Agreement between region-of-interest- and parametric map-based hepatic proton density fat fraction estimation in adults with chronic liver disease

Determination of the R2* relaxation rate constant for estimating hepatic iron concentration: A customized approach that considers liver fat infiltration

PURPOSE

Α customized approach to determine R₂* relaxation rate for hepatic iron concentration (HIC) estimation is presented, and is evaluated in the context of concurrent liver fat infiltration.

METHODS

The proposed method employs a customized acquisition protocol, featuring a 16-echo, gradient-echo sequence, and a bi-exponential least squares fitting that considers baseline noise and uses a cosine function to correct for fat-induced signal oscillation. 193 patients with wide-ranging HIC and liver fat fraction (FF) were imaged at 1.5 T. In severely iron-overload patients, a four-echo train technique was applied to enforce all 16 echoes in the 1.2-4.0 ms range. Acquired data were compared to corresponding results obtained with the IDEAL IQ method.

RESULTS

Techniques employed to counter the rapid signal decay in iron-overloaded liver, such as the offset and the truncation methods, have to be combined with the appropriate calibration curve to provide reliable HIC estimation. When high grade steatosis and siderosis co-exist, fat-suppression may downgrade siderosis. A high correlation was observed between data obtained with the proposed technique and the IDEAL IQ method, except from the high R₂* region. However, systematic differences were detected. In the concurrent presence of high FF and non-severe iron overload, it is postulated that the bi-exponential model may attribute patient siderosis grading more accurately than IDEAL IQ, while simultaneously providing reliable FF estimation.

CONCLUSIONS

The proposed approach is widely available and seems capable of providing reliable R₂* measurements regardless of liver steatosis grading, whilst it succeeds in averting significant R₂* underestimation in severely iron-overloaded liver.

Inter-reader agreement of magnetic resonance imaging proton density fat fraction and its longitudinal change in a clinical trial of adults with nonalcoholic steatohepatitis

PURPOSE

To determine the inter-reader agreement of magnetic resonance imaging proton density fat fraction (PDFF) and its longitudinal change in a clinical trial of adults with nonalcoholic steatohepatitis (NASH).

STUDY TYPE

We performed a secondary analysis of a placebo-controlled randomized clinical trial of a bile acid sequestrant in 45 adults with NASH. A six-echo spoiled gradient-recalled-echo magnitude-based fat quantification technique was performed at 3 T. Three independent readers measured MRI-PDFF by placing one primary and two additional regions of interest (ROIs) in each segment at both time points. Cross-sectional agreement between the three readers was evaluated using intra-class correlation coefficients (ICCs) and coefficients of variation (CV). Additionally, we used Bland-Altman analyses to examine pairwise agreement between the three readers at baseline, end of treatment (EOT), and for longitudinal change.

RESULTS

Using all ROIs by all readers, mean PDFF at baseline, at EOT, and mean change in PDFF was 16.1%, 16.0%, and 0.07%, respectively. The 27-ROI PDFF measurements had 0.998 ICC and 1.8% CV at baseline, 0.998 ICC and 1.8% CV at EOT, and 0.997 ICC for longitudinal change. The 9-ROI PDFF measurements had corresponding values of 0.997 and 2.6%, 0.996 and 2.4%, and 0.994. Using 27 ROIs, the magnitude of the bias between readers for whole-liver PDFF measurement ranged from 0.03% to 0.06% points at baseline, 0.01% to 0.07% points at EOT, and 0.01% to 0.02% points for longitudinal change.

CONCLUSION

Inter-reader agreement for measuring whole-liver PDFF and its longitudinal change is high. 9-ROI measurements have only slightly lower agreement than 27-ROI measurements.

Diagnostic accuracy of magnetic resonance imaging hepatic proton density fat fraction in pediatric nonalcoholic fatty liver disease

We assessed the performance of magnetic resonance imaging (MRI) proton density fat fraction (PDFF) in children to stratify hepatic steatosis grade before and after treatment in the Cysteamine Bitartrate Delayed-Release for the Treatment of Nonalcoholic Fatty Liver Disease in Children (CyNCh) trial, using centrally scored histology as reference. Participants had multiecho 1.5 Tesla (T) or 3T MRI on scanners from three manufacturers. Of 169 enrolled children, 110 (65%) and 83 (49%) had MRI and liver biopsy at baseline and at end of treatment (EOT; 52 weeks), respectively. At baseline, 17% (19 of 110), 28% (31 of 110), and 55% (60 of 110) of liver biopsies showed grades 1, 2, and 3 histological steatosis; corresponding PDFF (mean ± SD) values were 10.9 ± 4.1%, 18.4 ± 6.2%, and 25.7 ± 9.7%, respectively. PDFF classified grade 1 versus 2-3 and 1-2 versus 3 steatosis with areas under receiving operator characteristic curves (AUROCs) of 0.87 (95% confidence interval [CI], 0.80, 0.94) and 0.79 (0.70, 0.87), respectively. PDFF cutoffs at 90% specificity were 17.5% for grades 2-3 steatosis and 23.3% for grade 3 steatosis. At EOT, 47% (39 of 83), 41% (34 of 83), and 12% (10 of 83) of biopsies showed improved, unchanged, and worsened steatosis grade, respectively, with corresponding PDFF (mean ± SD) changes of -7.8 ± 6.3%, -1.2 ± 7.8%, and 4.9 ± 5.0%, respectively. PDFF change classified steatosis grade improvement and worsening with AUROCs (95% CIs) of 0.76 (0.66, 0.87) and 0.83 (0.73, 0.92), respectively. PDFF change cut-off values at 90% specificity were -11.0% and +5.5% for improvement and worsening.

