Access to this full-text is provided by Frontiers.
Content available from Frontiers in Surgery
This content is subject to copyright.
ORIGINAL RESEARCH
published: 03 May 2022
doi: 10.3389/fsurg.2022.827526
Frontiers in Surgery | www.frontiersin.org 1May 2022 | Volume 9 | Article 827526
Edited by:
Peter Schemmer,
Medical University of Graz, Austria
Reviewed by:
Behzad Hatami,
Shahid Beheshti University of Medical
Sciences, Iran
Martin Krššák,
Medical University of Vienna, Austria
*Correspondence:
YoungRok Choi
choiyoungrok@gmail.com
Specialty section:
This article was submitted to
Visceral Surgery,
a section of the journal
Frontiers in Surgery
Received: 02 December 2021
Accepted: 28 March 2022
Published: 03 May 2022
Citation:
Choi J, Choi Y, Hong SY, Suh S,
Hong K, Han ES, Lee JM, Hong SK,
Yi NJ, Lee KW and Suh KS (2022)
Changes in Indices of Steatosis and
Fibrosis in Liver Grafts of Living
Donors After Weight Reduction.
Front. Surg. 9:827526.
doi: 10.3389/fsurg.2022.827526
Changes in Indices of Steatosis and
Fibrosis in Liver Grafts of Living
Donors After Weight Reduction
Jaehyuk Choi, YoungRok Choi*, Su young Hong, Sanggyun Suh, Kwangpyo Hong,
Eui Soo Han, Jeong-Moo Lee, Suk Kyun Hong, Nam-Joon Yi, Kwang-Woong Lee and
Kyung-Suk Suh
Department of Surgery, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, South Korea
Background: A short-term weight reduction program for potential living donors was
introduced to reduce the extent of hepatic steatosis prior to liver transplantation. We
aimed to investigate changes in non-invasive hepatic steatosis and fibrosis indices
among those who completed the program.
Methods: Among 1,950 potential living liver donors between January 2011 and
May 2019, 160 living donors joined the weight reduction program. The prospectively
collected clinical data of these potential liver donors were analyzed retrospectively.
Hepatic steatosis and fibrosis scores were determined using the fatty liver index (FLI),
hepatic steatosis index (HSI), and NAFLD fibrosis score (NFS) and compared to MR
spectroscopy (MRS) fat fraction results before and after weight reduction.
Results: Thirty-nine potential living donors who had undergone MRS both before and
after weight reduction were included in the analysis. Their body weight decreased from
78.02 ±10.89 kg to 72.36 ±10.38 kg over a mean of 71.74 ±58.11 days. FLI, HSI,
and MRS values decreased significantly from 41.52 ±19.05 to 24.53 ±15.93, 39.64
±3.74 to 35.06 ±3.82, and 12.20 ±4.05 to 6.24 ±3.36, respectively. No significant
decreases in NFS were observed. There was a significant correlation between the extent
of HSI change and the extent of MRS change (R2value =0.69, P<0.001), although
there was no correlation between MRS and FLI.
Conclusion: The weight reduction program significantly improved non-invasive indices
of hepatic steatosis over a short period. HSI may allow for prediction of simple decreases
in hepatic steatosis.
Keywords: hepatic steatosis, hepatic fibrosis, fatty liver, living donor, NAFLD, weight loss
INTRODUCTION
The prevalence of non-alcoholic fatty liver disease (NAFLD) in the general population ranges from
20 to 30% in Europe (1,2), and is as high as 46% in the United States (3). In Korea, the prevalence
of NAFLD among potential donors is also increasing due to increasing adoption of a sedentary
and Westernized lifestyle (4–6). However, NAFLD—which is related to metabolic syndrome—has
an adverse effect on liver transplantation. Indeed, NAFLD has been associated with postoperative
morbidity and mortality in patients with liver grafts (7,8).
Choi et al. Hepatic Steatosis and Fibrosis Indices After Weight Loss
Although NAFLD in the donor is an exclusion criterion
for living donor liver transplantation (LDLT) (9), donors with
NAFLD are considered marginal donors because the supply of
deceased donors has not met the demand for liver transplantation
in Korea. Previous studies have indicated that weight reduction
and lifestyle modification can reduce hepatic steatosis in such
marginal donors (10–14).
