BibTex RIS Kaynak Göster

Can Breast MRI Findings Predict Molecular Subtypes of Breast Cancer?

Yıl 2019, Cilt: 5 Sayı: 2, 273 - 281, 01.01.2019

Öz

Objective: To investigate the association between the morphologic and kinetic results obtained with the dynamic contrast-enhanced magnetic resonance imaging MRI , and the apparent diffusion coefficient ADC values obtained using diffusion-weighted imaging DWI in breast cancer with the histopathologic subtypes of tumors.Material and Methods: The MRI results of 271 breast lesions of 258 patients were retrospectively evaluated. Lesion morphology and contrast-enhancement characteristics were evaluated using conventional MRI, and ADC measurements were performed with DWI. Results: An association was detected between regular margins in the masses, the presence of intratumoral necrosis, and annular contrast enhancement with triple-negative type TN , spiculated margin luminal A type. Higher histological grade was mostly detected in TN 45.7% , and human epidermal growth factor receptor 2 positive HER2+ tumors 47.1% p

Kaynakça

  • Bae MS, Seo M, Kim KG, Park IA, Moon WK. Quantitative MRI morphology of invasive breast cancer: Correlation with immunohistochemical biomarkers and subtypes. Acta Radiol 2015; 56:269-75.
  • Navarro Vilar L, Alandete German SP, Medina Garcia R, Blanc García E, Camarasa Lillo N, Vilar Samper J. MR Imaging findings in molecular subtypes of breast cancer according to BIRADS system. Breast J 2017; 23:421-8.
  • Sung SJ, Jochelson MS, Brennan S, Wen YH, Moskowitz C, Zheng J, Dershaw DD, Morris EA. MR imaging features of triple negative breast cancers. Breast J 2013; 19:643-9.
  • Blaschke E, Abe H. MRI phenotype of breast cancer: Kinetic assessment for molecular subtypes. J Magn Reson Imaging 2015; 42:920-4.
  • Youk JH, Son EJ, Chung J, Kim J, Kim E. Triple-negative invasive breast cancer on dynamic contrast-enhanced and diffusion-weighted MR imaging: Comparison with other breast cancer subtypes. Eur Radiol 2012; 22:1724-34.
  • Park SH, Choi HY, Hahn SY. Correlations between apparent diffusion coefficient values of invasive ductal carcinoma and pathologic factors on diffusion-weighted MRI at 3.0 tesla. Journal of Magnetic Resonance Imaging 2015; 41:175-82.
  • Kim Y, Ko K, Kim D, Min C, Kim SG, Joo J, Park B. Intravoxel incoherent motion diffusion-weighted MR imaging of breast cancer: Association with histopathological features and subtypes. Br J Radiol 2016; 89(1063):20160140.
  • Sharma U, Sah RG, Agarwal K, Parshad R, Seenu V, Mathur SR, Hari S, Jagannathan NR. Potential of diffusion-weighted imaging in the characterization of malignant, benign, and healthy breast tissues and molecular subtypes of breast cancer. Front Oncol 2016; 6:126.
  • Rakha EA, Reis-Filho JS, Baehner F, Dabbs DJ, Decker T, Eusebi V, Fox SB, Ichihara S, Jacquemier J, Lakhani SR, Palacios J, Richardson AL, Schnitt SJ, Schmitt FC, Tan PH, Tse GM, Badve S, Ellis IO. Breast cancer prognostic classification in the molecular era: The role of histological grade. Breast Cancer Res 2010; 12:207.
  • Kato F, Kudo K, Yamashita H, Wang J, Hosoda M, Hatanaka KC, Mimura R, Oyama-Manabe N, Shirato H. Differences in morphological features and minimum apparent diffusion coefficient values among breast cancer subtypes using 3-tesla MRI. European Journal of Radiology 2016; 85:96-102.
  • Lee SH, Cho N, Kim SJ, Cha JH, Cho KS, Ko ES, Ko ES, Moon WK. Correlation between high resolution dynamicMR features and prognostic factors in breast cancer. Kor J Radiol 2008; 9(1):10-8.
  • Yoshikawa MI, Ohsumi S, Sugata S, Kataoka M, Takashima S, Mochizuki T, Ikura H, Imai Y. Relation between cancer cellularity and apparent diffusion coefficient values using diffusion-weighted magnetic resonance imaging in breast cancer. Radiat Med 2008; 26:222-6.
