Correlation between Histopathological Molecular Markers and Magnetic Resonance Imaging of Spiculated Breast Cancers

Öz

To compare the relationship between MRI and histopathological findings of spiculated and non-spiculated breast cancer. Between January 2014 and January 2018, 90 women who had undergone ultrasonography guided biopsies or lumpectomy/mastectomy with 50 spiculated and 40 non-spiculated masses were separated accoding to BI-RADS criteria on mammography. Estrogen receptor (ER), progesterone receptor (PR), HER2 expression and Ki67 index were used as markers to identify molecular markers of breast cancer. Pearson chi-square test was employed to measure statistical significance of correlations. There was no difference for age between two groups (p=0.331). The size of the masses were not different between the two groups (p =0.244). More hypointense signal features were detected in T2-weighted images for the spiculated masses (p = 0.004). There was no difference between the two groups in terms of multifocal or multicentric involvement, non-mass type enhancement, peripheral rim enhancement and axillary lymph node involvement in the MRI (p=0.237, p=0.622, p=0.096, p=0.295 and p=0.764, respectively). ER and PR positivity were higher in the spiculated masses (p=0.027 and p=0.03, respectively). For the HER2 positivity and Ki67 index, statistically significant a difference were not found between two groups (p=0.571 and p=0.596, respectively). ER and PR positivity tends to be higher in the spiculated masses. This could be helpfull to predict the course of the disease as well as the effectiveness of the treatment.

Anahtar Kelimeler

• Spiculation,Breast cancer,Tumor receptor,MRI

Spiküle Meme Kanserlerinin Histopatolojik Moleküler Biyobelirteçler ve Manyetik Rezonans Görüntüleme Arasındaki Korelasyonu

Öz

Bu çalışmanın amacı spiküle ve spiküle olmayan meme kanserinin MRG ve histopatolojik bulguları arasındaki ilişkiyi karşılaştırmaktır. Ocak 2014 ile Ocak 2018 arasında, mamografide BI-RADS kriterlerine göre 50 spiküle ve 40 spiküle olmayan kitle olarak ultrasonografi kılavuzluğunda biyopsi veya lumpektomi/mastektomi yapılan 90 kadın çalışmaya alındı. Meme kanserinin moleküler biyobelirteçlerini tanımlamak için östrojen reseptörü (ÖR), progesteron reseptörü (PR), HER2 ekspresyonu ve Ki67 indeksi kullanıldı. Korelasyonların istatistiksel önemini ölçmek için Pearson ki-kare testi yapıldı. İki grup arasında yaş açısından fark yoktu (p=0.331). Kitlelerin büyüklüğü iki grup arasında farklı değildi (p=0.244). Spiküle kitlelerde T2A görüntülerde (T2AG) daha fazla hipointens sinyal özelliği tespit edildi (p=0.004). MRG'de multifokal veya multisentrik tutulum, kitlesiz boyanma, periferik halkasal boyanma ve aksiller lenf nodu tutulumu açısından iki grup arasında fark yoktu (sırasıyla p=0.237, p=0.622, p=0.096, p=0.295 ve p=0.764). ÖR ve PR pozitifliği spiküle kitlelerde daha yüksekti (sırasıyla p=0.027 ve p=0.03). HER2 pozitifliği ve Ki67 indeksi için iki grup arasında istatistiksel olarak anlamlı bir fark bulunmadı (sırasıyla p=0.571 ve p=0.596).ÖR ve PR pozitifliği spiküle kitlelerde daha fazla olma eğilimindedir. Bu, hastalığın seyrini ve tedavinin etkinliğini tahmin etmede yardımcı olabilir.

Anahtar Kelimeler

• Spikülasyon,meme kanseri,tümör belirteçleri

Kaynakça

1. 1. Lam SW, Jimenez CR, Boven E. Breast cancer classification by proteomic technologies: current state of knowledge. Cancer Treat Rev 2014;40:129-38.
2. 2. Beral V, Bull D, Doll R, Peto R, Reeves G. Breast cancer and breastfeeding: Collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50 302 women with breast cancer and 96 973 women without the disease. Lancet 2002;360;187-95.
3. 3. Yersal O, Barutca S. Biological subtypes of breast cancer: Prognostic and therapeutic implications. World J Clin Oncol 2014;5:412-24.
4. 4. Guiu S, Michiels S, André F, Cortes J, Denkert C, Di Leo A, et al. Molecular subclasses of breast cancer: how do we define them? The IMPAKT 2012 Working Group Statement. Ann Oncol 2012;23:2997-3006.
5. 5. Burstein HJ, Curigliano G, Loibl S, Dubsky P, Gnant M, Poortmans P et al. Estimating the benefits of therapy for early-stage breast cancer: the St. Gallen International Consensus Guidelines for the primary therapy of early breast cancer 2019. Ann Oncol 2019; 30(10): 1541–1557.
6. 6. Jin YH, Hua QF, Zheng JJ, Ma XH, Chen TX, Zhang S et al. Diagnostic Value of ER, PR, FR and HER-2-Targeted Molecular Probes for Magnetic Resonance Imaging in Patients with Breast Cancer. Cell Physiol Biochem. 2018;49:271-81.
7. 7. Woodard GA, Ray KM, Joe BN, Price ER. Qualitative Radiogenomics: Association between Oncotype DX Test Recurrence Score and BI-RADS Mammographic and Breast MR Imaging Features. Radiology. 2018 Jan;286:60-70.
8. 8. Liu S, Wu XD, Xu WJ, Lin Q, Liu XJ, Li Y. Is There a Correlation between the Presence of a Spiculated Mass on Mammogram and Luminal A Subtype Breast Cancer? Korean J Radiol. 2016;17:846-52.

