Accuracy of magnetic resonance imaging for predicting pathological complete response of breast cancer after neoadjuvant chemotherapy: association with breast cancer subtype
© Fukuda et al. 2016
Received: 19 November 2015
Accepted: 12 February 2016
Published: 24 February 2016
A pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) is a signature of favorable prognosis in breast cancer. The aim of this study was to assess the accuracy of magnetic resonance imaging (MRI) in predicting the pCR after NAC. 265 women with stage II or III breast cancer who underwent surgery after NAC were retrospectively investigated for MRI findings before and after the NAC. Correlation of pCR with an “imaging complete response” (iCR), defined as no detectable tumor on all serial images with dynamic contrast-enhanced T1-weighted imaging, was evaluated with respect to each tumor subtype. Of 265 cases, 44 (16.6 %) and 24 (9.1 %) were diagnosed as iCR and pCR, respectively. Nineteen of the 44 iCR cases (43.2 %) were assessed as pCR, and 216 (97.7 %) of the 221 non-iCR cases were assessed as non-pCR. The accuracy (ACC), the pCR predictive value (PPV) and the non-pCR predictive value (NPV) were 88.7, 43.2, and 97.7 %, respectively. When assessed according to each tumor subtype, the ACC, PPV and NPV were 93.2, 21.4 and 100 % for luminal subtype, 70.8, 0 and 89.5 % for luminal/HER2 subtype, 75, 57.1 and 88.8 % for HER2-enriched subtype, and 90.9, 72.7 and 97 % for triple-negative subtype, respectively. MRI is a valuable modality for predicting pCR of breast cancer after NAC treatment. However, its accuracy varies greatly in different breast cancer subtypes. Whereas MRI closely predicts pCR in the triple-negative subtype, iCR in the luminal subtype is often an over-estimation. On the other hand, residual lesions identified by MRI are reliable markers of non-pCR for the luminal subtype.
Neoadjuvant chemotherapy (NAC) is one of the recommended treatments for operable invasive breast cancer. Published clinical trials have shown that breast cancer patients with pathological complete responses (pCR) to NAC have significantly better prognosis than those without pCR (Wolmark et al. 2001; Van der Hage et al. 2001; Bear et al. 2006). Therefore, pCR is an important prognostic factor in breast cancer treated with NAC. Von Minckwitz et al. reported that the prognostic impact of pCR varied among tumor subtypes classified by their expression of hormone receptors (HRs) and human epidermal growth factor receptor 2 (ErbB2, hereinafter called HER2). Although pCR significantly correlates with favorable prognosis in triple-negative and HER2-enriched subtypes, it fails to predict the prognosis of luminal and luminal/HER2 subtypes (von Minckwitz et al. 2012).
Monitoring therapeutic responses to NAC, including early detection of progressive disease, is of pivotal importance in clinical practice. Physical examination, mammography, ultrasonography and magnetic resonance imaging (MRI) are widely used for the assessment of therapeutic effect.
MRI is a useful device to assess the size and extent of lesions in breast cancer. The size of the invasive component of the tumor estimated by MRI closely correlates with that determined pathologically. MRI is also capable of detecting small residual cancer nests after NAC (Partridge et al. 2002). Londero et al. reported that MRI could assess responses to NAC better than physical examination, mammography or ultrasonography (Londero et al. 2004). Ideally, if MRI were able to perfectly distinguish pCR from non-pCR, additional mastectomy would be avoided. The present study was conducted to determine the accuracy of MRI estimation of tumor regression in predicting pCR. We propose that assessments with respect to each tumor subtype would further enhance diagnostic accuracy.
A total of 2767 cases with primary breast cancer underwent surgery from January 2005 to December 2007 at the Cancer Institute Hospital of the Japanese Foundation for Cancer Research. During this period 402 patients were treated with NAC. Of these, 265 with stage II–III invasive breast cancer, no special type, where MRI had been performed before and after chemotherapy, were included in this study. In our hospital, breast cancer patients usually undergo MRI before treatment. MRI after NAC is performed preferentially in patients, where indications for breast-conserving therapy need to be assessed. We retrospectively investigated the relationship between pCR and imaging complete response (iCR) evaluated by MRI.
