{"paper_id":"2b705d3f-1541-4612-aa5f-856fc09d2e1e","body_text":"The impact of a low-calorie, reduced-fat diet on liver attenuation imaging: A randomized clinical trial | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The impact of a low-calorie, reduced-fat diet on liver attenuation imaging: A randomized clinical trial Renjie Li, Jie Li, Danni He, Yajuan Sui, Wenfen Liu, Wentao Li, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5303569/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Dec, 2024 Read the published version in Abdominal Radiology → Version 1 posted 11 You are reading this latest preprint version Abstract Purpose: To investigate whether a low-calorie, reduced-fat diet affects liver Attenuation Imaging (ATI) measurements. Methods: A total of 320 patients were enrolled in this prospective study. They were randomly assigned to four groups: a fasting group; a postprandial 0.5-hour examination group; a postprandial 2-hour examination group; and a postprandial 4-hour examination group. All participants first underwent liver ATI examination in a fasting state. Those in the postprandial groups then consumed a low-calorie, reduced-fat diet before undergoing a second ATI examination at 0.5h, 2h, or 4h after the meal, respectively. The ATI values were compared among the groups. The differences between postprandial and fasting ATI values were also analyzed for the postprandial groups. Additionally, the consistency of the grading diagnosis of hepatic steatosis between the postprandial and fasting states was evaluated in the postprandial groups. Results: The ATI values for the postprandial 0.5h group, postprandial 2h group, and postprandial 4h group were not significantly different from the fasting group's ATI value ( P = 0.576, 0.471, and 0.992, respectively). No significant differences were noted in the ATI values that were recorded during the postprandial and fasting states within each of the postprandial groups ( P = 0.573, 0.076, and 0.805, respectively). The consistency of the grading diagnosis of hepatic steatosis between the postprandial and fasting states across the three postprandial groups was high according to three different diagnostic criteria. Conclusion: Consuming a low-calorie, reduced-fat diet has no significant effects on liver ATI measurements and the grading diagnosis of hepatic steatosis. Clinical Trial Number: (ChiCTR2200062314,August 2022) Fasting Reduced-fat diet Hepatic steatosis Attenuation imaging Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction With the remarkable improvement in living standards and the increasing prevalence of metabolic disorders and obesity, the incidence of Metabolic Dysfunction Associated Fatty Liver Disease (MAFLD) is also on the rise. MAFLD has become the most common chronic liver disease globally, having surpassed viral hepatitis[ 1 ]. MAFLD positively correlates with the development of metabolic disorders and cardiovascular diseases[ 2 , 3 ]. The precondition for diagnosing MAFLD is the diagnosis of hepatic steatosis. Attenuation Imaging (ATI) is a novel, non-invasive technology that is increasingly being clinically used for assessing hepatic steatosis[ 4 , 5 ]. ATI plays a significant role in the early detection, diagnosis, and prognosis assessment of MAFLD. Typically, patients are required to fast for over 6 hours before undergoing ATI. However, prolonged fasting can lead to anxiety and a series of adverse effects, such as hypoglycemia, fainting, or even shock, all of which pose a threat to health. Based on clinical experience, consuming a light diet before an abdominal ultrasound did not exhibit any negative impact on the ultrasound examination for some patients. Since ATI is performed based on conventional grayscale imaging, we hypothesize that consuming a certain amount of low-fat food before the examination may not affect liver ATI results. This study aims to investigate whether a low-calorie, reduced-fat diet influences ATI measurements and the grading diagnosis of hepatic steatosis. Materials and methods Participants This is a prospective randomized controlled study that was conducted between December 2022 and August 2024. It involved 320 patients who underwent routine liver ATI examinations in the ultrasound department of the hospital where the researcher works. The inclusion criteria were as follows: (a) Patients undergoing routine liver ATI examinations; (b) Patients aged between 18–80 years; (c) Patients who are conscious enough to understand and sign informed consent; (d) Patients with no history of allergy to the foods used in this study; (e) Patients who can eat normally. The exclusion criteria were as follows: (a) Patients with acute, critical illnesses; (b) Patients with special dietary restrictions; (c) Patients involved in other examinations or treatments that may conflict with this study. A simple randomization method was used to assign the participants to groups, during the scheduling of ATI examinations. Randomization information was sealed in opaque envelopes that were prepared by a researcher who was not involved in data collection or analysis. The participants were randomly assigned to one of the following four groups: a fasting group; a postprandial 0.5h examination group; a postprandial 2h examination group; and a postprandial 4h examination group. Study procedures Instrumentation The Aplio i900 ultrasound system (Canon Ltd, Japan) was used in this study. ATI examination was performed using a convex array transducer (i8CX1, 1.8–6.2 MHz). Pre-examination dietary instructions The participants were instructed to consume a light meal the evening before the examination and to fast after 22:00. The baseline demographic characteristics of all participants were recorded. Assessment of hunger severity Assessing participants' hunger severity using the visual analogue scales (VAS) before each ATI examination: rated on a scale of 0–10, where \"0\" represents no hunger at all, and \"10\" represents intolerable hunger. ATI examination procedure ATI examinations were performed using the same equipment by one of three radiologists, each with over 10 years of experience in ultrasound imaging. They received standardized training on liver ATI examination procedures. The examinations were performed in a blinded manner. The radiologists were unaware of the participants' grouping informations and did not know whether they were in fasting or postprandial states prior to the examination. All participants first underwent liver ATI examination on the trial day while they were fasting. After the initial examination, participants in the postprandial groups consumed a low-calorie, reduced-fat diet. The energy content of these meals was more than 25% lower than that required for the standard breakfast for an adult. The fat content was below 3 g/100 g of solid food or 1.5 g/100 mL of liquid food. Two meal combinations were provided, and participants had the leverage to choose their preferences. Both meal combinations met the low-fat criteria. Meal Option 1 involved one white steamed bun (100 g, 983 kJ, 1.63 g fat) and a bowl of plain porridge (200 mL, 356 kJ, 0.22 g fat), with a total energy content of 1339 kJ and total fat content of 1.85 g. Meal Option 2 included a slice of white toast (100 g, 1067 kJ, 1.9 g fat) and jam (20 mL, 233 kJ, 0.02 g fat), with a total energy content of 1300 kJ and total fat content of 1.92 g. Participants were instructed to finish the meal within 10 minutes under the supervision of the study staff. Then, the participants in the postprandial groups underwent a second ATI examination at 0.5h, 2h, or 4h after the meal. Each participant only underwent one follow-up examination. The participants were not allowed to eat any additional food before the second examination. The postprandial ATI measurements for each participant were independently conducted by a different radiologist using the same ultrasound machine. All this was done to ensure that the initial fasting scan results would not influence the postprandial scan. Attenuation imaging procedure The radiologist avoided calcifications, artifacts, and large ductal structures within the liver, and identified an optimal intercostal scanning plane in the right hepatic lobe. Then the radiologist switched to the ATI mode, with the upper edge of the sample box placed 1 cm below the liver capsule. The size of the sample box was set to 4 × 3 cm, and the image was frozen. When the yellow sample box appeared, it was positioned within the green sample box to display the ATI value. The coefficient of determination (R2) was used to assess the reliability of the displayed ATI value. An R2 > 90% indicated excellent reliability. The R2 between 80% and 90% showed good reliability, while R2 < 80% highlighted poor reliability. Only ATI values with an R2 above 90%, displayed as white numerals, met the inclusion criteria for this study. Five valid ATI values were measured for each examination, and the median of these five measurements was recorded as the ATI value for that session. Outcomes As the primary outcomes, the ATI values were compared among the groups and the differences between postprandial and fasting ATI values were also analyzed in the three postprandial groups. As the secondary outcomes, the consistency of the grading diagnosis of hepatic steatosis between the postprandial and fasting states was evaluated in the three postprandial groups and the hunger severity scores were compared among the groups. Sample size calculation This research is designed as a randomized, controlled, and equivalence clinical trial. Participants are randomly allocated into four groups: a fasting control group, and three postprandial groups at 0.5 hours, 2 hours, and 4 hours, respectively. The study presupposes a mean difference of 0 and a standard deviation of 0.13 between any two groups in the four groups, with an equivalence margin set at 0.085. Utilizing a two-sided α = 0.05 and a test power of 1-β = 0.90, PASS15 software calculations determine that an initial sample size of 52 per group is required. Given a 10% dropout rate, the final sample size for each group is 58, resulting in a total sample size of 232. Statistical analysis Statistical analyses were performed using SAS 9.4(version 9.4 for Windows, SAS Institute, Inc, Cary, NC, USA). Categorical data were presented as frequencies and percentages, while quantitative data were expressed as means ± standard deviations (normal distribution) or M (IQR) (non-normal distribution). The Mann-Whitney U test was used to compare the differences in ATI values and hunger severity scores between each postprandial group and the fasting group. The Wilcoxon Signed Rank Test was employed to assess the differences in ATI values between fasting and postprandial states within the same group. The Kappa coefficient was used to evaluate the consistency of the grading diagnosis of hepatic steatosis between fasting and postprandial states among the three postprandial groups. The Kappa value was interpreted as follows: < 0.2 indicates poor agreement; 0.2–0.4 shows fair agreement; 0.4–0.6 represents moderate agreement; 0.6–0.8 signaled substantial agreement; and 0.8-1.0 suggests almost perfect agreement. A two-tailed α level of 0.05 was set as the significance threshold, with P < 0.05 being considered statistically significant. Results Baseline characteristics A total of 320 participants were initially enrolled in this study. However, 12 participants did not attend the examination on the scheduled day and 5 ultrasound examinations were canceled. Eight of the participants had temporary conflicts with the study time due to other examinations or treatments. Ultimately, 25 participants were excluded from the final analysis, consequently leaving 295 participants who were then included in the statistical analyses. The participant flowchart is presented in Figure. 