Accuracy of MRI in predicting pathologic complete response after neoadjuvant chemotherapy in breast cancer_CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Authors：

ZHANG Jing ¹ , SONG Jun ² ,  XU Weiyun ¹ , ZHANG Xiaohong ¹ , ZHAO Lijuan ¹

1. Department of Breast Surgery, Mianyang Central Hospital, Mianyang, Sichuan 621000, P. R. China;
2. Department of Radiology, Mianyang Central Hospital, Mianyang, Sichuan 621000, P. R. China;

Corresponding?author：

XU Weiyun, Email: 33199823@qq.com

Keywords：

breast cancer; magnetic resonance imaging; neoadjuvant chemotherapy; pathological complete response

DOI：

10.7507/1007-9424.201909006

Video：

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Objective To observe the accuracy of magnetic resonance imaging (MRI) for predicting pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer, and to analyze the cause of the prediction error.Methods Data from 157 breast cancer patients who underwent NAC before surgery in Mianyang Central Hospital from January 2017 to January 2019 were analyzed. MRI parameters before and after NAC and pCR conditions were collected to analyze the parameters that produced false positives and false negatives.Results Of the 157 patients, 37 (23.6%) achieved pCR after NAC, and 33 (21.0%) achieved radiation complete remission (rCR) after NAC. The accuracy of MRI prediction was 70.7% (111/157), the sensitivity was 82.5% (99/120), and the specificity was 32.4% (12/37). A total of 25 cases did not achieve rCR, but postoperative evaluation achieved pCR (false positive), 21 cases achieved rCR, but postoperative evaluation did not achieve pCR (false negative). Diameter of tumor, peritumoral oedema, and background parenchymal enhancement were associated with MRI false positive prediction (P<0.05); gland density and tumor rim enhancement were associated with MRI false negative prediction (P<0.05).Conclusion MRI can be used as an important method to predict pCR after NAC in breast cancer patients, and its accuracy may be related to diameter of tumor, peritumoral oedema, background parenchymal enhancement, gland density, and tumor rim enhancement.

Citation： ZHANG Jing, SONG Jun, XU Weiyun, ZHANG Xiaohong, ZHAO Lijuan. Accuracy of MRI in predicting pathologic complete response after neoadjuvant chemotherapy in breast cancer. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2020, 27(8): 975-979. doi: 10.7507/1007-9424.201909006 Copy