Chemotherapy regimen of NAC
Standard anticancer drugs including anthracycline and/or taxane were administered to all patients as NAC. Sixty five patients received an anthracycline-based combination regimen, 22 received only taxane and the remaining 178 were treated with the anthracycline-based combination regimen followed by taxane. The former involved 4–6 cycles of CAF (cyclophosphamide 500 mg/m2, adriamycin 50 mg/m2, fluorouracil 500 mg/m2, q3w), AC (adriamycin 60 mg/m2, cyclophosphamide 600 mg/m2, q3w), and CEF (cyclophosphamide 500 mg/m2, epirubicin 100 mg/m2, fluorouracil 500 mg/m2, q3w) therapy. The taxane regimens were 12 cycles of weekly paclitaxel at a dose of 80 mg/m2 or 4 cycles of tri-weekly docetaxel at a dose of 75 mg/m2. In Japan, postoperative administration of trastuzumab was approved for health insurance coverage in 2008. In the present study, none of the patients were administered trastuzumab preoperatively.
MRI examinations were performed using a 1.5T MRI unit (Signa HD, GE Health Care, Milwaukee, USA) and a commercially-available dedicated four-channel breast array coil. Patients underwent MRI in the prone position. Our imaging protocol included a localizing sequence followed by unilateral fast spin-echo T2-weighted coronal imaging (TR/TE, 4800/85 ms; echo train length 16, and matrix 384 × 224) with fat suppression by chemical shift-selective imaging sequences. Other parameters were as follows: field of view, 260 mm; section thickness, 3 mm and interslice gap, 0 mm. This examination was followed by combined dynamic contrast-enhanced unilateral coronal breast imaging. An enhanced T1-weighted examination 3D gradient echo sequence with fat suppression by spectral inversion recovery was performed before and after contrast material injection. The image parameters were as follows: TR/TE/FA, 3.6 ms/1.0 ms/15°; FOV, 26 × 26 cm; matrix, 320 × 240; section thickness, 3.0 mm; interslice gap, 0 mm and acquisition time, 60 s. A dynamic study in the coronal plane was performed before and 60, 120, 180 and 240 s after starting intravenous injection of 0.2 mmol/kg of gadodiamide hydrate (Omniscan®, Daiichi-Sankyo, Tokyo, Japan) at a rate of 3 mL/s, followed by a 20 mL saline flush at the rate of 3 mL/s.
iCR was defined as no enhanced tumor visible on any serial images of dynamic contrast-enhanced T1-weighted images. If dynamic MRI showed any amount of enhanced area, the case was diagnosed as non-iCR in this study. Non-iCR included “partial response”, “stable disease” and “progressive disease” according to the Response Evaluation Criteria in Solid Tumors (RECIST) Guidelines.
Pathological examination of surgical specimens
Detailed evaluation of surgical specimens was carried out. Partial mastectomy specimens were cut into 5 mm thick serial sections and formalin-fixed paraffin blocks were made from the all sections. The all blocks cut into thin slices and were examined microscopically. In total mastectomy specimens, the location of the tumor bed was firstly identified from the clinical information and gross observation of the cut surfaces. Next, many tissue blocks broadly distributed around the tumor bed were sampled and microscopically examined.
pCR was defined as no invasive cancer cells in any slices of the resected breast specimen. pCR was allowed for in situ carcinoma and for positive lymph nodes.
Subtype classification by HR and HER2 status
Tumors were classified into four subtypes based on the two HRs, the estrogen receptor (ER) and the progesterone receptor (PgR), and HER2. The status of these biomarkers was estimated using biopsy samples obtained before chemotherapy. Immunohistochemical staining for ER and PgR was performed using antibody clone 1D5 for ER and for clone PgR636 for PgR (both Dako Japan Inc., Tokyo). Positive reactions for ER and PgR were defined as nuclear staining in ≥10 % of cancer cells, and negative reactions were defined as staining in <10 %. HR-positivity was defined as positivity for ER and/or PgR. Immunohistochemical staining for HER2 was performed using the Hercep Test (Dako Japan Inc.). Expression of HER2 protein was classified into 4 strata, i.e., 0, 1+, 2+ and 3+. In the 2+ cases, HER2 genetic testing by fluorescence in situ hybridization (FISH) was performed using the PathVysion HER2-DNA Probe Kit (Abbott Molecular Inc., Des Plaines, USA). Both protein and genetic status were estimated based on the guidelines for HER2 testing in breast cancer, as recommended by the American Society of Clinical Oncology/College of American Pathologists (Wolff et al. 2013). HER2 positivity was defined as HER2 protein 3+ or HER2 gene amplification. Subtype definitions were as follows: luminal subtype, HR-positive and HER2-negative; luminal/HER2 subtype, HR-positive and HER2-positive; HER2-enriched subtype, HR-negative and HER2-positive; and triple-negative subtype, HR-negative and HER2-negative.