1. The analyses were conducted based on the original group assignments, and the baseline characteristics across the groups were similar (Table 1 ). Table 1 Baseline characteristics of the participants Characteristic Fasting group ( n = 76) Postprandial 0.5h( n = 70) Postprandial 2h( n = 76) Postprandial 4h( n = 73) Statistics P Value Gender Female 52(68.42) 37(52.86) 49(64.47) 48(65.75) χ 2 = 4.358 0.225 Male 24(31.58) 33(47.14) 27(35.53) 25(34.25) Age(years) † 35.0(29.5,44.0) 34.0(25.0,46.0) 32.5(26.0,41.5) 38.0(28.0,44.0) H = 3.652 0.301 BMI (kg/m 2 ) † 22.2(20.3,24.8) 22.0(20.0,24.5) 22.4(20.2,24.4) 22.0(20.7,26.8) H = 0.964 0.809 Waist(cm) † 78.0(69.5,84.5) 77.0(69.0,85.0) 76.5(70.0,83.5) 76.0(71.0,86.0) H = 0.290 0.961 Note.—Except where indicated, data are numbers of participants, with percentages in parentheses. BMI = body mass index. † Data are M ( IQR ) Intergroup comparison of hunger severity scores As shown in Figure. 2, the hunger severity scores of the postprandial 0.5h and 2h groups were lower than those of the fasting group ( P < 0.001). However, there was no significant difference between the postprandial 4h group and the fasting group ( P = 0.430). Intergroup comparison of ATI values As shown in Figure. 3, the ATI values for the postprandial 0.5h group [0.56(0.50,0.62) dB/cm/MHz], postprandial 2h group [0.55(0.51,0.65) dB/cm/MHz], and postprandial 4h group [0.58(0.53,0.70) dB/cm/MHz] were not significantly different from the fasting group's ATI value [0.57(0.53,0.69) dB/cm/MHz] ( P = 0.576, 0.471, and 0.992, respectively). Intragroup comparison of ATI values in postprandial groups The study results indicated that the liver ATI values for the postprandial 0.5h group in the postprandial and fasting states were 0.56(0.50,0.62) dB/cm/MHz and 0.57(0.51,0.64) dB/cm/MHz, respectively. For the postprandial 2h group, the ATI values in the postprandial and fasting states were 0.55(0.51,0.65) dB/cm/MHz and 0.56(0.49,0.66) dB/cm/MHz, respectively. In the postprandial 4h group, the ATI values in the postprandial and fasting states were 0.58(0.53,0.70) dB/cm/MHz and 0.59(0.53,0.69) dB/cm/MHz, respectively. As shown in Table 2 , none of these numerical differences were statistically significant ( P = 0.573, 0.076, and 0.805, respectively). (Figure. 4A-F) Table 2 Intragroup comparison of ATI values in postprandial groups Group Fasting states Postprandial states P Postprandial 0.5h group 0.57(0.51,0.64) 0.56(0.50,0.62) 0.573 Postprandial 2h group 0.56(0.49,0.66) 0.55(0.51,0.65) 0.076 Postprandial 4h group 0.59(0.53,0.69) 0.58(0.53,0.70) 0.805 Note.—Data are ATI values. Data are M ( IQR ). Diagnosis of hepatic steatosis in each group The ATI values were used to assess the grade of hepatic steatosis. Absent, mild, moderate, and severe hepatic steatosis corresponded to grades S0 (< 5% of hepatocytes), S1 (5%-33% of hepatocytes), S2 (33%-66% of hepatocytes), and S3 (> 66% of hepatocytes), respectively. The corresponding ATI diagnostic cutoff values for each grade were 0.67, 0.72, and 0.86 dB/cm/MHz[ 6 ]. Using the ATI values of participants in each group under fasting states as the benchmark and referring to the ATI diagnostic threshold for hepatic steatosis, the fasting group detected 21 cases of hepatic steatosis (including 4 case of mild hepatic steatosis, 10 cases of moderate hepatic steatosis, and 7 cases of severe hepatic steatosis), with a detection rate of 27.63%; the postprandial 0.5h group detected 13 cases (including 3 mild, 6 moderate, and 4 severe), with a detection rate of 19.12%; the postprandial 2h group detected 18 cases (including 4 mild, 8 moderate, and 6 severe), with a detection rate of 25.00%; and the postprandial 4h group detected 22 cases (including 9 mild, 5 moderate, and 8 severe), with a detection rate of 30.99%. Consistency of grading diagnosis of hepatic steatosis in postprandial groups The consistency of grading diagnosis between the postprandial and fasting states were evaluated across three different criteria. First, when the diagnosis identified the presence or absence of hepatic steatosis, the Kappa values for diagnostic consistency between the postprandial and fasting states for the three postprandial groups were 0.951, 0.846, and 0.833, respectively (Table 3 , Figure. 5A-C). Second, when the diagnosis was based on the presence or absence of moderate-to-severe hepatic steatosis, the Kappa values were 0.831, 0.855, and 0.812, respectively (Table 4 , Figure. 6A-C). Finally, when the diagnosis distinguished between absent, mild, moderate, and severe hepatic steatosis, the Kappa values were 0.862, 0.756, and 0.737, respectively (Table 5 , Figure. 7A-C). These findings indicate that for all diagnostic criteria, the Kappa values were always high, suggesting a substantial degree of consistency in grading the diagnosis of hepatic steatosis. Table 3 The consistency of the presence or absence of hepatic steatosis Classification Classification Total Absence Presence P Kappa Postprandial 0.5h group χ 2 = 1.00 0.317 0.951 (0.856 ,1.000) Absence 55(80.88) 55(100.0) 0(0.00) Presence 13(19.12) 1(7.69) 12(92.31) Total 56(82.35) 12(17.65) Postprandial 2h group χ 2 = 1.00 0.317 0.846(0.701 ,0.992) Absence 54(75.00) 53(98.15) 1(1.85) Presence 18(25.00) 3(16.67) 15(83.33) Total 56(77.78) 16(22.22) Postprandial 4h group χ 2 = 0.20 0.655 0.833(0.693 ,0.974) Absence 49(69.01) 47(95.92) 2(4.08) Presence 22(30.99) 3(13.64) 19(86.36) Total 50(70.42) 21(29.58) Note.—Data are numbers of participants, with percentages in parentheses. Table 4 The consistency of the presence or absence of moderate-to-severe hepatic steatosis Classification Classification Total Absent and mild Moderate and severe P Kappa Postprandial 0.5h group χ 2 = 0.33 0.564 0.831 (0.646 ,1.000) Absent and mild 58(85.29) 56(96.55) 2(3.45) Moderate and severe 10(14.71) 1(10.00) 9(90.00) Total 57(83.82) 11(16.18) Postprandial 2h group χ 2 = 3.00 0.083 0.855(0.697 ,1.000) Absent and mild 58(80.56) 58(100.0) 0(0.00) Moderate and severe 14(19.44) 3(21.43) 11(78.57) Total 61(84.72) 11(15.28) Postprandial 4h group χ 2 = 0.00 1.000 0.812(0.634 ,0.990) Absent and mild 58(81.69) 56(96.55) 2(3.45) Moderate and severe 13(18.31) 2(15.38) 11(84.62) Total 58(81.69) 13(18.31) Note.—Data are numbers of participants, with percentages in parentheses. Table 5 The consistency of absent, mild, moderate, and severe hepatic steatosis Classification Classification Total Absent Mild Moderate Severe P Kappa Postprandial 0.5h group χ 2 = 3.00 0.809 0.862(0.721 ,1.000) Absent 55(80.88) 55(100.0) 0(0.00) 0(0.00) 0(0.00) Mild 3(4.41) 0(0.00) 1(33.33) 2(66.67) 0(0.00) Moderate 6(8.82) 1(16.67) 0(0.00) 5(83.33) 0(0.00) Severe 4(5.88) 0(0.00) 0(0.00) 0(0.00) 4(100.0) Total 56(82.35) 1(1.47) 7(10.29) 4(5.88) Postprandial 2h group χ 2 = 3.00 0.809 0.756(0.597 ,0.915) Absent 54(75.00) 53(98.15) 1(1.85) 0(0.00) 0(0.00) Mild 4(5.56) 1(25.00) 3(75.00) 0(0.00) 0(0.00) Moderate 8(11.11) 2(25.00) 1(12.50) 4(50.00) 1(12.50) Severe 6(8.33) 0(0.00) 0(0.00) 1(16.67) 5(83.33) Total 56(77.78) 5(6.94) 5(6.94) 6(8.33) Postprandial 4h group χ 2 = 3.33 0.766 0.737 (0.588 ,0.887) Absent 49(69.01) 47(95.92) 1(2.04) 1(2.04) 0(0.00) Mild 9(12.68) 3(33.33) 5(55.56) 1(11.11) 0(0.00) Moderate 5(7.04) 0(0.00) 2(40.00) 3(60.00) 0(0.00) Severe 8(11.27) 0(0.00) 0(0.00) 1(12.50) 7(87.50) Total 50(70.42) 8(11.27) 6(8.45) 7(9.86) Note.—Data are numbers of participants, with percentages in parentheses. Adverse events None of the participants reported any discomfort or adverse reactions during the examination. Discussion Liver biopsy is considered the gold standard for diagnosing MAFLD[ 7 ]. However, high costs and the higher risk of complications such as bleeding, bile leakage, and infection limit its application. As a result, non-invasive imaging techniques have increasingly gained attention for use in assessing hepatic steatosis. Among these, ATI offers the advantage of real-time imaging, which enables precise quantification of hepatic fat content[ 8 ]. The principle of ATI is based on the acoustic differences between fatty tissue and normal liver parenchyma[ 6 ]. The attenuation rate of sound waves is higher in fatty tissue than in normal liver tissue. By measuring the speed and attenuation of sound waves as they pass through different tissues, ATI can quantitatively assess the fat content in liver tissue[ 9 ]. Currently, studies recommend fasting for at least 6 hours before undergoing an ATI examination[ 10 – 12 ]. The possible reason is that postprandial increases in hepatic blood flow and vascular engorgement may alter the acoustic properties of liver tissue. Blood exhibits an absorptive and scattering effect on sound waves. Moreover, increased blood flow might enhance these effects, leading to greater attenuation, which may potentially affect ATI results. However, prolonged fasting presents some challenges. For instance, in patients with weaker constitutions, prolonged fasting may cause hypoglycemia and syncope[ 13 ]. Diabetic patients, who often have unstable blood glucose levels, are at risk of severe hypoglycemia if they engage in extended fasting, and this can be life-threatening[ 14 – 16 ]. For patients who take medication regularly and with food, prolonged fasting may interfere with their treatment. Thus, reducing the fasting period before examinations could help to avoid unnecessary harm and promote patient recovery. To the best of our knowledge, this prospective study is the first to investigate the impact of a low-fat diet on liver ATI. The study concluded that consuming a low-calorie, reduced-fat diet significantly alleviated participants' hunger severity. The results also demonstrate that the increase in ATI values observed in the postprandial groups was not significant. In addition, there were no statistically significant differences in the ATI values between the postprandial and fasting states within the three postprandial groups. Since ATI is clinically used for diagnosing the grade of hepatic steatosis, further consistency testing of the grading of hepatic steatosis between postprandial and fasting states was conducted to assess whether a low-calorie, reduced-fat diet might influence ATI examination. The results revealed that the Kappa values for consistency across three different diagnostic