Evidence map›Paper›PMID 38971790›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2024

Diagnostic efficiency of intravoxel incoherent motion-based virtual magnetic resonance elastography in pulmonary neoplasms.

Shuo Zhang, Yonghao Du, Ting Liang, Xuyin Zhang, Yinxia Guo, Jian Yang, Xianjun Li, Gang Niu

Abstract read
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

8 authors.

Shuo Zhang *Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Yanta District, Xi'an, 710061, P.R. China.
Yonghao Du *Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Yanta District, Xi'an, 710061, P.R. China.
Ting LiangDepartment of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Yanta District, Xi'an, 710061, P.R. China.
Xuyin ZhangDepartment of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Yanta District, Xi'an, 710061, P.R. China.
Yinxia GuoDepartment of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Yanta District, Xi'an, 710061, P.R. China.
Jian YangDepartment of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Yanta District, Xi'an, 710061, P.R. China.
Xianjun LiDepartment of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Yanta District, Xi'an, 710061, P.R. China. xianj.li@mail.xjtu.edu.cn.
Gang NiuDepartment of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta West Road, Yanta District, Xi'an, 710061, P.R. China. niugang369@mail.xjtu.edu.cn.ORCID http://orcid.org/0000-0003-4198-1717

Funding

Clinical Research Award of the First Affiliated Hospital of Xi'an Jiaotong University of China XJTU1AF2021CRF-015National Natural Science Foundation of China 82202998National Natural Science Foundation of China No. 82272073Natural Science Basic Research Program of Shaanxi Province 2021JQ-389Natural Science Basic Research Program of Shaanxi Province 2022JQ-884
6 · The paper itself

Abstract

backgroundThe aim of the study were as below. (1) To investigate the feasibility of intravoxel incoherent motion (IVIM)-based virtual magnetic resonance elastography (vMRE) to provide quantitative estimates of tissue stiffness in pulmonary neoplasms. (2) To verify the diagnostic performance of shifted apparent diffusion coefficient (sADC) and reconstructed virtual stiffness values in distinguishing neoplasm nature.

methodsThis study enrolled 59 patients (37 males, 22 females) with one pulmonary neoplasm who underwent computed tomography-guided percutaneous transthoracic needle biopsy (PTNB) with pathological diagnosis (26 adenocarcinoma, 10 squamous cell carcinoma, 3 small cell carcinoma, 4 tuberculosis and 16 non-specific benign; mean age, 60.81 ± 9.80 years). IVIM was performed on a 3 T magnetic resonance imaging scanner before biopsy. sADC and virtual shear stiffness maps reflecting lesion stiffness were reconstructed. sADC and virtual stiffness values of neoplasm were extracted, and the diagnostic performance of vMRE in distinguishing benign and malignant and detailed pathological type were explored.

resultsCompared to benign neoplasms, malignant ones had a significantly lower sADC and a higher virtual stiffness value (P < 0.001). Subsequent subtype analyses showed that the sADC values of adenocarcinoma and squamous cell carcinoma groups were significantly lower than non-specific benign group (P = 0.013 and 0.001, respectively). Additionally, virtual stiffness values of the adenocarcinoma and squamous cell carcinoma subtypes were significantly higher than non-specific benign group (P = 0.008 and 0.001, respectively). However, no significant correlation was found among other subtype groups.

conclusionsNon-invasive vMRE demonstrated diagnostic efficiency in differentiating the nature of pulmonary neoplasm. vMRE is promising as a new method for clinical diagnosis.

Indexed as

Elasticity Imaging TechniquesLung NeoplasmsAgedFeasibility StudiesFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedMotionTomography, X-Ray ComputedIntravoxel incoherent motionPulmonary neoplasmShifted apparent diffusion coefficientStiffnessVirtual magnetic resonance elastography

Identifiers

PMID38971790
PMCPMC11227719

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.