Dataset Information

Standardized Approach for ROI-Based Measurements of Proton Density Fat Fraction and R2* in the Liver.

ABSTRACT: OBJECTIVE:The purpose of this study was to evaluate the reproducibility (interreviewer agreement) and repeatability (intrareviewer agreement) of ROI sampling strategies to measure chemical shift-encoded (CSE) MRI-based liver proton density fat fraction (PDFF) and R2* (1 / T2*). A secondary purpose was to standardize ROI-based liver PDFF and R2* measurements by providing a compromise between measurement reproducibility and repeatability and time burden for image analysts. MATERIALS AND METHODS:CSE data from two cohorts were retrospectively analyzed. Cohort A included 53 patients referred for abdominal MRI and healthy subjects recruited for a comparison study of CT and MRI. Cohort B included 37 patients with suspected liver iron overload. Three reviewers measured liver PDFF and R2* using previously reported ROI sampling strategies. Inter- and intrareviewer agreement of liver PDFF and R2* were evaluated using Bland-Altman analysis. RESULTS:Averaging largest-fit ROIs over the nine Couinaud segments resulted in the narrowest limits of agreement (LOA) for liver PDFF and R2* measurements in both cohorts. For PDFF, interreviewer agreement had mean LOA of ± 0.8% for cohort A and ± 1.7% for cohort B. Intrareviewer agreement was ± 0.5% for cohort A and ± 0.9% for cohort B. For R2* interre-viewer agreement had mean LOA of ± 3.0 s-1 for cohort A and ± 17.9 s-1 for cohort B. Intrare-viewer agreement was ± 2.6 s-1 for cohort A and ± 14.6 s-1 for cohort B. This approach was the most time-burdensome, requiring a mean ± SD of 149.7 ± 8.6 s per dataset. CONCLUSION:For improved reproducibility and repeatability of liver PDFF and R2* measurements, clinicians and researchers should sample as much area of the liver as possible using multiple large ROIs.

SUBMITTER: Campo CA

PROVIDER: S-EPMC5639884 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Standardized Approach for ROI-Based Measurements of Proton Density Fat Fraction and R2* in the Liver.

Campo Camilo A CA Hernando Diego D Schubert Tilman T Bookwalter Candice A CA Pay Andrew J Van AJV Reeder Scott B SB

AJR. American journal of roentgenology 20170713 3

<h4>Objective</h4>The purpose of this study was to evaluate the reproducibility (interreviewer agreement) and repeatability (intrareviewer agreement) of ROI sampling strategies to measure chemical shift-encoded (CSE) MRI-based liver proton density fat fraction (PDFF) and R2* (1 / T2*). A secondary purpose was to standardize ROI-based liver PDFF and R2* measurements by providing a compromise between measurement reproducibility and repeatability and time burden for image analysts.<h4>Materials and ...[more]

PMID: 28705058

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Project description:Purpose To determine the linearity, bias, and precision of hepatic proton density fat fraction (PDFF) measurements by using magnetic resonance (MR) imaging across different field strengths, imager manufacturers, and reconstruction methods. Materials and Methods This meta-analysis was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A systematic literature search identified studies that evaluated the linearity and/or bias of hepatic PDFF measurements by using MR imaging (hereafter, MR imaging-PDFF) against PDFF measurements by using colocalized MR spectroscopy (hereafter, MR spectroscopy-PDFF) or the precision of MR imaging-PDFF. The quality of each study was evaluated by using the Quality Assessment of Studies of Diagnostic Accuracy 2 tool. De-identified original data sets from the selected studies were pooled. Linearity was evaluated by using linear regression between MR imaging-PDFF and MR spectroscopy-PDFF measurements. Bias, defined as the mean difference between MR imaging-PDFF and MR spectroscopy-PDFF measurements, was evaluated by using Bland-Altman analysis. Precision, defined as the agreement between repeated MR imaging-PDFF measurements, was evaluated by using a linear mixed-effects model, with field strength, imager manufacturer, reconstruction method, and region of interest as random effects. Results Twenty-three studies (1679 participants) were selected for linearity and bias analyses and 11 studies (425 participants) were selected for precision analyses. MR imaging-PDFF was linear with MR spectroscopy-PDFF (R2 = 0.96). Regression slope (0.97; P < .001) and mean Bland-Altman bias (-0.13%; 95% limits of agreement: -3.95%, 3.40%) indicated minimal underestimation by using MR imaging-PDFF. MR imaging-PDFF was precise at the region-of-interest level, with repeatability and reproducibility coefficients of 2.99% and 4.12%, respectively. Field strength, imager manufacturer, and reconstruction method each had minimal effects on reproducibility. Conclusion MR imaging-PDFF has excellent linearity, bias, and precision across different field strengths, imager manufacturers, and reconstruction methods. © RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on October 2, 2017.