criteria were always high, indicating a substantial level of agreement. Therefore, consuming a low-calorie, reduced-fat diet does not affect ATI measurements or the accuracy of the grading diagnosis of hepatic steatosis. One possible explanation for this finding is that the low-calorie, reduced-fat diet used in this study was predominantly carbohydrate-based, with simple ingredients that require relatively low energy for digestion and absorption[ 17 , 18 ]. As a result, the postprandial increase in hepatic portal venous blood flow was minimal. Moreover, the hepatic artery buffering effect possibly reduced the changes in hepatic hemodynamics, leading to stable liver perfusion[ 19 – 21 ]. Consequently, the ATI values remained unchanged. This study had certain limitations. First, the participants were predominantly aged between 20 to 60 years, thereby skewing towards a middle-aged and younger population. Therefore, it is unclear whether the findings entirely apply to older adults. The future research should consider including a broader age range, particularly those over 60 years of age. Second, the BMI of the participants in this study was relatively low compared to populations in many Western countries, possibly due to racial and dietary variations. Thus, the results may need to be validated in diverse populations from different regions and ethnic backgrounds. Finally, ATI measurements is a Canon-specific proprietary imaging modality. Conclusion In conclusion, consuming a low-calorie, reduced-fat diet not only effectively alleviated patients' hunger severity, but also does not significantly affect liver ATI measurements, nor does it interfere with the grading diagnosis of hepatic steatosis. Abbreviations ATI, attenuation imaging; MAFLD, metabolic dysfunction associated fatty liver disease; VAS, visual analogue scales. Declarations Author Contribution RJL, JL, and DNH designed the research. YJS, WFL, and JHP performed the research. WTL and WYM performed data analyses. RJL, JL, and DNH edited the manuscript. ZFX acquired funding. RJL, JL, and DNH contributed equally to this study. The order of the co–first authors’ names was determined on the basis of their contributions to this study. All authors read and approved the final manuscript. Acknowledgement This work was supported by the Seventh Affiliated Hospital, Sun Yat-Sen University Clinical Research 735 program (No. ZSQY735202210). The authors thank the study subjects for their participation. The authors would like to express their gratitude to EditSprings (https://www.editsprings.cn) for the expert linguistic services provided. References Eslam M, Newsome PN, Sarin SK, Anstee QM, Targher G, Romero-Gomez M, et al. A new definition for metabolic dysfunction-associated fatty liver disease: An international expert consensus statement. J Hepatol 2020;73(1):202-9. doi: 10.1016/j.jhep.2020.03.039. Peng HY, Duan SJ, Pan L, Wang MY, Chen JL, Wang YC, et al. Development and validation of machine learning models for nonalcoholic fatty liver disease. Hepatobiliary Pancreat Dis Int 2023;22(6):615-21. doi: 10.1016/j.hbpd.2023.03.009. Eslam M, Sanyal AJ, George J; International Consensus Panel. MAFLD: A Consensus-Driven Proposed Nomenclature for Metabolic Associated Fatty Liver Disease. Gastroenterology 2020;158(7):1999-2014.e1.doi: 0.1053/j.gastro.2019.11.312. Bae JS, Lee DH, Lee JY, Kim H, Yu SJ, Lee JH, et al. Assessment of hepatic steatosis by using attenuation imaging: a quantitative, easy-to-perform ultrasound technique. Eur Radiol 2019;29(12):6499-507. doi: 10.1007/s00330-019-06272-y. Tada T, Kumada T, Toyoda H, Nakamura S, Shibata Y, Yasuda S, et al. Attenuation imaging based on ultrasound technology for assessment of hepatic steatosis: A comparison with magnetic resonance imaging-determined proton density fat fraction. Hepatol Res 2020;50(12):1319-27. doi: 10.1111/hepr.13563. Sugimoto K, Moriyasu F, Oshiro H, Takeuchi H, Abe M, Yoshimasu Y, et al. The Role of Multiparametric US of the Liver for the Evaluation of Nonalcoholic Steatohepatitis. Radiology 2020;296(3): 532-40. doi: 10.1148/radiol.2020192665. Dioguardi Burgio M, Ronot M, Reizine E, Rautou PE, Castera L, Paradis V, et al. Quantification of hepatic steatosis with ultrasound: promising role of attenuation imaging coefficient in a biopsy-proven cohort. Eur Radiol 2020;30(4):2293-301. doi: 10.1007/s00330-019-06480-6. Tada T, Iijima H, Kobayashi N, Yoshida M, Nishimura T, Kumada T, et al. Usefulness of Attenuation Imaging with an Ultrasound Scanner for the Evaluation of Hepatic Steatosis. Ultrasound Med Biol 2019;45(10):2679-87. doi: 10.1016/j.ultrasmedbio.2019.05.033. Dioguardi Burgio M, Ronot M, Reizine E, Rautou PE, Castera L, Paradis V, et al. Quantification of hepatic steatosis with ultrasound: promising role of attenuation imaging coefficient in a biopsy-proven cohort. Eur Radiol 2020;30(4): 2293-301. doi: 10.1007/s00330-019-06480-6. Bae JS, Lee DH, Lee JY, Kim H, Yu SJ, Lee JH, et al. Assessment of hepatic steatosis by using attenuation imaging: a quantitative, easy-to-perform ultrasound technique. Eur Radiol 2019;29(12): 6499-507. doi: 10.1007/s00330-019-06272-y. Tada T, Kumada T, Toyoda H, Nakamura S, Shibata Y, Yasuda S, et al. Attenuation imaging based on ultrasound technology for assessment of hepatic steatosis: A comparison with magnetic resonance imaging-determined proton density fat fraction. Hepatol Res 2020;50(12): 1319-27. doi: 10.1111/hepr.13563. Yoo J, Lee JM, Joo I, Lee DH, Yoon JH, Kang HJ, et al. Reproducibility of ultrasound attenuation imaging for the noninvasive evaluation of hepatic steatosis. Ultrasonography 2020;39(2): 121-9. doi: 10.14366/usg.19034. Yi SW, Won YJ, Yi JJ. Low normal fasting glucose and risk of accidental death in Korean adults: A prospective cohort study. Diabetes Metab 2019;45(1):60-6. doi: 10.1016/j.diabet.2018.01.005. Chevli PA, Ahmad MI, Hari K, Anees MA, Soliman EZ. Impact of low fasting plasma glucose on mortality in the general population. Diab Vasc Dis Res 2020;17(3):1479164120930599. doi: 10.1177/1479164120930599. Lee JH, Han K, Huh JH. The sweet spot: fasting glucose, cardiovascular disease, and mortality in older adults with diabetes: a nationwide population-based study. Cardiovasc Diabetol 2020;19(1):44. doi: 10.1186/s12933-020-01021-8. Pinto PN, Chojniak R, Cohen MP, Yu LS, Queiroz-Andrade M, Bitencourt AG. Comparison of three types of preparations for abdominal sonography. J Clin Ultrasound 2011;39(4):203-8. doi: 10.1002/jcu.20790. Cohn JS, Kamili A, Wat E, Chung RW, Tandy S. Reduction in intestinal cholesterol absorption by various food components: mechanisms and implications. Atheroscler Suppl 2010, 11(1): 45-8. doi: 10.1016/j.atherosclerosissup.2010.04.004. Loveday SM. Protein digestion and absorption: the influence of food processing. Nutr Res Rev 2023, 36(2): 544-59. doi: 10.1017/S0954422422000245. Lautt WW. Mechanism and role of intrinsic regulation of hepatic arterial blood flow: hepatic arterial buffer response. Am J Physiol 1985;249(5 Pt 1): G549-56. doi: 10.1152/ajpgi.1985.249.5.G549. Joynt LK, Platt JF, Rubin JM, Ellis JH, Bude RO. Hepatic artery resistance before and after standard meal in subjects with diseased and healthy livers. Radiology 1995;196(2): 489-92. doi: 10.1148/radiology.196.2.7617865. Dauzat M, Lafortune M, Patriquin H, Pomier-Layrargues G. Meal induced changes in hepatic and splanchnic circulation: a noninvasive Doppler study in normal humans. Eur J Appl Physiol Occup Physiol 1994;68(5): 373-80. doi: 10.1007/BF00843732. Additional Declarations No competing interests reported. Supplementary Files CONSORTchecklist.docx Cite Share Download PDF Status: Published Journal Publication published 18 Dec, 2024 Read the published version in Abdominal Radiology → Version 1 posted Editorial decision: Revision requested 06 Nov, 2024 Reviews received at journal 04 Nov, 2024 Reviews received at journal 04 Nov, 2024 Reviews received at journal 01 Nov, 2024 Reviewers agreed at journal 25 Oct, 2024 Reviewers agreed at journal 24 Oct, 2024 Reviewers agreed at journal 22 Oct, 2024 Reviewers invited by journal 22 Oct, 2024 Editor assigned by journal 22 Oct, 2024 Submission checks completed at journal 22 Oct, 2024 First submitted to journal 21 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-5303569\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":373409792,\"identity\":\"917c1e23-c744-49eb-b866-4be0bc485db9\",\"order_by\":0,\"name\":\"Renjie Li\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The Seventh Affiliated Hospital of Sun Yat-sen University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Renjie\",\"middleName\":\"\",\"lastName\":\"Li\",\"suffix\":\"\"},{\"id\":373409793,\"identity\":\"1a8f1f8a-fe44-49e3-bbcb-9fa61763219f\",\"order_by\":1,\"name\":\"Jie Li\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The Seventh Affiliated Hospital of Sun Yat-sen University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jie\",\"middleName\":\"\",\"lastName\":\"Li\",\"suffix\":\"\"},{\"id\":373409794,\"identity\":\"3d5b3f5a-419f-4f17-9f77-d2b5aa64908a\",\"order_by\":2,\"name\":\"Danni He\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The Seventh Affiliated Hospital of Sun Yat-sen University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Danni\",\"middleName\":\"\",\"lastName\":\"He\",\"suffix\":\"\"},{\"id\":373409795,\"identity\":\"69c5fa38-494b-4bc0-95c9-2c911bcac3a0\",\"order_by\":3,\"name\":\"Yajuan Sui\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The Seventh Affiliated Hospital of Sun Yat-sen University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Yajuan\",\"middleName\":\"\",\"lastName\":\"Sui\",\"suffix\":\"\"},{\"id\":373409796,\"identity\":\"ac63d429-c15f-4762-b089-f4a593b8f128\",\"order_by\":4,\"name\":\"Wenfen Liu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The Seventh Affiliated Hospital of Sun Yat-sen University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Wenfen\",\"middleName\":\"\",\"lastName\":\"Liu\",\"suffix\":\"\"},{\"id\":373409797,\"identity\":\"c77b8203-46a6-4306-a284-089cb8dd8c1d\",\"order_by\":5,\"name\":\"Wentao Li\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The Seventh Affiliated Hospital of Sun Yat-sen University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Wentao\",\"middleName\":\"\",\"lastName\":\"Li\",\"suffix\":\"\"},{\"id\":373409798,\"identity\":\"432887db-530a-4f4b-b4da-36f1cc81ff75\",\"order_by\":6,\"name\":\"Wenyi Meng\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The Seventh Affiliated Hospital of Sun Yat-sen University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Wenyi\",\"middleName\":\"\",\"lastName\":\"Meng\",\"suffix\":\"\"},{\"id\":373409799,\"identity\":\"02581f10-0317-43cc-a3b6-416e0af407cc\",\"order_by\":7,\"name\":\"Jiahui Peng\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"The Seventh Affiliated Hospital of Sun Yat-sen University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jiahui\",\"middleName\":\"\",\"lastName\":\"Peng\",\"suffix\":\"\"},{\"id\":373409800,\"identity\":\"54d9f782-d379-44e8-a5c7-cfec442cff7f\",\"order_by\":8,\"name\":\"Zuofeng