Chemical Shift-encoded Magnetic Resonance Imaging Research Articles

Influence of Gd-EOB-DTPA on proton-density fat fraction in the liver using chemical shift-encoded magnetic resonance imaging at 3-T.

Non-alcoholic fatty liver disease (NAFLD) and its advanced stage, non-alcoholic steatohepatitis (NASH), have become increasingly prevalent owing to the rise in metabolic syndromes. Accurate assessment of hepatic fat deposition and inflammation is crucial for diagnosing and managing NAFLD/NASH. We investigated the influence of Gd-EOB-DTPA, (EOB) on proton-density fat fraction (PDFF) measurements using chemical shift-encoded magnetic resonance imaging (CSE-MRI) at 3-T. In total, 431 patients who underwent EOB contrast-enhanced MRI were included. PDFF measurements were obtained from pre- and post-contrast CSE-MRI. Linear regression and Bland-Altman analyses were performed to assess the correlation and agreement between pre- and post-EOB PDFF measurements. Relative enhancement (RE) of the liver was calculated as an EOB uptake index. There was a significant decrease in PDFF following EOB administration compared with the pre-contrast values (P < 0.0001), which was observed across all PDFF ranges (< 10% and ≥ 10%). Linear regression analysis revealed high correlation between pre- and post-EOB PDFF measurements. Bland-Altman analysis indicated a small bias between pre- and post-EOB PDFF values. Subgroup analysis based on RE showed a significant difference in ΔPDFF between patients with high RE (> 120%) and those with lower RE levels. EOB administration resulted in a slight decrease in PDFF measurements obtained using CSE-MRI at 3-T. We were able to generalize and clarify that the PDFF of the liver on 3D CSE-MRI at 3-T was slightly decreased after EOB administration as we used a larger group of patients compared to previous studies.

Chemical shift-encoded MRI with compressed sensing combined with parallel imaging for proton density fat fraction measurement of the lumbar vertebral bone marrow.

We aimed to investigate the accuracy of proton density fat fraction (PDFF) measurement of the lumbar vertebral bone marrow using chemical shift-encoded magnetic resonance imaging (CSE-MRI) with compressed sensing combined with parallel imaging (CSPI). This study recruited a commercially available phantom, and 43 patients. Fully sampled data without CSPI and under-sampled data with CSPI acceleration factors of 2.4, 3.6, and 4.8 were acquired using a 1.5T imaging system. The relationships between PDFF measurements obtained with the no-CSPI acquisition and those obtained with each CSPI acquisition were assessed using Pearson correlation coefficient (r), linear regression analyses, and Bland-Altman analysis. The intra- and inter-observer variabilities of the PDFF measurements were evaluated using the intraclass correlation coefficient. PDFF measurements obtained with all acquisitions showed a significant correlation and strong agreement with the reference PDFF measurement of the phantom. PDFF measurements obtained using CSE-MRI with and without CSPI were positively correlated (all acquisitions: r = 0.99; P < .001). The mean bias was -0.31% to -0.17% with 95% limits of agreement within ±2.02%. The intra- and inter-observer agreements were excellent (intraclass correlation coefficient: 0.988 and 0.981, respectively). A strong agreement and positive correlation were observed between the PDFF measurements obtained using CSE-MRI with and without CSPI. PDFF measurement of the lumbar vertebral bone marrow using CSE-MRI with CSPI can be acquired with a maximum reduction of approximately 75% in the acquisition time compared with a fully sampled acquisition.

Evaluation of masticatory muscles in temporomandibular joint disorder patients using quantitative MRI fat fraction analysis-Could it be a biomarker?

Temporomandibular joint disorders (TMDs) are closely related to the masticatory muscles, but objective and quantitative methods to evaluate muscle are lacking. IDEAL-IQ, a type of chemical shift-encoded magnetic resonance imaging (CSE-MRI), can quantify the fat fraction (FF). The purpose of this study was to develop an MR IDEAL-IQ-based method for quantitative muscle diagnosis in TMD patients. A total of 65 patients who underwent 3 T MRI scans, including CSE-MRI sequences, were retrospectively included. MRI diagnoses and clinical data were reviewed. There were 19 patients in the normal group and 46 patients in the TMD group with unilateral disc displacement. The TMD group was subdivided into those with and without clenching. The right and left FF values of the masseter, medial, and lateral pterygoid muscles were measured twice by two oral radiologists on CSE-MRI, and the average value was used. FF measurements using CSE-MRI showed excellent intra- and inter-observer agreement (ICC > 0.889 for both). There were no statistically significant differences between the right and left FF values in the masseter, medial pterygoid, and lateral pterygoid of the normal group (p > 0.05). A statistically significant difference was found in the TMD group without clenching, in which the masseter muscle had a statistically significantly lower FF value on the disc displacement side (3.94 ± 1.61) than on the normal side (4.52 ± 2.24) (p < 0.05). CSE-MRI, which can reproducibly quantify muscle FF values, is expected to be a biomarker for objective muscle evaluation in TMD patients. The masseter muscle is expected to be particularly useful compared to other masticatory muscles, but further research is needed.

