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. 2021 Jul 13;16(7):e0252928. doi: 10.1371/journal.pone.0252928

A comparison of liver fat fraction measurement on MRI at 3T and 1.5T

Lavanya Athithan 1,*, Gaurav S Gulsin 1, Michael J House 2,3, Wenjie Pang 3, Emer M Brady 1, Joanne Wormleighton 1, Kelly S Parke 1, Matthew Graham-Brown 1, Tim G St Pierre 2, Eylem Levelt 1,¤, Gerry P McCann 1
Editor: Peter Lundberg4
PMCID: PMC8277031  PMID: 34255778

Abstract

Purpose

Volumetric liver fat fraction (VLFF) measurements were made using the HepaFat-Scan® technique at 1.5T and 3T to determine the agreement between the measurements obtained at the two fields.

Methods

Sixty patients with type 2 diabetes (67% male, mean age 50.92 ± 6.56yrs) and thirty healthy volunteers (50% male, mean age 48.63 ± 6.32yrs) were scanned on 1.5T Aera and 3T Skyra (Siemens, Erlangen, Germany) MRI scanners on the same day using the HepaFat-Scan® gradient echo protocol with modification of echo times for 3T (TEs 2.38, 4.76, 7.14 ms at 1.5T and 1.2, 2.4, 3.6 ms at 3T). The 3T analyses were performed independently of the 1.5T analyses by a different analyst, blinded from the 1.5T results. Data were analysed for agreement and bias using Bland-Altman methods and intraclass correlation coefficients (ICC). A second cohort of 17 participants underwent interstudy repeatability assessment of VLFF measured by HepaFat-Scan® at 3T.

Results

A small, but statistically significant mean bias of 0.48% was observed between 3T and 1.5T with 95% limits of agreement -2.2% to 3.2% VLFF. The ICC for agreement between field strengths was 0.983 (95% CI 0.972–0.989). In the repeatability cohort studied at 3T the repeatability coefficient was 4.2%. The ICC for agreement was 0.971 (95% CI 0.921–0.989).

Conclusion

There is minimal bias and excellent agreement between the measures of VLFF using the HepaFat-Scan® at 1.5 and 3T. The test retest repeatability coefficient at 3T is comparable to the 95% limits of agreement between 1.5T and 3T suggesting that measurements can be made interchangeably between field strengths.

Introduction

Non-alcoholic fatty liver disease (NAFLD) poses a significant healthcare burden with its incidence affecting 17–46% of adults in Western countries [1, 2]. A hallmark of NAFLD is the increased accumulation of triglyceride content within hepatocytes that results in steatosis [3, 4]. Many studies have shown that hepatic fat content is associated with obesity related metabolic complications [5, 6]. The global prevalence of NAFLD in type 2 diabetes (T2DM) is now 55.5% and the presence of insulin resistance and diabetes is considered a risk factor for more severe liver disease in NAFLD [7, 8].

Liver biopsy has been regarded as the gold standard to diagnose and stage NAFLD [1]. However, this is an invasive, uncomfortable procedure with significant procedural risks, including infection, and major haemorrhage [9]. Liver biopsy is also subject to sampling variability [10–12]. As such, appropriate non-invasive methods of liver fat measurements are desirable. Over recent years, proton density fat fraction (PDFF) has emerged as the preferred non-invasive quantitative imaging biomarker in the diagnosis and grading of hepatic steatosis [12, 13]. PDFF measurement by spectroscopy has been the accepted gold standard of reference used in the quantification of liver steatosis as it has the ability to measure the proton densities of triglyceride content within liver tissue [14–16].

PDFF measurements have been previously compared between 1.5T and 3T, using different manufacturers [16–20]. The largest comparison cohort across manufacturers was in n = 24 obese individuals which made a comparison of 1.5T Ingenia Philips, 3T Ingenia Philips and 3T 750 W GE. The mean Bland-Altman bias was -1.75% in the comparison of two Phillips scanner and -2.4% in the comparison of 1.5T Phillips against 3T GE [13, 18]. Yokoo et al. have conducted a meta-analysis that included 80 participants who had PDFF measured across both 1.5T and 3T using the same technique [16]. The mean bias associated with field strength for this meta-analysis was -1.2%. Other smaller cohorts have compared normal individuals against phantoms, diabetics against non-diabetics and children, with biases varying between -0.4 to +1.2% [17–20].

