A Phase II Study of 3'-Deoxy-3'-18F-Fluorothymidine PET in the Assessment of Early Response of Breast Cancer to Neoadjuvant Chemotherapy: Results from ACRIN 6688

Lale Kostakoglu, Fenghai Duan, Michael O Idowu, Paul R Jolles, Harry D Bear, Mark Muzi, Jean Cormack, John P Muzi, Daniel A Pryma, Jennifer M Specht, Linda Hovanessian-Larsen, John Miliziano, Sharon Mallett, Anthony F Shields, David A Mankoff, ACRIN 668 Investigative Team, Lale Kostakoglu, Fenghai Duan, Michael O Idowu, Paul R Jolles, Harry D Bear, Mark Muzi, Jean Cormack, John P Muzi, Daniel A Pryma, Jennifer M Specht, Linda Hovanessian-Larsen, John Miliziano, Sharon Mallett, Anthony F Shields, David A Mankoff, ACRIN 668 Investigative Team

Abstract

Our objective was to determine whether early change in standardized uptake values (SUVs) of 3'deoxy-3'-(18)F-fluorothymidine ((18)F-FLT) using PET with CT could predict pathologic complete response (pCR) of primary breast cancer to neoadjuvant chemotherapy (NAC). The key secondary objective was to correlate SUV with the proliferation marker Ki-67 at baseline and after NAC.

Methods: This prospective, multicenter phase II study did not specify the therapeutic regimen, thus, NAC varied among centers. All evaluable patients underwent (18)F-FLT PET/CT at baseline (FLT1) and after 1 cycle of NAC (FLT2); 43 patients were imaged at FLT1, FLT2, and after NAC completion (FLT3). The percentage change in maximum SUV (%ΔSUVmax) between FLT1 and FLT2 and FLT3 was calculated for the primary tumors. The predictive value of ΔSUVmax for pCR was determined using receiver-operating-characteristic curve analysis. The correlation between SUVmax and Ki-67 was also assessed.

Results: Fifty-one of 90 recruited patients (median age, 54 y; stage IIA-IIIC) met the eligibility criteria for the primary objective analysis, with an additional 22 patients totaling 73 patients for secondary analyses. A pCR in the primary breast cancer was achieved in 9 of 51 patients. NAC resulted in a significant reduction in %SUVmax (mean Δ, 39%; 95% confidence interval, 31-46). There was a marginal difference in %ΔSUVmax_FLT1-FLT2 between pCR and no-pCR patient groups (Wilcoxon 1-sided P = 0.050). The area under the curve for ΔSUVmax in the prediction of pCR was 0.68 (90% confidence interval, 0.50-0.83; Delong 1-sided P = 0.05), with slightly better predictive value for percentage mean SUV (P = 0.02) and similar prediction for peak SUV (P = 0.04). There was a weak correlation with pretherapy SUVmax and Ki-67 (r = 0.29, P = 0.04), but the correlation between SUVmax and Ki-67 after completion of NAC was stronger (r = 0.68, P < 0.0001).

Conclusion: (18)F-FLT PET imaging of breast cancer after 1 cycle of NAC weakly predicted pCR in the setting of variable NAC regimens. Posttherapy (18)F-FLT uptake correlated with Ki-67 on surgical specimens. These results suggest some efficacy of (18)F-FLT as an indicator of early therapeutic response of breast cancer to NAC and support future multicenter studies to test (18)F-FLT PET in a more uniformly treated patient population.

Keywords: 18F-FLT PET; breast cancer; early treatment response; neoadjuvant therapy.

© 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Figures

FIGURE 1
FIGURE 1
18F-FLT PET/CT axial (upper) and coronal (lower) images demonstrate increased 18F-FLT uptake in an upper outer quarter breast tumor and axillary LN, before therapy (left) with substantial reduction in primary breast tumor 18F-FLT uptake after 1 cycle of NAC (middle) and resolution of 18F-FLT uptake after completion of NAC (right). Patient had pCR confirmed at surgery. Arrows refer to primary tumor site.
FIGURE 2
FIGURE 2
18F-FLT PET/CT axial (upper) and coronal (lower) images demonstrate increased 18F-FLT uptake in upper outer quarter breast tumor before therapy (left) with minimal decline in uptake and after 1 cycle of NAC (middle) and significant residual uptake after completion of NAC (right). At surgery, significant residual viable tumor was confirmed (i.e., no-pCR) with high Ki-67 index (62%). Arrows refer to primary tumor site.
FIGURE 3
FIGURE 3
ROC curve of using %ΔSUVmax_FLT1-FLT2 to predict pCR. Optimal cut point with corresponding specificity and sensitivity was identified through Youdan index.
FIGURE 4
FIGURE 4
ROC curve of using %ΔSUVmax_FLT1-FLT3 to predict pCR. Optimal cut point with corresponding specificity and sensitivity was identified through Youdan index.
FIGURE 5
FIGURE 5
Scatterplot for Ki-67 on biopsy specimens versus SUVmax at FLT1.
FIGURE 6
FIGURE 6
Scatterplot for Ki-67 on surgical specimens versus SUVmax at FLT3.

Source: PubMed

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