Xu\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYJCCDx8YGHj44NwDhHUwzpwB1MJGkpbZPECSeC0GN9IfNtvm2MmwMbA/k/zZxiDHdyOB8XMBHi2SMxISm3O3JQMdxmMmzdvGYCx5I4FZegYeLfwSCccf525jBmlhk2ZsY0jccCOBjZkHjxY2icTGZstt9Twwh9UT1MIvkczYzLjtMCjEzCSADkswIKRFsucZY2PvtuM8QGXG1jznJAxnnnnYLI1Pi8Hx9IcNP7dV2/Oztz+8+aPMRp7vePLBz/i0IAAzA4sEAwMQMTA2EKUBrOkD0UpHwSgYBaNgRAEAySRAiLQjhfEAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"The Seventh Affiliated Hospital of Sun Yat-sen University\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Zuofeng\",\"middleName\":\"\",\"lastName\":\"Xu\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-10-21 10:38:23\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-5303569/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-5303569/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1007/s00261-024-04762-2\",\"type\":\"published\",\"date\":\"2024-12-18T15:58:27+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":68689472,\"identity\":\"cfb9aeb1-5bd6-43fa-908e-febfa2ee421b\",\"added_by\":\"auto\",\"created_at\":\"2024-11-11 05:34:56\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":93478,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eParticipant flow diagram of the study\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5303569/v1/7959b47cf241605632f0f248.png\"},{\"id\":68688888,\"identity\":\"fb0f8e82-3f46-4132-bf31-5d80a6ed456f\",\"added_by\":\"auto\",\"created_at\":\"2024-11-11 05:26:56\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":69645,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe comparison of hunger severity scores between groups\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5303569/v1/2dc124abf13c9629c83c4b87.png\"},{\"id\":68688890,\"identity\":\"99a65b55-f850-4fa9-b72f-e8257f77647e\",\"added_by\":\"auto\",\"created_at\":\"2024-11-11 05:26:56\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":73435,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe comparison of ATI Values between groups\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5303569/v1/09ad30c5fbc22b22e89c1539.png\"},{\"id\":68688892,\"identity\":\"8795e3a4-b7f0-4721-8f24-4cebe2d8a262\",\"added_by\":\"auto\",\"created_at\":\"2024-11-11 05:26:56\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":30668,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe diagnosis was based on the presence or absence of hepatic steatosis, the consistency in the postprandial and fasting states\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5303569/v1/8fc5eb2a6ecd0ff0d56ced4a.png\"},{\"id\":68688895,\"identity\":\"88c8b47e-7aa1-4402-ba7f-d823ec9e2b28\",\"added_by\":\"auto\",\"created_at\":\"2024-11-11 05:26:57\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":30326,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe diagnosis was based on the presence or absence of moderate-to-severe hepatic steatosis, the consistency in the postprandial and fasting states\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5303569/v1/920f445db9d4a168d73de26f.png\"},{\"id\":68688894,\"identity\":\"30d1ed4b-3e4c-4690-a5fa-ad67d8e8cb04\",\"added_by\":\"auto\",\"created_at\":\"2024-11-11 05:26:57\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":34728,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe diagnosis was based on the absent, mild, moderate, and severe hepatic steatosis, the consistency in the postprandial and fasting states\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"7.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5303569/v1/8ba4b0213b32c59cc331d52a.png\"},{\"id\":72201986,\"identity\":\"bad595f2-56b3-4ae4-8b44-d3605cfee511\",\"added_by\":\"auto\",\"created_at\":\"2024-12-23 16:13:08\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1103867,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5303569/v1/cfc7ac50-f2dc-4921-8649-ae614c4ba341.pdf\"},{\"id\":68688893,\"identity\":\"43c9d665-2b67-4f08-aa3f-ca8569ef185c\",\"added_by\":\"auto\",\"created_at\":\"2024-11-11 05:26:57\",\"extension\":\"docx\",\"order_by\":3,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":24977,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"CONSORTchecklist.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-5303569/v1/c9b53d20b4aa73551b683130.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"The impact of a low-calorie, reduced-fat diet on liver attenuation imaging: A randomized clinical trial\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eWith the remarkable improvement in living standards and the increasing prevalence of metabolic disorders and obesity, the incidence of Metabolic Dysfunction Associated Fatty Liver Disease (MAFLD) is also on the rise. MAFLD has become the most common chronic liver disease globally, having surpassed viral hepatitis[\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. MAFLD positively correlates with the development of metabolic disorders and cardiovascular diseases[\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. The precondition for diagnosing MAFLD is the diagnosis of hepatic steatosis. Attenuation Imaging (ATI) is a novel, non-invasive technology that is increasingly being clinically used for assessing hepatic steatosis[\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]. ATI plays a significant role in the early detection, diagnosis, and prognosis assessment of MAFLD. Typically, patients are required to fast for over 6 hours before undergoing ATI. However, prolonged fasting can lead to anxiety and a series of adverse effects, such as hypoglycemia, fainting, or even shock, all of which pose a threat to health. Based on clinical experience, consuming a light diet before an abdominal ultrasound did not exhibit any negative impact on the ultrasound examination for some patients. Since ATI is performed based on conventional grayscale imaging, we hypothesize that consuming a certain amount of low-fat food before the examination may not affect liver ATI results. This study aims to investigate whether a low-calorie, reduced-fat diet influences ATI measurements and the grading diagnosis of hepatic steatosis.\\u003c/p\\u003e\"},{\"header\":\"Materials and methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eParticipants\\u003c/h2\\u003e \\u003cp\\u003eThis is a prospective randomized controlled study that was conducted between December 2022 and August 2024. It involved 320 patients who underwent routine liver ATI examinations in the ultrasound department of the hospital where the researcher works. The inclusion criteria were as follows: \\u003cem\\u003e(a)\\u003c/em\\u003e Patients undergoing routine liver ATI examinations; \\u003cem\\u003e(b)\\u003c/em\\u003e Patients aged between 18\\u0026ndash;80 years; \\u003cem\\u003e(c)\\u003c/em\\u003e Patients who are conscious enough to understand and sign informed consent; \\u003cem\\u003e(d)\\u003c/em\\u003e Patients with no history of allergy to the foods used in this study; \\u003cem\\u003e(e)\\u003c/em\\u003e Patients who can eat normally. The exclusion criteria were as follows: \\u003cem\\u003e(a)\\u003c/em\\u003e Patients with acute, critical illnesses; \\u003cem\\u003e(b)\\u003c/em\\u003e Patients with special dietary restrictions; \\u003cem\\u003e(c)\\u003c/em\\u003e Patients involved in other examinations or treatments that may conflict with this study.\\u003c/p\\u003e \\u003cp\\u003eA simple randomization method was used to assign the participants to groups, during the scheduling of ATI examinations. Randomization information was sealed in opaque envelopes that were prepared by a researcher who was not involved in data collection or analysis. The participants were randomly assigned to one of the following four groups: a fasting group; a postprandial 0.5h examination group; a postprandial 2h examination group; and a postprandial 4h examination group.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eStudy procedures\\u003c/h3\\u003e\\n\\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eInstrumentation\\u003c/h2\\u003e \\u003cp\\u003eThe Aplio i900 ultrasound system (Canon Ltd, Japan) was used in this study. ATI examination was performed using a convex array transducer (i8CX1, 1.8\\u0026ndash;6.2 MHz).\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003ePre-examination dietary instructions\\u003c/h3\\u003e\\n\\u003cp\\u003eThe participants were instructed to consume a light meal the evening before the examination and to fast after 22:00. The baseline demographic characteristics of all participants were recorded.\\u003c/p\\u003e\\n\\u003ch3\\u003eAssessment of hunger severity\\u003c/h3\\u003e\\n\\u003cp\\u003eAssessing participants' hunger severity using the visual analogue scales (VAS) before each ATI examination: rated on a scale of 0\\u0026ndash;10, where \\\"0\\\" represents no hunger at all, and \\\"10\\\" represents intolerable hunger.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eATI examination procedure\\u003c/h2\\u003e \\u003cp\\u003eATI examinations were performed using the same equipment by one of three radiologists, each with over 10 years of experience in ultrasound imaging. They received standardized training on liver ATI examination procedures. The examinations were performed in a blinded manner. The radiologists were unaware of the participants' grouping informations and did not know whether they were in fasting or postprandial states prior to the examination.\\u003c/p\\u003e \\u003cp\\u003eAll participants first underwent liver ATI examination on the trial day while they were fasting. After the initial examination, participants in the postprandial groups consumed a low-calorie, reduced-fat diet. The energy content of these meals was more than 25% lower than that required for the standard breakfast for an adult. The fat content was below 3 g/100 g of solid food or 1.5 g/100 mL of liquid food. Two meal combinations were provided, and participants had the leverage to choose their preferences. Both meal combinations met the low-fat criteria. Meal Option 1 involved one white steamed bun (100 g, 983 kJ, 1.63 g fat) and a bowl of plain porridge (200 mL, 356 kJ, 0.22 g fat), with a total energy content of 1339 kJ and total fat content of 1.85 g. Meal Option 2 included a slice of white toast (100 g, 1067 kJ, 1.9 g fat) and jam (20 mL, 233 kJ, 0.02 g fat), with a total energy content of 1300 kJ and total fat content of 1.92 g. Participants were instructed to finish the meal within 10 minutes under the supervision of the study staff.\\u003c/p\\u003e \\u003cp\\u003eThen, the participants in the postprandial groups underwent a second ATI examination at 0.5h, 2h, or 4h after the meal. Each participant only underwent one follow-up examination. The participants were not allowed to eat any additional food before the second examination. The postprandial ATI measurements for each participant were independently conducted by a different radiologist using the same ultrasound machine. All this was done to ensure that the initial fasting scan results would not influence the postprandial scan.