Pediatric Liver Fat Quantification (LFQ) Phase 2 Pilot Study: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Pediatric Liver Fat Quantification (LFQ) Phase 2 Pilot Study (NCT04800094), a na na study. The primary outcome is Correlation of the Liver Fat Percentage Reported From MRI-PDFF With Measurements of Hepatorenal Index (HRI) Ultrasound Biomarker for Liver Fat..

2. Clinical Question

3. Trial Design

NCT04800094 is listed as a completed Phase 2 pilot study, with phase recorded as not applicable. Enrollment was 30. The study began on 2021-03-02, reached primary completion on 2022-12-13, and has completed status in the registry record. The sponsor is Philips Clinical & Medical Affairs Global.

The design is single-group and non-randomized, with no masking. Participants received investigational ultrasound imaging for liver fat quantification; there was no separate treatment control group. MRI-PDFF served as a reference measurement for comparing liver fat assessments, rather than as a parallel intervention assigned to a control group. All subjects were to undergo an investigational abdominal ultrasound examination and an MRI-PDFF examination according to the clinical standard of care.

The primary assessment concerns the relationship between HRI from ultrasound and MRI-PDFF liver fat percentage. For each biomarker per subject, multiple quantitative measurements were acquired on the same day by two different operators. The record states that operator differences were calculated at the subject level by averaging multiple measurements. It also reports a total of 60 non-missing scans used to calculate HRI. The exact number of measurements contributed by each subject and details of the analysis population are not reported in the registry record.

Secondary objectives addressed same-day inter-operator variability and data acquisition failure rates for HRI, acoustic attenuation, and tissue stiffness. The registry lists 9 outcome measures and 15 analyses. Full protocol details, eligibility criteria, a statistical analysis plan, and the reason for the planned enrollment are not reported in the registry record.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Overall Study

Analysis population for the primary outcome, as defined in the registry: Each enrolled subject underwent up to two ultrasound scans conducted by two different operators, resulting in a total of 60 non missing scans reviewed for this study. The primary outcome measure, the Hepatorenal Index, was calculated based on these scans. The hepatorenal index measurement from each ultrasound scan was reviewed.

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

6. Primary Endpoint

The registry lists the primary outcome as Correlation of the Liver Fat Percentage Reported From MRI-PDFF With Measurements of Hepatorenal Index (HRI) Ultrasound Biomarker for Liver Fat., measured over Intra-procedural (1 day).

The primary endpoint concerns correlation between ultrasound-derived Hepatorenal Index (HRI) measurements and liver fat percentage measured by MRI-PDFF. HRI is a continuous biomarker. The registry describes a higher HRI as indicating greater liver fat accumulation and a lower HRI as suggesting less hepatic fat. MRI-PDFF is the reference measurement against which the ultrasound-derived measure was to be assessed.

Correlation is used to describe whether two measurements vary together, and the direction and strength of that relationship. In this setting, it can address whether subjects with different MRI-PDFF liver fat measurements also tend to have different HRI measurements. Correlation alone does not establish that the measurements agree numerically, that one can replace the other, or that either measurement predicts a clinical outcome. Those questions require additional analyses and evidence.

The record describes multiple measurements collected on the same day by two operators. It says that multiple measurements were averaged and operator differences calculated at the subject level. It does not specify the correlation statistic, the precise endpoint calculation, or a numerical correlation estimate and confidence interval. Those results are not reported in the registry record. The stated endpoint timeframe is intra-procedural (1 day).

7. Why No Re-analysis Is Shown

8. Statistical Interpretation

9. Statistical Methods Explained

The registry identifies the primary outcome as a continuous measure and describes its summary parameter as a mean with standard deviation. These summaries describe a measurement’s center and spread: the mean is an average, while the standard deviation describes variability around that average. They do not, by themselves, answer the primary correlation question. The actual primary analysis statistic and numerical summaries are not reported in the registry record.

What does correlation describe?