The fractional area of fatty vesicles seen in thin histopathology liver biopsy sections is numerically equivalent to the volumetric fraction of liver tissue occupied by fatty vesicles (the Delesse Principle) [21, 22]. HepaFat-Scan® is a proprietary magnitude-based MRI technique for measuring VLFF based on a series of 2D MR images that considers confounding factors. Adjustments are made to account for T2* decay, T1-amplification, noise bias, the differential between T1 relaxation times in water and fat, and the relative amount of MRI visible liver tissue. HepaFat-Scan® results have been shown to have negligible bias against biopsy and very high sensitivities and specificities for diagnosing all grades of liver steatosis [23]. The data acquisition protocol for HepaFat-Scan® was developed at a field strength of 1.5T, and has been modified for use at 3T prior to this study. The agreement between VLFF measurements acquired using HepaFat-Scan® measured at 3T and 1.5T has not been previously described. Furthermore, there have also been no previous studies comparing VLFF measurements of any technique using two Siemens scanners at different field strengths. The comparative interstudy repeatability of the VLFF measurements using HepaFat-Scan® at the different field-strengths as well as at 3T alone has also not been defined.

The primary purpose of this study was to compare the agreement of VLFF measurements made using the HepaFat-Scan® technique acquired at 1.5T and 3T. We hypothesised that there would be good agreement and no significant bias between field strengths. We also assessed the interstudy repeatability of VLFF measurement using the HepaFat-Scan® technique at 3T.

Methods

Study design

This was a single-centre prospective, cross-sectional case-control study conducted at the National Institute for Health Research (NIHR) Leicester Biomedical Research Centre and University Hospitals of Leicester NHS Trust. The study was conducted with the approval of the West Midlands–Coventry & Warwickshire Research Ethics Committee (REC Ref: 15/WM/0222) and Solihull Research Ethics Committee (REC Ref: 17/WM/0192) in accordance with the ethical standards of the UK REC and Health Research Authority (HRA) in line with the Helsinki Declaration. All participants recruited were over the age of 18. Written informed consent was obtained on ethics committee approved consent forms that were stored in accordance with study protocol. Participants were also provided with a copy of the signed consent form.

Study population

The baseline MRI scans of 90 participants from the DIASTOLIC trial (NCT02590822), assessing the effects of low-calorie diet and a structured program of exercise on cardiac structure and function were included for analysis. This consisted of 60 participants with diabetes and 30 healthy volunteers. Detailed study design and rationale as well as inclusion and exclusion criteria of participants are as previously described [24]. Healthy volunteers were recruited through interests from mailing out and poster advertisements. The inter-study repeatability cohort comprised of 17 participants from the PREDICT study (NCT03132129), made up of both diabetics and healthy volunteers.

MRI scan protocol

Participants underwent serial MRI examinations that included a multiparametric cardiac scan as well as assessment of the liver and pancreas on a 1.5T (Aera, Siemens Medical Imaging, Erlangen, Germany) and 3T (Skyra, Siemens Medical Imaging, Erlangen, Germany) MR platform using an 18-channel phased array receiver coil. Both scans were conducted on the same day one after the other. The coil was centred over the participant’s heart and liver. MRI data acquisition for measurement of VLFF via the HepaFat-Scan® protocol at 1.5T comprised an opposed-phase, in-phase, opposed-phase gradient echo sequence (TEs 2.38, 4.76, 7.14 ms, respectively, TR 88 ms, 1 excitation, flip angle 70 degrees, bandwidth 500 Hz) with a 10 second breath hold. Data from three 2D axial slices, positioned through the widest part of the liver, were acquired in a single breath-hold. The slice thickness was 4 mm and the matrix was 256 x 256 with a field of view 400 x 400 mm. The 3T HepaFat-Scan® acquisition used a similar gradient echo sequence again using three axial slices with modification of the TEs (1.2, 2.4, 3.6 ms, respectively), bandwidth 1300 Hz, and the number of slices. All other parameters were the same as the 1.5T acquisition.