Project description:BackgroundWhole-organ, noninvasive techniques for the detection and quantification of nonalcoholic fatty liver disease features have clinical and research applications. However, the effect of time of day, hydration status, and meals are unknown factors with potential to impact bias, precision, reproducibility, and repeatability of chemical shift-encoded MRI (CSE-MRI) to quantify liver proton density fat fraction (PDFF).PurposeTo assess the effect of diurnal variation on PDFF using CSE-MRI, including the effect of time of day, the effect of meals and hydration status, as well as the day to day variability.Study typeProspective.SubjectsEleven healthy subjects and nine patients with observed hepatic steatosis.Field strength/sequencesA commercial quantitative confounder-corrected CSE-MRI sequence (IDEAL IQ) and an MR spectroscopy (MRS) sequence (multiecho STEAM) were acquired at 1.5T.AssessmentMRI-PDFF and MRS-PDFF estimates were compared across six visits (before and after a controlled breakfast, before and after an uncontrolled lunch, at approximately 4 pm, and then before breakfast on the following day) with three repeated measures for a total of 360 MRI-PDFF and MRS-PDFF measurements.Statistical testsLinear regression, Bland-Altman analysis, and mixed effect models were used to determine the bias, precision, and repeatability of PDFF measurements.ResultsNo statistically significant linear trend was observed across visits for either MRI-PDFF or MRS-PDFF (P = 0.31 and 0.37, respectively). The repeatability was measured to be 0.86% for MRI-PDFF and 1.1% for MRS-PDFF over all six visits. For MRI-PDFF, the variability between all six visits (0.94%) was only slightly higher than within each visit (0.66%), with P < 0.001. For MRS-PDFF, the variability between all six visits was 1.29%, compared with 0.87% within each visit (P < 0.001).Data conclusionOur results may indicate that it is not necessary to control for the time of day or the fasting/fed state of the patient when measuring PDFF using CSE-MRI.Level of evidence2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:407-414.

Project description:Background & aimsPathologists quantify liver steatosis as the fraction of lipid droplet-containing hepatocytes out of all hepatocytes, whereas the magnetic resonance-determined proton density fat fraction (PDFF) reflects the tissue triacylglycerol concentration. We investigated the linearity, agreement, and correspondence thresholds between histological steatosis and PDFF across the full clinical spectrum of liver fat content associated with non-alcoholic fatty liver disease.MethodsUsing individual patient-level measurements, we conducted a systematic review and meta-analysis of studies comparing histological steatosis with PDFF determined by magnetic resonance spectroscopy or imaging in adults with suspected non-alcoholic fatty liver disease. Linearity was assessed by meta-analysis of correlation coefficients and by linear mixed modelling of pooled data, agreement by Bland-Altman analysis, and thresholds by receiver operating characteristic analysis. To explain observed differences between the methods, we used RNA-seq to determine the fraction of hepatocytes in human liver biopsies.ResultsEligible studies numbered 9 (N = 597). The relationship between PDFF and histology was predominantly linear (r = 0.85 [95% CI, 0.80-0.89]), and their values approximately coincided at 5% steatosis. Above 5% and towards higher levels of steatosis, absolute values of the methods diverged markedly, with histology exceeding PDFF by up to 3.4-fold. On average, 100% histological steatosis corresponded to a PDFF of 33.0% (29.5-36.7%). Targeting at a specificity of 90%, optimal PDFF thresholds to predict histological steatosis grades were ≥5.75% for ≥S1, ≥15.50% for ≥S2, and ≥21.35% for S3. Hepatocytes comprised 58 ± 5% of liver cells, which may partly explain the lower values of PDFF vs. histology.ConclusionsHistological steatosis and PDFF have non-perfect linearity and fundamentally different scales of measurement. Liver fat values obtained using these methods may be rendered comparable by conversion equations or threshold values.Impact and implicationsMagnetic resonance-proton density fat fraction (PDFF) is increasingly being used to measure liver fat in place of the invasive liver biopsy. Understanding the relationship between PDFF and histological steatosis fraction is important for preventing misjudgement of clinical status or treatment effects in patient care. Our analysis revealed that histological steatosis fraction is often significantly higher than PDFF, and their association varies across the spectrum of fatty liver severity. These findings are particularly important for physicians and clinical researchers, who may use these data to interpret PDFF measurements in the context of histologically evaluated liver fat content.

Project description: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.

Dataset Information

Standardized Approach for ROI-Based Measurements of Proton Density Fat Fraction and R2* in the Liver.

Publications

Standardized Approach for ROI-Based Measurements of Proton Density Fat Fraction and R2* in the Liver.

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