\\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eAttenuation imaging procedure\\u003c/h3\\u003e\\n\\u003cp\\u003eThe radiologist avoided calcifications, artifacts, and large ductal structures within the liver, and identified an optimal intercostal scanning plane in the right hepatic lobe. Then the radiologist switched to the ATI mode, with the upper edge of the sample box placed 1 cm below the liver capsule. The size of the sample box was set to 4 \\u0026times; 3 cm, and the image was frozen. When the yellow sample box appeared, it was positioned within the green sample box to display the ATI value.\\u003c/p\\u003e \\u003cp\\u003eThe coefficient of determination (R2) was used to assess the reliability of the displayed ATI value. An R2\\u0026thinsp;\\u0026gt;\\u0026thinsp;90% indicated excellent reliability. The R2 between 80% and 90% showed good reliability, while R2\\u0026thinsp;\\u0026lt;\\u0026thinsp;80% highlighted poor reliability. Only ATI values with an R2 above 90%, displayed as white numerals, met the inclusion criteria for this study. Five valid ATI values were measured for each examination, and the median of these five measurements was recorded as the ATI value for that session.\\u003c/p\\u003e\\n\\u003ch3\\u003eOutcomes\\u003c/h3\\u003e\\n\\u003cp\\u003eAs the primary outcomes, the ATI values were compared among the groups and the differences between postprandial and fasting ATI values were also analyzed in the three postprandial groups. As the secondary outcomes, the consistency of the grading diagnosis of hepatic steatosis between the postprandial and fasting states was evaluated in the three postprandial groups and the hunger severity scores were compared among the groups.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSample size calculation\\u003c/h2\\u003e \\u003cp\\u003eThis research is designed as a randomized, controlled, and equivalence clinical trial. Participants are randomly allocated into four groups: a fasting control group, and three postprandial groups at 0.5 hours, 2 hours, and 4 hours, respectively. The study presupposes a mean difference of 0 and a standard deviation of 0.13 between any two groups in the four groups, with an equivalence margin set at 0.085. Utilizing a two-sided α\\u0026thinsp;=\\u0026thinsp;0.05 and a test power of 1-β\\u0026thinsp;=\\u0026thinsp;0.90, PASS15 software calculations determine that an initial sample size of 52 per group is required. Given a 10% dropout rate, the final sample size for each group is 58, resulting in a total sample size of 232.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStatistical analysis\\u003c/h2\\u003e \\u003cp\\u003eStatistical analyses were performed using SAS 9.4(version 9.4 for Windows, SAS Institute, Inc, Cary, NC, USA). Categorical data were presented as frequencies and percentages, while quantitative data were expressed as means\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;standard deviations (normal distribution) or M (IQR) (non-normal distribution). The Mann-Whitney U test was used to compare the differences in ATI values and hunger severity scores between each postprandial group and the fasting group. The Wilcoxon Signed Rank Test was employed to assess the differences in ATI values between fasting and postprandial states within the same group. The Kappa coefficient was used to evaluate the consistency of the grading diagnosis of hepatic steatosis between fasting and postprandial states among the three postprandial groups. The Kappa value was interpreted as follows: \\u0026lt; 0.2 indicates poor agreement; 0.2\\u0026ndash;0.4 shows fair agreement; 0.4\\u0026ndash;0.6 represents moderate agreement; 0.6\\u0026ndash;0.8 signaled substantial agreement; and 0.8-1.0 suggests almost perfect agreement. A two-tailed α level of 0.05 was set as the significance threshold, with \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 being considered statistically significant.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eBaseline characteristics\\u003c/h2\\u003e \\u003cp\\u003eA total of 320 participants were initially enrolled in this study. However, 12 participants did not attend the examination on the scheduled day and 5 ultrasound examinations were canceled. Eight of the participants had temporary conflicts with the study time due to other examinations or treatments. Ultimately, 25 participants were excluded from the final analysis, consequently leaving 295 participants who were then included in the statistical analyses. The participant flowchart is presented in Figure. 1. The analyses were conducted based on the original group assignments, and the baseline characteristics across the groups were similar (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eBaseline characteristics of the participants\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCharacteristic\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eFasting group\\u003c/p\\u003e \\u003cp\\u003e(\\u003cem\\u003en\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;76)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003ePostprandial 0.5h(\\u003cem\\u003en\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;70)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ePostprandial 2h(\\u003cem\\u003en\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;76)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003ePostprandial 4h(\\u003cem\\u003en\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;73)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eStatistics\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e Value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGender\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e52(68.42)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e37(52.86)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e49(64.47)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e48(65.75)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eχ\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u0026thinsp;\\u003cem\\u003e=\\u003c/em\\u003e\\u0026thinsp;4.358\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.225\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e24(31.58)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e33(47.14)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e27(35.53)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c7\\\" namest=\\\"c6\\\"\\u003e \\u003cp\\u003e25(34.25)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge(years)\\u003csup\\u003e\\u0026dagger;\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e35.0(29.5,44.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e34.0(25.0,46.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e32.5(26.0,41.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e38.0(28.0,44.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eH\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;3.652\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.301\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBMI (kg/m\\u003csup\\u003e2\\u003c/sup\\u003e) \\u003csup\\u003e\\u0026dagger;\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e22.2(20.3,24.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e22.0(20.0,24.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e22.4(20.2,24.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e22.0(20.7,26.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eH\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.964\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.809\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eWaist(cm)\\u003csup\\u003e\\u0026dagger;\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e78.0(69.5,84.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e77.0(69.0,85.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e76.5(70.0,83.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e76.0(71.0,86.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eH\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.290\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.961\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"8\\\"\\u003eNote.\\u0026mdash;Except where indicated, data are numbers of participants, with percentages in parentheses. BMI\\u0026thinsp;=\\u0026thinsp;body mass index.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"8\\\"\\u003e\\u003csup\\u003e\\u0026dagger;\\u003c/sup\\u003e Data are M (\\u003cem\\u003eIQR\\u003c/em\\u003e)\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eIntergroup comparison of hunger severity scores\\u003c/h2\\u003e \\u003cp\\u003eAs shown in Figure. 2, the hunger severity scores of the postprandial 0.5h and 2h groups were lower than those of the fasting group (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). However, there was no significant difference between the postprandial 4h group and the fasting group (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.430).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec16\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eIntergroup comparison of ATI values\\u003c/h2\\u003e \\u003cp\\u003eAs shown in Figure. 3, the ATI values for the postprandial 0.5h group [0.56(0.50,0.62) dB/cm/MHz], postprandial 2h group [0.55(0.51,0.65) dB/cm/MHz], and postprandial 4h group [0.58(0.53,0.70) dB/cm/MHz] were not significantly different from the fasting group's ATI value [0.57(0.53,0.69) dB/cm/MHz] (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.576, 0.471, and 0.992, respectively).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec17\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eIntragroup comparison of ATI values in postprandial groups\\u003c/h2\\u003e \\u003cp\\u003eThe study results indicated that the liver ATI values for the postprandial 0.5h group in the postprandial and fasting states were 0.56(0.50,0.62) dB/cm/MHz and 0.57(0.51,0.64) dB/cm/MHz, respectively. For the postprandial 2h group, the ATI values in the postprandial and fasting states were 0.55(0.51,0.65) dB/cm/MHz and 0.56(0.49,0.66) dB/cm/MHz, respectively. In the postprandial 4h group, the ATI values in the postprandial and fasting states were 0.58(0.53,0.70) dB/cm/MHz and 0.59(0.53,0.69) dB/cm/MHz, respectively. As shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, none of these numerical differences were statistically significant (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.573, 0.076, and 0.805, respectively). (Figure. 