Education on weight reduction and lifestyle modification
is being provided to potential living donors with NAFLD
to improve outcomes. Potential donors who have successfully
reduced weight prior to liver transplantation exhibit comparable
outcomes to donors from whom liver transplantation is
completed using liver grafts with no NAFLD (11,15,16).
Hepatic steatosis can be assessed either via liver biopsy or MR
spectroscopy (MRS). However, liver biopsy can cause procedure-
related complications, and MRS is expensive. Therefore, there is
a need for a simple index that can predict the degree of tissue
change following weight reduction.
In this retrospective study, we investigated whether indices of
hepatic steatosis and fibrosis, which are already in use and can be
calculated simply from the donor’s data, can predict the extent of
NAFLD after weight loss.
MATERIALS AND METHODS
Study Design
This study involved a single-center retrospective analysis of
the electronic medical records of 1,950 potential donors
between January 2011 and May 2019. Of the 1,950 potential
donors, 160 potential donors with hepatic steatosis received
recommendations for weight reduction and lifestyle modification
programs. Ninety-three of 160 potential donors lost body weight
and underwent LDLT. In this study, the fat fraction of MRS was
used as the reference value for the extent of hepatic steatosis
(17–19). MRS acquired as previous described (20).
The study protocol conformed to the ethical guidelines of
the 1975 Declaration of Helsinki as reflected in a prior approval
by the appropriate Institutional Review Committee (2011-121-
1173) at Seoul National University Hospital.
Variable Definitions and Data Collection
Baseline body weight prior to weight loss and final weight
after weight loss were measured during the first and last MRI
sessions, respectively. Alanine transaminase (ALT), aspartate
transaminase (AST), gamma-glutamyl-transpeptidase (GGT),
platelet count, albumin, waist circumference, weight loss
duration, fat fraction on MRS, and body weight were compared
between the two measurement sessions.
Abbreviations: NAFLD, non-alcoholic fatty liver disease; LDLT, living donor
liver transplantation; MRS, magnetic resonance spectroscopy; ALT, alanine
transaminase; AST, aspartate transaminase; GGT,gamma-glutamyl transpeptidase;
FLI, fatty liver index; HSI, hepatic steatosis index; LAP, lipid accumulation product;
ION, Index of Nash; NAFLD-LFS, NAFLD Liver Fat Score; APRI, AST to platelet
ratio index; FIB-4, Fibrosis-4; ELF, Enhanced Liver Fibrosis; NFS, NAFLD Fibrosis
Score; BMI, body mass index; TG, triglycerides; DM, diabetes mellitus.
Indices
We noninvasively reviewed indices for NAFLD assessment,
including six indices [fatty liver index (FLI), hepatic steatosis
index (HSI), SteatoTest, lipid accumulation product (LAP), Index
of Nash (ION), NAFLD-Liver Fat Score (LFS)] for liver steatosis
and eight indices [AST to platelet ratio index (APRI), Fibrosis-4
(FIB-4), FibroTest, Fibrometer NAFLD, Enhanced Liver Fibrosis
(ELF), Hepacore, BARD score, NAFLD fibrosis score (NFS)]
for liver fibrosis (21,22). The FLI, HIS, and NFS were selected
for this study because these indices can be calculated with only
simple laboratory findings, body weight, and circumference using
retrospective data.
The FLI is used to predict the degree of hepatic steatosis
(23). Scores are derived based on body mass index (BMI), GGT,
triglycerides (TG), and waist circumference, as follows: FLI =
logistic (0.953 ×ln (TG) +0.139 ×BMI +0.718 ×ln (GGT) +
0.053 ×waist circumference – 15.745) ×100, where logistic(x) =
1/(1 +e−x) and ln denotes the natural logarithm. Its lower cutoff
is 30, while its upper cutoff is 60 (24,25).
The HSI predicts the degree of hepatic steatosis and is derived
using BMI, diabetes mellitus (DM) status, and AST/ALT ratio,
as follows: HSI =8×ALT/AST +BMI (+2, if DM) (+2, if
female). Its lower cutoff is 30, while its upper cutoff is 36. A prior
ultrasonography study revealed that HIS is correlated with the
extent of hepatic steatosis (26,27).
