ArticleQuantitative imaging in medicine and surgery2025
Multiparametric MRI-based radiomics nomogram for noninvasive stratification of HER2 expression status in breast cancer.
Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Accurate assessment of human epidermal growth factor receptor 2 (HER2) status, particularly HER2-low (formerly HER2-negative), is critical for guiding optimal HER2-targeted therapeutic decisions, as these patients may now be eligible for novel anti-HER2 antibody-drug conjugates. This study aimed to develop a radiomic nomogram based on multiparametric magnetic resonance imaging (MRI)-derived radiomic features combined with clinical characteristics for distinguishing HER2-positive and HER2-low breast cancer (BC) from HER2-negative BC (Task 1) and HER2-low from HER2-negative BC (Task 2). Methods: A total of 364 patients from two centers with invasive ductal carcinoma of BC were retrospectively enrolled from September 2022 to March 2024 and divided into two tasks. Patients from Center 1 (The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University) were randomly assigned to training cohort (Task 1: n=165; Task 2: n=112) and internal validation cohort (Task 1: n=71; Task 2: n=48). Patients from Center 2 (Ganzhou Cancer Hospital) were used as an external validation cohort (Task 1: n=78; Task 2: n=52). Radiomics signatures (RS) models were established using features from dynamic contrast-enhanced (DCE), T2-weighted image (T2WI), and combination (RS-Com). A clinical characteristic model was established through univariate and multivariate analyses, and a radiomics nomogram was developed by integrating radiomics score (Rad-score) with clinically significant characteristics. Its performance was evaluated through metrics such as the area under the curve (AUC), calibration assessment, and decision curve analysis (DCA). Results: For Task 1, RS-Com yielded a greater AUC for training, internal, and external validation of (0.861, 0.784, and 0.794, respectively) than did RS-DCE (AUC =0.743, 0.732, and 0.629, respectively) and RS-T2WI (AUC =0.741, 0.663, and 0.652 respectively). For Task 2, compared with RS-DCE (AUC =0.774/0.668/0.738) and RS-T2WI (AUC =0.771/0.677/0.637), RS-Com also exhibited greater AUCs for training, internal, and external validation (0.822/0.725/0.773). Univariate and multivariate analyses showed that the estrogen receptor (ER) and progesterone receptor (PR) statuses were independent predictors for distinguishing HER2 status. For both Tasks 1 and 2, the radiomic nomogram demonstrated the best performance with AUCs of 0.916/0.940/0.820 and 0.863/0.892/0.833, respectively. Conclusions: The multiparametric MRI-based radiomic nomogram can more accurately categorize the levels of HER2 expression in invasive ductal carcinoma patients, especially for those with HER2-low expression, serving as an early-stage aid for clinicians to devise tailored and precise therapeutic strategies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.