Behind BMI: The Potential Indicative Role of Abdominal Ectopic Fat on Glucose Metabolism

Introduction: The purpose of this study was to compare the difference in abdominal fat distribution between different metabolic groups and find the ectopic fat with the most risk significance. Methods: A total of 98 subjects were enrolled; there were 53 cases in the normal glucose metabolism group and 45 cases in the abnormal glucose metabolism group. Chemical shift-encoded magnetic resonance imaging was applied for quantification of pancreatic fat fraction (PFF) and hepatic fat fraction (HFF), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT). The correlation and the difference of fat distribution between different metabolism groups were analyzed. The receiver operating characteristic (ROC) curve was used to analyze the suggestive effect of different body fat fraction. Results: Correlation analysis showed that body mass index (BMI) had the strongest correlation with fasting insulin (r = 0.473, p < 0.001), HOMA-IR (r = 0.363, p < 0.001), and C-reactive protein (r = 0.245, p < 0.05). Pancreatic fat has a good correlation with fasting blood glucose (r = 0.247, p < 0.05) and HbA1c (r = 0.363, p < 0.001). With the increase of BMI, PFF, VAT, and SAT showed a clear upward trend, but liver fat was distributed relatively more randomly. The pancreatic fat content in the abnormal glucose metabolism group is significantly higher than that in the normal group, and pancreatic fat is also a reliable indicator of abnormal glucose metabolism, especially in the normal and overweight groups (the area under the curve was 0.859 and 0.864, respectively). Conclusion: MR-based fat quantification techniques can provide additional information on fat distribution. There are differences in fat distribution among people with different metabolic status. People with more severe pancreatic fat deposition have a higher risk of glucose metabolism disorders.

Assessing the histopathological features of rectal adenocarcinoma with chemical shift-encoded sequence (CSE)-MRI and diffusion-weighted imaging (DWI).

It is of clinical importance to assess the histopathological features of rectal cancer. The adipose tissue microenvironment is closely associated with tumor formation and progression. The chemical shift-encoded magnetic resonance imaging (CSE-MRI) sequence can noninvasively quantify adipose tissue. In this study, we aimed to investigate the feasibility of using CSE-MRI and diffusion-weighted imaging (DWI) to predict the histopathological features of rectal adenocarcinoma. In this retrospective study, 84 patients with rectal adenocarcinoma and 30 healthy controls were consecutively enrolled at the Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology. CSE-MRI and DWI sequences were performed. The intratumoral proton density fat fraction (PDFF) and R2* of rectal tumors and normal rectal walls were measured. The histopathological features, including pathological T/N stage, tumor grade, mesorectum fascia (MRF) involvement, and extramural venous invasion (EMVI) status were analyzed. The Mann-Whitney test, Spearman correlation, and receiver operating characteristic (ROC) curves were used for statistical analyses. Patients with rectal adenocarcinoma demonstrated significantly lower PDFF and R2* values than did the control participants (5.35%±1.70% vs. 11.55%±3.41%, P<0.001; 35.60 s-1±7.30 s-1 vs. 40.15 s-1±5.72 s-1, P=0.003). PDFF and R2* were significantly different in the discrimination of T/N stage, tumor grade, and MRF/EMVI status (P=0.000-0.005). A significant difference was only noted in the differentiation of the T stage for the apparent diffusion coefficient (ADC) (1.09±0.26×10-3 mm2/s vs. 1.00±0.11×10-3 mm2/s; P=0.001). PDFF and R2* exhibited positive correlations with all the histopathological features (r=0.306-0.734; P=0.000-0.005), while ADC was negatively correlated with the T stage (r=-0.380; P<0.001). PDFF demonstrated diagnostic ability, with a sensitivity of 95.00% and a specificity of 87.50%, while R2* had a sensitivity of 95.00% and a specificity of 79.20% in differentiating T stage; both demonstrated a better diagnostic performance than did ADC. Quantitative CSE-MRI imaging might serve as a noninvasive biomarker for assessing the histopathological features of rectal adenocarcinoma.