MRI image analysis

Quality control procedures were used to ensure data acquisition parameters included were accurate on all scans and conformed to the requirements of the protocol. Anonymised data were sent to Resonance Health for analysis and the HepaFat-Scan® result for both field strengths was calculated in an identical manner as previously described [23]. All analyses were conducted offline by two separate blinded observers at the core laboratory.

The measurements were processed by the HepaFat-Scan® software (Resonance Health Analysis Services Pty Ltd, Burswood, Australia) to generate a VLFF. Two regions of interest (ROI) about 580 mm2 were delineated within the right and left lobes of the liver on each of the three MRI slices, avoiding large intrahepatic vessels and any obvious motion-affected regions. The image intensity was measured within the liver ROIs and also in an artefact-free region of free space outside of the patient to sample the background signal levels. Fig 1 illustrates a series of images that better describes this process. The background signal was subtracted in quadrature from the liver signal of each echo time before further processing. The raw T2*-corrected Dixon ratio, α, was calculated for each ROI as previously described [25]. To generate the VLFF, the α value is further corrected using the relationship defined between α, the VLFF and a constant k [25]. The constant k takes into account i) the specific sequence acquisition parameters (TR, flip angle), ii) the difference in T1 longitudinal relaxation times between fat and liver water, iii) the ratio of the proton density in fat to the proton density in non-fatty liver tissue, and iv) the volume ratio between the MR-visible water phase and the MR-invisible phase. The VLFF in each ROI was then averaged to produce a single unconfounded VLFF result.

Fig 1. Example of MRI image acquired and analysis process.

Fig 1

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Top Row: Axial magnetic resonance images acquired at 1.5 T for VLFF measurement. Left: 2.38 ms (opposed phase), Middle: 4.76 ms (in phase), Right: 7.14 ms (opposed phase). Middle Row: Axial magnetic resonance images acquired at 3 T for VLFF measurement. Left: 1.21 ms (opposed phase), Middle: 2.38 ms (in phase), Right: 3.57 ms (opposed phase). Last Row: In-phase magnetic resonance images acquired at 1.5T (left) and 3T (right) for the same individual. The green ROIs indicate the two regions used for the analysis at each field strength. At 1.5T the VLFFs for regions 1 and 2 were 27.1% and 28.2%. At 3T the VLFFs for regions 1 and 2 were 28.5% and 28.0%.

The 3T analyses were performed independently of the 1.5T analyses. A different analyst, blinded from the 1.5T results, analysed the 3T data and no attempt was made to match the slices or regions of interest used in the 1.5T analyses.

Inter-study repeatability

Interstudy repeatability of VLFF measured by HepaFat-Scan® at 3T was assessed in 17 participants (15 participants with T2DM and 2 healthy volunteers) completely independent of the previous cohort of 90 participants, consented to and completed a repeat scan at 3T under identical conditions within 20 days of their baseline visit. Acquisition parameters were identical to the first scan, but no attempt was made to match slice locations or analysis regions of interest and analysts were blinded to the identity of the participants.

Statistical analysis

Data was analysed using SPSS Statistics version 25. Normally distributed data are shown as mean ± standard deviation and non-normally distributed data are expressed as median (interquartile range). The Bland-Altman method was used to calculate and display limits of agreement between measures and the presence of systematic bias between VLFF at different field strengths, and to assess the interstudy repeatability at 3T. The statistical significance of any bias was tested using a one-sample t-test. Two-way, random effect, intraclass correlation coefficients (ICCs) for absolute agreement was also used to assess the agreement of VLFF measures between repeat measurements at 3T.

Results

Baseline characteristics

The baseline MRI scans of 90 participants were included for analysis. This included 60 participants with type 2 diabetes and 30 healthy volunteers. Sixty seven percent of the participants with diabetes were male, and fifty percent of healthy volunteers were male. Mean age for participants with diabetes was 50.92 ± 6.56 yrs, mean BMI 36.50 ± 5.75 and for healthy volunteers mean age was 48.63 ± 6.32 yrs, BMI 24.32 ± 2.38 kg/m2.

