In the I-SPY 1 breast cancer clinical trial, change in size of the primary in-breast tumor in response to neoadjuvant therapy was a strong predictor of pathologic complete response. In this study, I-SPY 1 MRI lymph node characteristics was studied. Lymph nodes of patients who achieved pathologic complete response after chemotherapy had different characteristics from those who have residual disease in the tumor bed. The percent change of the signal enhancement ratio of each individual lymph node was the best parameter to differentiate between pathologic complete responders versus incomplete or non-responders.
Methods
The data was obtained from I-SPY 1 MRI of stage 2 and 3 breast cancer patients undergoing neoadjuvant therapy with anthracycline-cyclophosphamide alone or followed by taxane.1-4 The inclusion criteria were data with T2-weighted MRI and dynamic contrast-enhanced (DCE) data with adequate LN imaging, which included 28 patients: 10 “responders” and 18 “non-responders”. “Responders” was defined as patients achieving pCR and “non-responders” were patients who did not.
MR imaging included a DCE T1-weighted series performed on a 1.5T scanner. Pre- and post-chemotherapy DCE MRI was used to analyze LN volumes, post-contrast PE, and SER. The initial PE, defined as [(S1 − S0)/S0] · 100%, and SER, defined as (S1 − S0)/(S2 − S0), where S0, S1, and S2 represent the signal intensities on the pre-contrast, early post-contrast, and late post-contrast images, respectively. SER>1 is indicative of malignancy. Standard anatomical landmarks of the breast were used to identify the same LN pre- and post-chemotherapy. Based on the number of LNs visible on the pre-chemotherapy MRI, 1 to 6 LNs were contoured per patient. In total, 44 and 21 LNs were contoured for non-responders and responders, respectively.
Statistical analysis of MRI parameters was performed between responders and non-responders. Analysts performing MRI parameter analysis were blinded from clinical measures
The SERs of responders and non-responders were, respectively, 1.6±0.8 and 1.2±0.2 pre-chemotherapy, and 1.1±0.3 and 1.3±0.4 post-chemotherapy. The SER percent changes of pre- and post-chemotherapy were statistically different between responders and non-responders (−21±44% versus 3.5±44%, p=0.02). SER decreased markedly in responders (p<0.05), indicative of reduced malignancy, whereas SER did not change significantly in non-responders (p>0.05).
Volume percent changes pre- and post-chemotherapy were not significantly different between responders and non-responders (−60±35 versus −61±29, p>0.05). The PE percent changes was not significantly different between responders and non-responders (p>0.05).
The percent changes of primary breast tumor volume were statistically different between responders and non-responders (p<0.05). No correlations were found between primary breast tumor percent volume changes versus percent change in LN volume, PE, or SER.
Axillary LN characteristics provide valuable insight into cancer and prognosis. In addition to tumor debulking, neoadjuvant therapy increases the probability of pCR in the axilla.5 Consequently, structural and functional changes occur in the LNs over the course of treatment. In a previous study, metastatic LNs exhibited an early/peak enhancement within 3 minutes with a fast wash-out.6 In our study, chemotherapy responders were characterized by reductions in LN SER, while the LN SER of non-responders stayed the same. Of the 44 LNs analyzed from non-responders, 26 LNs had reductions in SER while 18 LNs had increases in SER. Furthermore, of the 18 non-responding subjects, 8 had a mix of LNs with increased and decreased SER. This highlights the heterogeneity of LN involvement. Responders had a much more uniform reduction in SER seen in 16 of 21 nodes.
Cancer affected LNs are usually larger and shrink as the cancer burden lessens. However, in our study, LN volume change pre- and post-chemotherapy was not significantly different between responders and non-responders. Overall, LN volume post-chemotherapy of responders (334±326) was significantly less than non-responders (593±650) (p<.05) but visualizing change of the volume within a single LN was not significantly predictive.
Limitations of this study include our small sample size, the absence of nodal status or LN histopathology, the possibility that not all LNs are positive or involved in the disease, our definition of responders as having pCR considering that metastasis could have occurred, and that more non-responders had adequately imaged LN regions compared to responders.
Conclusion
The LNs of patients who achieve a pCR after chemotherapy have different characteristics from those who have residual disease in the tumor bed. Specifically, the percent change of the SER of each individual LN was the best parameter to differentiate between patients who achieved pCR versus those who did not.1. Hylton NM, Blume JD, Bernreuter WK, et al. Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy--results from ACRIN 6657/I-SPY TRIAL. Radiology. 2012;263(3):663-672.
2. Multi-center breast DCE-MRI data and segmentations from patients in the I-SPY 1/ACRIN 6657 trials. 2016. http://doi.org/10.7937/K9/TCIA.2016.HdHpgJLK.
3. Hylton NM, Gatsonis CA, Rosen MA, et al. Neoadjuvant Chemotherapy for Breast Cancer: Functional Tumor Volume by MR Imaging Predicts Recurrence-free Survival-Results from the ACRIN 6657/CALGB 150007 I-SPY 1 TRIAL. Radiology. 2016;279(1):44-55.
4. Clark K, Vendt B, Smith K, et al. The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository. J Digit Imaging. 2013;26(6):1045-1057.
5. Steiman J, Soran A, McAuliffe P, et al. Predictive value of axillary nodal imaging by magnetic resonance imaging based on breast cancer subtype after neoadjuvant chemotherapy. J Surg Res. 2016;204(1):237-241.
6. He N, Xie C, Wei W, et al. A new, preoperative, MRI-based scoring system for diagnosing malignant axillary lymph nodes in women evaluated for breast cancer. European Journal of Radiology. 2012;81(10):2602-2612.