Evidence map›Paper›PMID 41405789›Full record

ArticleInsights into imaging2025

Early-phase semi-quantitative analysis versus full time-course quantitative modeling of ultrafast dynamic contrast-enhanced MRI for breast cancer diagnosis, molecular subtyping, and treatment response prediction.

Ying Cao, Xueqin Gong, Yao Huang, Huifang Chen, Jie Fang, Lu Wang, Lan Li, Sun Tang, Ting Yin, Xiaoxia Wang and 1 more

Erratum issuedAbstract read
In one paragraph

Article in Insights into imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

5 · Who and what money

Authors and funding

11 authors.

Ying CaoSchool of Medicine, Chongqing University, Chongqing, China.
Xueqin GongDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Yao HuangSchool of Medicine, Chongqing University, Chongqing, China.
Huifang ChenDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Jie FangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Lu WangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Lan LiDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Sun TangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Ting YinMR Collaborations, Siemens Healthineers Ltd., Chengdu, China.
Xiaoxia WangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Jiuquan ZhangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China. 76256127@qq.com.ORCID http://orcid.org/0000-0003-0239-6988

Funding

Chongqing Medical Research Project of Combination of Science and Medicine No. 2024MSXM171Fundamental Research Funds for the Central Universities 2023CDJYGRH-YB04Natural Science Foundation of Chongqing Municipality CSTB2024NSCQ-MSX0217Natural Science Foundation of Chongqing Municipality CSTB2024NSCQ-MSX0334Natural Science Foundation of Chongqing Municipality CSTB2024NSCQ-MSX0760the Chongqing University Cancer Hospital Scientific Research Capacity Improvement Project 2023nlts004
6 · The paper itself

Abstract

objectivesTo evaluate the performance of semi-quantitative analysis versus quantitative pharmacokinetic analysis applied to ultrafast dynamic contrast-enhanced (UF-DCE) MRI in: (1) differentiating benign from malignant breast lesions, (2) molecular subtyping, and (3) predicting pathologic complete response (pCR) following neoadjuvant chemotherapy. MATERIALS AND

methodsThis prospective noninferiority study enrolled 339 consecutive participants with suspected breast lesions between September 2022 and February 2024. All underwent breast DCE MRI with a temporal resolution of 4.5 s, totaling 100 phases. Using the initial 30 phases (early-phase UF-DCE), five semi-quantitative parameters were calculated: wash-in slope (WIS), time-to-peak, bolus arrival time, peak enhancement intensity (PEI), and initial area under the curve in 60 s. Furthermore, three quantitative parameters: volume transfer constant, rate constant (k

resultsAll semi-quantitative and quantitative parameters showed differences between benign and malignant breast lesions (p < 0.001). Semi-quantitative WIS demonstrated noninferior diagnostic performance to quantitative k

conclusionSemi-quantitative analysis of early-phase UF-DCE exhibits noninferior performance to quantitative analysis of full time-course UF-DCE MRI for distinguishing benign from malignant breast lesions. Both analytical approaches showed limited utility in molecular subtyping and pCR prediction. CRITICAL RELEVANCE STATEMENT: Early-phase UF-DCE MRI provides a cost-effective alternative to full time-course UF-DCE MRI for differentiating benign and malignant breast lesions, demonstrating noninferior diagnostic performance with reduced scan time and no need for pharmacokinetic modeling. KEY POINTS: Systematic comparison of early-phase UF-DCE and full time-course UF-DCE MRI for diagnosis, subtyping, and response prediction in a single breast cancer cohort remains limited. Early-phase UF-DCE MRI demonstrated noninferior diagnostic performance to full time-course UF-DCE MRI in differentiating benign and malignant breast lesions. Early-phase UF-DCE MRI is a time-efficient alternative to full time-course UF-DCE MRI for clinical implementation.

Indexed as

Breast neoplasmsDifferential diagnosisMagnetic resonance imagingNeoadjuvant chemotherapy

Identifiers

PMID41405789
PMCPMC12712255

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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.