Mean VLFF values at both 1.5T and 3T were significantly higher in diabetics (12.65 ± 7.34% at 1.5 T;13.34 ± 7.77% at 3T) compared to healthy volunteers (2.72 ± 1.80% at 1.5T; 2.76 ± 1.68% at 3T).

Interfield comparison and repeatability

Bland-Altman analysis showed good agreement and the mean bias between 3T and 1.5T was small at 0.48% (95% CI 0.19–0.77%) VLFF with 95% limits of agreement between 3.2 and -2.2% (Fig 2). This mean bias was statistically significant (t = 3.292, P = 0.001).

Fig 2. Comparison of VLFF (%) at 3T vs 1.5T.

Fig 2

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2(A) Liver VLFF measurement at 3T plotted against Liver VLFF measurement at 1.5T for the 90 subjects. The solid line is the line of equivalence. 2(B) The difference between the VLFF measured at 3T and the VLFF measured at 1.5T plotted against the mean of the 1.5T and 3T measurements for the 90 subjects. The dashed line is the mean bias and the solid lines indicate +/- 95% limits of agreement.

There was excellent agreement between the two field strength measurements of liver VLFF with ICC = 0.983 (95% CI 0.972–0.989) for single measures. The descriptive statistics are detailed within Table 1 with graphical representation in Fig 2.

Table 1. Values and statistical tests for inter-field strength comparison and repeatability cohort.

Interfield Comparison Values (95% CI)
Mean bias 0.48 (0.19–0.77) % VLFF
95% limits of agreement -2.2 to 3.2% VLFF
ICC for absolute agreement 0.983 (0.972–0.989)
Repeatability Cohort Values
Repeatability Coefficient 4.2 (2.8–5.6) % VLFF
ICC for absolute agreement 0.971 (0.921–0.989)
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Test-retest repeatability

The group of subjects for repeatability testing consisted of 15 with diabetes and 2 healthy volunteers who were 53% male, mean age was 63 years and average BMI 29.8 kg/m2. The average interval between scans for patients undergoing inter-study repeatability at 3T was 9.4 days (range 6–20 days). Table 1 details the significant statistical values for this analysis. The Mean VLFF % at 3T on visit 1 was 10.5 ± 8.99% and visit 2 10.9 ± 9.0%. Agreement was excellent with ICC of 0.971 (95% CI 0.921–0.989).

Fig 3 illustrates the VLFF repeatability data at 3T. The repeatability coefficient was 4.2% (95% CI 2.8–5.6%) at 3T indicating that 95% of pairs of measurements are expected to fall within 4.2% VLFF of each other. One pair of measurements from our study showed a large difference of 6% VLFF across a period of 7 days. While a real change in the VLFF cannot be ruled out, there were some technical differences between the data acquisitions. The first analysis from this participant was limited to a single ROI on a more inferiorly positioned slice compared to the second analysis where two ROIs (one in each lobe) were able to be positioned. Potentially this difference in anatomical position and number of analysed ROIs may have impacted on the repeatability of this case. Omitting this case would reduce the repeatability coefficient to 3.2%.

Fig 3. Repeatability of VLFF Measurements at 3T.

Fig 3

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(A) 3T VLFF at visit 1 plotted against 3T VLFF at visit 2. The solid line is the line of equivalence. (B) The difference between 3T VLFF at visit 1 and 3T VLFF at visit 2 plotted against the mean VLFF of visit 1 and visit 2. The solid lines indicate the 95% repeatability coefficient.

Discussion

This is the largest single cohort of patients scanned on the same day across two field strengths on scanners of the same manufacturer to measure liver fat fraction. It is the first study to assess the degree of agreement of HepaFat-Scan® VLFF measurements at 3T with those at 1.5T. This study also includes a test-retest repeatability cohort. The measurements obtained span a large range and include both participants with diabetes as well as healthy volunteers. Even examined as individual groups, these groups are larger cohorts than have previously been studied in inter-field comparisons.