Impact of arm position on vertebral bone marrow proton density fat fraction in chemical-shift-encoded magnetic resonance imaging: a preliminary study.

Arm positions employed during magnetic resonance imaging (MRI) can affect magnetic field distribution, which may result in variability in proton density fat fraction (PDFF) measurements. This study evaluated the effect of arm position on lumbar PDFF measured using chemical-shift-encoded MRI (CSE-MRI). Fifteen healthy volunteers from a single-center underwent lumbar CSE-MRI at two different arm positions (side and elevated) using a single 3T scanner. Scans were performed twice in each position. PDFFs of the L1-L5 vertebrae were independently measured by two readers, and reader measurements were compared by calculating intraclass correlation coefficients (ICC). We compared PDFF measurements from two arm positions and from two consecutive scans using the Wilcoxon test and Bland-Altman analysis. Measurements from the two readers were in high agreement [ICC =0.999; 95% confidence interval (CI), 0.998-0.999]. No significant difference was observed between PDFFs from the first and second scans of all vertebrae for each reader (all P>0.05); however, PDFF for the elevated arm position was significantly higher than that for the side arm position (37.9-44.8% vs. 37.0-43.8%; all P<0.05), except at the L2 level by reader 2. The mean differences in PDFF measurements from the first and second scans [0.1%; 95% limits of agreement (LoA), -1.8% to 1.9%] and from the side arm and elevated arm positions (0.8%; 95% LoA, -1.6% to 3.2%) were small. In conclusion, these preliminary data suggest that different arm positions during CSE-MRI can slightly affect lumbar PDFF; however, the mean absolute differences were very small.

Systematic review and meta-analysis: the value of MRI chemical-shift imaging in the evaluation of bone quality in patients with osteoporosis.

Osteoporosis is a systemic skeletal disease with no obvious symptoms in its early stages. The decreases in bone density and bone mass are associated with the deterioration of bony microstructure in the body, due to a variety of reasons. The current assessment criteria for osteoporosis are still not perfect. MRI chemical-shift imaging shows potential to be a valuable technique in the bone quality assessment of osteoporotic patients. Randomized controlled studies on osteoporosis assessment were searched for in English-language databases, including PubMed, Web of Science, Embase, and The Cochrane Library. Inclusion criteria were: (I) literature focused on the assessment of osteoporosis by chemical displacement imaging; (II) studies evaluating the bone quality of osteoporosis; (III) studies with at least 15 samples; (IV) studies concerned with the evaluation of osteoporosis by chemical shift encoded magnetic resonance imaging (CSE-MRI); and (V) studies with outcome indexes for bone mineral density (BMD), body mass index (BMI), and bone marrow fat fraction (BMFF). The Jadad tool was used to evaluate the quality of the included studies, and the Review Manager v. 5.3 software was used to conduct the meta-analysis of the experimental data. A total of 7 suitable articles were selected. According to the results of the meta-analysis, for the osteoporosis group and normal group: BMD: MD =41.91 [95% confidence interval (CI): 40.15 to 43.66], Z=46.82 (P<0.00001); BMI: MD =-1.43 (95% CI: -2.02 to -0.84), Z=4.76 (P<0.00001); BMFF: MD =-18.34 (95% CI: -20.32 to -16.36), Z=18.15 (P<0.00001). MRI chemical-shift imaging can effectively measure BMD and bone mass, including in osteoporotic patients. However, the outcome indicators included in this study are not sufficient to assess the utility of MRI chemical shift imaging for evaluating bone mass in osteoporotic patients, and further expansion of the sample size and outcome indicators is needed.