Statistical analysis was performed using SPSS statistics Ver17.0 (IBM Japan Inc., Tokyo, Japan). The Fisher’s exact test was used to compare iCR and pCR. P < 0.05 was taken to indicate statistical significance in all instances.
Informed consent for the use of specimens was obtained preoperatively from all patients participating in this study, which was approved by the Institutional Review Board of the authors’ institution and was disclosed information.
All patients studied were female with a mean age at the beginning of treatment of 49.9 years (range 25–78). Tumors were at Stage II (172 cases) or Stage III (93 cases) with a tumor size >2 cm (T2, 172 cases, 64.9 %; T3, 38 cases, 14.3 %; T4, 38 cases, 14.3 %) or/and positive for lymph node metastasis (199 cases, 75 %). The latter included seventeen cases of T1 with positive lymph node metastasis (6.4 %). Total mastectomy was performed on 165 patients (62.3 %) with the remaining 100 undergoing partial mastectomy (37.7 %). ER, PgR and HER2 were positive in 70.6, 46.4 and 21.1 % of cases, respectively. Data on at least one of the biomarkers were missing for 4 patients’ biopsies from other hospitals. Regarding subtype criteria combining HR and HER2, 161 cases were classified as luminal subtype (60.8 %), 24 were luminal/HER2 (9.1 %), 32 were HER2-enriched (12.1 %) and the remaining 44 were triple-negative (16.6 %).
Comparison of iCR with pCR in the whole patient cohort
Comparison between iCR and pCR
All patients (n = 265)
Luminal subtype (n = 161)
Luminal/HER2 subtype (n = 24)
HER2-enriched subtype (n = 32)
Triple-negative subtype (n = 44)
Sensitivity, specificity, ACC, PPV and NPV in each tumor subtype
All patients (n = 265)
Luminal subtype (n = 161)
Luminal/HER2 subtype (n = 24)
HER2-enriched subtype (n = 32)
Triple-negative subtype (n = 44)
Comparison of iCR and pCR with respect to subtype classification
Proportions of patients with iCR in each subtype were as follows: 8.7 % (14/161) luminal, 20.8 % (5/24) luminal/HER2, 43.8 % (14/32) HER2-enriched and 25.0 % (11/44) triple-negative. In contrast, proportions of patients with pCR in each subtype were 1.9 % (3/161) for luminal, 8.3 % (2/24) luminal/HER2, 31.3 % (10/32) HER2-enriched and 20.5 % (9/44) triple-negative. Statistically significant correlations between iCR and pCR were present for luminal (P = 0.001), HER2-enriched (P = 0.008) and triple-negative (P < 0.001) subtypes, but not for the luminal/HER2 subtype (P = 1.000) (Table 1).
The sensitivity, specificity, ACC, PPV and NPV for correlations of iCR with pCR with respect to each subtype are shown in Table 2. For the luminal subtype, the NPV was 100 %, with a perfect concordance for all 147 patients with non-iCR pathologically diagnosed as non-pCR. However, only 3 of 14 iCR cases were indeed pCR, indicating a low PPV of 21.4 %. Although the sensitivity (100 %), specificity (93.0 %) and the ACC (93.2 %) were very high, these rely on the high NPV and small proportion of pCR. In contrast to luminal subtype, the PPV for the triple-negative subtype was 72.7 %, the highest score among all the subtypes, with 8 of 11 iCR cases being pCR. Sensitivity (88.9 %), specificity (91.4 %), ACC (90.9 %) and NPV (97 %) were also significantly higher for the triple-negative subtype, suggesting that MRI is a valuable modality to predict pCR for this subtype. For the HER2-enriched subtype, sensitivity (80.0 %), specificity (72.7 %), ACC (75.0 %), PPV (57.1 %) and NPV (88.9 %) were reasonably high. On the other hand, sensitivity (0 %), specificity (77.3 %), ACC (70.8 %), PPV (0 %) and NPV (89.5 %) were relatively low for the luminal/HER2 subtype.