The NFS is used to predict the degree of hepatic fibrosis and
is derived based on age, sex, DM status, platelet count, AST/ALT
ratio, and albumin levels, as follows. NFS = −1.675 +0.037 ×age
+0.094 ×BMI +1.13 ×DM +0.99 ×AST/ALT ratio – 0.013
×platelet (109) – 0.66 ×ALB (g/dl). Its lower cutoff is −1.445,
while its upper cutoff is 0.676 (28–30).
Statistical Analysis
Statistical analyses were performed using SPSS 26.0 (IBM
Corp., Armonk, NY, USA). Continuous variables such as body
weight, BMI, AST, ALT, GGT, platelet count, albumin, waist
circumference, and indices (NFS, FLI, HSI, MRS) before and
after weight loss were compared using Student’s t-tests. Variable
distributions were subjected to a normality test prior to the
Student’s t-test. All p-values were one-sided, and P-values
<0.05 were considered statistically significant. Quantitative
variables are expressed as the mean ±standard deviation. Linear
regression analyses were performed to investigate correlations
between each index and the fat fraction obtained via MRS. R2>
0.6 with a p-value <0.05 was considered statistically significant.
Arrow graphs were drawn using the R ggplot 2 package.
RESULTS
Study Population
We analyzed data for 39 of 93 living donors who had undergone
assessments of fat fraction before and after weight loss via MRS
(Figure 1).
Patient Characteristics
The mean patient age was 35.03 ±10.45 years (range: 20–59
years), and 29 patients were male (29/39, 74.4%). No patients had
Frontiers in Surgery | www.frontiersin.org 2May 2022 | Volume 9 | Article 827526
Choi et al. Hepatic Steatosis and Fibrosis Indices After Weight Loss
FIGURE 1 | Flow diagram of participant selection.
TABLE 1 | Baseline characteristics of the 39 living donors.
Variables Before After P-value
Sex (male), n(%) 29 (74.4%) - NA
Age (years) 35.03 ±10.45 - NA
Weight (kg) 78.02 ±10.89 72.36 ±10.38 <0.001
Height (cm) 169.53 - NA
BMI (kg/m2) 27.10 ±2.83 25.11 ±2.60 <0.001
Waist circumference (mm) 909.35 ±59.58 879.92 ±61.16 <0.001
DM 0 - NA
HT, n(%) 2 (5.1%) - NA
Weight loss duration (days) 71.74 ±58.11 - NA
BMI, body mass index; DM, diabetes mellitus; HT, hypertension.
DM, although two donors (5.1%) had hypertension. The mean
duration of weight reduction was 71.74 ±58.11 days (range: 11–
298 days). Six donors (15.4%) had a body weight reduction period
of over 100 days (Table 1).
Participation in the program was associated with a significant
decrease in weight from 78.02 ±10.89 kg to 72.36 ±10.38 kg
(P<0.001), as well as a significant decrease in waist
circumference from 909.35 ±59.58 mm to 879.92 ±61.16 mm
(P<0.001). Moreover, BMI decreased from 27.10 ±2.83 kg/m2
to 25.11 ±2.60 kg/m2(P<0.001), and the distribution of
BMI changed. Thirty living donors (76.9%) had obesity (BMI
>25 kg/m2), eight donors (20.5%) were overweight (25 kg/m2
>BMI >23 kg/m2), and one donor’ s BMI was 22.89 kg/m2,
which is nearly borderline. After completing the weight reduction
program, 19 donors (48.8%) had obesity (BMI >25 kg/m2), 10
donors (25.6%) were overweight (25 kg/m2>BMI >23 kg/m2),
and 10 donors (25.6%) had normal weight (Table 1).
TABLE 2 | Laboratory findings.
Variables Before After P-value
AST (U/L) 21.28 ±5.88 19.23 ±6.58 0.167
ALT (U/L) 33.08 ±15.80 23.10 ±11.35 0.007
GGT (U/L) 33.13 ±18.41 21.69 ±10.79 <0.001
Platelet (×109/L) 256.36 ±57.66 249.44 ±58.28 1
Albumin (g/dL) 4.52 ±0.25 4.41 ±0.34 0.004
AST, aspartate aminotransferase; ALT, alanine aminotransferase; GGT, gamma-
glutamyl transferase.
TABLE 3 | Hepatic steatosis & fibrosis indices.
