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Baseline [18F]FDG PET/CT and MRI first-order breast tumor features do not improve pathological complete response prediction to neoadjuvant chemotherapy.
Oliveira, Carla; Oliveira, Francisco; Constantino, Cláudia; Alves, Celeste; Brito, Maria José; Cardoso, Fátima; Costa, Durval C.
Afiliación
  • Oliveira C; Nuclear Medicine-Radiopharmacology, Champalimaud Clinical Centre/Champalimaud Foundation, Lisbon, Portugal. carla.oliveira@fundacaochampalimaud.pt.
  • Oliveira F; Nuclear Medicine-Radiopharmacology, Champalimaud Clinical Centre/Champalimaud Foundation, Lisbon, Portugal.
  • Constantino C; Nuclear Medicine-Radiopharmacology, Champalimaud Clinical Centre/Champalimaud Foundation, Lisbon, Portugal.
  • Alves C; Breast Unit, Champalimaud Clinical Centre/Champalimaud Foundation, Lisbon, Portugal.
  • Brito MJ; Breast Unit, Champalimaud Clinical Centre/Champalimaud Foundation, Lisbon, Portugal.
  • Cardoso F; Pathology Department, Champalimaud Clinical Centre/Champalimaud Foundation, Lisbon, Portugal.
  • Costa DC; Breast Unit, Champalimaud Clinical Centre/Champalimaud Foundation, Lisbon, Portugal.
Article en En | MEDLINE | ID: mdl-38922396
ABSTRACT

PURPOSE:

To verify the ability of pretreatment [18F]FDG PET/CT and T1-weighed dynamic contrast-enhanced MRI to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients.

METHODS:

This retrospective study includes patients with BC of no special type submitted to baseline [18F]FDG PET/CT, NAC and surgery. [18F]FDG PET-based features reflecting intensity and heterogeneity of tracer uptake were extracted from the primary BC and suspicious axillary lymph nodes (ALN), for comparative analysis related to NAC response (pCR vs. non-pCR). Multivariate logistic regression was performed for response prediction combining the breast tumor-extracted PET-based features and clinicopathological features. A subanalysis was performed in a patients' subsample by adding breast tumor-extracted first-order MRI-based features to the multivariate logistic regression.

RESULTS:

A total of 170 tumors from 168 patients were included. pCR was observed in 60/170 tumors (20/107 luminal B-like, 25/45 triple-negative and 15/18 HER2-enriched surrogate molecular subtypes). Higher intensity and higher heterogeneity of [18F]FDG uptake in the primary BC were associated with NAC response in HER2-negative tumors (immunohistochemistry score 0, 1 + or 2 + non-amplified by in situ hybridization). Also, higher intensity of tracer uptake was observed in ALN in the pCR group among HER2-negative tumors. No [18F]FDG PET-based features were associated with pCR in the other subgroup analyses. A subsample of 103 tumors was also submitted to extraction of MRI-based features. When combined with clinicopathological features, neither [18F]FDG PET nor MRI-based features had additional value for pCR prediction. The only significant predictors were estrogen receptor status, HER2 expression and grade.

CONCLUSION:

Pretreatment [18F]FDG PET-based features from primary BC and ALN are not associated with response to NAC, except in HER2-negative tumors. As compared with pathological features, no breast tumor-extracted PET or MRI-based feature improved response prediction.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Eur J Nucl Med Mol Imaging Asunto de la revista: MEDICINA NUCLEAR Año: 2024 Tipo del documento: Article País de afiliación: Portugal

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Eur J Nucl Med Mol Imaging Asunto de la revista: MEDICINA NUCLEAR Año: 2024 Tipo del documento: Article País de afiliación: Portugal