Influence of arm position on proton density fat fraction in the liver using chemical shift-encoded magnetic resonance imaging

PurposeTo evaluate the influence of arm position on B1 and proton density fat fraction (PDFF) in the liver using chemical shift-encoded magnetic resonance imaging. Materials and methodsParticipants were 8 healthy volunteers without liver disease and 36 patients with presumed or proven fatty liver. We assessed two preliminary examinations in healthy subjects, i.e., arm position influence on B1 and the variability of the PDFF between two scans within a short period of time. To verify the changes in PDFF measurement, 36 patients with fatty liver were conducted to compare 2 different arm positions—the elevated arms and side arms positions. The measurement location was based on the Healey & Schroy classification. The Wilcoxon test was used to analyze the difference in B1 in between the elevated arms and side arms positions. The Bland-Altman analysis was used to assess the agreement between two measurements of PDFF: two same scans within a short period of time, and two scans with different arms positions. ResultsB1 was significantly different in all segments except for medial segment. The variability of the PDFF between two scans within a short period of time was small in all segments. Some patients had large fluctuations in all segments, although the mean differences in PDFF were small. Upper and lower limits of agreement were 2.064% to 2.871% and − 2.430% to −1.462%, respectively. The relative difference in the rate of PDFF changes as the median (interquartile range [IQR]) in the lateral, medial, anterior, and posterior segments between both the arms positions were 0.0% (9.4), 1.1% (7.3), 1.5% (8.2) and − 0.2% (10.3), respectively. ConclusionsArm position can significantly affect B1 and PDFF in the liver. Although the absolute change in PDFF between arm positions was not so large, the difference in arm positions can cause large relative PDFF fluctuations.

Multisite multivendor validation of a quantitative MRI and CT compatible fat phantom.

Chemical shift-encoded magnetic resonance imaging enables accurate quantification of liver fat content though estimation of proton density fat-fraction (PDFF). Computed tomography (CT) is capable of quantifying fat, based on decreased attenuation with increased fat concentration. Current quantitative fat phantoms do not accurately mimic the CT number of human liver. The purpose of this work was to develop and validate an optimized phantom that simultaneously mimics the MRI and CT signals of fatty liver. An agar-based phantom containing 12 vials doped with iodinated contrast, and with a granular range of fat fractions was designed and constructed within a novel CT and MR compatible spherical housing design. A four-site, three-vendor validation study was performed. MRI (1.5T and 3T) and CT images were obtained using each vendor's PDFF and CT reconstruction, respectively. An ROI centered in each vial was placed to measure MRI-PDFF (%) and CT number (HU). Mixed-effects model, linear regression, and Bland-Altman analysis were used for statistical analysis. MRI-PDFF agreed closely with nominal PDFF values across both field strengths and all MRI vendors. A linear relationship (slope=-0.54±0.01%/HU, intercept= 37.15±0.03%) with an R2 of 0.999 was observed between MRI-PDFF and CT number, replicating established in vivo signal behavior. Excellent test-retest repeatability across vendors (MRI: mean=-0.04%, 95% limits of agreement=[-0.24%, 0.16%]; CT: mean= 0.16 HU, 95% limits of agreement=[-0.15HU, 0.47HU]) and good reproducibility using GE scanners (MRI: mean=-0.21%, 95% limits of agreement=[-1.47%, 1.06%]; CT: mean=-0.18HU, 95% limits of agreement=[-1.96HU, 1.6HU]) were demonstrated. The proposed fat phantom successfully mimicked quantitative liver signal for both MRI and CT. The proposed fat phantom in this study may facilitate broader application and harmonization of liver fat quantification techniques using MRI and CT across institutions, vendors and imaging platforms.

Feasibility of Hepatic Fat Quantification Using Proton Density Fat Fraction by Multi-Echo Chemical-Shift-Encoded MRI at 7T.

Fat fraction quantification and assessment of its distribution in the hepatic tissue become more important with the growing epidemic of obesity, and the increasing prevalence of diabetes mellitus type 2 and non-alcoholic fatty liver disease. At 3Tesla, the multi-echo, chemical-shift-encoded magnetic resonance imaging (CSE-MRI)-based acquisition allows the measurement of proton density fat-fraction (PDFF) even in clinical protocols. Further improvements in SNR can be achieved by the use of phased array coils and increased static magnetic field. The purpose of the study is to evaluate the feasibility of PDFF imaging using a multi-echo CSE-MRI technique at ultra-high magnetic field (7Tesla). Thirteen volunteers (M/F) with a broad range of age, body mass index, and hepatic PDFF were measured at 3 and 7T by multi-gradient-echo MRI and single-voxel spectroscopy MRS. All measurements were performed in breath-hold (exhalation); the MRI protocols were optimized for a short measurement time, thus minimizing motion-related problems. 7T data were processed off-line using Matlab® (MRI:multi-gradient-echo) and jMRUI (MRS), respectively. For quantitative validation of the PDFF results, a similar protocol was performed at 3T, including on-line data processing provided by the system manufacturer, and correlation analyses between 7 and 3T data were performed off-line. The multi-echo CSE-MRI measurements at 7T with a phased-array coil configuration and an optimal post-processing yielded liver volume coverage ranging from 30 to 90% for high- and low-BMI subjects, respectively. PDFFs ranged between 1 and 20%. We found significant correlations between 7T MRI and -MRS measurements (R2 ≅ 0.97; p < 0.005), and between MRI-PDFF at 7T and 3T fields (R2 ≅ 0.94; p < 0.005) in the evaluated volumes. Based on the measurements and analyses performed, the multi-echo CSE-MRI method using a 32-channel coil at 7T showed its aptitude for MRI-based quantitation of PDFF in the investigated volumes. The results are the first step toward qMRI of the whole liver at 7T with further improvements in hardware.