9. 9. Boisserie-Lacroix M, Bullier B, Hurtevent-Labrot G, Ferron S, Lippa N, Mac Grogan G. Correlation between imaging and prognostic factors: molecular classification of breast cancers. Diagn Interv Imaging. 2014;95:227-33.
10. 10. Trop I, LeBlanc SM, David J, Lalonde L, Tran-Thanh D, Labelle M, et al. Molecular classification of infiltrating breast cancer: toward personalized therapy. Radiographics. 2014;34:1178-95. 11. Alili C, Pages E, Curros Doyon F, Perrochia H, Millet I, Taourel P. Correlation between MR imaging - prognosis factors and molecular classification of breast cancers. Diagn Interv Imaging. 2014 Feb;95(2):235-42.
11. 12. Ha R, Jin B, Mango V, Friedlander L, Miloshev V, Malak S, et al. Breast cancer molecular subtype as a predictor of the utility of preoperative MRI. AJR 2015;204:1354-60.
12. 13. Chen JH, Baek HM, Nalcioglu O, Su MY. Estrogen receptor and breast MR imaging features: a correlation study. J Magn Reson Imaging 2008;27(4):825-33.
13. 14. Cho N. Molecular subtypes and imaging phenotypes of breast cancer. Ultrasonography. 2016;35:281-8.
14. 15. Koukourakis MI, Manolas C, Minopoulos G, Giatromanolaki A, Sivridis E. Angiogenesis relates to estrogen receptor negativity, c-erbB-2 overexpression and early relapse in node-negative ductal carcinoma of the breast. Int J Surg Pathol 2003;11:29–34.
15. 16. Fuckar D, Dekanic A, Stifter S, Mustać E, Krstulja M, Dobrila F, et al. VEGF expression is associated with negative estrogen receptor status in patients with breast cancer. Int J Surg Pathol 2006;14:49–55.
16. 17. Killelea BK, Chagpar AB, Bishop J, Horowitz NR, Christy C, Tsangaris T, et al. Is there a correlation between breast cancer molecular subtype using receptors as surrogates and mammographic appearance? Ann Surg Oncol 2013;20:3247-53.
17. 18. Grimm LJ, Mazurowski MA. Breast Cancer Radiogenomics: Current Status and Future Directions. Acad Radiol. 2020;27:39-46.
18. 19. Evans AJ, Pinder SE, James JJ, Ellis IO, Cornford E. Is mammographic spiculation an independent, good prognostic factor in screening-detected invasive breast cancer? AJR 2006;187:1377-80.
19. 20. Jiang L, Ma T, Moran MS, Kong X, Li X, Haffty BG, et al. Mammographic features are associated with clinicopathological characteristics in invasive breast cancer. Anticancer Res 2011;31:2327-34.
20. 21. Moriuchi H, Yamaguchi J, Hayashi H, Ohtani H, Shimokawa I, Abiru H, et al. Cancer cell interaction with adipose tissue: correlation with the finding of spiculation at mammography. Radiology 2016;279:56-64.
21. 22. Shin HJ, Kim HH, Huh MO, Kim MJ, Yi A, Kim H, et al. Correlation between mammographic and sonographic findings and prognostic factors in patients with node‑negative invasive breast cancer. Br J Radiol 2011;84:19-30.
22. 23. Wu M, Zhong X, Peng Q, Xu M, Huang S, Yuan J, et al.Prediction of molecular subtypes of breast cancer using BI-RADS features based on a "white box" machine learning approach in a multi-modal imaging setting. Eur J Radiol. 2019;114:175-184.
23. 24. Montemezzi S, Camera L, Giri MG, Pozzetto A, Caliò A, Meliadò G, et al.Is there a correlation between 3T multiparametric MRI and molecular subtypes of breast cancer? Eur J Radiol. 2018;108:120-7.
24. 25. Schmitz AM1, Loo CE, Wesseling J, Pijnappel RM, Gilhuijs KG. Association between rim enhancement of breast cancer on dynamic contrast-enhanced MRI and patient outcome: impact of subtype. Breast Cancer Res Treat. 2014;148:541-51.
25. 26. Jinguji M, Kajiya Y, Kamimura K, Nakajo M, Sagara Y, Takahama T, et al. Rim enhancement of breast cancers on contrast-enhanced MR imaging: relationship with prognostic factors. Breast Cancer. 2006;13:64-73.
26. 27. Gokalp G, Topal U, Yildirim N, Tolunay S. Malignant spiculated breast masses: dynamic contrast enhanced MR (DCE-MR) imaging enhancement characteristics and histopathological correlation. Eur J Radiol 2012;81:203-8.
27. 28. Macura KJ, Ouwerkerk R, Jacobs MA, Bluemke DA. Patterns of enhancement on breast MR images: interpretation and imaging pitfalls. Radiographics. 2006;26:1719-34.