1.	Holmes D, Colfry A, Czerniecki B, et al. Performance and practice guideline for the use of neoadjuvant systemic therapy in the management of breast cancer. Ann Surg Oncol, 2015, 22(10): 3184-3190.
2.	Hortobagyi GN. Definition and impact of pathologic complete response on prognosis after neoadjuvant chemotherapy in various intrinsic breast cancer subtypes. Breast Diseases: A Year Book Quarterly, 2012, 23(4): 374-375.
3.	Heil J, Schaefgen B, Sinn P, et al. Can a pathological complete response of breast cancer after neoadjuvant chemotherapy be diagnosed by minimal invasive biopsy? Eur J Cancer, 2016, 69: 142-150.
4.	Fukuda T, Horii R, Gomi N, et al. Accuracy of magnetic resonance imaging for predicting pathological complete response of breast cancer after neoadjuvant chemotherapy: association with breast cancer subtype. Springerplus, 2016, 5: 152.
5.	Panda SK, Goel A, Nayak V, et al. Can preoperative ultrasonography and MRI replace sentinel lymph node biopsy in management of axilla in early breast cancer-a prospective study from a Tertiary Cancer Center. Indian J Surg Oncol, 2019, 10(3): 483-488.
6.	Ahern V. PET scans for locally advanced breast cancer and diagnostic MRI to determine the extent of operation and radiotherapy (PET LABRADOR); TROG 12.02. The Breast, 2015, 24(3): 304-305.
7.	李俊杰, 邵志敏. 2018年美國《國家綜合癌癥網絡乳腺癌臨床實踐指南》解讀. 中華乳腺病雜志: 電子版, 2018, 12(3): 129-134.
8.	Schaefgen B, Mati M, Sinn HP, et al. Can routine imaging after neoadjuvant chemotherapy in breast cancer predict pathologic complete response? Ann Surg Oncol, 2016, 23(3): 789-795.
9.	朱慶莉, 姜玉新. 乳腺影像報告與數據系統指南 (第5版) 超聲內容更新介紹. 中華醫學超聲雜志: 電子版, 2016, 13(1): 5-7.
10.	Santamaría G, Bargalló X, Fernández PL, et al. Neoadjuvant systemic therapy in breast cancer: association of contrast-enhanced MR imaging findings, diffusion-weighted imaging findings, and tumor subtype with tumor response. Radiology, 2017, 283(3): 663-672.
11.	Cortazar P, Zhang L, Untch M, et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet, 2014, 384(9938): 164-172.
12.	Yu N, Leung VWY, Meterissian S. MRI performance in detecting pCR after neoadjuvant chemotherapy by molecular subtype of breast cancer. World J Surg, 2019, 43(9): 2254-2261.
13.	袁紅梅, 余建群, 褚志剛, 等. 動態增強MRI、超聲及X射線對乳腺良惡性病灶診斷的對比研究. 中國普外基礎與臨床雜志, 2015, 22(2): 246-250.
14.	Su MYL. Magnetic resonance imaging as a predictor of pathologic response in patients treated with neoadjuvant systemic treatment for operable breast cancer: Translational Breast Cancer Research Consortium Trial 017. Breast Diseases: A Year Book Quarterly, 2013, 24(4): 343-345.
15.	Mukhtar RA, Yau C, Rosen M, et al. Clinically meaningful tumor reduction rates vary by prechemotherapy MRI phenotype and tumor subtype in the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657). Ann Surg Oncol, 2013, 20(12): 3823-3830.
16.	Bae MS, Shin SU, Ryu HS, et al. Pretreatment MR imaging features of triple-negative breast cancer: association with response to neoadjuvant chemotherapy and recurrence-free survival. Radiology, 2016, 281(2): 392-400.
17.	Yuan Y, Chen XS, Liu SY, et al. Accuracy of MRI in prediction of pathologic complete remission in breast cancer after preoperative therapy: a meta-analysis. AJR Am J Roentgenol, 2010, 195(1): 260-268.
18.	張麗芝, 曾涵江, 黃子星, 等. MRI擴散加權成像對乳腺浸潤性導管癌新輔助化療效果的評價. 中國普外基礎與臨床雜志, 2013, 20(1): 88-91.
19.	羅益賢, 馬捷, 劉永光, 等. 動態增強MRI對乳腺癌新輔助化療的療效評價及預測. 中國醫學物理學雜志, 2019, 36(7): 794-799.
20.	李亭, 李俊峰. MRI對診斷乳腺癌輔助化療的臨床療效分析. 影像研究與醫學應用, 2017, 1(17): 134-135.
21.	劉紅宇, 吳海鸰, 徐祖良, 等. 應用MRI預測三陰性乳腺癌的危險因素分析. 中國臨床醫學影像雜志, 2013, 24(4): 274-277.
22.	Liao GJ, Henze Bancroft LC, Strigel RM, et al. Background parenchymal enhancement on breast MRI: a comprehensive review. J Magn Reson Imaging, 2020, 51(1): 43-61.
23.	徐衛云, 趙潔玉, 張靖, 等. 西部二級城市女性乳腺癌發病風險相關因素分析及風險預測模型的建立. 中國普外基礎與臨床雜志, 2013, 20(10): 1106-1112.
24.	趙麗娟, 徐衛云, 張曉紅, 等. 乳腺密度對乳腺X線攝影診斷乳腺癌的影響. 四川醫學, 2013, 34(11): 1670-1672.
25.	Schmitz AM, Loo CE, Wesseling J, et al. Association between rim enhancement of breast cancer on dynamic contrast-enhanced MRI and patient outcome: impact of subtype. Breast Cancer Res Treat, 2014, 148(3): 541-551.