Variables Before After P-value
NFS −3.45 ±0.89 −3.22 ±0.94 1
FLI 41.52 ±19.05 24.53 ±15.93 <0.001
HIS 39.64 ±3.74 35.06 ±3.82 <0.001
MRS 12.20 ±4.05 6.24 ±3.36 <0.001
NFS, NAFLD fibrosis score; FLI, fatty liver index; HSI, hepatic steatosis index; MRS, MR
spectroscopy liver fat fraction; NAFLD, non-alcoholic fatty liver disease.
There was no significant difference in AST levels between
the baseline and final assessments (21.28 ±5.88 U/L vs. 19.23
±6.58 U/L, P-value =0.167); however, there were significant
decreases in ALT (33.08 ±15.80 U/L vs. 23.10 ±11.35 U/L, P=
0.007) and GGT levels (33.13 ±18.41 U/L vs. 21.69 ±10.79 U/L,
P<0.001) between the two time points. The number of patients
with ALT levels above the normal range (0–40 U/L) changed
from 9/39 to 3/39, while the number of patients with GGT levels
above the normal range changed from 19/39 to 6/39. There was
a significant decrease in albumin levels between the baseline and
final assessments (4.52 ±0.25 g/dl vs. 4.41 ±0.34 g/dl, P=0.004).
However, platelet count did not significantly differ between the
two time points (P=1.00) (Table 2).
Index Analysis
There was a significant decrease in HSI between the baseline and
final assessments (39.64 ±3.74 vs. 35.06 ±3.82, P<0.001).
Before weight loss, there were 37 donors (94.9%) in the high HSI
group (HSI >36) and two donors (5.1%) in the intermediate HSI
group (36 >HSI >30). After weight loss, there were 16 donors
(41.0%) in the high HSI group (HSI >36), 21 donors (53.8%) in
the intermediate HSI group (36 >HSI >30), and two donors
(5.2%) in the low HSI group (HSI <30) (Table 3).
There was a significant decrease in FLI between the baseline
and final assessments (41.52 ±19.05 vs. 24.53 ±15.93, P<
0.001). Before weight loss, there were seven donors (17.9%) in the
high FLI group (FLI >60), 27 donors (69.2%) in the intermediate
FLI group (60 >FLI >20), and five donors (12.9%) in the low FLI
group (FLI <20). After weight loss, there was one donor (2.6%)
in the high FLI group (FLI >60), while there were 17 donors
(43.6%) in the intermediate FLI group (60 >FLI >20) and 21
donors (53.8%) in the low FLI group (FLI <20).
No significant changes in NFS were observed (P=1).
Frontiers in Surgery | www.frontiersin.org 3May 2022 | Volume 9 | Article 827526
Choi et al. Hepatic Steatosis and Fibrosis Indices After Weight Loss
FIGURE 2 | Trend line for identifying the correlation between the change in
MRS fat fraction and the change in HSI. MRS, magnetic resonance
spectroscopy; HSI, hepatic stenosis index.
Measurements of fat fraction obtained via MRS significantly
decreased from 12.20 ±4.05% to 6.24 ±3.36% (P<0.001)
between the two periods. Before weight loss, the fat fraction was
10% or higher in 26 donors, and the maximum value was 22.73%.
After weight loss, only four donors had fat fractions of 10% or
higher (Table 3).
Correlation in the Value of Delta Between
HSI and MRS
There were no significant correlations between the extent of
change on MRS and indices, except HSI (R2=0.69 and P<
0.001) (Figure 2).
The gradient trend of the delta HSI/delta MRS graph was
similar to that of the trend line, but there were some exceptional
cases (Figure 3). No correlations were observed in the other two
graphs (Figures 4,5).
DISCUSSION
Previous studies have reported that MRS can accurately predict
steatosis, although it remains controversial to what extent it can
predict the degree of fibrosis (25,31,32). MRS is also non-
invasive and more objective than biopsy assessments. In the
present study, we investigated whether indices of hepatic steatosis
and fibrosis can predict the extent of NAFLD after weight loss.
Our findings indicated that there was no strong correlation
between either of the two indices and the degree of steatosis,
suggesting that the extent of change in hepatic steatosis due
to weight reduction can only be roughly determined based on
changes in HSI and FLI values.
Kahl et al. and Cuthbertson et al. reported the similar result
that these HSI and FLI would be surrogate parameters for hepatic
steatosis clinically, but could not replace MRS (33,34).