The data from this study indicate very good agreement between VLFF measures at these two field strengths. The small bias measured between 1.5T and 3T VLFF (0.48%, 95% CI 0.19–0.77%) is comparable with and generally smaller than other examples from the literature [13, 17, 18]. Although the mean bias was statistically significant, the small magnitude of the mean differences suggests that the interchangeable use of HepaFat-Scan results from 1.5T and 3T is unlikely to impact clinical decision making.

Although the VLFF values between the two groups are very different, with the participants with diabetes having strikingly higher values than healthy volunteers, the agreement remains excellent. This shows that at either field strength, HepaFat-Scan® VLFF measurements clearly distinguishes between health and disease states.

This study cohort has shown a positive bias in the difference between 3T and 1.5T MRI liver fat measurements (i.e. 3T VLFF higher on average than 1.5T VLFF). In the most recently published comparison of MRI-PDFF between two field strengths, both in GE scanners, although in a small population the magnitude of the bias was similar to our study, i.e. 0.4%, however it was a negative bias (i.e. 1.5T PDFF higher than 3T PDFF). Note that while PDFF and VLFF are different physical aspects of liver fat concentration, they are numerically very similar in magnitude and are strongly correlated with each other. Hence this is the basis of the validity of these comparisons. While two recent studies also reported that on average the MRI-PDFF at 1.5T was higher than at 3T, they also reported, conversely, that the 3T MRS-determined PDFF was higher on average than the 1.5 MRS-determined PDFF [13, 17]. In our study, the 3T scan was always conducted after the 1.5 T scan and this could also be a contributing factor to the bias.

The test-retest measurement of Hepafat-Scan® at 3T is again novel and showed excellent repeatability suggesting precise measurements and robust analysis methodology. Our repeatability coefficient, 4.2 (± 1.4)% at 3T is higher compared to the 2.3 (± 0.3) % reported by Kim et al. [20]. A potential reason for this has been explained within the results section. Therefore, we have a technique that agrees at different field strength both in disease states and healthy volunteers and has good test-retest repeatability. Importantly, the repeatability coefficient is comparable to the 95% limits of agreement between the results from 1.5T and 3T. Taken together with the clinically insignificant bias between the results from the two field strengths, the data suggest that the HepaFat-Scan® method can be used interchangeably between the two field strengths for clinical purposes.

Limitations

In principle, the small but systematic bias we measured could be used as a basis for correcting the 3T data, or vice versa, but as this is a single centre study confined to two specific Siemens scanners, it cannot be implied the results are applicable to other models and manufacturers although the excellent reproducibility is consistent with the previous literature. More data from other manufacturers would be required to determine whether the bias measured in this study using the Hepafat-Scan® methodology was applicable more widely. No phantom data acquisitions were made in this study, which may have limited the variability between field strength even further [26], however it is the measurement in patients that is clinically meaningful.

A limitation of this technique is that it does not sample the entire liver in 3D, but consists of three 2D slices. In the context of steatosis that is spatially heterogenous, this could present a potential problem in trying to colocalize images across longitudinal studies. Only one patient population was studied, diabetes, but this is unlikely to affect the results in other patients with steatosis since the analysis technique is generic.

Conclusion

Inter-field strength agreement between the VLFF measured using Hepafat Scan® at 1.5 and 3T is good in a mixed cohort of subjects with diabetes and healthy volunteers. There was a systematic positive bias in VLFF measured at 3T compared to 1.5T but this difference was so small as to be considered clinically unimportant. Repeatability of VLFF measured using Hepafat Scan® at 3T was comparable to the 95% limits of agreement between 1.5T and 3T suggesting that measurements can be made interchangeably between field strengths.

Data Availability

Data cannot be shared publicly because of the nature of the human research participant data. The data contains potentially identifying or sensitive patient information and availability of this data would not be in compliance with the ethical approvals obtained. Data are available from the University of Leicester NIHR Leicester Biomedical Research Centre and the Leicester Clinical Trials Unit Institutional Data Access for researchers who meet the criteria for access to confidential data. Contact via Sally Utton, Research Manager Cardiovascular Imaging Research Group. All requests for data to be submitted in writing to su47@leicester.ac.uk.