1. Holmes D, Colfry A, Czerniecki B, et al. Performance and practice guideline for the use of neoadjuvant systemic therapy in the management of breast cancer. Ann Surg Oncol, 2015, 22(10): 3184-3190.
2. Hortobagyi GN. Definition and impact of pathologic complete response on prognosis after neoadjuvant chemotherapy in various intrinsic breast cancer subtypes. Breast Diseases: A Year Book Quarterly, 2012, 23(4): 374-375.
3. Heil J, Schaefgen B, Sinn P, et al. Can a pathological complete response of breast cancer after neoadjuvant chemotherapy be diagnosed by minimal invasive biopsy? Eur J Cancer, 2016, 69: 142-150.
4. Fukuda T, Horii R, Gomi N, et al. Accuracy of magnetic resonance imaging for predicting pathological complete response of breast cancer after neoadjuvant chemotherapy: association with breast cancer subtype. Springerplus, 2016, 5: 152.
5. Panda SK, Goel A, Nayak V, et al. Can preoperative ultrasonography and MRI replace sentinel lymph node biopsy in management of axilla in early breast cancer-a prospective study from a Tertiary Cancer Center. Indian J Surg Oncol, 2019, 10(3): 483-488.
6. Ahern V. PET scans for locally advanced breast cancer and diagnostic MRI to determine the extent of operation and radiotherapy (PET LABRADOR); TROG 12.02. The Breast, 2015, 24(3): 304-305.
7. 李俊杰, 邵志敏. 2018年美國《國家綜合癌癥網絡乳腺癌臨床實踐指南》解讀. 中華乳腺病雜志: 電子版, 2018, 12(3): 129-134.
8. Schaefgen B, Mati M, Sinn HP, et al. Can routine imaging after neoadjuvant chemotherapy in breast cancer predict pathologic complete response? Ann Surg Oncol, 2016, 23(3): 789-795.
9. 朱慶莉, 姜玉新. 乳腺影像報告與數據系統指南 (第5版) 超聲內容更新介紹. 中華醫學超聲雜志: 電子版, 2016, 13(1): 5-7.
10. Santamaría G, Bargalló X, Fernández PL, et al. Neoadjuvant systemic therapy in breast cancer: association of contrast-enhanced MR imaging findings, diffusion-weighted imaging findings, and tumor subtype with tumor response. Radiology, 2017, 283(3): 663-672.
11. Cortazar P, Zhang L, Untch M, et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet, 2014, 384(9938): 164-172.
12. Yu N, Leung VWY, Meterissian S. MRI performance in detecting pCR after neoadjuvant chemotherapy by molecular subtype of breast cancer. World J Surg, 2019, 43(9): 2254-2261.
13. 袁紅梅, 余建群, 褚志剛, 等. 動態增強MRI、超聲及X射線對乳腺良惡性病灶診斷的對比研究. 中國普外基礎與臨床雜志, 2015, 22(2): 246-250.
14. Su MYL. Magnetic resonance imaging as a predictor of pathologic response in patients treated with neoadjuvant systemic treatment for operable breast cancer: Translational Breast Cancer Research Consortium Trial 017. Breast Diseases: A Year Book Quarterly, 2013, 24(4): 343-345.
15. Mukhtar RA, Yau C, Rosen M, et al. Clinically meaningful tumor reduction rates vary by prechemotherapy MRI phenotype and tumor subtype in the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657). Ann Surg Oncol, 2013, 20(12): 3823-3830.
16. Bae MS, Shin SU, Ryu HS, et al. Pretreatment MR imaging features of triple-negative breast cancer: association with response to neoadjuvant chemotherapy and recurrence-free survival. Radiology, 2016, 281(2): 392-400.
17. Yuan Y, Chen XS, Liu SY, et al. Accuracy of MRI in prediction of pathologic complete remission in breast cancer after preoperative therapy: a meta-analysis. AJR Am J Roentgenol, 2010, 195(1): 260-268.
18. 張麗芝, 曾涵江, 黃子星, 等. MRI擴散加權成像對乳腺浸潤性導管癌新輔助化療效果的評價. 中國普外基礎與臨床雜志, 2013, 20(1): 88-91.
19. 羅益賢, 馬捷, 劉永光, 等. 動態增強MRI對乳腺癌新輔助化療的療效評價及預測. 中國醫學物理學雜志, 2019, 36(7): 794-799.
20. 李亭, 李俊峰. MRI對診斷乳腺癌輔助化療的臨床療效分析. 影像研究與醫學應用, 2017, 1(17): 134-135.
21. 劉紅宇, 吳海鸰, 徐祖良, 等. 應用MRI預測三陰性乳腺癌的危險因素分析. 中國臨床醫學影像雜志, 2013, 24(4): 274-277.
22. Liao GJ, Henze Bancroft LC, Strigel RM, et al. Background parenchymal enhancement on breast MRI: a comprehensive review. J Magn Reson Imaging, 2020, 51(1): 43-61.
23. 徐衛云, 趙潔玉, 張靖, 等. 西部二級城市女性乳腺癌發病風險相關因素分析及風險預測模型的建立. 中國普外基礎與臨床雜志, 2013, 20(10): 1106-1112.
24. 趙麗娟, 徐衛云, 張曉紅, 等. 乳腺密度對乳腺X線攝影診斷乳腺癌的影響. 四川醫學, 2013, 34(11): 1670-1672.
25. Schmitz AM, Loo CE, Wesseling J, et al. Association between rim enhancement of breast cancer on dynamic contrast-enhanced MRI and patient outcome: impact of subtype. Breast Cancer Res Treat, 2014, 148(3): 541-551.

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CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Accuracy of MRI in predicting pathologic complete response after neoadjuvant chemotherapy in breast cancer

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