Title: Exploring Factors Associated with Non-Alcoholic Fatty Liver Disease Using
Longitudinal MRI
Version: 0 Date: 13 May 2024
Reviewer's report:
The manuscript titled "Exploring Causative Factors for Non-Alcoholic Fatty Liver Disease
Using Longitudinal MRI" describes a longitudinal study following participants from the general
population with the aim of determining what percentage of them develop fatty liver disease
and what factors are associated with fatty liver disease development over the 5 year follow-up
time. The authors use MRI-derived fat fraction measurements as the basis of their diagnosis
of fatty liver disease. Whilst the findings of the paper are interesting, these aren’t deserving a
grandiose title such as the authors have come up with. The methodology of this research does
not allow for the determination of causative factors, only association can be implied. As such,
I not only suggest toning down the title, but also rephrasing and clarifying the aim of the paper
to something like: "Therefore, the aim of this study is to identify factors associated with and a
risk score predicting the development of NAFLD over a 5-year period."
A few other comments can be found below.
Methods
- Perhaps make it clearer on Figure 1 which participant groups received MRI (e.g. by using
colour shading)
- I suggest including a flowchart describing participant selection from the SHIP-START-2 group
- The reported mean age doesn’t exactly match between the Methods section and the Abstract
- There are significant differences between the two sequences carried out at baseline and at
follow-up, e.g. the flip angle and the prescribed slice orientation - and the authors acknowledge
these limitations. However, the change of flip angle in particular is worrisome, as T1 bias will be
non-negligible when using FA=10°, leading to an overestimation of fat fraction. Please specify
whether the authors have corrected for this T1 bias.
- Authors are fairly vague when describing PDFF determination. Was an IDEAL approach used?
Again, differences in the two sequences will leave a mark here as more echo times employed
during the follow-up visit will lead to higher accuracy in determining fat fraction as they allow
for more precise accounting for multispectral lipid modelling and accurate R2* quantification.
- Instead of picking a data-driven cut-off for defining who has developed fatty liver disease
after 5 years, the authors should consider an absolute change of +/- 5% PDFF, as suggested
by the QIBA profile for PDFF of the liver (2023 edition, stage 2, longitudinal claim: https://
qibawiki.rsna.org/images/5/55/QIBA_PDFF_Profile_Stage2_FINAL.pdf)
- Intra- and inter-observer agreement is known to be very high for PDFF (see e.g. https://
doi.org/10.1007/s00261-018-1745-3). Reporting yet another set of ICCs and Bland-Altman
plots does not add anything new to the literature, and as such, I suggest removing this section
altogether.
- How was food frequency score defined? Similarly, how was arterial hypertension defined?
Results
- Please double check that numbers in Table 3 are correct. For example, the OR for BMI is
outside of the quoted 95% CI.
- Please be consistent with the use of abbreviations, e.g. ALAT vs ALT
- I suggest replacing “fictitious” with “hypothetical” in the example calculations of the risk score.
- Discrimination for what exactly is tested with the ROC analysis? I presume it’s identifying
fatty liver disease, but this needs to be specified. Please also report the 95% CI for the estimated
AUROC.
Title: Exploring Factors Associated with Non-Alcoholic Fatty Liver Disease Using
Longitudinal MRI
Version: 0 Date: 13 May 2024
Reviewer's report:
The manuscript titled "Exploring Causative Factors for Non-Alcoholic Fatty Liver Disease
Using Longitudinal MRI" describes a longitudinal study following participants from the general
population with the aim of determining what percentage of them develop fatty liver disease
and what factors are associated with fatty liver disease development over the 5 year follow-up
time. The authors use MRI-derived fat fraction measurements as the basis of their diagnosis
of fatty liver disease. Whilst the findings of the paper are interesting, these aren’t deserving a
grandiose title such as the authors have come up with. The methodology of this research does
not allow for the determination of causative factors, only association can be implied. As such,
I not only suggest toning down the title, but also rephrasing and clarifying the aim of the paper
to something like: "Therefore, the aim of this study is to identify factors associated with and a
risk score predicting the development of NAFLD over a 5-year period."
A few other comments can be found below.
Methods
- Perhaps make it clearer on Figure 1 which participant groups received MRI (e.g. by using
colour shading)
- I suggest including a flowchart describing participant selection from the SHIP-START-2 group
- The reported mean age doesn’t exactly match between the Methods section and the Abstract
- There are significant differences between the two sequences carried out at baseline and at
follow-up, e.g. the flip angle and the prescribed slice orientation - and the authors acknowledge
these limitations. However, the change of flip angle in particular is worrisome, as T1 bias will be
non-negligible when using FA=10°, leading to an overestimation of fat fraction. Please specify
whether the authors have corrected for this T1 bias.