Funding Statement

The study was supported by the National Institute for Health Research (NIHR) Leicester Clinical Research facility and patients were recruited through a Career Development Fellowship granted to GPM. The NIHR provided support in the form of salary for GPM, research materials and study consumables. The salaries for LA and GSG was supported by Clinical Research Training Fellowships from the British Heart Foundation (BHF). The funders did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the "author contributions" section.

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Decision Letter 0

Peter Lundberg

23 Dec 2020

PONE-D-20-28831

A comparison of volumetric liver fat fraction measurement on MRI at 3T and 1.5T.

PLOS ONE

Dear Dr. Athithan,

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Reviewers' comments:

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

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Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

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Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: PLOS ONE PONE-D-20-28831 “A Comparison of Volumetric Liver Fat Fraction Measurement on MRI at 3T and 1.5T”

Summary: This is a well written article describing comparison of Volumetric Liver Fat Fraction (VLFF) aimed at determining the reproducibility of these measurements at 1.5T and 3T. The authors are using a proprietary technique, HepaFat-Scan, aimed at measuring liver fat content. As this is a proprietary technique, the technical details of this method are not well described and is a minor limitation of this work. The authors perform same day comparison in 60 patients and 30 healthy controls to assess the reproducibility of VLFF across field strength (1.5T v 3T). This has important practical consideration and therefore has value. The overall contribution to the field is modest, but these sorts of studies are important for those designing multicenter clinical trials where multiple MRI systems are being used. I have a number of comments that I believe should be addressed, as well as some larger philosophical issues that I describe below.

Specific Comments:

1. The term volumetric liver fat fraction is misleading. This implies that you are measuring volumetric liver fat content, ie: fat content over the entire volume of the liver. I realize that this is not what is being measured, but I would strongly discourage the use of this term, at least without a strong qualification early in the paper, and should be removed from the title of the paper. The term VLFF is unfortunate and arises from the calibration and assumption that the authors have performed in previous work comparing their method to the steatosis area fraction. The underlying assumption that volume fraction and area fraction from a biopsy slide are equivalent is not well accepted, in my opinion. It is certainly true that those will correlate well with one another, but I think that the term volumetric fraction is unfortunate and misleading. This term should either not be used in this paper or a major qualifier that addresses my concern is needed in the introduction and the abstract. I would ask that this term not be included in the title of the paper.

2. Related to the last point, a major limitation of this technique is that it is not “volumetric”. Rather, the method only measures liver fat over 3 slices. This is a major limitation for a variety of reasons including reproducibility for longitudinal studies. Unlike all commercial techniques that measure PDFF over the entire liver, ie: volumetric, the HepaFat-Scan technique does not. This is a problem for longitudinal reproducibility because it assumes that you can colocalize images across longitudinal studies, which is important because steatosis is known to be spatial heterogeneous. This limitation should be included in the Discussion. This is a same limitation that spectroscopy techniques have due to incomplete sampling of the liver (albeit not as bad for MRS).

3. This paper would have been much stronger had it done a direct comparison with VLFF and PDFF. Given that PDFF only requires a single breath hold for the entire liver, and these methods are available on Siemens scanners, I am a little surprised that this wasn’t performed. If these data are available, I would highly recommend that you include them here. It would be good to understand the relative performance across field strength of the two techniques.

4. Please specify that the HepaFat-Scan technique is a 2D technique. Please include the breath-hold time.

5. In the Introduction, please avoid the term “global pandemic”. Bad choice of words in 2020.

6. In the last paragraph of the first page of the introduction describing a cohort of 25 obese individuals, this study was performed only with GE scanners, not Philips and GE. Related to this general area the authors are making a big deal out of the fact that there are no other studies comparing the reproducibility of 1.5T versus 3T for liver fat measurements with MRI. This is somewhat disingenuous. It is true that there are not many studies with direct comparison on the same day, in the same subjects. However, if you read the Yokoo meta-analysis paper in Radiology which had over 1,600 patients, you will note that a large number of these patients has both 1.5T and 3T using the same spectroscopy technique. Therefore, that paper was able to assess the reproducibility of PDFF measurements across field strength in a very large number of patients. Please include those numbers in the introduction and please tone down the language highlighting the fact that this study has such a large number of patients to assess reproducibility. I do agree that the current paper is the largest study (60 patients, 30 healthy controls) with direct same day comparison, but the way it’s currently phrased is a little misleading.

