Abstract
Background
Stiffness thresholds for liver MR elastography in children vary between studies and may differ from thresholds in adults. Normative liver stiffness data are needed to optimize diagnostic thresholds for children.
Purpose
To determine normal liver stiffness, and associated normal ranges for children, as measured with MR elastography across vendors and field strengths.
Materials and Methods
This was a prospective multicenter cohort study (ClinicalTrials.gov identifier: NCT03235414). Volunteers aged 7–17.9 years without a known history of liver disease were recruited at four sites for a research MRI and blood draw between February 2018 and October 2019. MRI was performed on three vendor platforms and at two field strengths (1.5 T and 3.0 T). All MRI scans were centrally analyzed; stiffness, proton density fat fraction (PDFF), and R2* values were expressed as means of means. Mean and 95% confidence intervals (CIs) for liver stiffness were calculated. Pearson correlation coefficient (r), two-sample t test, or analysis of variance was used to assess univariable associations.
Results
Seventy-one volunteers had complete data and no documented exclusion criterion (median age, 12 years; interquartile range [IQR], 10–15 years; 39 female participants). Median body mass index percentile was 54% (IQR, 32.5%–69.5%). Mean liver stiffness was 2.1 kPa (95% CI: 2.0, 2.2 kPa) with mean ± 1.96 kPa standard deviation of 1.5–2.8 kPa. Median liver PDFF was 2.0% (IQR, 1.7%–2.6%). There was no association between liver stiffness and any patient variable or MRI scanner factor.
Conclusion
Mean liver stiffness measured with MR elastography in children without liver disease was 2.1 kPa (similar to that in adults). The 95th percentile of normal liver stiffness was 2.8 kPa. Liver stiffness was independent of sex, age, or body mass index and did not vary with MRI scanner vendor or field strength.
© RSNA, 2020
Online supplemental material is available for this article.
See also the editorial by Yin in this issue.
Summary
Mean liver stiffness in healthy children without liver disease was 2.1 kPa; the 95th percentile was equal to 2.8 kPa.
Key Results
■ Median liver stiffness value for healthy children without liver disease was 2.1 kPa (interquartile range, 1.9–2.3 kPa).
■ The 95th percentile value (mean ± 1.96 standard deviation) for liver stiffness in healthy children without liver disease was 2.8 kPa.
■ There was no association between liver stiffness as measured with MR elastography and any patient demographic factor or MRI scanner factor.
Introduction
Pediatric chronic liver disease encompasses both inherited and sporadic diseases that have the potential to progress to liver fibrosis in children. These diseases may require liver transplantation because of end-stage liver disease or development of hepatocellular carcinoma. Nonalcoholic fatty liver disease is rapidly eclipsing other causes of liver disease in children and is now the second most common indication for liver transplantation in adults (1,2).
MR elastography, alongside US elastography, has gained substantial traction as a noninvasive marker of diffuse liver disease in both children and adults (3–5). Elastography techniques produce a quantitative measure used to diagnose and monitor disease severity. Liver stiffness thresholds separate healthy from diseased liver. However, the body of literature defining liver stiffness thresholds for MR elastography in children remains small with varying thresholds (5–7). Furthermore, defined thresholds for abnormal liver stiffness in children differ from those in adults, raising the possibility that pediatric liver disease differs from adult liver disease (4). Studies of children with no liver disease also suggest that the stiffness of healthy liver in children differs from that in adults, which would affect diagnostic thresholds. Specifically, Etchell et al (8) found that normal liver stiffness values were lower for healthy children than for healthy adults. However, Sawh et al (9) recently showed that liver stiffness in children was higher than previously reported for adults.
Conflicting results in prior pediatric studies may reflect technical or platform-related differences in field strength, MRI scanner vendor, or driver frequency used for MR elastography. Alternatively, differences may reflect population differences between studies. Whatever the explanation, normative liver stiffness data for children are necessary to help establish diagnostic thresholds. The purpose of our study was to determine normal liver stiffness, and associated normal ranges for children, as measured with MR elastography. Specifically, we sought to define differences related to age, MRI scanner vendor, and field strength through a multi-institutional approach.
Materials and Methods
This was a prospective multicenter cohort study (ClinicalTrials.gov identifier: NCT03235414) that was approved by the institutional review board at all participating institutions, with Cincinnati Children's Hospital Medical Center acting as lead study site. This study was supported by a multi-institutional pilot award from the Society for Pediatric Radiology Research and Education Foundation. Data generated or analyzed during the study are available from the corresponding author by request. All study activities were Health Insurance Portability and Accountability Act compliant. Data shared between institutions were deidentified prior to sharing. Written informed consent was obtained in person from parents or guardians of participants. In addition to parent/guardian informed consent, assent was obtained from all participants aged 11 years or older.