4A-F)\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eIntragroup comparison of ATI values in postprandial groups\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGroup\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eFasting states\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ePostprandial states\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePostprandial 0.5h group\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.57(0.51,0.64)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.56(0.50,0.62)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.573\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePostprandial 2h group\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.56(0.49,0.66)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.55(0.51,0.65)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.076\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePostprandial 4h group\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.59(0.53,0.69)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.58(0.53,0.70)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.805\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003eNote.\\u0026mdash;Data are ATI values. Data are M (\\u003cem\\u003eIQR\\u003c/em\\u003e).\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec18\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDiagnosis of hepatic steatosis in each group\\u003c/h2\\u003e \\u003cp\\u003eThe ATI values were used to assess the grade of hepatic steatosis. Absent, mild, moderate, and severe hepatic steatosis corresponded to grades S0 (\\u0026lt;\\u0026thinsp;5% of hepatocytes), S1 (5%-33% of hepatocytes), S2 (33%-66% of hepatocytes), and S3 (\\u0026gt;\\u0026thinsp;66% of hepatocytes), respectively. The corresponding ATI diagnostic cutoff values for each grade were 0.67, 0.72, and 0.86 dB/cm/MHz[\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. Using the ATI values of participants in each group under fasting states as the benchmark and referring to the ATI diagnostic threshold for hepatic steatosis, the fasting group detected 21 cases of hepatic steatosis (including 4 case of mild hepatic steatosis, 10 cases of moderate hepatic steatosis, and 7 cases of severe hepatic steatosis), with a detection rate of 27.63%; the postprandial 0.5h group detected 13 cases (including 3 mild, 6 moderate, and 4 severe), with a detection rate of 19.12%; the postprandial 2h group detected 18 cases (including 4 mild, 8 moderate, and 6 severe), with a detection rate of 25.00%; and the postprandial 4h group detected 22 cases (including 9 mild, 5 moderate, and 8 severe), with a detection rate of 30.99%.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec19\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eConsistency of grading diagnosis of hepatic steatosis in postprandial groups\\u003c/h2\\u003e \\u003cp\\u003eThe consistency of grading diagnosis between the postprandial and fasting states were evaluated across three different criteria. First, when the diagnosis identified the presence or absence of hepatic steatosis, the Kappa values for diagnostic consistency between the postprandial and fasting states for the three postprandial groups were 0.951, 0.846, and 0.833, respectively (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e, Figure. 5A-C). Second, when the diagnosis was based on the presence or absence of moderate-to-severe hepatic steatosis, the Kappa values were 0.831, 0.855, and 0.812, respectively (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e, Figure. 6A-C). Finally, when the diagnosis distinguished between absent, mild, moderate, and severe hepatic steatosis, the Kappa values were 0.862, 0.756, and 0.737, respectively (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e, Figure. 7A-C). These findings indicate that for all diagnostic criteria, the Kappa values were always high, suggesting a substantial degree of consistency in grading the diagnosis of hepatic steatosis.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eThe consistency of the presence or absence of hepatic steatosis\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"7\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003eClassification\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eClassification\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAbsence\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003ePresence\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eKappa\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePostprandial 0.5h group\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eχ\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;1.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.317\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.951 (0.856 ,1.000)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAbsence\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e55(80.88)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e55(100.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePresence\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e13(19.12)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1(7.69)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e12(92.31)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e56(82.35)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e12(17.65)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePostprandial 2h group\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eχ\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;1.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.317\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.846(0.701 ,0.992)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAbsence\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e54(75.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e53(98.15)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1(1.85)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePresence\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e18(25.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3(16.67)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e15(83.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e56(77.78)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e16(22.22)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePostprandial 4h group\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eχ\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;0.20\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.655\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.833(0.693 ,0.974)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAbsence\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e49(69.01)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e47(95.92)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2(4.08)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePresence\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e22(30.99)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3(13.64)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e19(86.36)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e50(70.42)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e21(29.58)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"7\\\"\\u003eNote.\\u0026mdash;Data are numbers of participants, with percentages in parentheses.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eThe consistency of the presence or absence of moderate-to-severe hepatic steatosis\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"7\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003eClassification\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eClassification\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAbsent and mild\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eModerate and severe\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eKappa\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePostprandial 0.5h group\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eχ\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;0.33\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.564\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.831 (0.646 ,1.000)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAbsent and mild\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e58(85.29)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e56(96.55)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2(3.45)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate and severe\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e10(14.71)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1(10.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e9(90.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e57(83.82)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e11(16.18)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePostprandial 2h group\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eχ\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;3.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.083\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.855(0.697 ,1.000)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAbsent and mild\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e58(80.56)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e58(100.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate and severe\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e14(19.44)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3(21.43)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e11(78.57)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e61(84.72)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e11(15.28)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePostprandial 4h group\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eχ\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;0.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1.000\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e0.812(0.634 ,0.990)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAbsent and mild\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e58(81.69)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e56(96.55)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2(3.45)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate and severe\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e13(18.31)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2(15.38)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e11(84.62)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e58(81.69)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e13(18.31)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"7\\\"\\u003eNote.\\u0026mdash;Data are numbers of participants, with percentages in parentheses.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab5\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 5\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eThe consistency of absent, mild, moderate, and severe hepatic steatosis\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"9\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"4\\\" nameend=\\\"c6\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003eClassification\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eClassification\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAbsent\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eMild\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eModerate\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eSevere\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003eKappa\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePostprandial 0.5h group\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eχ\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;3.