Evidence map›Paper›PMID 35720027›Full record

ArticleComputational and mathematical methods in medicine2022

Repeatability and Image Quality of IDEAL-IQ in Human Lumbar Vertebrae for Fat and Iron Quantification across Acquisition Parameters.

Ben Shan, Haiyan Ding, Qianzao Lin, Xiaohua Zuo, Lili Lin, Dongyang Yu, Chunhong Hu

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 46% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
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

7 authors at 3 institutions in 1 country.

Ben ShanDepartment of Radiology, The First Affiliated Hospital of Soochow University, 188 Shizi Street, Suzhou 215006, China.ORCID https://orcid.org/0000-0002-0517-2384
Haiyan DingDepartment of Radiology, Huai'an Fifth People's Hospital, 1 East Huaihe Road, Huai'an 223001, China.ORCID https://orcid.org/0000-0002-1692-2304
Qianzao LinDepartment of Radiology, The Affiliated Huai'an Hospital of Xuzhou Medical University, 62 South Huaihai Road, Huai'an 223001, China.ORCID https://orcid.org/0000-0001-8367-6441
Xiaohua ZuoDepartment of Pain Management, The Affiliated Huai'an Hospital of Xuzhou Medical University, 62 South Huaihai Road, Huai'an 223001, China.ORCID https://orcid.org/0000-0002-2085-1035
Lili LinThe First Clinical Medical College, Gansu University of Chinese Medicine, 35 East Dingxi Road, Lanzhou 730000, China.ORCID https://orcid.org/0000-0001-6741-9277
Dongyang YuDepartment of Radiology, The Affiliated Huai'an Hospital of Xuzhou Medical University, 62 South Huaihai Road, Huai'an 223001, China.ORCID https://orcid.org/0000-0001-7622-1254
Chunhong HuDepartment of Radiology, The First Affiliated Hospital of Soochow University, 188 Shizi Street, Suzhou 215006, China.ORCID https://orcid.org/0000-0003-1406-9343
Xuzhou Medical College · CNGansu University of Traditional Chinese Medicine · CNSoochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Echo asymmetry and least square estimation-IQ (IDEAL-IQ) were used to quantify fat and iron to verify the effects of collection parameters on repeatability and image quality of water and fat in human vertebral body. Six IDEAL-IQ sequences were used to scan 48 healthy adult women. Reproducibility of fat and iron quantification and image quality were assessed for six IDEAL-IQ sequences. The results showed that the correlation index (0.987, 0.721) of FF and R2∗ between scans of sequence 2 was higher than that of other sequences, and the consistency of fat quantification was better than that of iron (0.860 vs. 0.579) (

Indexed as

IronLumbar VertebraeAdultFemaleHumansMagnetic Resonance ImagingReproducibility of ResultsWaterIronWater

Identifiers

PMID35720027
PMCPMC9203175
OpenAlexW4281611662

What OpenQuestion 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 OpenQuestion graph.