- Authors are fairly vague when describing PDFF determination. Was an IDEAL approach used?
Again, differences in the two sequences will leave a mark here as more echo times employed
during the follow-up visit will lead to higher accuracy in determining fat fraction as they allow
for more precise accounting for multispectral lipid modelling and accurate R2* quantification.
- Instead of picking a data-driven cut-off for defining who has developed fatty liver disease
after 5 years, the authors should consider an absolute change of +/- 5% PDFF, as suggested
by the QIBA profile for PDFF of the liver (2023 edition, stage 2, longitudinal claim: https://
qibawiki.rsna.org/images/5/55/QIBA_PDFF_Profile_Stage2_FINAL.pdf)
- Intra- and inter-observer agreement is known to be very high for PDFF (see e.g. https://
doi.org/10.1007/s00261-018-1745-3). Reporting yet another set of ICCs and Bland-Altman
plots does not add anything new to the literature, and as such, I suggest removing this section
altogether.
- How was food frequency score defined? Similarly, how was arterial hypertension defined?
Results
- Please double check that numbers in Table 3 are correct. For example, the OR for BMI is
outside of the quoted 95% CI.
- Please be consistent with the use of abbreviations, e.g. ALAT vs ALT
- I suggest replacing “fictitious” with “hypothetical” in the example calculations of the risk score.
- Discrimination for what exactly is tested with the ROC analysis? I presume it’s identifying
fatty liver disease, but this needs to be specified. Please also report the 95% CI for the estimated
AUROC.
Please review this paper.
user
Title: Exploring Factors Associated with Non-Alcoholic Fatty Liver Disease Using
Longitudinal MRI
Version: 0 Date: 13 May 2024
Reviewer's report:
The manuscript titled "Exploring Causative Factors for Non-Alcoholic Fatty Liver Disease
Using Longitudinal MRI" describes a longitudinal study following participants from the general
population with the aim of determining what percentage of them develop fatty liver disease
and what factors are associated with fatty liver disease development over the 5 year follow-up
time. The authors use MRI-derived fat fraction measurements as the basis of their diagnosis
of fatty liver disease. Whilst the findings of the paper are interesting, these aren’t deserving a
grandiose title such as the authors have come up with. The methodology of this research does
not allow for the determination of causative factors, only association can be implied. As such,
I not only suggest toning down the title, but also rephrasing and clarifying the aim of the paper
to something like: "Therefore, the aim of this study is to identify factors associated with and a
risk score predicting the development of NAFLD over a 5-year period."
A few other comments can be found below.
Methods
- Perhaps make it clearer on Figure 1 which participant groups received MRI (e.g. by using
colour shading)
- I suggest including a flowchart describing participant selection from the SHIP-START-2 group
- The reported mean age doesn’t exactly match between the Methods section and the Abstract
- There are significant differences between the two sequences carried out at baseline and at
follow-up, e.g. the flip angle and the prescribed slice orientation - and the authors acknowledge
these limitations. However, the change of flip angle in particular is worrisome, as T1 bias will be
non-negligible when using FA=10°, leading to an overestimation of fat fraction. Please specify
whether the authors have corrected for this T1 bias.
- Authors are fairly vague when describing PDFF determination. Was an IDEAL approach used?
Again, differences in the two sequences will leave a mark here as more echo times employed
during the follow-up visit will lead to higher accuracy in determining fat fraction as they allow
for more precise accounting for multispectral lipid modelling and accurate R2* quantification.
- Instead of picking a data-driven cut-off for defining who has developed fatty liver disease
after 5 years, the authors should consider an absolute change of +/- 5% PDFF, as suggested
by the QIBA profile for PDFF of the liver (2023 edition, stage 2, longitudinal claim: https://
qibawiki.rsna.org/images/5/55/QIBA_PDFF_Profile_Stage2_FINAL.pdf)
- Intra- and inter-observer agreement is known to be very high for PDFF (see e.g. https://
doi.org/10.1007/s00261-018-1745-3). Reporting yet another set of ICCs and Bland-Altman
plots does not add anything new to the literature, and as such, I suggest removing this section
altogether.
- How was food frequency score defined? Similarly, how was arterial hypertension defined?
Results
- Please double check that numbers in Table 3 are correct. For example, the OR for BMI is
outside of the quoted 95% CI.
- Please be consistent with the use of abbreviations, e.g. ALAT vs ALT
- I suggest replacing “fictitious” with “hypothetical” in the example calculations of the risk score.
- Discrimination for what exactly is tested with the ROC analysis? I presume it’s identifying
fatty liver disease, but this needs to be specified. Please also report the 95% CI for the estimated
AUROC.
assistant