Evidence map›Paper›PMID 35066632›Full record

ArticleEuropean radiology2022

Intratumoral and peritumoral radiomics for preoperative prediction of neoadjuvant chemotherapy effect in breast cancer based on contrast-enhanced spectral mammography.

Ning Mao, Yinghong Shi, Chun Lian, Zhongyi Wang, Kun Zhang, Haizhu Xie, Haicheng Zhang, Qianqian Chen, Guanxun Cheng, Cong Xu and 1 more

Abstract read
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In one paragraph

Article in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed
13.1field-weighted citation impact, top 1% 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

72 citing papers in PubMed, 95 citations in OpenAlex.

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12 more citing papers are in PubMed but not listed here.

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

11 authors at 2 institutions in 1 country.

Ning MaoDepartment of Radiology, Yantai Yuhuangding Hospital, Qingdao University, No.20 Yuhuangding East Street, Yantai, Shandong, 264000, People's Republic of China.
Yinghong ShiDepartment of Radiology, Yantai Yuhuangding Hospital, Qingdao University, No.20 Yuhuangding East Street, Yantai, Shandong, 264000, People's Republic of China.
Chun LianDepartment of Radiology, Peking University Shenzhen Hospital, No.1120 Lianhua Road, Shenzhen, Guangdong, 518036, People's Republic of China.
Zhongyi WangDepartment of Radiology, Yantai Yuhuangding Hospital, Qingdao University, No.20 Yuhuangding East Street, Yantai, Shandong, 264000, People's Republic of China.
Kun ZhangBig Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, People's Republic of China.
Haizhu XieDepartment of Radiology, Yantai Yuhuangding Hospital, Qingdao University, No.20 Yuhuangding East Street, Yantai, Shandong, 264000, People's Republic of China.
Haicheng ZhangBig Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, People's Republic of China.
Qianqian ChenPrecision Health Institution, GE Healthcare, Shanghai, 200000, People's Republic of China.
Guanxun ChengDepartment of Radiology, Peking University Shenzhen Hospital, No.1120 Lianhua Road, Shenzhen, Guangdong, 518036, People's Republic of China.
Cong XuPhysical Examination Center, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, People's Republic of China. 616574369@qq.com.
Yi DaiDepartment of Radiology, Peking University Shenzhen Hospital, No.1120 Lianhua Road, Shenzhen, Guangdong, 518036, People's Republic of China. dalydp@126.com.ORCID http://orcid.org/0000-0002-1919-1885
Qingdao University · CNPeking University Shenzhen Hospital · CN

Funding

National Natural Science Foundation of China 61773244National Natural Science Foundation of China 82001775Taishan Scholar Foundation of Shandong Province tsqn202103197
6 · The paper itself

Abstract

objectiveTo investigative the performance of intratumoral and peritumoral radiomics based on contrast-enhanced spectral mammography (CESM) to preoperatively predict the effect of the neoadjuvant chemotherapy (NAC) of breast cancers. MATERIALS AND

methodsA total of 118 patients with breast cancer who underwent preoperative CESM and NAC from July 2017 to June 2020 were retrospectively analyzed, and the patients were grouped into training (n = 81) and test sets (n = 37) according to the CESM examination time. NAC effect for each patient was assessed by pathology. Intratumoral and peritumoral radiomics features were extracted from CESM images, and feature selection was performed through the Mann-Whitney U test and least absolute shrinkage and selection operator regression (LASSO). Five radiomics signatures based on intratumoral regions, 5-mm peritumoral regions, 10-mm peritumoral regions, intratumoral regions + 5-mm peritumoral regions, and intratumoral regions + 10-mm peritumoral regions were calculated through a linear combination of selected features weighted by their respective coefficients. The prediction performance of radiomics signatures was assessed by the area under the receiver operator characteristic (ROC) curve, the precision-recall (P-R) curve, the calibration curve, and decision curve analysis (DCA).

resultsTen radiomics features were selected to establish the radiomics signature of intratumoral regions + 5-mm peritumoral regions, which yielded a maximum AUC of 0.85 (95% CI, 0.72-0.98) in the test set. The calibration curves, P-R curves, and DCA showed favorable predictive performance of the five radiomics signatures.

conclusionThe intratumoral and peritumoral radiomics based on CESM exhibited potential for predicting the NAC effect in breast cancer, which could guide treatment decisions. KEY POINTS: • The intratumoral and peritumoral CESM-based radiomics signatures show good performance in predicting the NAC effect in breast cancer.

Indexed as

Breast NeoplasmsNeoadjuvant TherapyFemaleHumansMammographyRetrospective StudiesBreast NeoplasmsMachine LearningMammographyNeoadjuvant therapy

Identifiers

PMID35066632
OpenAlexW4206941699

What OpenQuestion holds

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Registered trials

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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.