Comparison Between 18F-FDG PET Image-Derived Indices for Early Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer.

Mathieu Hatt (1) , David Groheux (2) , Antoine Martineau (2) , Marc Espié (3) , Elif Hindié (4) , Sylvie Giacchetti (5, 6) , Anne de Roquancourt (7) , Dimitris Visvikis (8) , Catherine Cheze Le Rest (8, 9)

1 LaTIM - Laboratoire de Traitement de l'Information Medicale
2 Département de médecine nucléaire
3 Centre des maladies du sein
4 Département de médecine nucléaire
5 Rythmes Biologiques et Cancers
6 Service d'anatomie pathologique
7 Departement de pathologie
8 Optimisation Continue des Actions Thérapeutiques par l'Intégration d'Informations Multimodales
9 Département de médecine nucléaire

The goal of this study was to determine the best predictive factor among image-derived parameters extracted from sequential F-FDG PET scans for early tumor response prediction after 2 cycles of neoadjuvant chemotherapy in breast cancer. METHODS: 51 breast cancer patients were included. Responder and nonresponder status was determined by histopathologic examination according to the tumor and node Sataloff scale. PET indices (maximum and mean standardized uptake value [SUV], metabolically active tumor volume, and total lesion glycolysis [TLG]), at baseline and their variation (Δ) after 2 cycles of neoadjuvant chemotherapy were extracted from the PET images. Their predictive value was investigated using Mann-Whitney U tests and receiver-operating-characteristic analysis. Subgroup analysis was also performed by considering estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative, triple-negative, and HER2-positive tumors separately. The impact of partial-volume correction was also investigated using an iterative deconvolution algorithm. RESULTS: There were 24 pathologic nonresponders and 27 responders. None of the baseline PET parameters was correlated with response. After 2 neoadjuvant chemotherapy cycles, the reduction of each parameter was significantly associated with response, the best prediction of response being obtained with ΔTLG (96% sensitivity, 92% specificity, and 94% accuracy), which had a significantly higher area under the curve (0.91 vs. 0.82, P = 0.01) than did ΔSUV (63% sensitivity, 92% specificity, and 77% accuracy). Subgroup analysis confirmed a significantly higher accuracy for ΔTLG than ΔSUV for ER-positive/HER-negative but not for triple-negative and HER2-positive tumors. Partial-volume correction had no impact on the predictive value of any of the PET image-derived parameters despite significant changes in their absolute values. CONCLUSION: Our results suggest that the reduction after 2 neoadjuvant chemotherapy cycles of the metabolically active volume of primary tumor measurements such as ΔTLG predicts histopathologic tumor response with higher accuracy than does ΔSUV measurements, especially for ER-positive/HER2-negative breast cancer. These results should be confirmed in a larger group of patients as they may potentially increase the clinical value and efficiency of F-FDG PET for early prediction of response to neoadjuvant chemotherapy.

Mots clés: Breast cancer; Neoadjuvant chemotherapy; 18F-FDG; tumor delineation; pathological response

Domaines: Cancer; Imagerie médicale

Mathieu Hatt, David Groheux, Antoine Martineau, Marc Espié, Elif Hindié, et al.. Comparison Between 18F-FDG PET Image-Derived Indices for Early Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer.. Journal of Nuclear Medicine, 2013, 54 (3), pp.341-9. ⟨10.2967/jnumed.112.108837⟩. ⟨hal-00748923⟩