (CT) or magnetic resonance imaging (MRI) data of the spine, thus potentially improving fracture risk estimation beyond areal BMD. However, it is largely unknown whether MRI-derived texture analysis can predict volumetric BMD (vBMD), or whether a model incorporating texture analysis based on CT and MRI may be capable of differentiating between patients with and without osteoporotic vertebral fractures.Materials and MethodsTwenty-six patients (15 females, median age: 73 years, 11 patients showing at least one osteoporotic vertebral fracture) who had CT and 3-Tesla chemical shift encoding-based water-fat MRI (CSE-MRI) available were analyzed. In total, 171 vertebral bodies of the thoracolumbar spine were segmented using an automatic convolutional neural network (CNN)-based framework, followed by extraction of integral and trabecular vBMD using CT data. For CSE-MRI, manual segmentation of vertebral bodies and consecutive extraction of the mean proton density fat fraction (PDFF) and T2* was performed. First-order, second-order, and higher-order texture features were derived from texture analysis using CT and CSE-MRI data. Stepwise multivariate linear regression models were computed using integral vBMD and fracture status as dependent variables.ResultsPatients with osteoporotic vertebral fractures showed significantly lower integral and trabecular vBMD when compared to patients without fractures (p<0.001). For the model with integral vBMD as the dependent variable, T2* combined with three PDFF-based texture features explained 40% of the variance (adjusted R2[Ra2] = 0.40; p<0.001). Furthermore, regarding the differentiation between patients with and without osteoporotic vertebral fractures, a model including texture features from CT and CSE-MRI data showed better performance than a model based on integral vBMD and PDFF only (Ra2 = 0.47 vs. Ra2 = 0.81; included texture features in the final model: integral vBMD, CT_Short-run_emphasis, CT_Varianceglobal, and PDFF_Variance).ConclusionUsing texture analysis for spine CT and CSE-MRI can facilitate the differentiation between patients with and without osteoporotic vertebral fractures, implicating that future fracture prediction in osteoporosis may be improved.

Sweep imaging with Fourier transform as a tool with MRI for evaluating the effect of teriparatide on cortical bone formation in an ovariectomized rat model

Background Teriparatide (TPTD) is a drug for osteoporosis that promotes bone formation and improves bone quality. However, the effects of TPTD on cortical bone are not well understood. Sweep imaging with Fourier transform (SWIFT) has been reported as a useful tool for evaluating bound water of cortical bone, but it has yet to be used to investigate the effects of TPTD on cortical bone. This study aimed to evaluate the consequences of the effect of TPTD on cortical bone formation using SWIFT. Methods Twelve-week-old female Sprague-Dawley rats (n = 36) were reared after ovariectomy to create a postmenopausal osteoporosis model. They were divided into two groups: the TPTD and non-TPTD groups. Rats were euthanized at 4, 12, and 24 weeks after initiating TPTD treatment. Tibial bones were evaluated using magnetic resonance imaging (MRI) and bone histomorphometry. In MRI, proton density-weighted imaging (PDWI) and SWIFT imaging were performed. The signal-to-noise ratio (SNR) was calculated for each method. The same area evaluated by MRI was then used to calculate the bone formation rate by bone histomorphometry. Measurements were compared using the Mann-Whitney U-test, and a P-value of < 0.05 was considered significant. Results PDWI-SNR was not significantly different between the two groups at any time point (P = 0.589, 0.394, and 0.394 at 4, 12, and 24 weeks, respectively). Contrarily, SWIFT-SNR was significantly higher in the TPTD group than in the non-TPTD group at 4 weeks after initiating treatment, but it was not significantly different at 12 and 24 weeks (P = 0.009, 0.937, and 0.818 at 4, 12, and 24 weeks, respectively). The bone formation rate assessed by histomorphometry was significantly higher in the TPTD group than in the non-TPTD group at all timepoints (P < 0.05, all weeks). In particular, at 4 weeks, the bone formation rate was markedly higher in the TPTD group than in the non-TPTD group (P = 0.028, 1.98 ± 0.33 vs. 0.09 ± 0.05 μm3/μm2/day). Conclusions SWIFT could detect increased signals of bound water, reflecting the effect of TPTD on the cortical bone. The signal detected by SWIFT reflects a marked increase in the cortical bone formation rate.

Proton Density Fat Fraction Spine MRI for Differentiation of Erosive Vertebral Endplate Degeneration and Infectious Spondylitis

Vertebral Modic type 1 (MT1) degeneration may mimic infectious disease on conventional spine magnetic resonance imaging (MRI), potentially leading to additional costly and invasive investigations. This study evaluated the diagnostic performance of the proton density fat fraction (PDFF) for distinguishing MT1 degenerative endplate changes from infectious spondylitis. A total of 31 and 22 patients with equivocal diagnosis of MT1 degeneration and infectious spondylitis, respectively, were retrospectively enrolled in this IRB-approved retrospective study and examined with a chemical-shift encoding (CSE)-based water-fat 3D six-echo modified Dixon sequence in addition to routine clinical spine MRI. Diagnostic reference standard was established according to histopathology or clinical and imaging follow-up. Intravertebral PDFF [%] and PDFFratio (i.e., vertebral endplate PDFF/normal vertebrae PDFF) were calculated voxel-wise within the single most prominent edematous bone marrow lesion per patient and examined for differences between MT1 degeneration and infectious spondylitis. Mean PDFF and PDFFratio of infectious spondylitis were significantly lower compared to MT1 degenerative changes (mean PDFF, 4.28 ± 3.12% vs. 35.29 ± 17.15% [p < 0.001]; PDFFratio, 0.09 ± 0.06 vs. 0.67 ± 0.37 [p < 0.001]). The areas under the curve (AUC) and diagnostic accuracies were 0.977 (p < 0.001) and 98.1% (cut-off at 12.9%) for PDFF and 0.971 (p < 0.001) and 98.1% (cut-off at 0.27) for PDFFratio. Our data suggest that quantitative evaluation of vertebral PDFF can provide a high diagnostic accuracy for differentiating erosive MT1 endplate changes from infectious spondylitis.

Triglyceride Saturation in Patients at Risk of NASH and NAFLD: A Cross-Sectional Study

Chemical shift magnetic resonance imaging (MRI) is commonly used to estimate the amount of fat in tissues, namely the proton density fat fraction (PDFF). In addition to PDFF, the type of fat can be inferred and characterized in terms of the number of double bonds (NDB), number of methylene-interrupted double bonds (NMIDB) and the chain length (CL) of the fatty acid chains. The saturation index is potentially a marker for metabolic disorders. This study assesses the feasibility of estimating these parameters independently or in a constrained manner. Correlations with spectroscopy were measured in 109 subjects’ subcutaneous and visceral fat depots (p = 2 × 10−28), and with the NAFLD Activity Score (NAS) from histological evaluation of biopsies. The findings indicate that imaging estimates are comparable to spectroscopy (p = 0.0002), but there is no significant association of NDB with NAS (p = 0.1).