Evidence map›Paper›PMID 35442093›Full record

ArticleThe British journal of radiology2022

Comparative study of conventional diffusion-weighted imaging and introvoxel incoherent motion in assessment of pathological grade of clear cell renal cell carcinoma.

Qingqiang Zhu, Wenrong Zhu, Jingtao Wu, Wenxin Chen, Jing Ye, Jun Ling

Open access · greenAbstract read
In one paragraph

Article in The British journal of radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

9 citing papers in PubMed, 10 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

6 authors at 1 institution in 1 country.

Qingqiang ZhuDepartment of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China.
Wenrong ZhuDepartment of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China.
Jingtao WuDepartment of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China.
Wenxin ChenDepartment of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China.
Jing YeDepartment of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China.
Jun LingDepartment of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China.
Yangzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo quantitatively compare the diagnostic values of conventional diffusion-weighted imaging (DWI) and introvoxel incoherent motion (IVIM) analysis of microstructural differences for clear cell renal cell carcinoma (ccRCC).

methodsMultiple b value DWIs and IVIMs were performed in patients with 146 ccRCCs, 42 with Grade Ⅰ, 46 with Grade Ⅱ, 28 with Grade Ⅲ and 30 with Grade Ⅳ. These tumours were divided into low (Ⅰ+Ⅱ,

resultsThe mean signal-to-noise ratios (SNRs) of IVIM images at

conclusionIVIM parameters have better performance than ADC in differentiating ccRCC grading, given an adequate SNR of IVIM images. ADVANCES IN KNOWLEDGE: 1. D values had the highest diagnostic efficacy in differentiating low/high and Ⅱ/Ⅲ ccRCC grading. 2. IVIM parameters have better performance than ADC in differentiating ccRCC grading, given an adequate SNR of IVIM images. 3. The ADC, D and D* values correlated negatively with ccRCC grading, however, f values correlated positively with ccRCC grading.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsDiffusion Magnetic Resonance ImagingFemaleHumansMaleMotionROC CurveSensitivity and Specificity

Identifiers

PMID35442093
PMCPMC10993952
OpenAlexW4210863998

What OpenQuestion holds

Textmetadata
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.