Evidence map›Paper›PMID 33609166›Full record

ArticleAbdominal radiology (New York)2021

Repeatability and accuracy of various region-of-interest sampling strategies for hepatic MRI proton density fat fraction quantification.

Cheng William Hong, Jennifer Y Cui, Danielle Batakis, Yang Xu, Tanya Wolfson, Anthony C Gamst, Alexandra N Schlein, Lindsey M Negrete, Michael S Middleton, Gavin Hamilton and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Abdominal radiology (New York), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Cheng William HongDepartment of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA. cwhong@ucsd.edu.ORCID 0000-0002-5219-6039
Jennifer Y CuiDepartment of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA.
Danielle BatakisDepartment of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA.
Yang XuDepartment of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA.
Tanya WolfsonComputational and Applied Statistics Laboratory, University of California San Diego, San Diego, CA, USA.
Anthony C GamstComputational and Applied Statistics Laboratory, University of California San Diego, San Diego, CA, USA.
Alexandra N SchleinDepartment of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA.
Lindsey M NegreteDepartment of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA.
Michael S MiddletonDepartment of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA.
Gavin HamiltonDepartment of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA.
Rohit LoombaDivision of Gastroenterology, Department of Medicine, University of California San Diego, San Diego, USA.
Jeffrey B SchwimmerDepartment of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA.
Kathryn J FowlerDepartment of Radiology, University of California San Diego, 200 W. Arbor Drive #8756, San Diego, CA, 92103-8756, USA.
Claude B SirlinDepartment of Radiology, University of California San Diego, 9500 Gilman Drive #0888, La Jolla, CA, 92093-0888, USA. csirlin@ucsd.edu.

Funding

Training Clinical Scientists in Radiological ImagingT32EB005970 · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2025 to 2025
$92k
NIBIB NIH HHS T32 EB005970NIBIB NIH HHS T32 EB005970-09NIDDK NIH HHS R01 DK106419NIDDK NIH HHS R01 DK106419-02
6 · The paper itself

Abstract

purposeTo evaluate repeatability of ROI-sampling strategies for quantifying hepatic proton density fat fraction (PDFF) and to assess error relative to the 9-ROI PDFF.

methodsThis was a secondary analysis in subjects with known or suspected nonalcoholic fatty liver disease who underwent MRI for magnitude-based hepatic PDFF quantification. Each subject underwent three exams, each including three acquisitions (nine acquisitions total). An ROI was placed in each hepatic segment on the first acquisition of the first exam and propagated to other acquisitions. PDFF was calculated for each of 511 sampling strategies using every combination of 1, 2, …, all 9 ROIs. Intra- and inter-exam intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs) were estimated for each sampling strategy. Mean absolute error (MAE) was estimated relative to the 9-ROI PDFF. Strategies that sampled both lobes evenly ("balanced") were compared with those that did not ("unbalanced") using two-sample t tests.

resultsThe 29 enrolled subjects (23 male, mean age 24 years) had mean 9-ROI PDFF 11.8% (1.1-36.3%). With more ROIs, ICCs increased, RCs decreased, and MAE decreased. Of the 60 balanced strategies with 4 ROIs, all (100%) achieved inter- and intra-exam ICCs > 0.998, 55 (92%) achieved intra-exam RC < 1%, 50 (83%) achieved inter-exam RC < 1%, and all (100%) achieved MAE < 1%. Balanced sampling strategies had higher ICCs and lower RCs, and lower MAEs than unbalanced strategies in aggregate (p < 0.001 for comparisons between balanced vs. unbalanced strategies).

conclusionRepeatability improves and error diminishes with more ROIs. Balanced 4-ROI strategies provide high repeatability and low error.

Indexed as

Non-alcoholic Fatty Liver DiseaseProtonsAdultHumansLiverMagnetic Resonance ImagingMaleProspective StudiesReproducibility of ResultsYoung AdultProtonsHepatic fat quantificationHepatic PDFFQIBQuantitative imaging biomarkerRegion-of-interestRepeatabilitySampling strategy

Identifiers

PMID33609166
PMCPMC8983333

What Socratic holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.