Evidence map›Paper›PMID 36295617›Full record

ArticleMedicina (Kaunas, Lithuania)2022

Hepatic Fat Quantification with the Multi-Material Decomposition Algorithm by Using Low-Dose Non-Contrast Material-Enhanced Dual-Energy Computed Tomography in a Prospectively Enrolled Cohort.

Seung Baek Hong, Nam Kyung Lee, Suk Kim, Kyunga Um, Keunyoung Kim, In Joo Kim

Abstract read
In one paragraph

Article in Medicina (Kaunas, Lithuania), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Spectral CT: Current Liver Applications.Diagnostics (Basel, Switzerland) · 2023
    Review
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

6 authors.

Seung Baek HongDepartment of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Pusan 46241, Korea.ORCID 0000-0002-1731-0430
Nam Kyung LeeDepartment of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Pusan 46241, Korea.
Suk KimDepartment of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Pusan 46241, Korea.
Kyunga UmGeneral Electronics (GE) Healthcare Korea, Seoul 04637, Korea.
Keunyoung KimDepartment of Nuclear Medicine and Biomedical Research Institute, Pusan National University Hospital, Pusan 46241, Korea.
In Joo KimDivision of Endocrinology and Metabolism, Department of Internal Medicine, Biomedical Research Institute, Pusan National University Hospital, Pusan 46241, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The early diagnosis of hepatic steatosis is important. No study has assessed hepatic fat quantification by using low-dose dual-energy computed tomography (CT). We assessed the accuracy of hepatic fat quantification using the multi-material decomposition (MMD) algorithm with low-dose non-contrast material-enhanced dual-energy CT. We retrospectively reviewed 33 prospectively enrolled patients who had undergone low-dose non-contrast material-enhanced dual-energy CT and magnetic resonance image (MRI) proton density fat fraction (PDFF) on the same day. Percentage fat volume fraction (FVF) images were generated using the MMD algorithm on the low-dose dual-energy CT data. We assessed the correlation between FVFs and MRI-PDFFs by using Spearman's rank correlation. With a 5% cutoff value of MRI-PDFF for fatty liver, a receiver operating characteristic (ROC) curve analysis was performed to identify the optimal criteria of FVF for diagnosing fatty liver. CTDIvol of CT was 2.94 mGy. FVF showed a strong correlation with MRI-PDFF (r = 0.756). The ROC curve analysis demonstrated that FVF ≥ 4.61% was the optimal cutoff for fatty liver. With this cutoff value for diagnosing the fatty liver on low-dose dual-energy CT, the sensitivity, specificity, and area under the curve were 90%, 100%, and 0.987, respectively. The MMD algorithm using low-dose non-contrast material-enhanced dual-energy CT is feasible for quantifying hepatic fat.

Indexed as

Fatty LiverProtonsAlgorithmsHumansLiverMagnetic Resonance ImagingRetrospective StudiesTomography, X-Ray ComputedProtonscomputed tomographydiagnostic performancehepatic fatmagnetic resonance imageradiation

Identifiers

PMID36295617
PMCPMC9609129

What Socratic holds

Textmetadata
LicenceCC BY
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.