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.809\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.862(0.721 ,1.000)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAbsent\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e55(80.88)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e55(100.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e 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align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6(8.82)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1(16.67)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e5(83.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSevere\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4(5.88)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e4(100.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e56(82.35)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1(1.47)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e7(10.29)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e4(5.88)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePostprandial 2h group\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eχ\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;3.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.809\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.756(0.597 ,0.915)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAbsent\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e54(75.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e53(98.15)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1(1.85)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMild\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4(5.56)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1(25.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3(75.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e8(11.11)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2(25.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1(12.50)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e4(50.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1(12.50)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSevere\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6(8.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1(16.67)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e5(83.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e56(77.78)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5(6.94)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e5(6.94)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e6(8.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePostprandial 4h group\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eχ\\u003c/em\\u003e\\u003csup\\u003e\\u003cem\\u003e2\\u003c/em\\u003e\\u003c/sup\\u003e\\u0026thinsp;=\\u0026thinsp;3.33\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.766\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.737 (0.588 ,0.887)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAbsent\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e49(69.01)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e47(95.92)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1(2.04)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1(2.04)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMild\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e9(12.68)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3(33.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5(55.56)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1(11.11)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModerate\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5(7.04)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2(40.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e3(60.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSevere\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e8(11.27)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1(12.50)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e7(87.50)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e50(70.42)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8(11.27)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e6(8.45)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e7(9.86)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"9\\\"\\u003eNote.\\u0026mdash;Data are numbers of participants, with percentages in parentheses.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec20\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eAdverse events\\u003c/h2\\u003e \\u003cp\\u003eNone of the participants reported any discomfort or adverse reactions during the examination.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eLiver biopsy is considered the gold standard for diagnosing MAFLD[\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]. However, high costs and the higher risk of complications such as bleeding, bile leakage, and infection limit its application. As a result, non-invasive imaging techniques have increasingly gained attention for use in assessing hepatic steatosis. Among these, ATI offers the advantage of real-time imaging, which enables precise quantification of hepatic fat content[\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]. The principle of ATI is based on the acoustic differences between fatty tissue and normal liver parenchyma[\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]. The attenuation rate of sound waves is higher in fatty tissue than in normal liver tissue. By measuring the speed and attenuation of sound waves as they pass through different tissues, ATI can quantitatively assess the fat content in liver tissue[\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eCurrently, studies recommend fasting for at least 6 hours before undergoing an ATI examination[\\u003cspan additionalcitationids=\\\"CR11\\\" citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e]. The possible reason is that postprandial increases in hepatic blood flow and vascular engorgement may alter the acoustic properties of liver tissue. Blood exhibits an absorptive and scattering effect on sound waves. Moreover, increased blood flow might enhance these effects, leading to greater attenuation, which may potentially affect ATI results. However, prolonged fasting presents some challenges. For instance, in patients with weaker constitutions, prolonged fasting may cause hypoglycemia and syncope[\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. Diabetic patients, who often have unstable blood glucose levels, are at risk of severe hypoglycemia if they engage in extended fasting, and this can be life-threatening[\\u003cspan additionalcitationids=\\\"CR15\\\" citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. For patients who take medication regularly and with food, prolonged fasting may interfere with their treatment. Thus, reducing the fasting period before examinations could help to avoid unnecessary harm and promote patient recovery.\\u003c/p\\u003e \\u003cp\\u003eTo the best of our knowledge, this prospective study is the first to investigate the impact of a low-fat diet on liver ATI. The study concluded that consuming a low-calorie, reduced-fat diet significantly alleviated participants' hunger severity. The results also demonstrate that the increase in ATI values observed in the postprandial groups was not significant. In addition, there were no statistically significant differences in the ATI values between the postprandial and fasting states within the three postprandial groups. Since ATI is clinically used for diagnosing the grade of hepatic steatosis, further consistency testing of the grading of hepatic steatosis between postprandial and fasting states was conducted to assess whether a low-calorie, reduced-fat diet might influence ATI examination. The results revealed that the Kappa values for consistency across three different diagnostic criteria were always high, indicating a substantial level of agreement. Therefore, consuming a low-calorie, reduced-fat diet does not affect ATI measurements or the accuracy of the grading diagnosis of hepatic steatosis. One possible explanation for this finding is that the low-calorie, reduced-fat diet used in this study was predominantly carbohydrate-based, with simple ingredients that require relatively low energy for digestion and absorption[\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e]. As a result, the postprandial increase in hepatic portal venous blood flow was minimal. Moreover, the hepatic artery buffering effect possibly reduced the changes in hepatic hemodynamics, leading to stable liver perfusion[\\u003cspan additionalcitationids=\\\"CR20\\\" citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]. Consequently, the ATI values remained unchanged.\\u003c/p\\u003e \\u003cp\\u003eThis study had certain limitations. First, the participants were predominantly aged between 20 to 60 years, thereby skewing towards a middle-aged and younger population. Therefore, it is unclear whether the findings entirely apply to older adults. The future research should consider including a broader age range, particularly those over 60 years of age. Second, the BMI of the participants in this study was relatively low compared to populations in many Western countries, possibly due to racial and dietary variations. Thus, the results may need to be validated in diverse populations from different regions and ethnic backgrounds. Finally, ATI measurements is a Canon-specific proprietary imaging modality.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eIn conclusion, consuming a low-calorie, reduced-fat diet not only effectively alleviated patients' hunger severity, but also does not significantly affect liver ATI measurements, nor does it interfere with the grading diagnosis of hepatic steatosis.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cp\\u003eATI, attenuation imaging; MAFLD, metabolic dysfunction associated fatty liver disease; VAS, visual analogue scales.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eRJL, JL, and DNH designed the research. YJS, WFL, and JHP performed the research. WTL and WYM performed data analyses. RJL, JL, and DNH edited the manuscript. ZFX acquired funding. RJL, JL, and DNH contributed equally to this study. The order of the co\\u0026ndash;first authors\\u0026rsquo; names was determined on the basis of their contributions to this study. All authors read and approved the final manuscript.\\u003c/p\\u003e\\u003ch2\\u003eAcknowledgement\\u003c/h2\\u003e\\u003cp\\u003eThis work was supported by the Seventh Affiliated Hospital, Sun Yat-Sen University Clinical Research 735 program (No. ZSQY735202210). The authors thank the study subjects for their participation. The authors would like to express their gratitude to EditSprings (https://www.editsprings.cn) for the expert linguistic services provided.