An example of a case diagnosed as both iCR and pCR
Analysis of cases diagnosed as iCR but non-pCR
Analysis of cases diagnosed as non-iCR but with pCR
In the present study, we investigated the accuracy of MRI for predicting pCR of breast cancer after NAC, especially focusing on its value in respect to each tumor subtype. When all cases were considered together, the iCR results were found to correlate significantly with pCR. These results are consistent with previously reported data (Straver et al. 2010; Yuan et al. 2010; McGuire et al. 2011; Hayashi et al. 2013). However, the degree of accuracy was found to differ markedly according to the tumor subtype considered. For the luminal subtype, whereas NPV was high, PPV was considerably low. This suggests that remnant lesions identified by MRI are reliable markers of non-pCR for the luminal subtype, i.e., MRI is effective for predicting non-pCR after NAC; however, iCR diagnosed by MRI in the luminal subtype is mostly an over-estimation. On the other hand, MRI accurately predicted pCR in the triple-negative subtype with a high degree of sensitivity, specificity, ACC, PPV and NPV compared to the other subtypes. These results are consistent with previous reports (Straver et al. 2010; Yuan et al. 2010; McGuire et al. 2011; Hayashi et al. 2013; Chen et al. 2014; De Los et al. 2011; Loo et al. 2011). Although a larger cohort would be required before drawing definitive conclusions, especially for the luminal and luminal/HER2 subtypes, which comprised only a small number of pCR cases, our data suggest that the overall accuracy of prediction by MRI for pCR can be enhanced by subgroup analyses. The relationship between the accuracy of MRI and subtype classification may be caused by the following points. The pCR rate of the triple-negative subtype was higher than the luminal subtype. MRI for predicting pCR is generally more accurate in tumors that have a better response. It is also known that the ER-negative tumor have higher contrast uptake on MRI after NAC than ER-positive tumor (Chen et al. 2014). In the triple-negative subtype, the high contrast uptake may result the high accuracy of MRI diagnosis.
In the present study, cases with results discordant between iCR and pCR were carefully analyzed for pathological findings. MRI diagnosed 25 cases of non-pCR as iCR. There likely to be at least two different reasons for this misdiagnosis. For HER2-enriched and triple-negative subtypes, the small volume of the residual cancer cells, often present with a scattered distribution pattern, could be responsible for their evading detection by MRI. In the cases of luminal subtype, MRI may fail to detect tumors with low nuclear grade despite a relatively large tumor size. The proportion of non-pCR in the iCR group was disturbingly high in this subtype, despite the majority of the cases having relatively large tumors and showing slight therapeutic responses. These cases all had low nuclear grade tumors. Reciprocally, MRI diagnosed five cases of pCR as non-iCR. These five shared the common findings of fibrosis and granulation occupying the tumor bed of the surgical specimen. Because the fibrous granulation tissue contained numerous small vessels and inflammatory cells, it is most likely that these NAC-responsive structures mimicked the remnant tumor in the MRI findings (Woodhams et al. 2010).
In conclusion, subgroup analysis with respect to each tumor subtype enhances the accuracy of MRI for predicting pCR after NAC treatment of breast cancer. It is an especially valuable technique for the prediction of pCR in triple-negative breast cancer. Now, we are planning a study which confirms this result with lager patients.
All authors contributed to this work. TF and RH designed it and collected and analyzed the data. They wrote the manuscript. NG and YM assessed the MRI findings. FA diagnosed histological materials. ST and YI administered NAC treatment. TI and SO supervised this study. All authors discussed the results and implications. All authors read and approved the final manuscript.
We thank Dr. Tomohiko Ohta for critical advice and assistance in manuscript preparation.