Study Participants
Pediatric volunteers aged 7–17.9 years without a known personal or family history of liver disease were recruited as a consecutive series at four large academic pediatric hospitals. Study visits occurred between February 2018 and October 2019. Participating sites were selected on the basis of MRI scanner availability, as follows: Cincinnati Children’s Hospital Medical Center (Philips 1.5 T and 3.0 T; Philips Healthcare, Best, the Netherlands), Children's Hospital of Philadelphia (GE Healthcare 3.0 T; GE Healthcare, Milwaukee, Wis; and Siemens 3.0 T; Siemens Healthineers, Erlangen, Germany), Mallinckrodt Institute of Radiology (Siemens 1.5 T), and Massachusetts General Hospital (GE Healthcare 1.5 T).
Study visits included a nonsedated research MRI examination and a research venous blood draw. Participants were weighed and measured immediately before their MRI examination. Body mass index (BMI) percentiles were calculated by using the Centers for Disease Control and Prevention calculator (10). Exclusion criteria included: (a) BMI percentile less than 10% or greater than 85%, (b) abnormal blood laboratory value, (c) liver proton density fat fraction (PDFF) larger than 5%, and (d) T2* less than 19 msec at 1.5 T or less than 10 msec at 3.0 T (11).
Thirty-two of the participants recruited at Cincinnati Children’s Hospital Medical Center and included in the current study were previously reported in a publication concerning T1 relaxometry of the liver, pancreas, and spleen (12). That prior study included demographic data about those participants but no other data presented in the current study.
Power Calculation
A priori we powered our study for a primary aim of determining normal liver stiffness values for two pediatric age groups at two MRI field strengths: 7–11.9 years and 12–17.9 years at 1.5 T and 3.0 T. Based on the standard deviation of normal pediatric liver stiffness measurements in the study by Etchell et al (8) (standard deviation ± 0.3 kPa) and the width of the confidence intervals (CIs) from a study of healthy adult livers by Lee et al (13) (± 0.1 kPa), we calculated that a sample size of n = 18 was needed in each group to achieve two-sided 95% CIs with a distance from the mean to the limits equal to 0.15 kPa in each group. This sample size was also predicted to provide 80% power to detect an effect size (Cohen d) of 0.67 between the two age groups. Based on prior published and unpublished MRI studies in healthy volunteers at our institution, we expected that up to 25% of volunteers would have unsuspected liver disease manifesting as abnormalities in liver function test results or liver fat fraction values greater than 5% according to MRI PDFF (14). Therefore, recruitment targets were increased by 25% over the levels required to achieve adequate statistical power. Accordingly, we planned to recruit at least 24 volunteers to each of two age groups at each of two field strengths for a total study recruitment of at least 96 participants (Table 1).
Table 1:
Study Recruitment
Exclusion of Liver Disease
To confirm absence of known liver disease, a screening survey was administered to all interested participants (Appendix E1 [online]) and, when available, medical records were reviewed to exclude liver disease. Furthermore, a research venous blood draw of approximately 2.5 mL was performed within 24 hours of MRI to measure aspartate aminotransferase, alanine aminotransferase, γ-glutamyltransferase, alkaline phosphatase, and total and direct bilirubin. Blood analyses were performed locally at participating sites, and values outside of the local reference ranges for age were considered abnormal. A magnitude-based, confounder-corrected chemical shift–encoded PDFF sequence was also performed as part of the research MRI examination to exclude unexpected hepatic steatosis or iron overload. Parametric PDFF and R2* (or T2* depending on vendor) parametric maps were automatically generated on the scanner console.
Research MRI
Study participants were asked to take nothing by mouth for 4 hours before research MRI. Images were acquired with the patient supine in the MRI scanner by using an anterior surface array coil. Sequences performed included an axial T2-weighted fast spin-echo sequence for anatomic localization, manufacturer-recommended MR elastography sequence (Table E1 [online]), and manufacturer-recommended PDFF sequence. MR elastography images were obtained per manufacturer recommendations by using an active-passive driver system operated at the manufacturer-recommended frequency of 60 Hz, as previously described (3). For gradient-recalled-echo MR elastography, vibration amplitude was adjusted based on participant weight, increasing in 10% increments for each 10 kg of weight from 40% at 49 kg or less to 80% for participants weighing 80–89 kg. All spin-echo echo-planar imaging MR elastography examinations were performed with vibration amplitude of 50%. Images were submitted for central analysis at Cincinnati Children’s Hospital Medical Center.