Liver Fat Assessment in Multiview Sonography Using Transfer Learning With Convolutional Neural Networks.

To develop and evaluate deep learning models devised for liver fat assessment based on ultrasound (US) images acquired from four different liver views: transverse plane (hepatic veins at the confluence with the inferior vena cava, right portal vein, right posterior portal vein) and sagittal plane (liver/kidney). US images (four separate views) were acquired from 135 participants with known or suspected nonalcoholic fatty liver disease. Proton density fat fraction (PDFF) values derived from chemical shift-encoded magnetic resonance imaging served as ground truth. Transfer learning with a deep convolutional neural network (CNN) was applied to develop models for diagnosis of fatty liver (PDFF ≥ 5%), diagnosis of advanced steatosis (PDFF ≥ 10%), and PDFF quantification for each liver view separately. In addition, an ensemble model based on all four liver view models was investigated. Diagnostic performance was assessed using the area under the receiver operating characteristics curve (AUC), and quantification was assessed using the Spearman correlation coefficient (SCC). The most accurate single view was the right posterior portal vein, with an SCC of 0.78 for quantifying PDFF and AUC values of 0.90 (PDFF ≥ 5%) and 0.79 (PDFF ≥ 10%). The ensemble of models achieved an SCC of 0.81 and AUCs of 0.91 (PDFF ≥ 5%) and 0.86 (PDFF ≥ 10%). Deep learning-based analysis of US images from different liver views can help assess liver fat.

Accuracies of Chemical Shift In/Opposed Phase and Chemical Shift Encoded Magnetic Resonance Imaging to Detect Intratumoral Fat in Hepatocellular Carcinoma

Magnetic Resonance Imaging (MRI) being a noninvasive modality may help in preoperative evaluation of intratumoral fat in hepatocellular carcinoma (HCC) using chemical shift encoded (CSE) MRI and in-/opposed-phase (IOP) imaging sequences. To compare the diagnostic accuracy of chemical shift encoded fat fraction at three different flip angles (FAs) using quantitative chemical shift encoded MRI (CSE-MRI) with in-/opposed phase (IOP) imaging to evaluate intratumoral fat in HCC. Retrospective. Eighty-six patients with 87 pathology proven HCCs. IOP (LAVA-Flex) and CSE-MRI (IDEAL IQ) a three-dimensional spoiled gradient-echo pulse sequences acquired at 3 T. Regions of interest (ROIs) were manually drawn by two observers in the tumors to measure mean fat fractions. Surgical specimens were reassessed for intratumoral fat content. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed for CSE-MRI sequence at FA 3°, 8°, and 9°. Intraclass correlation coefficient (ICC) was expressed in terms of inter- and intra-observer agreements. Receiver operating characteristic curve analysis was performed for the diagnostic performance followed by combined metric of both. SNR/CNR were analyzed by Kruskal-Wallis test. Excellent inter- and intra-observer agreements (ICC >0.95, P < 0.001) were observed for both IOP and CSE-MRI. IOP (86.4%) showed higher sensitivity than CSE-MRI at FA 3° (72.5%), FA 8° (76.4%) and FA 9° (76.3%). In contrast, the specificity for CSE-MRI at FA 3° (86%), FA 8° (87%), and FA 9° (87%) were greater than IOP (72%). A combined metric of IOP and CSE-MRI derived fat fractions at FA 8° gave highest AUC of 87% and accuracy of 86%. SNR and CNR for CSE-MRI were significantly higher at FA 8° and FA 9° than FA 3° (P < 0.05). IOP and quantitative CSE-MRI are both feasible methods to detect intratumoral fat in HCC with higher accuracy and SNR for CSE-MRI at FA 8° and 9°. 3 TECHNICAL EFFICACY: Stage 2.

