DCE-MRI radiomics of primary breast lesions combined with ipsilateral axillary lymph nodes for predicting efficacy of NAT.

Publisher: BioMed Central Country of Publication: England NLM ID: 100967800 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2407 (Electronic) Linking ISSN: 14712407 NLM ISO Abbreviation: BMC Cancer Subsets: MEDLINE

Original Publication: London : BioMed Central, [2001-

Breast Neoplasms*/diagnostic imaging ; Breast Neoplasms*/pathology ; Magnetic Resonance Imaging*/methods ; Axilla* ; Lymph Nodes*/diagnostic imaging ; Lymph Nodes*/pathology ; Neoadjuvant Therapy*/methods ; Nomograms*; Humans ; Female ; Middle Aged ; Retrospective Studies ; Adult ; Aged ; Contrast Media/administration & dosage ; ROC Curve ; Lymphatic Metastasis/diagnostic imaging ; Treatment Outcome ; Radiomics

Competing Interests: Declarations. Ethics approval and consent to participate: This retrospective analysis was approved by the Ethics Committee of Liaoning Cancer Hospital, affiliated with Liaoning Cancer Hospital (Approval No. [20221101]), and the Ethics Committee of the Affiliated Hospital of Qingdao University, affiliated with Qingdao University (Approval No. [QYFY WZLL 28631]), with a waiver of written informed consent from the institutional review board. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.
Background: This study aimed to assess the predictive value of radiomic analysis derived from primary lesions and ipsilateral axillary suspicious lymph nodes (SLN) on dynamic contrast-enhanced MRI (DCE-MRI) for evaluating the response to neoadjuvant therapy (NAT) in early high-risk and advanced breast cancer (BC) patients.
Methods: A retrospective analysis was conducted on 222 BC patients (192 from Center I and 30 from Center II) who underwent NAT. Radiomic features were extracted from the primary lesion (intra- and peritumoral regions) and ipsilateral axillary SLN to develop radiomic signatures (RS-primary, RS-SLN). An integrated signature (RS-Com) combined features from both regions. Feature selection was performed using correlation analysis, the Mann-Whitney U test, and least absolute shrinkage and selection operator (LASSO) regression. A diagnostic nomogram was constructed by integrating RS-Com with key clinical factors. Model performance was evaluated using receiver operating characteristic (ROC) and decision curve analysis (DCA).
Results: RS-Com demonstrated superior predictive performance compared to RS-primary and RS-SLN alone. The DeLong test confirmed that axillary SLNs provide supplementary information to the primary lesion. Among clinical factors, N staging and HER2 status were significant contributors. The nomogram, integrating RS-Com, N staging, and HER2 status, achieved the highest performance in the training (AUC: 0.926), validation (AUC: 0.868), and test (AUC: 0.839) cohorts, outperforming both the clinical models and RS-Com alone.
Conclusion: Radiomic features from axillary SLNs offer valuable supplementary information for predicting NAT response in BC patients. The proposed nomogram, incorporating radiomics and clinical factors, provides a robust tool for individualized treatment planning.
(© 2025. The Author(s).)

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Keywords: Breast cancer; MRI; Neoadjuvant therapy; Radiomics

0 (Contrast Media)

Date Created: 20250401 Date Completed: 20250402 Latest Revision: 20250404

20250407

PMC11963401

10.1186/s12885-025-14004-3

40170181