Purpose: Neoadjuvant endocrine therapy (NET) is increasingly used for patients with hormone receptor-positive (HR+) breast cancer. Dynamic contract-enhanced breast MRI is the most accurate modality to monitor tumor response during neoadjuvant chemotherapy (NAC)1, but there is limited research on response to NET.The Endocrine Optimization Protocol (EOP) is a sub-study of the ongoing I-SPY 2 TRIAL testing amcenestrant (an oral selective estrogen receptor degrader [SERD]), with or without addition of abemaciclib (a CDK4/6 inhibitor) or letrozole (an aromatase inhibitor) in patients with stage 2/3, MammaPrint (MP) low-risk (index 0 to 1) or high-risk 1 (index -0.57 to 0), HR+/HER2-negative breast cancer. All I-SPY2 (including EOP) patients undergo MRI at baseline (T0), 3 weeks (T1), 12 weeks (T2), and 6 months, prior to surgery (T3). Functional tumor volume (FTV)2,3 is derived as a quantitative measure of tumor burden from each MRI. A subset of EOP patients also have 3 dedicated breast PET (dbPET) exams with 18F-fluoroestradiol (an estrogen receptor-targeted tracer, FES) at T0, T1, and T3. FES uptake on dbPET indicates the presence of functional estrogen receptor.This study evaluates changes in FTV and FES uptake in patients receiving NET in the ongoing EOP trial. FTV changes in EOP were compared with those in a cohort of patients who received NAC in I-SPY 2.

Methods: The breast MRI and FES-dbPET images from patients in the EOP trial as of June 2022 were evaluated by a blinded central radiology team at a single institution. FTV was measured using standard procedure in I-SPY 2. Percent FTV change (ΔFTV) at Tn (n = 1, 2, or 3) was calculated by 100x(FTVTn-FTVT0)/FTVT0. FES uptake was quantified as standardized uptake value (SUV). Maximum SUV over the tumor volume (SUVmax) was measured using Osirix MD (Pixmeo SARL) and percent change (ΔSUVmax) was similarly defined. For comparison, FTV was evaluated using curated imaging data of I-SPY 2 patients with stage 2/3, MP high-risk 1, HR+/HER2-negative cancer who completed standard NAC between 2010–2016.

Results: We included 55 EOP patients (NET cohort) and 68 I-SPY 2 patients (NAC cohort). At T0, median FTV was 9.8cc for the NET cohort and 10.1cc for the NAC cohort. Table 1 shows the longitudinal FTV change in the two cohorts. At T1, median FTV change was similar in the NET cohort (-33.8%) and NAC cohort (-33.9%). The NET cohort showed a dynamic range of FTV change from -65.4% (1st quartile) to -11.0% (3rd quartile), which covered the 1st to 3rd quartile ranges for the NAC cohort. At T2 and T3, FTV change was more gradual in the NET cohort compared to the NAC cohort.Seven patients in the NET cohort underwent FES-dbPET. At T0, tumor FES uptake exceeded background uptake in all 7 patients with a median SUVmax of 8.2. At T1 and T3, tumor uptake decreased in all patients. Tumor uptake was indistinguishable from background for 3 patients (43%) at T1 and 5 patients (71%) at T3, despite evidence of residual tumor on MRI. The median change of SUVmax was -45.9% at T1 and -74.7% for T3 (Table 2).

Discussion: After 3 weeks of NET, we observed a large dynamic range of FTV change similar to that seen in NAC and a robust decrease in FES uptake. These results suggest the potential for combined use of early MRI change and FES-dbPET to provide scalable biomarkers to stratify response-based NET strategies.

References:

1. Radiology 285: 358–375, 2017

2. Radiology 263:663–672, 2012

3. Radiology 279:44–55, 2016