Use of proton density fat fraction MRI to predict the radiographic progression of osteoporotic vertebral compression fracture.

This study evaluated the diagnostic performance of the proton density fat fraction (PDFF) in predicting the progression of osteoporotic vertebral compression fractures (OVCFs). The cohort in this retrospective study consisted of 48 patients with OVCFs who underwent spine MRI that included PDFF between December 2016 and June 2018. The patients were divided into two groups (with versus without OVCF progression, based on the radiographic results obtained at the 6-month follow-up examination). Two musculoskeletal radiologists independently calculated the PDFF of the fracture and the PDFF ratio (fracture PDFF/normal vertebrae PDFF) using regions of interest. The mean values of these parameters were compared between the two groups, and the receiver operating characteristic curves were analysed. The mean age was significantly higher in the group with OVCF progression (71.6 ± 8.4 years) than in the group without (64.8 ± 10.5 years) (p = 0.018). According to reader 1, the PDFF ratio was significantly lower in the group with OVCF progression versus that without OVCF progression (0.38 ± 0.13 vs 0.51 ± 0.20; p = 0.009), whereas the difference in the PDFF itself was not statistically significant. The PDFF ratio [area under the curve (AUC) = 0.723; 95% confidence interval (CI), 0.575-0.842] had a larger AUC than did the PDFF (AUC = 0.667; 95% CI, 0.516-0.796). The optimal cut-off value of the PDFF ratio for predicting OVCF progression was 0.42; this threshold corresponded to sensitivity, specificity, and accuracy values of 84.0%, 60.9%, and 72.9%, respectively. The age and PDFF ratio can be used to predict OVCF progression. • Chemical shift-encoded magnetic resonance imaging provides quantitative parameters for predicting OVCF progression. • The PDFF ratio is significantly lower in patients with OVCF progression. • The PDFF ratio is superior to the PDFF for predicting OVCF progression.

Analysis of muscle, hip, and subcutaneous fat in osteoporosis patients with varying degrees of fracture risk using 3T Chemical Shift Encoded MRI

Osteoporosis (OP) is a major disease that affects 200 million people worldwide. Fatty acid metabolism plays an important role in bone health and plays an important role in bone quality and remodeling. Increased bone marrow fat quantity has been shown to be associated with a decrease in bone mineral density (BMD), which is used to predict fracture risk. Chemical-Shift Encoded magnetic resonance imaging (CSE-MRI) allows noninvasive and quantitative assessment of adipose tissues (AT). The aim of our study was to assess hip or proximal femoral bone marrow adipose tissue (BMAT), thigh muscle (MUS), and subcutaneous adipose tissue (SAT) in 128 OP subjects matched for age, BMD, weight and height with different degrees of fracture risk assessed through the FRAX score (low, moderate and high). Our results showed an increase in BMAT and in MUS in high compared to low fracture risk patients. We also assessed the relationship between fracture risk as assessed by FRAX and AT quantities. Overall, the results of this study suggest that assessment of adipose tissue via 3T CSE-MRI provides insight into the pathophysiology fracture risk by showing differences in the bone marrow and muscle fat content in subjects with similarly osteoporotic BMD as assessed by DXA, but with varying degrees of fracture risk as assessed by FRAX.

Pancreas fat quantification with quantitative CT: an MRI correlation analysis

To assess the fat content of the pancreas using quantitative computed tomography (QCT) and to correlate the results with chemical-shift-encoded magnetic resonance imaging (CSE-MRI) measurements of proton density fat fraction (PDFF). Institutional review board approval for this research was obtained and 52 participants (25 men, 27 women; mean age 35.1 years; age range 22-50 years), who were enrolled in the Prospective Urban Rural Epidemiology (PURE) Study, underwent QCT and CSE-MRI for quantification of fat content in the pancreas. Two observers placed regions of interest (area of 100-130mm2) in the head, body, and tail of the pancreas as closely matched as possible on the two scans. Pearson correlation and Bland-Altman analysis were performed to evaluate the correlation between the QCT and CSE-MRI measurements and the systematic difference between the two techniques. The QCT and CSE-MRI measurements of pancreatic fat content were well correlated (r=0.805, p<0.0001), although Bland-Altman analysis showed that the QCT measurements were systematically lower by 6.3% compared to CSE-MRI PDFF. In conclusion, the results of this study suggest good correlation between QCT and CSE-MRI measurements of pancreatic fat content. Further studies are required to improve the numerical agreement of QCT measurements with PDFF.

