Evidence map›Paper›PMID 34249624›Full record

ArticleQuantitative imaging in medicine and surgery2021

Hepatic fat quantification of magnetic resonance imaging whole-liver segmentation for assessing the severity of nonalcoholic fatty liver disease: comparison with a region of interest sampling method.

Qin-He Zhang, Ying Zhao, Shi-Feng Tian, Lu-Han Xie, Li-Hua Chen, An-Liang Chen, Nan Wang, Qing-Wei Song, Hao-Nan Zhang, Li-Zhi Xie and 2 more

Open access · diamondAbstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
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

22 citing papers in PubMed, 23 citations in OpenAlex.

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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

12 authors at 3 institutions in 1 country.

Qin-He ZhangDepartment of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China.
Ying ZhaoDepartment of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China.
Shi-Feng TianDepartment of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China.
Lu-Han XieDepartment of Pathology and Forensics, Dalian Medical University, Dalian, China.
Li-Hua ChenDepartment of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China.
An-Liang ChenDepartment of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China.
Nan WangDepartment of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China.
Qing-Wei SongDepartment of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China.
Hao-Nan ZhangDepartment of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China.
Li-Zhi XieGE Healthcare, MR Research, Beijing, China.
Zhi-Wei ShenPhilips Healthcare, Beijing, China.
Ai-Lian LiuDepartment of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, China.
Dalian Medical University · CNFirst Affiliated Hospital of Dalian Medical University · CNPhilips (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate and early assessment of the hepatic fat content is crucial for patients with nonalcoholic fatty liver disease (NAFLD). For years, magnetic resonance imaging (MRI) has been considered the optimal noninvasive method for the assessment of fat accumulation. To avoid time-consuming manual placement of multiple regions of interest (ROI), the use of whole-liver segmentation has been proposed to measure liver fat, mainly for heterogeneous fat deposition. However, it remains uncertain whether the hepatic mean fat fraction (FF) obtained by whole-liver segmentation with the inclusion of intrahepatic vasculature is consistent with the traditional ROI sampling method. In this study, we assessed the accuracy of hepatic mean FF obtained by whole-liver segmentation in patients of NAFLD with different severities using the ROI sampling method as a reference standard.

methodsHepatic FFs were measured by whole-liver segmentation and the ROI sampling method (reference standard) using MRI scanning with the iterative decomposition of water and fat with echo an asymmetry at least-square estimation-iron quantification (IDEAL-IQ) sequence. SPSS version 25.0 software was used to analyze the correlation and consistency of data between the two methods.

resultsThere was a strong correlation in hepatic FF between whole-liver segmentation and the ROI sampling method in healthy, mild, and moderate steatosis patients (r = 0.943, 0.990, and 0.961, respectively). Bland-Altman analysis showed a small bias of +0.50±0.27 and +0.05±0.30, which indicated a small overestimation when using whole-liver segmentation in healthy subjects and mild NAFLD patients. The 95% limits of agreement ranged from +1.02 to -0.03, and from +0.65 to -0.55, respectively. However, a small bias of -0.96±0.77 was also evident, which indicated a small underestimation when using whole-liver segmentation in moderate NAFLD patients. The 95% limits of agreement ranged from +0.56 to -2.48.

conclusionsDue to inclusion of the intrahepatic vasculature, whole-liver segmentation has some effects on hepatic FF assessment in patients with different NAFLD severities; yet, it does not significantly affect the assessment of whole-liver FF in MRI FF maps.

Indexed as

Hepatic fatmagnetic resonance imaging (MRI)nonalcoholic fatty liver disease (NAFLD)whole-liver segmentation

Identifiers

PMID34249624
PMCPMC8250014
OpenAlexW3152527232

What Socratic holds

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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.