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eEslam M, Newsome PN, Sarin SK, Anstee QM, Targher G, Romero-Gomez M, et al. A new definition for metabolic dysfunction-associated fatty liver disease: An international expert consensus statement. J Hepatol 2020;73(1):202-9. doi: 10.1016/j.jhep.2020.03.039.\\u003c/li\\u003e\\n\\u003cli\\u003ePeng HY, Duan SJ, Pan L, Wang MY, Chen JL, Wang YC, et al. Development and validation of machine learning models for nonalcoholic fatty liver disease. Hepatobiliary Pancreat Dis Int 2023;22(6):615-21. doi: 10.1016/j.hbpd.2023.03.009.\\u003c/li\\u003e\\n\\u003cli\\u003eEslam M, Sanyal AJ, George J; International Consensus Panel. MAFLD: A Consensus-Driven Proposed Nomenclature for Metabolic Associated Fatty Liver Disease. Gastroenterology 2020;158(7):1999-2014.e1.doi: 0.1053/j.gastro.2019.11.312. \\u003c/li\\u003e\\n\\u003cli\\u003eBae JS, Lee DH, Lee JY, Kim H, Yu SJ, Lee JH, et al. Assessment of hepatic steatosis by using attenuation imaging: a quantitative, easy-to-perform ultrasound technique. Eur Radiol 2019;29(12):6499-507. doi: 10.1007/s00330-019-06272-y. \\u003c/li\\u003e\\n\\u003cli\\u003eTada T, Kumada T, Toyoda H, Nakamura S, Shibata Y, Yasuda S, et al. Attenuation imaging based on ultrasound technology for assessment of hepatic steatosis: A comparison with magnetic resonance imaging-determined proton density fat fraction. Hepatol Res 2020;50(12):1319-27. doi: 10.1111/hepr.13563.\\u003c/li\\u003e\\n\\u003cli\\u003eSugimoto K, Moriyasu F, Oshiro H, Takeuchi H, Abe M, Yoshimasu Y, et al. The Role of Multiparametric US of the Liver for the Evaluation of Nonalcoholic Steatohepatitis. Radiology 2020;296(3): 532-40. doi: 10.1148/radiol.2020192665.\\u003c/li\\u003e\\n\\u003cli\\u003eDioguardi Burgio M, Ronot M, Reizine E, Rautou PE, Castera L, Paradis V, et al. Quantification of hepatic steatosis with ultrasound: promising role of attenuation imaging coefficient in a biopsy-proven cohort. Eur Radiol 2020;30(4):2293-301. doi: 10.1007/s00330-019-06480-6.\\u003c/li\\u003e\\n\\u003cli\\u003eTada T, Iijima H, Kobayashi N, Yoshida M, Nishimura T, Kumada T, et al. Usefulness of Attenuation Imaging with an Ultrasound Scanner for the Evaluation of Hepatic Steatosis. Ultrasound Med Biol 2019;45(10):2679-87. doi: 10.1016/j.ultrasmedbio.2019.05.033.\\u003c/li\\u003e\\n\\u003cli\\u003eDioguardi Burgio M, Ronot M, Reizine E, Rautou PE, Castera L, Paradis V, et al. Quantification of hepatic steatosis with ultrasound: promising role of attenuation imaging coefficient in a biopsy-proven cohort. Eur Radiol 2020;30(4): 2293-301. doi: 10.1007/s00330-019-06480-6.\\u003c/li\\u003e\\n\\u003cli\\u003eBae JS, Lee DH, Lee JY, Kim H, Yu SJ, Lee JH, et al. Assessment of hepatic steatosis by using attenuation imaging: a quantitative, easy-to-perform ultrasound technique. Eur Radiol 2019;29(12): 6499-507. doi: 10.1007/s00330-019-06272-y.\\u003c/li\\u003e\\n\\u003cli\\u003eTada T, Kumada T, Toyoda H, Nakamura S, Shibata Y, Yasuda S, et al. Attenuation imaging based on ultrasound technology for assessment of hepatic steatosis: A comparison with magnetic resonance imaging-determined proton density fat fraction. Hepatol Res 2020;50(12): 1319-27. doi: 10.1111/hepr.13563.\\u003c/li\\u003e\\n\\u003cli\\u003eYoo J, Lee JM, Joo I, Lee DH, Yoon JH, Kang HJ, et al. Reproducibility of ultrasound attenuation imaging for the noninvasive evaluation of hepatic steatosis. Ultrasonography 2020;39(2): 121-9. doi: 10.14366/usg.19034.\\u003c/li\\u003e\\n\\u003cli\\u003eYi SW, Won YJ, Yi JJ. Low normal fasting glucose and risk of accidental death in Korean adults: A prospective cohort study. Diabetes Metab 2019;45(1):60-6. doi: 10.1016/j.diabet.2018.01.005.\\u003c/li\\u003e\\n\\u003cli\\u003eChevli PA, Ahmad MI, Hari K, Anees MA, Soliman EZ. Impact of low fasting plasma glucose on mortality in the general population. Diab Vasc Dis Res 2020;17(3):1479164120930599. doi: 10.1177/1479164120930599.\\u003c/li\\u003e\\n\\u003cli\\u003eLee JH, Han K, Huh JH. The sweet spot: fasting glucose, cardiovascular disease, and mortality in older adults with diabetes: a nationwide population-based study. Cardiovasc Diabetol 2020;19(1):44. doi: 10.1186/s12933-020-01021-8.\\u003c/li\\u003e\\n\\u003cli\\u003ePinto PN, Chojniak R, Cohen MP, Yu LS, Queiroz-Andrade M, Bitencourt AG. Comparison of three types of preparations for abdominal sonography. J Clin Ultrasound 2011;39(4):203-8. doi: 10.1002/jcu.20790.\\u003c/li\\u003e\\n\\u003cli\\u003eCohn JS, Kamili A, Wat E, Chung RW, Tandy S. Reduction in intestinal cholesterol absorption by various food components: mechanisms and implications. Atheroscler Suppl 2010, 11(1): 45-8. doi: 10.1016/j.atherosclerosissup.2010.04.004.\\u003c/li\\u003e\\n\\u003cli\\u003eLoveday SM. Protein digestion and absorption: the influence of food processing. Nutr Res Rev 2023, 36(2): 544-59. doi: 10.1017/S0954422422000245.\\u003c/li\\u003e\\n\\u003cli\\u003eLautt WW. Mechanism and role of intrinsic regulation of hepatic arterial blood flow: hepatic arterial buffer response. Am J Physiol 1985;249(5 Pt 1): G549-56. doi: 10.1152/ajpgi.1985.249.5.G549.\\u003c/li\\u003e\\n\\u003cli\\u003eJoynt LK, Platt JF, Rubin JM, Ellis JH, Bude RO. Hepatic artery resistance before and after standard meal in subjects with diseased and healthy livers. Radiology 1995;196(2): 489-92. doi: 10.1148/radiology.196.2.7617865.\\u003c/li\\u003e\\n\\u003cli\\u003eDauzat M, Lafortune M, Patriquin H, Pomier-Layrargues G. Meal induced changes in hepatic and splanchnic circulation: a noninvasive Doppler study in normal humans. Eur J Appl Physiol Occup Physiol 1994;68(5): 373-80. doi: 10.1007/BF00843732.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"abdominal-radiology\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"aima\",\"sideBox\":\"Learn more about [Abdominal Radiology](http://link.springer.com/journal/261)\",\"snPcode\":\"261\",\"submissionUrl\":\"https://submission.springernature.com/new-submission/261/3\",\"title\":\"Abdominal Radiology\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false},\"keywords\":\"Fasting, Reduced-fat diet, Hepatic steatosis, Attenuation imaging\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-5303569/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-5303569/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003ePurpose: \\u003c/strong\\u003eTo investigate whether a low-calorie, reduced-fat diet affects liver Attenuation Imaging (ATI) measurements.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods: \\u003c/strong\\u003eA total of 320 patients were enrolled in this prospective study. They were randomly assigned to four groups: a fasting group; a postprandial 0.5-hour examination group; a postprandial 2-hour examination group; and a postprandial 4-hour examination group. All participants first underwent liver ATI examination in a fasting state. Those in the postprandial groups then consumed a low-calorie, reduced-fat diet before undergoing a second ATI examination at 0.5h, 2h, or 4h after the meal, respectively. The ATI values were compared among the groups. The differences between postprandial and fasting ATI values were also analyzed for the postprandial groups. Additionally, the consistency of the grading diagnosis of hepatic steatosis between the postprandial and fasting states was evaluated in the postprandial groups.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults: \\u003c/strong\\u003eThe ATI values for the postprandial 0.5h group, postprandial 2h group, and postprandial 4h group were not significantly different from the fasting group's ATI value (\\u003cem\\u003eP\\u003c/em\\u003e = 0.576, 0.471, and\\u003cem\\u003e \\u003c/em\\u003e0.992, respectively). No significant differences were noted in the ATI values that were recorded during the postprandial and fasting states within each of the postprandial groups (\\u003cem\\u003eP\\u003c/em\\u003e= 0.573, 0.076, and 0.805, respectively). The consistency of the grading diagnosis of hepatic steatosis between the postprandial and fasting states across the three postprandial groups was high according to three different diagnostic criteria.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusion:\\u003c/strong\\u003e Consuming a low-calorie, reduced-fat diet has no significant effects on liver ATI measurements and the grading diagnosis of hepatic steatosis.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eClinical Trial Number:\\u003c/strong\\u003e (ChiCTR2200062314,August 2022)\\u003c/p\\u003e\",\"manuscriptTitle\":\"The impact of a low-calorie, reduced-fat diet on liver attenuation imaging: A randomized clinical trial\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-11-11 05:26:51\",\"doi\":\"10.21203/rs.3.rs-5303569/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2024-11-06T13:40:08+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-11-04T20:38:27+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-11-04T14:49:52+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-11-01T20:03:22+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"232147956747577185836619075630866246833\",\"date\":\"2024-10-25T08:02:00+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"230799283113003295958152507958746350508\",\"date\":\"2024-10-24T08:41:20+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"266870518611947652883896297684639147509\",\"date\":\"2024-10-22T20:51:37+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2024-10-22T20:44:41+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2024-10-22T07:07:11+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2024-10-22T07:04:57+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Abdominal Radiology\",\"date\":\"2024-10-21T10:32:55+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"abdominal-radiology\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"aima\",\"sideBox\":\"Learn more about [Abdominal Radiology](http://link.springer.com/journal/261)\",\"snPcode\":\"261\",\"submissionUrl\":\"https://submission.springernature.com/new-submission/261/3\",\"title\":\"Abdominal Radiology\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false}}],\"origin\":\"\",\"ownerIdentity\":\"fcb29bb0-120f-4e48-a8c2-2c27428d821a\",\"owner\":[],\"postedDate\":\"November 11th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-12-23T16:05:53+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-5303569\",\"link\":\"https://doi.org/10.1007/s00261-024-04762-2\",\"journal\":{\"identity\":\"abdominal-radiology\",\"isVorOnly\":false,\"title\":\"Abdominal Radiology\"},\"publishedOn\":\"2024-12-18 15:58:27\",\"publishedOnDateReadable\":\"December 18th, 2024\"},\"versionCreatedAt\":\"2024-11-11 05:26:51\",\"video\":\"\",\"vorDoi\":\"10.1007/s00261-024-04762-2\",\"vorDoiUrl\":\"https://doi.org/10.1007/s00261-024-04762-2\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-5303569\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-5303569\",\"identity\":\"rs-5303569\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}