Multiparametric MRI-based radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer.
Diffusion-weighted imaging
Dynamic contrast-enhanced breast MRI
Neoadjuvant systemic therapy
Radiomic features
Treatment response
Triple-negative breast cancer
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
12 Jul 2024
12 Jul 2024
Historique:
received:
26
07
2023
accepted:
28
06
2024
medline:
12
7
2024
pubmed:
12
7
2024
entrez:
11
7
2024
Statut:
epublish
Résumé
Triple-negative breast cancer (TNBC) is often treated with neoadjuvant systemic therapy (NAST). We investigated if radiomic models based on multiparametric Magnetic Resonance Imaging (MRI) obtained early during NAST predict pathologic complete response (pCR). We included 163 patients with stage I-III TNBC with multiparametric MRI at baseline and after 2 (C2) and 4 cycles of NAST. Seventy-eight patients (48%) had pCR, and 85 (52%) had non-pCR. Thirty-six multivariate models combining radiomic features from dynamic contrast-enhanced MRI and diffusion-weighted imaging had an area under the receiver operating characteristics curve (AUC) > 0.7. The top-performing model combined 35 radiomic features of relative difference between C2 and baseline; had an AUC = 0.905 in the training and AUC = 0.802 in the testing set. There was high inter-reader agreement and very similar AUC values of the pCR prediction models for the 2 readers. Our data supports multiparametric MRI-based radiomic models for early prediction of NAST response in TNBC.
Identifiants
pubmed: 38992094
doi: 10.1038/s41598-024-66220-9
pii: 10.1038/s41598-024-66220-9
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
16073Informations de copyright
© 2024. The Author(s).
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