  • Bogner W, Gruber S, Pinker K, Grabner G, Stadlbauer A, Weber M, Moser E, Helbich TH, Trattnig S. Diffusion- weighted MR for differentiation of breast lesions at 3.0 T: How does selection of diffusion protocols affect diagnosis? Radiology 2009; 253(2):341-51.
  • Whitman GJ, Albarracin CT, Gonzalez-Angulo AM. Triple negative breast cancer: What the radiologist needs to know. Semin Roentgenol 2011; 46:26-39.
  • Dent R, Trudeau M, Pritchard KI, Hanna WM, Kahn HK, Sawka CA, Lickley LA, Rawlinson E, Sun P, Narod SA.Triple-negative breast cancer: Clinical features and patterns of recurrence. Clin Cancer Res 2007; 13:4429- 34.
  • Choi SY, Chang YW, Park HJ, Kim HJ, Hong SS, Seo DY. Correlation of the apparent diffusion coefficiency values on diffusion-weighted imaging with prognostic factors for breast cancer. Br J Radiol 2012; 85:474-9.
  • Cho GY, Moy L, Kim SG, Baete SH, Moccaldi M, Babb JS, Sodickson DK, Sigmund EE. Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: Comparison with malignant status, histological subtype, and molecular prog-nostic factors. Eur Radiol 2016; 26(8):2547-58.
  • Martincich L, Deantoni V, Bertotto I, Redana S, Kubatzki F, Sarotto I Rossi V, Liotti M, Ponzone R, Aglietta M, Regge D, Montemurro F. Correlations between diffusion- weighted imaging and breast cancer biomark-ers. Eur Radiol 2012; 22:1519-28.
  • Kim SH, Cha ES, Kim HS, Kang BJ, Choi JJ, Jung JH, Park YG, Suh YJ. Diffusion-weighted imaging of breast cancer: Correlation of the apparent diffusion coefficient value with prognostic factors. J Magn Reson Imaging 2009; 30(3):615-20.
  • Choi BB, Kim SH, Kang BJ, Lee JH, Song BJ, Jeong SH, Yim HW. Diffusion- weighted imaging and FDG PET/ CT: Predicting the prognoses with apparent diffusion coefficient values and maximum standardized uptake values in patients with invasive ductal carcinoma. World J Surg Oncol 2012; 10:126.
  • Park EK, Cho KR, Seo BK, Woo OH, Cho SB, Bae JW. Additional value of diffusion-weighted imaging to evaluate prognostic factors of breast cancer: Correlation with the apparent diffusion coefficient. Iran J Radiol 2016; 13(1):e33133.
  • Durando M, Gennaro L, Cho CY, Giri DD, Gnanasigamani MM, Patil S. Quantitative apparent diffusion coefficient measurement obtained by 3.0 tesla MRI as a potential noninvasive marker of tumor aggressiveness in breast cancer. Eur J Radiol 2016; 85(9):1651-8.
  • Guo Y, Cai YQ, Cai ZL, Gao YG, An NY, Ma L, Mahankali S, Gao JH. Differentiation of clinically benign and malignant breast lesions using diffusion weighted imaging. J Magn Reson Imaging 2002; 16(2):172-8.
  • Woodhams R, Matsunaga K, Iwabuchi K, Kan S, Hata H, Kuranami M, Watanabe M, Hayakawa K. Diffusion- weighted imaging of malignant breast tumors: The usefulness of apparent diffusion coefficient (ADC) value and ADC map for the detection of malignant breast tumors and evaluation of cancer extension. J Comput Assist Tomogr 2005; 29(5):644-9.
  • Mori N, Ota H, Mugikura S, Takasawa C, Ishida T, Watanabe G, Tada H, Watanabe M, Takase K, Takahashi S. Luminal-type breast cancer: Correlation of apparent diffusion coefficients with the Ki-67 labeling index. Radiology 2015; 274:66-73.
  • Molinari C, Clauser P, Girometti R, Linda A, Cimino E, Puglisi F, Zuiani C, Bazzocchi M. MR mammography using diffusion-weighted imaging in evaluating breast cancer: A correlation with proliferation index. La Radiologia Medica 2015; 120(10):911-8.
  • Rabasco P, Caivano R, Simeon V, Dinardo G, Lotumolo A, Gioioso M, Villonio A, Iannelli G, D’Antuono F, Zandolino A, Macarini L, Guglielmi G, Cammarota A. Can diffusion-weighted imaging and related apparent diffusion coefficient be a prognostic value in women with breast cancer? Cancer Investigation 2017; 35(2):92-9.
  • De Felice C, Cipolla V, Guerrieri D, Santucci D, Musella A, Porfiri LM, Meggiorini ML. Apparent diffusion coefficient on 3.0 tesla magnetic resonance imaging and prognostic factors in breast cancer. Eur J Gynaecol Oncol 2014; 35:408-14.