CONCLUSION

MRI-estimated PDFF has high diagnostic accuracy to both classify and predict histological steatosis grade and change in histological steatosis grade in children with NAFLD. (Hepatology 2018;67:858-872).

Accuracy of PDFF estimation by magnitude-based and complex-based MRI in children with MR spectroscopy as a reference

PURPOSE

To assess and compare the accuracy of magnitude-based magnetic resonance imaging (MRI-M) and complex-based MRI (MRI-C) for estimating hepatic proton density fat fraction (PDFF) in children, using MR spectroscopy (MRS) as the reference standard. A secondary aim was to assess the agreement between MRI-M and MRI-C.

MATERIALS AND METHODS

This was a HIPAA-compliant, retrospective analysis of data collected in children enrolled in prospective, Institutional Review Board (IRB)-approved studies between 2012 and 2014. Informed consent was obtained from 200 children (ages 8-19 years) who subsequently underwent 3T MR exams that included MRI-M, MRI-C, and T1 -independent, T2 -corrected, single-voxel stimulated echo acquisition mode (STEAM) MRS. Both MRI methods acquired six echoes at low flip angles. T2*-corrected PDFF parametric maps were generated. PDFF values were recorded from regions of interest (ROIs) drawn on the maps in each of the nine Couinaud segments and three ROIs colocalized to the MRS voxel location. Regression analyses assessing agreement with MRS were performed to evaluate the accuracy of each MRI method, and Bland-Altman and intraclass correlation coefficient (ICC) analyses were performed to assess agreement between the MRI methods.

RESULTS

MRI-M and MRI-C PDFF were accurate relative to the colocalized MRS reference standard, with regression intercepts of 0.63% and -0.07%, slopes of 0.998 and 0.975, and proportion-of-explained-variance values (R2 ) of 0.982 and 0.979, respectively. For individual Couinaud segments and for the whole liver averages, Bland-Altman biases between MRI-M and MRI-C were small (ranging from 0.04 to 1.11%) and ICCs were high (≥0.978).

CONCLUSION

Both MRI-M and MRI-C accurately estimated hepatic PDFF in children, and high intermethod agreement was observed.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1641-1647.

Estimating of hepatic fat amount using MRI proton density fat fraction in a real practice setting

The recently developed magnetic resonance imaging (MRI) proton density fat fraction (PDFF) allows measurement of the fat in all segments of hepatic tissue. However, it is time consuming and inconvenient to measure each segment repeatedly. Moreover, volume of each segment also should be adjusted with arithmetic mean of the selected segments when total amount of liver fat is estimated. Therefore, we try to develop a clinically-relevant and applicable method of estimating hepatic fat in PDFF image.A total of 164 adults were enrolled. We addressed the measurement frequency and segment selection to determine the optimal method of measuring intrahepatic fat. Total hepatic fat was estimated by the weighted mean of each segment reflecting their respective segmental volumes. We designed 2 models. In Model 1, we determined the segment order by which the mean was closest to the whole weighted mean. In Model 2, we determined the segment order by which the arithmetic mean of the selected segments was closest to the whole weighted mean.Fat fraction (FF) was most important risk factor of hepatic heterogeneity in multivariable analysis (β = 0.534, P < .001). In severe fatty liver (FF > 22.1%), intrahepatic fat variability was 2.47% (1.16-6.26%). The arithmetic mean total intrahepatic FF was 12.66%. But the weighted mean that applied to each segmental volume was 12.90%. In Model 1, arithmetic mean of segments 4 and 5 was closest to the total estimated hepatic fat amount. However, when we added segment 8, the mean of segments 4, 5, and 8 was significantly different from the estimated total hepatic fat amount (P = .0021). In Model 2, arithmetic mean of segments 4 and 5 was closest to the total estimated hepatic fat amount. There was a significant reduction in variability between segment 4 and segments 4 and 5 (P < .0001).Averaging the mean hepatic FF of segments 4 and 5 was the most reasonable method for estimating total intrahepatic fat in practice.