Background: Strong background parenchymal enhancement (BPE) may cause overestimation in tumor volume measured from dynamic contrast-enhanced (DCE) MRI, which may adversely affect the ability of MR tumor volume to predict treatment outcome for patients undergoing neoadjuvant chemotherapy (NAC). Specifically, an overestimation of tumor volume can result in misclassification of patients with complete pathologic response (pCR) as non-responders, leading to less confidence in MRI prediction. As well, overestimation of extent of disease might lead to more aggressive surgical therapy than necessary. This study investigated whether high BPE in the contralateral breast influences the predictive performance of MRI-measured functional tumor volume (FTV) for patients with locally advanced breast cancer undergoing NAC.

Methods: patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Each patient had 4 MRI exams: pre-NAC (T0), after 3 weeks of NAC (T1), between NAC regimens (T2), and post-NAC (T3). FTV was calculated at each MRI exam by summing voxels meeting enhancement thresholds. Background parenchymal enhancement (BPE) in the contralateral breast was calculated automatically as mean percentage enhancement on the early (nominal 150sec post-contrast) image in the fibroglandular tissue segmented from 5 continuous axial slices centered in the inferior-to-superior stack. For each treatment time point, patients having both FTV and BPE measurements were included in the analysis. The area under the ROC curve (AUC) was estimated as the association between FTV and pCR at T1, T2, and T3. The analysis was conducted in the full patient cohort and in sub-cohorts defined by hormone receptor (HR) and HER2 status. In each patient cohort, a cut-off BPE value was selected to classify patients with high vs. low BPE by testing AUCs estimated with low-BPE patients reached maximum when the cut-off value varied from median to maximum in steps of 10%.

Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Table 1 shows the number of patients, pCR rate, and AUC of FTV for predicting pCR using all patients available vs. a subset patients with low BPE (< BPE cut-off). In the full cohort, AUC increased slightly across all time points after patients with high BPE were removed. In the HR+/HER2- subtype, AUC increased at T1 after removal of cases with high BPE (0.65 vs. 0.71). For HR-/HER2+, AUC increased substantially after removal of high BPE cases (0.65 to 0.86 at T1, 0.71 to 0.87 at T2, and 0.71 to 0.89 at T3), with greater improvement at the early time point (T1) compared to later time points (T2 and T3). Only a slight improvement in the AUC was observed in the HR+/HER2+ and HR-/HER2- subtypes across all time points.

Conclusions: High background parenchymal enhancement adversely affected the predictive performance of functional tumor volume measured by DCE-MRI, at early treatment time point for HR+/HER2- and across all time points for HR-/HER2+ cancer subtype. The adverse effect might be offset using subtype-optimized enhancement threshold in calculating functional tumor volume.

Table 1 Effect of BPE on the prediction of pCR using FTV at various treatment time points

T1T2T3
npCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offnpCR rateAUCBPE cut-off
Full All 647 34% 0.66 27 623 34% 0.70 17 611 34% 0.69 25 
 Subset 453 34% 0.68  311 33% 0.72  305 34% 0.72  
HR+/HER2- All 262 18% 0.65 19 249 18% 0.71 82 255 18% 0.75 19 
 Subset 131 18% 0.71  248 18% 0.71  204 19% 0.76  
HR+/HER2+ All 106 36% 0.64 21 105 38% 0.62 26 96 34% 0.71 20 
 Subset 53 32% 0.66  84 38% 0.66  57 40% 0.73  
HR-/HER2+ All 51 75% 0.65 20 47 74% 0.71 20 49 73% 0.71 16 
 Subset 30 73% 0.86  28 71% 0.87  24 75% 0.89  
HR-/HER2- All 228 42% 0.68 28 222 43% 0.75 18 211 43% 0.69 16 
 Subset 159 40% 0.71  111 37% 0.78  105 40% 0.75  
T1T2T3
npCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offnpCR rateAUCBPE cut-off
Full All 647 34% 0.66 27 623 34% 0.70 17 611 34% 0.69 25 
 Subset 453 34% 0.68  311 33% 0.72  305 34% 0.72  
HR+/HER2- All 262 18% 0.65 19 249 18% 0.71 82 255 18% 0.75 19 
 Subset 131 18% 0.71  248 18% 0.71  204 19% 0.76  
HR+/HER2+ All 106 36% 0.64 21 105 38% 0.62 26 96 34% 0.71 20 
 Subset 53 32% 0.66  84 38% 0.66  57 40% 0.73  
HR-/HER2+ All 51 75% 0.65 20 47 74% 0.71 20 49 73% 0.71 16 
 Subset 30 73% 0.86  28 71% 0.87  24 75% 0.89  
HR-/HER2- All 228 42% 0.68 28 222 43% 0.75 18 211 43% 0.69 16 
 Subset 159 40% 0.71  111 37% 0.78  105 40% 0.75  
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Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Roy Harnish, Ella F Jones, Lisa J Wilmes, Jessica Gibbs, Elissa Price, Bonnie N Joe, A. Jo Chien, Donald A Berry, Judy C Boughey, Kathy S Albain, Amy S Clark, Kirsten K Edmiston, Anthony D Elias, Erin D Ellis, David M Euhus, Heather S Han, Claudine Isaacs, Qamar J Khan, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Christina Yau, Smita M Asare, Angela DeMichele, Sally Goudreau, Hiroyuki Abe, Deepa Sheth, Dulcy Wolverton, Kelly Fountain, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Theresa Kuritza, Kevin Morley, Michael Nelson, An Church, Bethany Niell, Jennifer Drukteinis, Karen Y Oh, Neda Jafarian, Kathy Brandt, Sadia Choudhery, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Mohammad Eghedari, Pulin Sheth, Linda Hovanessian-Larsen, Mark Rosen, Elizabeth S McDonald, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Laura J Esserman, Nola M Hylton. The effect of background parenchymal enhancement on the predictive performance of functional tumor volume measured in MRI [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-02-01.

©2020 American Association for Cancer Research.
2020
American Association for Cancer Research.