Low-level fat fraction quantification at 3 T: comparative study of different tools for water–fat reconstruction and MR spectroscopy

Chemical Shift Encoded Magnetic Resonance Imaging (CSE-MRI)-based quantification of low-level (< 5% of proton density fat fraction-PDFF) fat infiltration requires highly accurate data reconstruction for the assessment of hepatic or pancreatic fat accumulation in diagnostics and biomedical research. We compare three software tools available for water/fat image reconstruction and PDFF quantification with MRS as the reference method. Based on the algorithm exploited in the tested software, the accuracy of fat fraction quantification varies. We evaluate them in phantom and in vivo MRS and MRI measurements. The signal model of Intralipid 20% emulsion used for phantoms was established for 3T and 9.4T fields. In all cases, we noticed a high coefficient of determination (R-squared) between MRS and MRI-PDFF measurements: in phantoms <0.9924-0.9990>; and in vivo <0.8069-0.9552>. Bland-Altman analysis was applied to phantom and in vivo measurements. Multi-echo MRI in combination with an advanced algorithm including multi-peak spectrum modeling appears as a valuable and accurate method for low-level PDFF quantification over large FOV in high resolution, and is much faster than MRS methods. The graph-cut algorithm (GC) showed the fewest water/fat swaps in the PDFF maps, and hence stands out as the most robust method of those tested.

Correction of QCT vBMD using MRI measurements of marrow adipose tissue.

Quantitative computed tomography (QCT) measurements of volumetric bone mineral density (vBMD) are subject to errors due to variations in the amount of bone marrow adipose tissue (BMAT). The purpose of our study was to describe and validate a novel method to correct lumbar spine trabecular vBMD measurements for BMAT using chemical shift-encoded magnetic resonance imaging (CSE-MRI). CSE-MRI measurements of proton density fat fraction (PDFF) were used to correct QCT spine vBMD measurements for BMAT based on the H2O and K2HPO4 basis set equivalent densities of bone, red and yellow bone marrow. BMAT corrected and uncorrected vBMD measurements of the L1 vertebra were compared with dual-energy QCT (DEQCT) measurements in 18 subjects (mean age: 68 y, range 60 to 93 y). A further 400 subjects (mean age: 53 y, range 21 to 82 y) had 120 kVp single-energy QCT and CES-MRI scans of L2-L4 and the data used to simplify the adipose tissue correction by deriving a linear equation between the CSE-MRI vBMD correction and fractional BMAT content. Application of the CSE-MRI derived vBMD correction changed the bias (95% limits of agreement) compared with DEQCT from 26.7 (11.0 to 42.4) mg/cm3 to 2.2 (-9.5 to 13.9) mg/cm3 at 80 kVp, and from 22.4 (3.3 to 41.6) mg/cm3 to 2.9 (-12.6 to 18.4) mg/cm3 at 120 kVp. Data for the 400 subjects gave the following relationship valid at 120 kVp: vBMD correction (mg/cm3) = -12.96 + 75.76 × BMAT. CSE-MRI measurements of PDFF can be used to correct for BMAT content and improve the accuracy of lumbar spine QCT vBMD measurements calibrated using a K2HPO4 phantom.

MRI liver fat quantification in an oncologic population: the added value of complex chemical shift-encoded MRI

IntroductionChemotherapy prolongs the survival of patients with advanced and metastatic tumors. Since the liver plays an active role in the metabolism of chemotherapy agents, hepatic injury is a common adverse effect. The purpose of this study is to compare a novel quantitative chemical shift encoded magnetic resonance imaging (CSE-MRI) method with conventional T1-weighted In and Out of phase (T1 IOP) MR for evaluating the reproducibility of the methods in an oncologic population exposed to chemotherapy. Materials and methodsThis retrospective study was approved by the institutional review board with a waiver for informed consent. The study included patients who underwent chemotherapy, no suspected liver iron overload, and underwent upper abdomen MRI. Two radiologists independently draw circular ROIsin the liver parenchyma. The fat fraction was calculated from IOP imaging and measured from IDEAL-IQ fat fraction maps. Two different equations were used to estimate fat with IOP sequences. Intra-class correlation coefficient and repeatability coefficient were estimated to evaluate agreement between two readers on iron level and fat fraction measurement. ResultsCSE-MRI showed a higher reliability in fat quantification compared with both IOP methods, with a substantially higher inter-reader agreement (0.961 vs 0.372). This has important clinical implications. ConclusionThe novel CSE-MRI method described here provides increased reproducibility and confidence in diagnosing hepatic steatosis in a oncologic clinical setting. IDEAL-IQ has been proved to be more reproducible than conventional IOP imaging.