The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
- Bear HD, Anderson S, Smith RE, Geyer CE Jr, Mamounas EP, Fisher B et al (2006) Sequential preoperative or postoperative docetaxel added to preoperative doxorubicin plus cyclophosphamide for operable breast cancer: National Surgical Adjuvant Breast and Bowel Project Protocol B-27. J Clin Oncol 24:2019–2027View ArticleGoogle Scholar
- Chen JH, Bahri S, Mehta RS, Carpenter PM, McLaren CE, Chen WP et al (2014) Impact of factors affecting the residual tumor size diagnosed by MRI following neoadjuvant chemotherapy in comparison to pathology. J Surg Oncol 109(2):158–167View ArticleGoogle Scholar
- De Los Santos J, Bernreuter W, Keene K, Krontiras H, Carpenter J, Bland K et al (2011) Accuracy of breast magnetic resonance imaging in predicting pathologic response in patients treated with neoadjuvant chemotherapy. Clin Breast Cancer 11(5):312–319View ArticleGoogle Scholar
- Hayashi Y, Takei H, Nozu S, Tochigi Y, Ichikawa A, Kobayashi N et al (2013) Analysis of complete response by MRI following neoadjuvant chemotherapy predicts pathological tumor responses differently for molecular subtypes of breast cancer. Oncol Lett 5(1):83–89Google Scholar
- Kurosumi M, Akashi-Tanaka S, Akiyama F, Komoike Y, Mukai H, Nakamura S et al (2008) Histological criteria for assessment of therapeutic response in breast cancer (2007 version). Breast Cancer 15(1):5–7View ArticleGoogle Scholar
- Londero V, Bazzocchi M, Del Frate C, Puglisi F, Francescutti G, Zuiani C (2004) Locally advanced breast cancer: comparison of mammography, sonography and MR imaging in evaluation of residual disease in women receiving neoadjuvant chemotherapy. Eur Radiol 14:1371–1379View ArticleGoogle Scholar
- Loo CE, Straver ME, Rodenhuis S, Muller SH, Wesseling J, Vrancken Peeters MJ et al (2011) Magnetic resonance imaging response monitoring of breast cancer during neoadjuvant chemotherapy: relevance of breast cancer subtype. J Clin Oncol 29(6):660–666View ArticleGoogle Scholar
- McGuire KP, Topo-Burguete J, Dang H, Young J, Soran A, Zuley M et al (2011) MRI staging after neoadjuvant chemotherapy for breast cancer: does tumor biology affect accuracy? Ann Surg Oncol 18(11):3149–3154View ArticleGoogle Scholar
- Partridge SC, Gibbs JE, Lu Y, Esserman LJ, Sudilovsky D, Hylton NM (2002) Accuracy of MR imaging for revealing residual breast cancer in patients who have undergone neoadjuvant chemotherapy. AJR Am J Roentgenol 179:1193–1199View ArticleGoogle Scholar
- Straver ME, Loo CE, Rutgers EJ, Oldenburg HS, Wesseling J, Vranchen Peeters MJ et al (2010) MRI-model to guide the surgical treatment in breast cancer patients after neoadjuvant chemotherapy. Ann Surg 251(4):701–707View ArticleGoogle Scholar
- Van der Hage JA, van de Velde CJ, Julien JP, Tubiana-Hulin M, Vandervelden C, Duchateau L (2001) Preoperative chemotherapy in primary operable breast cancer: results from the European Organization for Research and Treatment of Cancer trial 10902. J Clin Oncol 19:4224–4237Google Scholar
- von Minckwitz G, Untch M, Blohmer JU, Costa SD, Eidtmann H, Fasching PA et al (2012) Definition and impact of pathologic complete response on prognosis after neoadjuvant chemotherapy in various intrinsic breast cancer subtypes. J Clin Oncol 15:1796–1804View ArticleGoogle Scholar
- Wolff AC, Hammond ME, Hicks DG, Dowsett M, McShane LM, Allison KH et al (2013) Recommendation for human epidermal growth factor receptor 2 testing in breast cancer. American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update. J Clin Oncol 31:3997–4013View ArticleGoogle Scholar
- Wolmark N, Wang J, Mamounas E, Bryant J, Fisher B (2001) Preoperative chemotherapy in patients with operable breast cancer: nine-year results from National Surgical Adjuvant Breast and Bowel Project B-18. J Natl Cancer Inst Monogr 30:96–102View ArticleGoogle Scholar
- Woodhams R, Kakita S, Hata H, Iwabuchi K, Kuranami M, Gautam S et al (2010) Identification of residual breast carcinoma following neoadjuvant chemotherapy: diffusion-weighted imaging—comparison with contrast-enhanced MR imaging and pathological findings. Radiology 254(2):357–366View ArticleGoogle Scholar
- Yuan Y, Chen XS, Liu SY, Shen KW (2010) Accuracy of MRI in prediction of pathologic complete remission in breast cancer after preoperative therapy: a meta-analysis. Am J Roentgenol 195(1):260–268View ArticleGoogle Scholar