Meme MRG Bulguları Meme Kanserinin Moleküler Alt Tiplerini Öngörebilir mi?

Yıl 2019, Cilt: 5 Sayı: 2, 273 - 281, 01.01.2019

Öz

Amaç: Meme kanserinde dinamik kontrastlı manyetik rezonans görüntüleme MRG ile saptanan morfolojik ve kinetik bulgularla, difüzyon ağırlıklı görüntüleme ile elde edilen apparent diffusion coefficient ADC değerlerinin tümör histopatolojik alt tipleri ile ilişkisini araştırmak.Gereç ve Yöntemler: 258 kadın hastaya ait 271 meme lezyonunun MRG bulguları geriye dönük olarak değerlendirildi. Konvansiyonel MRG’de lezyon morfolojisi ve kontrastlanma özellikleri değerlendirilirken, difüzyon ağırlıklı MRG’de ADC ölçümleri yapıldı. Morfolojik, kinetik özellikler ve ortalama ADC değerleri ile tümör boyutu, histolojik grade, aksiller lenf nodu tutulumu, ki-67 indeksi ve histolojik subtipler arasındaki ilişki analiz edildi.Bulgular: Kitlelerde düzgün kenar, tümör içi nekroz varlığı ve halkasal kontrastlanma bulgularıyla triple negatif tip; spiküle kenar luminal A tip, aksilla lenf nodu tutulumu ile human epidermal growth factor reseptör 2 pozitif HER2+ tip arasında ilişki saptandı. Yüksek histolojik grade en fazla TN %45,7 ve HER2 + %47,1 tümörlerde saptandı p=0.000 . Ortalama ADC değeri 1001x10-6mm2/sn olarak ölçüldü. Triple negatif TN tümörlerde ortalama ADC değeri diğer subtiplerden daha yüksekti. Ancak, ADC değeri moleküler subtipler arasında önemli farklılık göstermedi p=0,396 . Östrojen ve progesteron reseptörü pozitif ER/PR+ subgrubun ADC değerleri HER2+ ve TN grupla karşılaştırıldığında iki grup aralarında anlamlı farklılık saptanmadı p=0,556 . Ki-67 proliferasyon indeksi ve ortalama ADC değerleri arasında korelasyon saptanmadı p=0,207 .Sonuç: Dinamik kontrastlı meme MRG morfoloji bulguları özellikle bazı moleküler alt tipleri işaret ederken, DAG ile saptanan ADC değerlerinin moleküler alt tip belirlemede iddialı olmadığı söylenebilir

