Work

18F-FDG PET/CT for early prediction of pathological complete response in breast cancer neoadjuvant therapy: a retrospective analysis

Year: 2024
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Neoadjuvant treatment has been developed as a systematic approach for patients with early breast cancer and has resulted in improved breast-conserving rate and survival. However, identifying treatment-sensitive patients at the early phase of therapy remains a problem, hampering disease management and raising the possibility of disease progression during treatment. METHODS: In this retrospective analysis, we collected 2-deoxy-2-[F-18] fluoro-d-glucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) images of primary tumor sites and axillary areas and reciprocal clinical pathological data from 121 patients who underwent neoadjuvant treatment and surgery in our center. The univariate and multivariate logistic regression analyses were performed to investigate features associated with pathological complete response (pCR). An 18F-FDG PET/CT-based prediction model was trained, and the performance was evaluated by receiver operating characteristic curves (ROC). RESULTS: The maximum standard uptake values (SUVmax) of 18F-FDG PET/CT were a powerful indicator of tumor status. The SUVmax values of axillary areas were closely related to metastatic lymph node counts (R = 0.62). Moreover, the early SUVmax reduction rates (between baseline and second cycle of neoadjuvant treatment) were statistically different between pCR and non-pCR patients. The early SUVmax reduction rates-based model showed great ability to predict pCR (AUC = 0.89), with all molecular subtypes (HR+HER2-, HR+HER2+, HR-HER2+, and HR-HER2-) considered. CONCLUSION: Our research proved that the SUVmax reduction rate of 18F-FDG PET/CT contributed to the early prediction of pCR, providing rationales for utilizing PET/CT in NAT in the future.
Language: English
Field: Medicine
Open Access status: gold
Estimated APC paid: $4,045
OpenAlex ID: W4400968074
FWCI: 3.057
Cites: 33
Cited by: 12
Related to: 10