Previous studies have suggested a correlation between HSI and
fat fraction on ultrasonography; however, the R2value was 0.334,
and ultrasonography is a user-dependent method. Thus, the
results were not clinically significant. Furthermore, the authors
did not validate the correlation using liver histology findings
FIGURE 3 | The changes of HIS according to MRI fat before and after body
weight reduction. The values of HSI and MRS tend to decrease with weight
loss. The line slope representing the change is the ratio of the MRS decrease
and the HSI decrease. Therefore, the HSI value changes appropriately
according to the change amount of the MRI fat fraction. MRS, magnetic
resonance spectroscopy; HSI, hepatic stenosis index. Blue circle, before
weight reduction; red circle and arrows, after weight reduction.
FIGURE 4 | The changes of FLI according to MRI fat before and after body
weight reduction. The slope of each line appears in various ways without a
particular pattern. Since the amount of change in the FLI value according to
the amount of change in the MRS fat fraction is not constant, it appears that
the FLI cannot consistently reflect the MRS fat fraction. MRS, magnetic
resonance spectroscopy; FLI, fatty liver index. Blue circle, before weight
reduction; red circle and arrows, after weight reduction.
(26). Although they attempted to determine the correlation
between the index and MRS, no indices exhibited a quantitative
correlation. Because we used the objective value for the fat
fraction obtained via MRS as the reference value, our trends
observed for HSI and FLI may be more reliable. Our regression
analysis revealed a correlation for HSI only. Given that one can
infer the extent of change on MRS based on the extent of change
Frontiers in Surgery | www.frontiersin.org 4May 2022 | Volume 9 | Article 827526
Choi et al. Hepatic Steatosis and Fibrosis Indices After Weight Loss
FIGURE 5 | The changes of NFS according to MRI fat before and after body
weight reduction. Regardless of the change in the MRS fat fraction according
to the change in body weight, there was little change in the NFS value. MRS,
magnetic resonance spectroscopy; NFS, NAFLD fibrosis score. Blue circle,
before weight reduction; red circle and arrows, after weight reduction.
in HSI, this tool may allow clinicians to predict improvements in
liver fat fraction without additional MRI or biopsy.
Liu et al. reported that FLI had a high diagnostic predictive
rate for metabolic-associated fatty liver disease, but this may be
due to triglyceride, gamma GT, which is highly correlated with
metabolic diseases (35).
While NFS values increased, the change was not statistically
significant, likely because we observed unexpected decreases
in platelet levels, which are used in the calculation of NFS.
Therefore, the results may have been clinically insignificant
because the extent of change was not large. In addition, the NFS
value was significantly smaller than the lower cutoff of −1.455
(−3.45 ±0.89 before weight loss and −3.22 ±0.94 after weight
loss), and there was no donor with an index value exceeding the
lower cutoff at either time point. Such findings indicate a degree
of fibrosis without clinical significance. Since the study involved
only those patients who had completed liver transplantation,
our results were likely influenced by selection bias due to the
inclusion of people with relatively healthy livers. For the same
reason, most patients may have had low NFS values caused by
simple steatosis. However, since this is also an index that suggests
the probability of fibrosis, it is limited in that the true extent of
fibrosis cannot be determined without a direct biopsy.
Our findings indicate that improvements in NAFLD can
be predicted based only on routine laboratory examination
results, which may aid in improving outcomes among donors
with NAFLD. However, the arrow graph shows cases outside
the normal gradient range. For clinical use, an additional
understanding of the characteristics of exceptional cases will be
required. In this study, we did not perform feature analysis of
exceptional cases due to the small number of cases, although such
analyses will be possible in larger-scale studies.
Our results also indicated that the fibrosis index was clinically
and statistically insignificant; therefore, only steatosis could be
identified. Pathological analyses should be performed before and
after weight reduction to identify other factors that contribute to
NAFLD, such as inflammation, ballooning injury, and fibrosis.
The results of this study should also be validated based on
pathological results.
Previous studies that have examined pathological findings
at 1-year post-operatively have reported that recipient-related
factors can influence the risk of recipient NAFLD after liver
transplantation (36). To exclude these factors, future studies
should examine pathology findings 7 days post-operatively, as
this will help to ascertain the effect of weight reduction on liver
engraftment in a linear fashion.
DATA AVAILABILITY STATEMENT
The raw data supporting the conclusions of this article will be
made available by the authors, with permission of IRB.