Kaynakça

  • Bae MS, Seo M, Kim KG, Park IA, Moon WK. Quantitative MRI morphology of invasive breast cancer: Correlation with immunohistochemical biomarkers and subtypes. Acta Radiol 2015; 56:269-75.
  • Navarro Vilar L, Alandete German SP, Medina Garcia R, Blanc García E, Camarasa Lillo N, Vilar Samper J. MR Imaging findings in molecular subtypes of breast cancer according to BIRADS system. Breast J 2017; 23:421-8.
  • Sung SJ, Jochelson MS, Brennan S, Wen YH, Moskowitz C, Zheng J, Dershaw DD, Morris EA. MR imaging features of triple negative breast cancers. Breast J 2013; 19:643-9.
  • Blaschke E, Abe H. MRI phenotype of breast cancer: Kinetic assessment for molecular subtypes. J Magn Reson Imaging 2015; 42:920-4.
  • Youk JH, Son EJ, Chung J, Kim J, Kim E. Triple-negative invasive breast cancer on dynamic contrast-enhanced and diffusion-weighted MR imaging: Comparison with other breast cancer subtypes. Eur Radiol 2012; 22:1724-34.
  • Park SH, Choi HY, Hahn SY. Correlations between apparent diffusion coefficient values of invasive ductal carcinoma and pathologic factors on diffusion-weighted MRI at 3.0 tesla. Journal of Magnetic Resonance Imaging 2015; 41:175-82.
  • Kim Y, Ko K, Kim D, Min C, Kim SG, Joo J, Park B. Intravoxel incoherent motion diffusion-weighted MR imaging of breast cancer: Association with histopathological features and subtypes. Br J Radiol 2016; 89(1063):20160140.
  • Sharma U, Sah RG, Agarwal K, Parshad R, Seenu V, Mathur SR, Hari S, Jagannathan NR. Potential of diffusion-weighted imaging in the characterization of malignant, benign, and healthy breast tissues and molecular subtypes of breast cancer. Front Oncol 2016; 6:126.
  • Rakha EA, Reis-Filho JS, Baehner F, Dabbs DJ, Decker T, Eusebi V, Fox SB, Ichihara S, Jacquemier J, Lakhani SR, Palacios J, Richardson AL, Schnitt SJ, Schmitt FC, Tan PH, Tse GM, Badve S, Ellis IO. Breast cancer prognostic classification in the molecular era: The role of histological grade. Breast Cancer Res 2010; 12:207.
  • Kato F, Kudo K, Yamashita H, Wang J, Hosoda M, Hatanaka KC, Mimura R, Oyama-Manabe N, Shirato H. Differences in morphological features and minimum apparent diffusion coefficient values among breast cancer subtypes using 3-tesla MRI. European Journal of Radiology 2016; 85:96-102.
  • Lee SH, Cho N, Kim SJ, Cha JH, Cho KS, Ko ES, Ko ES, Moon WK. Correlation between high resolution dynamicMR features and prognostic factors in breast cancer. Kor J Radiol 2008; 9(1):10-8.
  • Yoshikawa MI, Ohsumi S, Sugata S, Kataoka M, Takashima S, Mochizuki T, Ikura H, Imai Y. Relation between cancer cellularity and apparent diffusion coefficient values using diffusion-weighted magnetic resonance imaging in breast cancer. Radiat Med 2008; 26:222-6.
  • Bogner W, Gruber S, Pinker K, Grabner G, Stadlbauer A, Weber M, Moser E, Helbich TH, Trattnig S. Diffusion- weighted MR for differentiation of breast lesions at 3.0 T: How does selection of diffusion protocols affect diagnosis? Radiology 2009; 253(2):341-51.
  • Whitman GJ, Albarracin CT, Gonzalez-Angulo AM. Triple negative breast cancer: What the radiologist needs to know. Semin Roentgenol 2011; 46:26-39.
  • Dent R, Trudeau M, Pritchard KI, Hanna WM, Kahn HK, Sawka CA, Lickley LA, Rawlinson E, Sun P, Narod SA.Triple-negative breast cancer: Clinical features and patterns of recurrence. Clin Cancer Res 2007; 13:4429- 34.