In general, correlation describes how two measured quantities vary together. A positive relationship means that larger values of one measure tend to occur with larger values of the other; a negative relationship means that larger values of one tend to occur with smaller values of the other. The magnitude indicates the strength of the pattern according to the chosen correlation method. Correlation is not the same as agreement. Two methods can be strongly correlated while producing systematically different values, so assessing whether ultrasound can reproduce MRI-PDFF values would require analyses beyond correlation.

The study’s intended comparison is HRI from investigational ultrasound against MRI-PDFF liver fat percentage. The record does not say whether the correlation was Pearson, Spearman, or another statistic. In general, Pearson correlation characterizes a linear relationship and can be sensitive to influential observations; rank-based approaches assess whether values tend to move in the same order and may be appropriate for different data patterns. Which assumptions and method apply to this analysis are not reported in the registry record. No correlation estimate, confidence interval, or p-value is reported there either.

Why do repeated measurements matter?

Multiple quantitative measurements were collected on the same day by two operators. The registry says that measurements were averaged and that the difference between operators was calculated at the subject level. Repeated measurements can help characterize within-subject measurement variation, but observations from the same person are generally not independent. In general, analyses need to account for that clustering when estimating uncertainty. The exact aggregation procedure, the number of measurements for each subject, and the statistical method used to account for repeated data are not reported in the registry record.

The record reports 60 non-missing scans used to calculate HRI, with 30 enrolled subjects and up to two ultrasound scans per subject. These figures describe scans and enrollment, not necessarily the number of independent observations in the primary correlation analysis. The precise analysis population and whether all enrolled subjects contributed a matched HRI and MRI-PDFF pair are not reported in the registry record. That distinction is important: a correlation requires paired measurements, and its precision depends on the analyzed paired data and their distribution.

What would uncertainty add?

In general, a confidence interval conveys uncertainty around an estimate. A narrow interval indicates greater precision under the analysis assumptions, while a wide interval indicates less precision. A p-value, if used, assesses how compatible the observed data are with a specified null hypothesis under a statistical model; it is not a measure of the size or practical importance of a relationship. The registry record does not report an interval or p-value for the primary endpoint, so neither the precision nor the strength of statistical evidence can be evaluated from the posted information.

Measurement error in either method can affect observed association. If HRI values vary across operators, the resulting correlation with MRI-PDFF may be affected. The study lists secondary objectives concerning same-day inter-operator variability and data acquisition failure rates for HRI, acoustic attenuation, and tissue stiffness. Numerical results for those objectives and the methods used to estimate variability are not reported in the registry record. General statistical interpretation therefore distinguishes the intended reliability questions from the unreported quantitative evidence.

How should planning illustrations be read?

The registry’s sample-size assumptions describe a planning illustration based on an observed effect, rather than the original design justification. The illustration assumes a two-sided significance level of 0.05, equal allocation between two arms, and a normal approximation; the effect to detect is expressed as a stated fraction of the observed effect. For time-to-event outcomes, the described convention is a total number of events, while other outcomes use participants per arm. This trial itself is single-group, so the equal-allocation, two-arm setup is a hypothetical planning framework, not a description of the study’s actual assignment.

In general, sample-size planning asks how much information a future study might need to detect a specified effect under chosen statistical assumptions. Such figures are not observed results, do not measure the power achieved by the completed study, and should not be interpreted as evidence that an effect exists. The actual sample-size justification, target effect, and details of the original design calculation are not reported in the registry record. No specific sample-size illustration values are reported in the record details available for this analysis.

Finally, the registry lists 9 outcome measures and 15 analyses. When multiple outcomes or statistical tests are considered, the chance of obtaining at least one apparently notable result can increase; general approaches to multiplicity control may adjust interpretation or testing thresholds. Whether any adjustment was planned or applied, and how the 15 analyses were organized, are not reported in the registry record. The posted information therefore does not establish how multiplicity was handled.

10. Confidence Intervals for Each Arm

No two-arm comparison is shown for this trial, but each arm's mean can be given with a t-based 95% confidence interval computed from the posted mean, spread and number of participants.