ETHICS STATEMENT
The studies involving human participants were reviewed and
approved by Seoul National University Hospital. Written
informed consent for participation was not required for this
study in accordance with the national legislation and the
institutional requirements.
AUTHOR CONTRIBUTIONS
JC: data collection, draft, and the final manuscript. YC: initial
idea, study conceptualization, critical review, draft, and the final
manuscript. SYH, SS, KH, and EH: data collection and draft
review. JML: data collection, study conceptualization, critical
review, draft, and review. SKH, NJY, KWL, and KSS: study
conceptualization, critical review, and draft review. All authors
contributed to the article and approved the submitted version.
REFERENCES
1. Bedogni G, Miglioli L, Masutti F, Tiribelli C, Marchesini G, Bellentani
S. Prevalence of and risk factors for nonalcoholic fatty liver disease:
the Dionysos nutrition and liver study. Hepatology. (2005) 42:44–52.
doi: 10.1002/hep.20734
2. Armstrong MJ, Houlihan DD, Bentham L, Shaw JC, Cramb R, Olliff
S, et al. Presence and severity of non-alcoholic fatty liver disease in
a large prospective primary care cohort. J Hepatol. (2012) 56:234–40.
doi: 10.1016/j.jhep.2011.03.020
3. Williams CD, Stengel J, Asike MI, Torres DM, Shaw J, Contreras
M, et al. Prevalence of nonalcoholic fatty liver disease and
nonalcoholic steatohepatitis among a largely middle-aged
population utilizing ultrasound and liver biopsy: a prospective
study. Gastroenterology. (2011) 140:124–31. doi: 10.1053/j.gastro.20
10.09.038
Frontiers in Surgery | www.frontiersin.org 5May 2022 | Volume 9 | Article 827526
Choi et al. Hepatic Steatosis and Fibrosis Indices After Weight Loss
4. Lee JY, Kim KM, Lee SG, Yu E, Lim Y-S, Lee HC, et al. Prevalence and risk
factors of non-alcoholic fatty liver disease in potential living liver donors in
Korea: a review of 589 consecutive liver biopsies in a single center. J Hepatol.
(2007) 47:239–44. doi: 10.1016/j.jhep.2007.02.007
5. Farrell GC, Wong VW, Chitturi S. NAFLD in Asia–as common and
important as in the West. Nat Rev Gastroenterol Hepatol. (2013) 10:307–18.
doi: 10.1038/nrgastro.2013.34
6. Jeong EH, Jun DW, Cho YK, Choe YG, Ryu S, Lee SM, et al. Regional
prevalence of non-alcoholic fatty liver disease in Seoul and Gyeonggi-do,
Korea. Clin Mol Hepatol. (2013) 19:266. doi: 10.3350/cmh.2013.19.3.266
7. Chu MJ, Dare AJ, Phillips AR, Bartlett AS. Donor hepatic steatosis and
outcome after liver transplantation: a systematic review. J Gastrointest Surg.
(2015) 19:1713–24. doi: 10.1007/s11605-015-2832-1
8. Zhang QY, Zhang QF, Zhang DZ. The impact of steatosis on the outcome of
liver transplantation: a meta-analysis. Biomed Res Int. (2019) 2019:3962785.
doi: 10.1155/2019/3962785
9. Nugroho A, Kim OK, Lee KW, Song S, Kim H, Hong SK, et al. Evaluation of
donor workups and exclusions in a single-center experience of living donor
liver transplantation. Liver Transpl. (2017) 23:614–24. doi: 10.1002/lt.24762
10. Mattar SG, Velcu LM, Rabinovitz M, Demetris AJ, Krasinskas AM, Barinas-
Mitchell E, et al. Surgically-induced weight loss significantly improves
nonalcoholic fatty liver disease and the metabolic syndrome. Ann Surg. (2005)
242:610-7; discussion 618–20. doi: 10.1097/01.sla.0000179652.07502.3f
11. Nakamuta M, Morizono S, Soejima Y, Yoshizumi T, Aishima S, Takasugi
S, et al. Short-term intensive treatment for donors with hepatic steatosis
in living-donor liver transplantation. Transplantation. (2005) 80:608–12.
