Evidence map›Paper›PMID 36006063›Full record

ArticleTomography (Ann Arbor, Mich.)2022

B

Yibing Chen, Xujian Dang, Benqi Zhao, Zhuozhao Zheng, Xiaowei He, Xiaolei Song

Open access · goldAbstract read
In one paragraph

Article in Tomography (Ann Arbor, Mich.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.6field-weighted citation impact, top 35% 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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 3 institutions in 1 country.

Yibing ChenXi'an Key Laboratory of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an 710069, China.
Xujian DangXi'an Key Laboratory of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an 710069, China.ORCID 0000-0003-0674-2518
Benqi ZhaoDepartment of Radiology, Beijing Tsinghua Changgung Hospital, Beijing 102218, China.
Zhuozhao ZhengDepartment of Radiology, Beijing Tsinghua Changgung Hospital, Beijing 102218, China.
Xiaowei HeXi'an Key Laboratory of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an 710069, China.
Xiaolei SongCenter for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.ORCID 0000-0002-0206-1574
Northwest University · CNBeijing Tsinghua Chang Gung Hospital · CNTsinghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amide proton transfer (APT)-weighted MRI is a promising molecular imaging technique that has been employed in clinic for detection and grading of brain tumors. MTRasym, the quantification method of APT, is easily influenced by B0 inhomogeneity and causes artifacts. Current model-free interpolation methods have enabled moderate B0 correction for middle offsets, but have performed poorly at limbic offsets. To address this shortcoming, we proposed a practical B0 correction approach that is suitable under time-limited sparse acquisition scenarios and for B1 ≥ 1 μT under 3T. In this study, this approach employed a simplified Lorentzian model containing only two pools of symmetric water and asymmetric solutes, to describe the Z-spectral shape with wide and ‘invisible’ CEST peaks. The B0 correction was then performed on the basis of the fitted two-pool Lorentzian lines, instead of using conventional model-free interpolation. The approach was firstly evaluated on densely sampled Z-spectra data by using the spline interpolation of all acquired 16 offsets as the gold standard. When only six offsets were available for B0 correction, our method outperformed conventional methods. In particular, the errors at limbic offsets were significantly reduced (n = 8, p < 0.01). Secondly, our method was assessed on the six-offset APT data of nine brain tumor patients. Our MTRasym (3.5 ppm), using the two-pool model, displayed a similar contrast to the vendor-provided B0-orrected MTRasym (3.5 ppm). While the vendor failed in correcting B0 at 4.3 and 2.7 ppm for a large portion of voxels, our method enabled well differentiation of B0 artifacts from tumors. In conclusion, the proposed approach could alleviate analysis errors caused by B0 inhomogeneity, which is useful for facilitating the comprehensive metabolic analysis of brain tumors.

Indexed as

Brain NeoplasmsProtonsAmidesDimapritHumansMagnetic Resonance ImagingWaterAmidesAPTDimapritProtonsWateramide proton transfer (APT) MRIB0 inhomogeneity correctionbrain tumorschemical exchange saturation transfer (CEST) MRILorentzian fitting

Identifiers

PMID36006063
PMCPMC9412582
OpenAlexW4289525650

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.