R code and output

arm <- c("Hepatorenal Index: Investigational Ultrasound Imag")
n   <- c(30)
m   <- c(1.7)
sp  <- c(0.7)
sd  <- sp      # posted standard deviations
for (i in seq_along(n)) {
  se <- sd[i] / sqrt(n[i]); h <- qt(0.975, n[i] - 1) * se
  cat(sprintf("CARM|%s|%d|%.3f|%.3f|%.3f|%.3f\n", arm[i], n[i], m[i], sd[i], m[i] - h, m[i] + h))
}

CARM  Hepatorenal Index: Investigational Ultrasound Imag  30  1.700  0.700  1.439  1.961

11. Multiplicity, Missing Data and Analysis Populations

The registry lists 9 outcome measures and 15 analyses. The secondary objectives include same-day inter-operator variability and data acquisition failure rates for HRI, acoustic attenuation, and tissue stiffness. With multiple outcomes and analyses, interpretation can be affected by multiplicity: in general, testing more hypotheses can increase the chance of at least one apparently notable finding. Whether the study prespecified a primary analysis hierarchy, adjusted for multiple testing, or treated secondary analyses as exploratory is not reported in the registry record.

Missingness is relevant to both the primary comparison and the acquisition-failure objectives. The record reports 60 non-missing scans used to calculate HRI, but does not provide the number of missing scans, the number of participants with paired MRI-PDFF and HRI data, or the number included in each analysis. The handling of missing observations, incomplete procedures, failed acquisitions, or unavailable MRI-PDFF values is not reported in the registry record.

The analysis population is also not described in sufficient detail to determine whether the primary analysis included every enrolled subject, only subjects with evaluable paired measurements, or another defined group. The record does not state how exclusions were decided or whether any sensitivity analyses assessed the effect of missing data. In general, an analysis restricted to complete measurements can represent a selected subset if the availability of measurements is related to participant or measurement characteristics. The posted record does not establish whether that issue arose in this study.

The reported scan count should not be treated as an independent participant count. Repeated observations from a subject may be correlated, and the statistical approach to that dependence is not reported in the registry record. These gaps limit assessment of the analysis population, uncertainty, and robustness of the reported objectives.

12. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

The registry lists 30 participants at risk for serious adverse events in the investigational ultrasound group, with 0 participants affected. It also lists 30 participants at risk for other adverse events, with 0 affected, and 0 deaths. No serious adverse-event terms are listed.

These entries describe what was recorded in the registry for the stated group. They do not establish that no events of any kind occurred outside the definitions, observation period, or reporting procedures used for the record. The methods for adverse-event collection, the observation period for safety, and the definitions applied are not reported in the registry record.

Because this was a single-group study, these figures do not provide a comparative estimate against a control group. They should be read as registry-reported counts for enrolled participants, not as proof of safety or as a basis for comparing interventions.

13. What the Result Does, and Does Not, Mean

The study addresses a measurement question: whether an investigational ultrasound-derived HRI is associated with MRI-PDFF liver fat measurements in a pediatric population. It also includes objectives related to operator variability and acquisition failure for several ultrasound biomarkers. This makes the study relevant to evaluating the feasibility and measurement characteristics of the approach, rather than estimating the effect of a treatment.

The registry record reports 30 enrolled subjects and 60 non-missing ultrasound scans used to calculate HRI. It describes same-day measurements by two operators and identifies MRI-PDFF as the reference measure. However, the numerical primary correlation result, uncertainty around that result, and numerical secondary outcome results are not reported in the registry record. The available information therefore does not show how strong or precise the relationship was, how reproducible the measurements were, or how often acquisition failed.

Correlation, even when available, would not by itself show that HRI and MRI-PDFF give interchangeable values. Nor would it establish that the ultrasound measure can replace MRI-PDFF in other settings. Agreement, calibration, and performance across a broader population are distinct questions that require suitable data and analyses. Those results are not reported in the registry record.

The study also does not compare clinical outcomes between treatment groups. It has no randomized control group, and the posted objectives concern measurement feasibility and performance. It therefore cannot establish a treatment benefit or harm. Its completed status indicates that the registry lists the study as completed; it does not fill gaps in the numerical outcome reporting.