doi: 10.1097/01.tp.0000166009.77444.f3
12. Promrat K, Kleiner DE, Niemeier HM, Jackvony E, Kearns M, Wands JR, et al.
Randomized controlled trial testing the effects of weight loss on nonalcoholic
steatohepatitis. Hepatology. (2010) 51:121–9. doi: 10.1002/hep.23276
13. Sanyal AJ, Chalasani N, Kowdley KV, Mccullough A, Diehl AM, Bass NM, et
al. Pioglitazone, vitamin E, or placebo for nonalcoholic steatohepatitis. N Engl
J Med. (2010) 362:1675–85. doi: 10.1056/NEJMoa0907929
14. Jin YJ, Kim KM, Hwang S, Lee SG, Ha TY, Song GW, et al. Exercise and
diet modification in non-obese non-alcoholic fatty liver disease: analysis of
biopsies of living liver donors. J Gastroenterol Hepatol. (2012) 27:1341–7.
doi: 10.1111/j.1440-1746.2012.07165.x
15. Hwang S, Lee SG, Jang SJ, Cho SH, Kim KH, Ahn CS, et al. The effect of donor
weight reduction on hepatic steatosis for living donor liver transplantation.
Liver Transpl. (2004) 10:721–5. doi: 10.1002/lt.20172
16. Doyle A, Adeyi O, Khalili K, Fischer S, Dib M, Goldaracena N, et al.
Treatment with Optifast reduces hepatic steatosis and increases candidacy
rates for living donor liver transplantation. Liver Transpl. (2016) 22:1295–300.
doi: 10.1002/lt.24495
17. Bohte AE, Van Werven JR, Bipat S, Stoker J. The diagnostic accuracy
of US, CT, MRI and 1H-MRS for the evaluation of hepatic steatosis
compared with liver biopsy: a meta-analysis. Eur Radiol. (2011) 21:87–97.
doi: 10.1007/s00330-010-1905-5
18. Chabanova E, Bille DS, Thisted E, Holm JC, Thomsen HS. (1)H MRS
assessment of hepatic steatosis in overweight children and adolescents:
comparison between 3T and open 1T MR-systems. Abdom Imaging. (2013)
38:315–9. doi: 10.1007/s00261-012-9930-2
19. Choi Y, Lee JM, Yi NJ, Kim H, Park MS, Hong G, et al. Heterogeneous living
donor hepatic fat distribution on MRI chemical shift imaging. Ann Surg Treat
Res. (2015) 89:37–42. doi: 10.4174/astr.2015.89.1.37
20. Hwang I, Lee JM, Lee KB, Yoon JH, Kiefer B, Han JK, et al. Hepatic steatosis
in living liver donor candidates: preoperative assessment by using breath-
hold triple-echo MR imaging and 1H MR spectroscopy. Radiology. (2014)
271:730–8. doi: 10.1148/radiol.14130863
21. Castera L, Friedrich-Rust M, Loomba R. Noninvasive assessment of liver
disease in patients with nonalcoholic fatty liver disease. Gastroenterology.
(2019) 156:1264-81 e1264. doi: 10.1053/j.gastro.2018.12.036
22. Sahin T, Arikan BT, Serin A, Emek E, Bozkurt B, Server S, et al. The
utility of noninvasive scoring systems for prediction of hepatic steatosis in
liver transplantation donor candidates. Transplant Proc. (2019) 51:2383–6.
doi: 10.1016/j.transproceed.2019.01.177
23. Bedogni G, Bellentani S, Miglioli L, Masutti F, Passalacqua M, Castiglione
A, et al. The Fatty Liver Index: a simple and accurate predictor of
hepatic steatosis in the general population. BMC Gastroenterol. (2006) 6:33.
doi: 10.1186/1471-230X-6-33
24. Koehler EM, Schouten JN, Hansen BE, Hofman A, Stricker BH, Janssen HL.
External validation of the fatty liver index for identifying nonalcoholic fatty
liver disease in a population-based study. Clin Gastroenterol Hepatol. (2013)
11:1201–4. doi: 10.1016/j.cgh.2012.12.031
25. Khang AR, Lee HW, Yi D, Kang YH, Son SM. The fatty liver index, a simple
and useful predictor of metabolic syndrome: analysis of the Korea National
Health and Nutrition Examination Survey 2010-2011. Diabetes Metab Syndr
Obes. (2019) 12:181–90. doi: 10.2147/DMSO.S189544
26. Lee JH, Kim D, Kim HJ, Lee CH, YangJI, Kim W, et al. Hepatic steatosis index:
a simple screening tool reflecting nonalcoholic fatty liver disease. Dig Liver
Dis. (2010) 42:503–8. doi: 10.1016/j.dld.2009.08.002
27. Sviklane L, Olmane E, Dzerve Z, Kupcs K, Pirags V, Sokolovska J. Fatty
liver index and hepatic steatosis index for prediction of non-alcoholic fatty
liver disease in type 1 diabetes. J Gastroenterol Hepatol. (2018) 33:270–6.