Image Analysis
Submitted MR elastography images were reviewed for technical adequacy initially by the study principal investigator (A.T.T.), who visually inspected the images for midliver slice positioning and for visible propagation of waves. All MR elastography images and R2* and PDFF parametric maps were processed independently by a single image analyst with 6 years of experience in processing such images for clinical care. The image analyst was blinded to all participant data but blinding to scanner manufacturer and field strength was not possible. MR elastography images were processed with MRE Quant (version 1.3; Mayo Clinic, Rochester, Minn). Manual irregular regions of interest (ROIs) were placed on each of four slices through the midliver, guided by anatomic imaging and 95% confidence maps generated by the software, and avoiding large blood vessels and areas of artifact. The ROIs were confined to the right hepatic lobe and medial section of the left hepatic lobe, remaining greater than 1-cm deep to the liver capsule. During image processing, the image analyst again assessed for technical adequacy of the MR elastography images based on generated confidence maps and ROI size. ROIs smaller than 400 mm2 were reviewed by the principal investigator to confirm good wave propagation. Participant liver stiffness was expressed as a mean of means calculated from the mean stiffness value for each of the four levels, weighted according to ROI size.
Liver PDFF and R2* were similarly measured by manual placement of irregular ROIs on each of four images at the level of the midliver, avoiding large blood vessels and areas of artifact. PDFF and R2* images were processed with IntelliSpace Portal (version 10.1; Philips Healthcare), with participant liver PDFF and R2* values expressed as a mean of the mean values from each of the four measurements.
Statistical Analysis
Descriptive analysis was performed to summarize participant demographics. Sample statistics were expressed as means and standard deviations or medians and interquartile ranges (IQRs) as appropriate. Pearson correlation coefficient (r) was used to evaluate the correlation between liver stiffness and continuous variables. The difference in liver stiffness across categorical variables was analyzed by using an equal variance two-sample t test or one-way analysis of variance as appropriate. In addition, multiple regression modeling with stepwise selection was applied for analysis of differences in liver stiffness across variables of interest. Criteria for model entry and exit were both P value of .15. All analyses were performed with SAS (version 9.4; SAS Institute; Cary, NC). P < .05 was considered to indicate a statistically significant difference.
Results
A total of 101 healthy volunteers were recruited for this study. A study sample flowchart (Fig 1) details the analyzed subgroups. Post hoc power analysis based on the subgroup with complete data and without exclusion(s) (n = 71) confirmed statistical power sufficient to provide 96% and 98% CIs of 0.15 kPa for the two age groups. However, statistical power to identify significance for the 0.1-kPa difference between groups was only 18%.
Figure 1:
Study sample flow diagram. Boxes on right denote excluded participants based on established exclusion criteria or missing data. BMI = body mass index, LFTs = liver function tests, PDFF = liver proton density fat fraction, %ile = percentile.
Recruited Sample
Among the 101 recruited volunteers, 52 (51%) were male participants and 49 (49%) were female participants. Median age was 12 years (IQR, 10–15 years). Summary statistics for size measurements and laboratory data are in Table 2. Median liver stiffness for the recruited sample was 2.1 kPa (IQR, 1.9–2.4 kPa) on the basis of a median mean ROI size of 1065 mm2 (IQR, 853–1350 mm2). Mean liver stiffness was 2.2 kPa (95% CI: 2.1kPa, 2.3 kPa). Median liver PDFF was 2.0% (IQR, 1.7%–3.0%). There was no association between liver stiffness as measured with MR elastography and any patient demographic factor or MRI scanner factor (Tables 3, 4).
Table 2:
Study Participant and Subgroup Summary Statistics for Measures of Volunteer Size and for Laboratory Data
Table 3:
Univariable Relationships between Continuous Patient and Scanner Variables and Liver Stiffness Measured with MR Elastography
Table 4:
Univariable Relationships between Categorical Patient and Scanner Variables and Liver Stiffness Measured with MR Elastography
Subgroup without Documented Exclusion(s)
Among 101 participants, 78 (77%) had no documented exclusion criteria. Seven of these 78 had missing data. Among 78 participants, 37 (47%) were male and 41 (53%) were female. Summary statistics for size measurements and laboratory data for this subgroup are detailed in Table 2. Median liver stiffness for this subgroup was 2.1 kPa (IQR, 1.9–2.4 kPa) based on a median mean ROI size of 1062 mm2 (IQR, 780–1365 mm2). Mean liver stiffness was 2.2 kPa (95% CI: 2.1 kPa, 2.3 kPa). Median liver PDFF was 2.0% (IQR, 1.6%–2.5%). There was no association between liver stiffness as measured with MR elastography and any patient demographic factor or MRI scanner factor (Tables 3, 4).