Lower Ectopic Fat Accumulation in Obese Women May Help Explain Sex Differences in the Magnitude of Insulin Resistance

Accumulating evidence suggests obese women maintain higher insulin sensitivity than obese men, but factors underlying this sex difference in insulin resistance remain unclear. We recently developed a semi-automated method for quantifying visceral and hepatic fat using advanced chemical shift-encoded magnetic resonance imaging (MRI). Using this method, we explored whether sex differences in ectopic fat accumulation may contribute to differences in insulin resistance. Twenty-one obese women (32 ± 6 year, 34.5 ± 3.1 kg/m2, 43.1 ± 5.5 kg fat mass (FM)) and a well-matched cohort of fifteen obese men (29 ± 6 year, 34.5 ± 3.3 kg/m2, 42.0 ± 7.8 kg FM) underwent an MRI scan during which 5mm axial slices were acquired from the abdominal region. Using 3D Slicer software, visceral fat area was quantified on three axial slices from the L2-L3 vertebrae region and averaged. Hepatic fat was quantified as the average percentage fat from three axial slices of the liver. On a separate day, subjects underwent a hyperinsulinemic-euglycemic clamp to quantify insulin sensitivity. Compared with men, women had lower hepatic (4.2 ± 5.5 vs. 13.1 ± 9.7%, p&amp;lt;0.001) and visceral (114 ± 49 vs. 201 ± 87 cm2, p&amp;lt;0.001) fat, which corresponded with higher insulin sensitivity (Glucose infusion rate during clamp [GIR]: 514 ± 330 vs. 263 ± 134 umol/kgFFM/SSI/min, p&amp;lt;0.05). To further examine the relationship between ectopic lipid accumulation and insulin resistance, we stratified subjects into tertiles by hepatic fat content (n=12 per group). Interestingly, nearly all subjects in the lowest tertile for hepatic fat (1.1 ± 0.6%) were women, and when compared to the highest hepatic fat tertile (17.7 ± 8.2%), they also had lower visceral fat (101 ± 61 vs. 214 ± 83 cm2, p&amp;lt;0.001) and importantly, were also more insulin sensitive (GIR: 626 ± 350 vs. 279 ± 238 umol/kgFFM/SSI/min, p&amp;lt;0.05). Our findings suggest lower ectopic fat deposition may help explain the lower degree of insulin resistance in obese women compared with men. Disclosure J.B. Gillen: None. B.J. Ryan: None. R.A. Gioscia-Ryan: None. A. Ludzki: None. T.L. Chenevert: None. J.F. Horowitz: None.

Validation of goose liver fat measurement by QCT and CSE-MRI with biochemical extraction and pathology as reference.

This study aimed to validate the accuracy and reliability of quantitative computed tomography (QCT) and chemical shift encoded magnetic resonance imaging (CSE-MRI) to assess hepatic steatosis. Twenty-two geese with a wide range of hepatic steatosis were collected. After QCT and CSE-MRI examinations, the liver of each goose was removed and samples were taken from the left lobe, upper and lower half of the right lobe for biochemical measurement and histology. Fat percentages by QCT and proton density fat fraction by MRI (MRI-PDFF) were measured within the sample regions of biochemical measurement and histology. The accuracy of QCT and MR measurements were assessed through Spearman correlation coefficients (r) and Passing and Bablok regression equations using biochemical measurement as the "gold standard". Both QCT and MRI correlated highly with chemical extraction [r = 0.922 (p < 0.001) and r = 0.949 (p < 0.001) respectively]. Chemically extracted triglyceride was accurately predicted by both QCT liver fat percentages (Y = 0.6 + 0.866 × X) and by MRI-PDFF (Y = -1.8 + 0.773 × X). QCT and CSE-MRI measurements of goose liver fat were accurate and reliable compared with biochemical measurement. • QCT and CSE-MRI can measure liver fat content accurately and reliably • Histological grading of hepatic steatosis has larger sampling variability • QCT and CSE-MRI have potential in the clinical setting.