Evidence map›Paper›PMID 36176389›Full record

ArticleFrontiers in oncology2022

Evaluation of a new method of calculating breast tumor volume based on automated breast ultrasound.

Jing-Jing Ma, Shan Meng, Sha-Jie Dang, Jia-Zhong Wang, Quan Yuan, Qi Yang, Can-Xu Song

Abstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Jing-Jing MaDepartment of Internal Medicine, Xi'an Fifth Hospital, Xi'an, China.
Shan MengDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Sha-Jie DangDepartment of Anesthesia, Shaanxi Provincial Cancer Hospital, Affiliated to Xi'an Jiaotong University, Xi'an, China.
Jia-Zhong WangDepartment of General Surgery, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Quan YuanDepartment of Ultrasound, Shaanxi Provincial Cancer Hospital, Affiliated to Xi'an Jiaotong University, Xi'an, China.
Qi YangDepartment of Surgery, Shaanxi Provincial Cancer Hospital, Affiliated to Xi'an Jiaotong University, Xi'an, China.
Can-Xu SongDepartment of Ultrasound, Shaanxi Provincial Cancer Hospital, Affiliated to Xi'an Jiaotong University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To evaluate the effectiveness and advantages of a new method for calculating breast tumor volume based on an automated breast ultrasound system (ABUS). Methods: A total of 42 patients (18-70 years old) with breast lesions were selected for this study. The Ivenia ABUS 2.0 (General Electric Company, USA) was used, with a probe frequency of 6-15 MHz. Adobe Photoshop CS6 software was used to calculate the pixel ratio of each ABUS image, and to draw an outline of the tumor cross-section. The resulting area (in pixels) was multiplied by the pixel ratio to yield the area of the tumor cross-section. The Wilcoxon signed rank test and Bland-Altman plot were used to compare mean differences and mean values, respectively, between the two methods. Results: There was no significant difference between the tumor volumes calculated by pixel method as compared to the traditional method ( Conclusion: The new pixel method is feasible for measuring breast tumor volume and has good validity and measurement stability.

Indexed as

automated breast ultrasound systembreast lesionpixel methodsurgeryvolume

Identifiers

PMID36176389
PMCPMC9513394

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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.