Evidence map›Paper›PMID 35035845›Full record

ArticleJournal of healthcare engineering2022

Shear Wave Elastography-Assisted Ultrasound Breast Image Analysis and Identification of Abnormal Data.

Caoxin Yan, Zhiyan Luo, Zimei Lin, Huilin He, Yunkai Luo, Jian Chen

Abstract read
In one paragraph

Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
  6. 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

6 authors.

Caoxin YanDepartment of Ultrasound in Medicine, The Fourth Affiliated Hospital of Zhejiang University School of Medicine, Yiwu, Zhejiang 322000, China.ORCID 0000-0001-6548-6695
Zhiyan LuoDepartment of Ultrasound in Medicine, The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.ORCID 0000-0002-5163-3719
Zimei LinDepartment of Ultrasound in Medicine, The Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.ORCID 0000-0002-2337-3382
Huilin HeDepartment of Ultrasound in Medicine, The Fourth Affiliated Hospital of Zhejiang University School of Medicine, Yiwu, Zhejiang 322000, China.ORCID 0000-0002-3404-3506
Yunkai LuoDepartment of Ultrasound in Medicine, The Fourth Affiliated Hospital of Zhejiang University School of Medicine, Yiwu, Zhejiang 322000, China.ORCID 0000-0001-9081-5577
Jian ChenDepartment of Ultrasound in Medicine, The Fourth Affiliated Hospital of Zhejiang University School of Medicine, Yiwu, Zhejiang 322000, China.ORCID 0000-0003-2295-5505

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, shear wave elastography was used to study and analyze the images of the breast in-depth and identify the abnormal image data. Sixty breast lesions were evaluated, and quantitative metrics were reproducible in the static and dynamic modes of shear wave elastography with a higher interobserver agreement in dynamic qualitative metrics than in the static mode. There were no statistically significant differences between the two modes of imaging in quantitative metrics, and quantitative metrics were more effective than qualitative metrics. Postoperative immunohistochemical expression of ER, PR, HER-2, Ki-67, molecular typing, pathological type, histological grading, and axillary lymph node status of breast cancer was obtained based on pathological results. The correlation between mass size, patient age, and WiMAX values of breast cancer masses was analyzed using Pearson correlation, and the differences in SWVmax values of breast cancer masses between different expressions of immunohistochemical parameters ER, PR, HER-2, Ki-67, and axillary lymph node status were compared using tests. The variables with correlations and differences were included in the multiple linear regression analysis to assess the factors influencing the SWVmax values. The performance of TDPM, SPM, and TSPM was compared using PVA body models with different freeze-thaw cycles. The results showed that TSPM performed better than SPM in general, and TDPM showed excellent performance because of high temporal resolution and low random error, especially when the number of freeze-thaw cycles increased and the hardness of the PVA body mold increased. Measurements at different depths of inhomogeneous body models also showed that the TDPM method was less affected by depth, and the results were more stable. Finally, the reliability of the shear wave velocity (SWS) measured by the TDPM and SPM methods was investigated using porcine ligament tissue, and the results showed that the mean values of SWS goodness of fit for TDPM and SPM were 0.94 and 0.87, respectively, and the estimated elastic modulus of TDPM was very close to the mechanical test results.

Indexed as

Breast NeoplasmsElasticity Imaging TechniquesAnimalsFemaleHumansKi-67 AntigenReproducibility of ResultsSensitivity and SpecificitySwineKi-67 Antigen

Identifiers

PMID35035845
PMCPMC8759893

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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.