Overall, the record gives a clear description of the intended comparison and some information about the sample and scan collection, but not the quantitative findings needed to judge the primary association or secondary measurement objectives. Conclusions about the degree of correlation, precision, reproducibility, or broader applicability are not supported by the reported numerical results.

14. Why This Trial Matters Statistically

Measurement studies raise statistical questions that differ from treatment trials. Here, the target is a relationship between two ways of assessing liver fat: ultrasound-derived HRI and MRI-PDFF. The distinction matters because an association is not equivalent to agreement or interchangeability. A strong correlation could coexist with systematic differences in measurement values, while poor measurement reliability can obscure the relationship being studied.

The design also involves repeated measurements and two operators. Those features make the unit of analysis important: scans are not automatically independent simply because they are separate measurement records. Subject-level averaging and operator differences are described in the registry, but the exact statistical handling of repeated observations is not reported. Reporting those details alongside estimates and confidence intervals would help readers assess precision and reproducibility.

Acquisition failure and inter-operator variability are not secondary technical details in a measurement study. They affect how often a measurement can be obtained and how consistently operators obtain it. The registry lists these objectives for HRI, acoustic attenuation, and tissue stiffness, but numerical findings are not reported in the registry record. Without those results, the practical measurement characteristics cannot be quantified.

Finally, the registry describes 9 outcome measures and 15 analyses, while the design is a single-group pilot. Clear reporting of prespecified outcomes, analysis populations, missing-data handling, and multiplicity methods is important for interpreting several related analyses. Those details are not reported in the registry record. The example illustrates why a study’s stated objective and completion status are not substitutes for numerical estimates and transparent analysis details.

15. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The primary limitation for statistical interpretation is that the registry record does not report the numerical HRI–MRI-PDFF correlation, its confidence interval, or a p-value. The endpoint objective is described, but the strength and precision of the relationship cannot be assessed from the posted results. Numerical findings for the listed secondary objectives are also not reported in the registry record.

The enrolled sample was 30 subjects, and the record reports 60 non-missing scans used to calculate HRI. The exact number of subjects with complete paired HRI and MRI-PDFF data, the analysis population, and the contribution of repeated measurements are not reported in the registry record. The record also does not describe handling of missing measurements, acquisition failures, or other exclusions.

The study is a single-group pilot with no randomized comparator group. MRI-PDFF is a measurement reference, not a control treatment. This design addresses a measurement relationship and does not estimate a comparative treatment effect. The registry describes an investigational ultrasound procedure and the MRI-PDFF examination but does not report detailed eligibility criteria, participant characteristics, or the range of liver fat values represented. Generalizability beyond the enrolled pediatric population therefore cannot be assessed from the record.

Other limitations include unreported details of the correlation method, uncertainty estimation, and handling of repeated observations. Although same-day operator variability and data acquisition failure were objectives, their numerical results and analysis methods are not reported in the registry record. The statistical analysis plan, sample-size justification, and multiplicity procedures are also not reported in the registry record. These omissions restrict assessment of analytic choices and robustness.

16. Related Tutorials

17. Related Statistical Calculators

18. Sources

• ClinicalTrials.gov: Pediatric Liver Fat Quantification (LFQ) Phase 2 Pilot Study — NCT04800094.
• Registry record last updated 2026-01-27; status last verified 2024-09.
• Results first posted 2026-01-27.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

19. Record Summary

NCT04800094 is a completed, single-group pilot study of investigational ultrasound liver fat quantification in a pediatric population. Enrollment was 30, and the listed study dates are 2021-03-02 to primary completion on 2022-12-13. Participants underwent ultrasound imaging and MRI-PDFF assessment. The primary objective was to assess correlation between ultrasound HRI and MRI-PDFF liver fat percentage.

The registry reports 60 non-missing ultrasound scans used to calculate HRI, with measurements collected by two operators. Secondary objectives concerned inter-operator variability and acquisition failure for HRI, acoustic attenuation, and tissue stiffness. The record lists 9 outcome measures and 15 analyses. Numerical primary and secondary results, detailed analysis methods, and missing-data procedures are not reported in the registry record.