7. Not many technical details about the proprietary technique are provided. This is fine but is a weakness of the study and should be acknowledged in the discussion. A few other questions that are remaining: how is the spectral complexity of fat considered in the fit for water and fat signals, and how are phase shifts related to concomitant gradients in eddy currents handled? Is this a magnitude-based technique? A few more details to this effect would be reasonable and helpful to the reviewers.

8. A limitation of the interstudy repeatability is that repeat scans 20 days after their baseline can lead to significant bias, especially if there is treatment that is occurring during this time (I believe this was one of the weight loss studies?). Further, variation in steatosis can occur over this time frame. The fact that 3T imaging occurred after 1.5T is another potential source of bias. These limitations should be addressed in the discussion.

9. First sentence of the discussion “largest single cohort of patients scanned on the same day across 2 field strengths”. Again, this is technically correct, but somewhat misleading considering the scope and magnitude of the Yokoo meta-analysis. Please see my comment above.

10. The figures appear very pixelated in my version. I am assuming that this was related to the submission process. Assuming that they are higher resolution, the quality of the figures looks good.

11. The use of a single vendor for this comparison limits the generalizability of this study. In addition, the Siemens scanners are actually 2.89T, not 3.0T, thus in my opinion, this sort of study would also need to be performed on Philips and GE systems in order to demonstrate generalizability. A comment to this effect, including the fact that the Siemens magnet is lower than 3.0T, should be included in the Discussion.

Summary: Overall, this sort of study has modest impact, but I do think is important for researchers looking to use the HepaFat-Scan method for multicenter studies that involve more than one platform, including 1.5T and 3T. I have a few minor concerns that I think should be easy for the authors to address. A limitation of this being a proprietary technique also limits my enthusiasm for the generalizability of these results. The limitation to a single vendor also limits my enthusiasm, as this does not provide the same of definitive reproducibility data that the Yokoo study provides for PDFF.

Reviewer #2: Summary

This study compares the measurement for liver fat fraction from two MR scanners from the same manufacturer at two different field strengths. There were two main research questions in this study. The first one was to evaluate the measurement of volumetric liver fat fraction (VLFF) when data has been acquired on a 1.5 T and a 3.0 T scanner. Both scanners were Siemens scanners and the data was acquired the same day. The second research question was to evaluate the repeatability of the VLFF measurement at 3T. They conclude that the repeatability results from the two 3T examinations are relatable with the 95 % limits of agreements of the 1.5 T and 3 T comparison, in which a significant but small bias was observed. Hence, they claim that the method for VLFF could be used interchangeable from choice of MR-scanners.

The authors present the study in a clear, easy interpretable way. It is easy to follow, clearly written and the authors addresses the literature well regarding alternative methodology for fat fractions measurement (although not comparing why an alternative to the PDFF measurement is needed and what benefits VLFF might addresses). However, in order to interpret the result properly and interpret the authors conclusions I do miss a few analyzes in the result part, mainly confidence intervals for the ICC as well as a residual plot/regression line for figure 2 and figure 3 to investigate potential proportional biases. My recommendation for this paper is therefore Minor Revision.

Below follows some discussion regarding specific areas for improvement:

Major issues

1. Introduction (Page 4, Row 53). At page 3 other common techniques are discussed for fat estimation using invasive a non-invasive techniques are discussed. However, page 4 starts with introducing VLFF without comparing it to the methodologies on page 3 more than it has comparable results to biopsy (based on ref 21). I miss a small motivation for VLFF as a technique. What benefits do it have compared to invasive methods or to spectroscopy and PDFF? Or are they totally interchangeable? Is there any situations where VLFF could be more beneficial?

2. Method (Page 6, Row 107): The number of slices for the 3 T acquisition is missing.

3. Method (Page 7, Row 131): The algorithm addresses correction for confounding factors including correction for different T1 relaxations times between fat and water signal, T2*-correction etc. However, no remarks are adressessed regarding B0 and B1 inhomogeneity. Is the VLFF measurement sensitive to that and how would it affect the results?