Subgroup with Complete Data and without Documented Exclusion(s)
Among 101 volunteers, 71 (70%) had complete data and no documented exclusion criteria. Of this subgroup, 32 (45%) were male and 39 (55%) were female. Median age was 12 years (IQR, 10–15 years). Summary statistics for size measurements and laboratory data for this subgroup are detailed in Table 2. Median liver stiffness for this subgroup was 2.1 kPa (IQR, 1.9–2.3 kPa) based on a median mean ROI size of 1104.3 mm2 (IQR, 838.8–1377.1 mm2). Figure 2 graphically displays the subgroup distribution of liver stiffness values. Mean liver stiffness was 2.2 kPa (95% CI: 2.1 kPa, 2.3 kPa). Median liver PDFF was 2.0% (IQR, 1.7%–2.6%). There was no association between liver stiffness as measured with MR elastography and any patient demographic factor or MRI scanner factor (Fig 3; Tables 3, 4). Summary results for each scanner field strength are in Table E2 (online). No individual variable met threshold significance for inclusion in multiple regression modeling.
Figure 2a:
(a) Histogram and (b) Tukey box/dot plot show distribution of liver stiffness values measured with MR elastography in subgroup of 71 children with complete data and no documented exclusion criteria. Dots in b reflect individual participant stiffness measurements, box boundaries reflect first and third quartile values, and whiskers reflect 1.5 times the interquartile range.
Figure 3:
Scatterplot of liver stiffness versus age for subgroup of 71 children with complete data and no documented exclusion criteria. There was no association between age and liver stiffness (r = 0.06; P = .62).
On the basis of the mean and 95% CIs, and as shown in Figure 2b, there were three volunteers who were statistical outliers in terms of measured liver stiffness. Two of these volunteers had technically limited examinations with measurable data on only one of four MR elastography images. The third volunteer, with a measured liver stiffness of 3.4 kPa, was an 18-year-old male participant with BMI percentile of 45%. Stiffness values were measurable in all four MR elastography images, with a mean ROI size of 1801 mm2. All research laboratory values were in the normal range (aspartate aminotransferase, 26 units/L; alanine aminotransferase, 20 units/L), and mean PDFF was 1.4%. No explanation for the apparently elevated liver stiffness value in this volunteer was identified. After exclusion of these outliers, mean and median liver stiffness values for the remaining 68 patients were both 2.1 kPa, and based on the standard deviation of the mean, the 95th percentile value was 2.8 kPa.
Figure 2b:
(a) Histogram and (b) Tukey box/dot plot show distribution of liver stiffness values measured with MR elastography in subgroup of 71 children with complete data and no documented exclusion criteria. Dots in b reflect individual participant stiffness measurements, box boundaries reflect first and third quartile values, and whiskers reflect 1.5 times the interquartile range.
Discussion
Normative liver stiffness data are needed to optimize diagnostic thresholds in children. We showed that mean liver stiffness measured with MR elastography in healthy normal-weight children without history or laboratory evidence of liver disease was 2.1 kPa, with the 95th percentile equal to 2.8 kPa. We found no difference in measured liver stiffness based on sex, age, height, weight, body mass index, MRI scanner vendor, or field strength (1.5 T vs 3.0 T).
To date, we are aware of only one other study that has rigorously measured liver stiffness with MR elastography in healthy children. In that study, Sawh et al (9) performed MR elastography at 1.5 T in 81 children. Although that study included obese children, its population is otherwise similar to the population in our study. In the population in that study, measured liver stiffness was higher than in our study population, with a mean of 2.45 kPa ± 0.35 kPa standard deviation, and the 95th percentile value was 3.19 kPa. This discrepancy is of unclear origin. Normal liver stiffness derived from our study is more similar to that previously reported by Etchell et al (8) in a small cohort of children and is more similar to published values for healthy adults. Etchell et al (8) previously reported liver stiffness values of 2.2 kPa in a cohort of 24 healthy children. Also, several studies in adults found liver stiffness values in healthy adults to be around 2.1 kPa (13,15–18).
Our findings of no association between liver stiffness and age, sex, or BMI are concordant with findings by Sawh et al (9) and multiple prior MR elastography studies in adults (15,16). However, conflicting data exist. Etchell et al (8) showed that liver stiffness values as measured with MR elastography were lower in children compared with adults—2.2 kPa versus 2.6 kPa. By using transient elastography, Engelmann et al (19) showed differences in liver stiffness between children aged 0–5, 6–11, and 12–18 years, with overall increasing stiffness with age. Also, the authors showed that adolescent girls had lower liver stiffness values than adolescent boys. It is unclear why the results of these studies are discrepant with both our results and the rest of the literature.