doi: 10.1111/jgh.13814
28. Angulo P, Hui JM, Marchesini G, Bugianesi E, George J, Farrell GC, et al. The
NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in
patients with NAFLD. Hepatology. (2007) 45:846–54. doi: 10.1002/hep.21496
29. Treeprasertsuk S, Bjornsson E, Enders F, Suwanwalaikorn S, Lindor KD.
NAFLD fibrosis score: a prognostic predictor for mortality and liver
complications among NAFLD patients. World J Gastroenterol. (2013)
19:1219–29. doi: 10.3748/wjg.v19.i8.1219
30. Jun DW, Kim SG, Park SH, Jin SY, Lee JS, Lee JW, et al. External validation
of the non-alcoholic fatty liver disease fibrosis score for assessing advanced
fibrosis in Korean patients. J Gastroenterol Hepatol. (2017) 32:1094–9.
doi: 10.1111/jgh.13648
31. Cho SG, Kim MY, Kim HJ, Kim YS, Choi W, Shin SH, et al. Chronic
hepatitis: in vivo proton MR spectroscopic evaluation of the liver and
correlation with histopathologic findings. Radiology. (2001) 221:740–6.
doi: 10.1148/radiol.2213010106
32. Bonekamp S, Kamel I, Solga S, Clark J. Can imaging modalities diagnose and
stage hepatic fibrosis and cirrhosis accurately? J Hepatol. (2009) 50:17–35.
doi: 10.1016/j.jhep.2008.10.016
33. Kahl S, Straßburger K, Nowotny B, Livingstone R, Klüppelholz B,
Keßel K, et al. Comparison of liver fat indices for the diagnosis of
hepatic steatosis and insulin resistance. PLoS One. (2014) 9:e94059.
doi: 10.1371/journal.pone.0094059
34. Cuthbertson DJ, Weickert MO, Lythgoe D, Sprung VS, Dobson R, Shoajee-
Moradie F, et al. External validation of the fatty liver index and lipid
accumulation product indices, using 1H-magnetic resonance spectroscopy,
to identify hepatic steatosis in healthy controls and obese, insulin-resistant
individuals. Eur J Endocrinol. (2014) 171:561–9. doi: 10.1530/EJE-14-0112
35. Liu Y, Liu S, Huang J, Zhu Y, Lin S. Validation of five hepatic steatosis
algorithms in metabolic- associated fatty liver disease: a population based
study. J Gastroenterol Hepatol. (2022). doi: 10.1111/jgh.15799. [Epub ahead
of print].
36. Kim H, Lee K, Lee KW, Yi NJ, Lee HW, Hong G, et al. Histologically proven
non-alcoholic fatty liver disease and clinically related factors in recipients
after liver transplantation. Clin Transplant. (2014) 28:521–9. doi: 10.1111/c
tr.12343
Conflict of Interest: The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could be construed as a
potential conflict of interest.
Publisher’s Note: All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their affiliated organizations, or those of
the publisher, the editors and the reviewers. Any product that may be evaluated in
this article, or claim that may be made by its manufacturer, is not guaranteed or
endorsed by the publisher.
Copyright © 2022 Choi, Choi, Hong, Suh, Hong, Han, Lee, Hong, Yi, Lee and Suh.
This is an open-access article distributed under the terms of the Creative Commons
Attribution License (CC BY). The use, distribution or reproduction in other forums
is permitted, provided the original author(s) and the copyright owner(s) are credited
and that the original publication in this journal is cited, in accordance with accepted
academic practice. No use, distribution or reproduction is permitted which does not
comply with these terms.
Frontiers in Surgery | www.frontiersin.org 6May 2022 | Volume 9 | Article 827526
Available via license: CC BY
Content may be subject to copyright.