4. Method (Page 7, Row 151): Were there any reason for the “not on the same day” of the inter-scanner repeatability investigation at the 3T scanner? Would there be any benefits on testing the variability on the same day? `

5. Results (Page 9, Row 186): Please include the confidence interval (CI) for the ICC calculations (both for 1.5 vs 3T comparison as well as the 3 T repeatability investigation. Rephrase (if needed) the statement of the agreement. Include the CI in Table 1 and abstract.

6. Results (Page 9, Row 189) Table 1: Change “Values (CI)” change to “(95 % CI)”. Indicate the significance of the bias would help the interpretation of table 1 without needing to read the main text. Table 1 would increase the possibility to interpret the results if indicating the significant bias.

7. Results (Page 9, Row 176; Page 25 (Figure2)) No Residual plot or any analysis is done to investigate a potential proportional bias of the correlation. An overall overestimation of 3T compared to 1.5 T is observed. Although the bias is small, it might be valuable to investigate any proportional biases if intended use is for diagnosing fatty liver. Especially since the cut-off between healthy and fatty liver is considered to be as low as 5 %. Is it therefore possible to include a report of the looking at the residual plot or add a regression line at Figure 2 (and 3)?

8. Results (Page 25) Figure 2: Is it possible to increase the resolution of the Figure to increase readability? (In the PDF link I read and when I downloaded the .tiff image I found it hard to read figure 2 and figure 3. A higher resolution would increase the readability a lot. )

9. Results (Page 26) Figure 3: Is it possible to increase the resolution of the Figure to increase readability? (In the PDF link I read and when I downloaded the .tiff image I found it hard to read figure 2 and figure 3. A higher resolution would increase the readability a lot. )

10. Discussion (Page 11, Row 233): I find the paragraph starting with “It is also interesting to note that although the VLFF values between the two groups are very different…” is a bit out of scope, not necessarily correct, and hard for the reader to interpret themselves based on what is presented in the result section. The authors claim the VLFF clearly distinguish between health and diseased states but the only measurement we have access to as a reader is the mean value and standard deviation. So based on the population level, it seems that patients diagnosed with type II diabetes seems to have a higher fat fraction in there liver but we don't know the overlap or the distribution of the distribution of the fat content. However, the cohort are not included based on their known fatty liver status, but if they have a type II diabetes diagnose. I suggest removing this paragraph alternatively re-phrasing it to avoid misunderstandings. I don’t think the conclusions from that paragraph is possible based on the data that was provided.

Minor issues

11. Results (Page 24) Figure 1: Is it possible to increase the size of number 1 and 2 of the ROI:s alternatively increase the resolution a bit for readability?

12. Results (Page 25 - Page 26) Figure 2 and Figure 3: In Figure 2, Bland-Altman is written with an “-“ in the middle. In Figure 3, Bland-Altman is written as to separate words. Consider being consequent.

13. Results (Page 26) Figure 3: In figure 3, indicate the unit (%) on the axes.

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2021 Jul 13;16(7):e0252928. doi: 10.1371/journal.pone.0252928.r002

Author response to Decision Letter 0

6 May 2021

Detailed response to each comment within "Response to Reviewer" document.

System will not allow all comments to be posted here despite multiple tries. ? Too large

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Decision Letter 1

Peter Lundberg

26 May 2021

A comparison of liver fat fraction measurement on MRI at 3T and 1.5T.

PONE-D-20-28831R1

Dear Dr. Athithan,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Peter Lundberg

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Peter Lundberg

5 Jul 2021

PONE-D-20-28831R1

A comparison of liver fat fraction measurement on MRI at 3T and 1.5T

Dear Dr. Athithan:

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    Data Availability Statement

    Data cannot be shared publicly because of the nature of the human research participant data. The data contains potentially identifying or sensitive patient information and availability of this data would not be in compliance with the ethical approvals obtained. Data are available from the University of Leicester NIHR Leicester Biomedical Research Centre and the Leicester Clinical Trials Unit Institutional Data Access for researchers who meet the criteria for access to confidential data. Contact via Sally Utton, Research Manager Cardiovascular Imaging Research Group. All requests for data to be submitted in writing to su47@leicester.ac.uk.

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