In addition to defining liver stiffness in a healthy group of children, we found no differences in liver stiffness across MRI vendors and field strengths, consistent with prior literature (14). This suggests that threshold stiffness values can be uniformly applied across MRI platforms. Post hoc power analysis, with Bonferroni correction for multiple comparisons, suggests that our sample size was sufficient to detect a difference of 0.3 kPa across MRI field strengths.
Of note, 23% (23 of 101) of volunteers for this study who believed themselves to be healthy had an abnormality considered to be an exclusion criterion. Specifically, 17 volunteers (16.8%) had abnormalities in results of liver function tests on the basis of research blood draw, and six volunteers (5.9%) had an elevated liver PDFF at MRI. Not all abnormalities in liver function test results reflect occult liver disease, particularly given that we considered any elevation of a laboratory value above the local laboratory reference to be “abnormal.” Accordingly, the clinical significance of this high frequency of occult liver function test abnormalities is uncertain. Median liver fat fraction in the five volunteers with unexpected elevated liver PDFF was 6.4%, and only one had an elevated laboratory value (aspartate aminotransferase, 51 units/L; upper limit of normal, 36 U/L), which suggested the presence of steatosis.
Our study had limitations. Although we undertook to rigorously define normal liver stiffness values in children, our study assumed liver health on the basis of careful screening, a research MRI examination, and research blood draws. We did not have liver biopsy findings to confirm the absence of occult liver pathology. A single experienced image analyst centrally processed all MR elastography data by using an offline program rather than manufacturer inline software. Thus, variation in measured stiffness arising from differences in image processing by different observers and use of different software was not accounted for and might widen the 95% CIs defining the limits of normal liver stiffness. Although we found no difference in measured liver stiffness between groups of children who underwent imaging on different vendor platforms, the same children were not scanned across all platforms to rigorously test for cross-vendor or field strength differences. These sources of variability were not accounted for in the current analysis, but prior literature suggests that intraindividual variability based on scanner and field strength differences is, on average, less than 0.05 kPa and that interobserver variability for measured liver stiffness is, on average, approximately 0.1 kPa (14,20). Finally, our statistical analysis focused on mean values for groups. Although we report 95th percentile values, we did not formally compare these between groups.
In conclusion, we showed liver stiffness in healthy children without liver disease to be similar to that described for adults at 2.1 kPa with the 95th percentile equal to 2.8 kPa. This approximates the threshold of 2.74 kPa suggested by Sawh et al (9) and likely reflects a reasonable threshold for separating healthy from diseased liver. Liver stiffness in healthy children is not sex, age, or body mass index dependent and does not vary between MRI scanners vendor or field strengths.
APPENDIX
Acknowledgments
Acknowledgments
We thank Victoria Goodwin, BS, RT (R)(CT)(MRI) for her support with image analysis. We thank Jaylynn Hill, BS for her support with study coordination. We thank the Washington University Radiology Clinical Research Core for regulatory support, and Angela A. Hempen, MS, BS for help with subject recruitment.
Supported by the Society for Pediatric Radiology Research and Education Foundation. S.A.X. supported by the National Institute of Biomedical Imaging and Bioengineering, and the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health (K23 EB020710, R01 DK119860).
Disclosures of Conflicts of Interest: A.T.T. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: disclosed money to author’s institution for lectures from Applied Radiology; disclosed money for support of research assistant from Perspectum; disclosed money to author for research agreement from Mayo Clinic. Other relationships: disclosed no relevant relationships. S.A.A. disclosed no relevant relationships. M.S.G. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: disclosed money to author for grant from Takeda Millennium Pharmaceuticals. Other relationships: disclosed no relevant relationships. G.K. disclosed no relevant relationships. S.A.X. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: disclosed money to author for consultancy from Intercept; disclosed money to author’s institution for grant from TargetPharmaSolutions, Axcella Health; disclosed royalties from UpToDate. Other relationships: disclosed no relevant relationships S.D.S. disclosed no relevant relationships. M.B. disclosed no relevant relationships. J.S.C.T. disclosed no relevant relationships. A.O. disclosed no relevant relationships. B.Z. disclosed no relevant relationships. J.R.D. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: disclosed money to author for consultancy from Perspectum; disclosed grants from Canon Medical Systems and Siemens Medical Solutions. Other relationships: disclosed no relevant relationships.
Abbreviations:
- BMI
- body mass index
- CI
- confidence interval
- IQR
- interquartile range
- PDFF
- proton density fat fraction
- ROI
- region of interest
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