  • Choi SY, Chang YW, Park HJ, Kim HJ, Hong SS, Seo DY. Correlation of the apparent diffusion coefficiency values on diffusion-weighted imaging with prognostic factors for breast cancer. Br J Radiol 2012; 85:474-9.
  • Cho GY, Moy L, Kim SG, Baete SH, Moccaldi M, Babb JS, Sodickson DK, Sigmund EE. Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: Comparison with malignant status, histological subtype, and molecular prog-nostic factors. Eur Radiol 2016; 26(8):2547-58.
  • Martincich L, Deantoni V, Bertotto I, Redana S, Kubatzki F, Sarotto I Rossi V, Liotti M, Ponzone R, Aglietta M, Regge D, Montemurro F. Correlations between diffusion- weighted imaging and breast cancer biomark-ers. Eur Radiol 2012; 22:1519-28.
  • Kim SH, Cha ES, Kim HS, Kang BJ, Choi JJ, Jung JH, Park YG, Suh YJ. Diffusion-weighted imaging of breast cancer: Correlation of the apparent diffusion coefficient value with prognostic factors. J Magn Reson Imaging 2009; 30(3):615-20.
  • Choi BB, Kim SH, Kang BJ, Lee JH, Song BJ, Jeong SH, Yim HW. Diffusion- weighted imaging and FDG PET/ CT: Predicting the prognoses with apparent diffusion coefficient values and maximum standardized uptake values in patients with invasive ductal carcinoma. World J Surg Oncol 2012; 10:126.
  • Park EK, Cho KR, Seo BK, Woo OH, Cho SB, Bae JW. Additional value of diffusion-weighted imaging to evaluate prognostic factors of breast cancer: Correlation with the apparent diffusion coefficient. Iran J Radiol 2016; 13(1):e33133.
  • Durando M, Gennaro L, Cho CY, Giri DD, Gnanasigamani MM, Patil S. Quantitative apparent diffusion coefficient measurement obtained by 3.0 tesla MRI as a potential noninvasive marker of tumor aggressiveness in breast cancer. Eur J Radiol 2016; 85(9):1651-8.
  • Guo Y, Cai YQ, Cai ZL, Gao YG, An NY, Ma L, Mahankali S, Gao JH. Differentiation of clinically benign and malignant breast lesions using diffusion weighted imaging. J Magn Reson Imaging 2002; 16(2):172-8.
  • Woodhams R, Matsunaga K, Iwabuchi K, Kan S, Hata H, Kuranami M, Watanabe M, Hayakawa K. Diffusion- weighted imaging of malignant breast tumors: The usefulness of apparent diffusion coefficient (ADC) value and ADC map for the detection of malignant breast tumors and evaluation of cancer extension. J Comput Assist Tomogr 2005; 29(5):644-9.
  • Mori N, Ota H, Mugikura S, Takasawa C, Ishida T, Watanabe G, Tada H, Watanabe M, Takase K, Takahashi S. Luminal-type breast cancer: Correlation of apparent diffusion coefficients with the Ki-67 labeling index. Radiology 2015; 274:66-73.
  • Molinari C, Clauser P, Girometti R, Linda A, Cimino E, Puglisi F, Zuiani C, Bazzocchi M. MR mammography using diffusion-weighted imaging in evaluating breast cancer: A correlation with proliferation index. La Radiologia Medica 2015; 120(10):911-8.
  • Rabasco P, Caivano R, Simeon V, Dinardo G, Lotumolo A, Gioioso M, Villonio A, Iannelli G, D’Antuono F, Zandolino A, Macarini L, Guglielmi G, Cammarota A. Can diffusion-weighted imaging and related apparent diffusion coefficient be a prognostic value in women with breast cancer? Cancer Investigation 2017; 35(2):92-9.
  • De Felice C, Cipolla V, Guerrieri D, Santucci D, Musella A, Porfiri LM, Meggiorini ML. Apparent diffusion coefficient on 3.0 tesla magnetic resonance imaging and prognostic factors in breast cancer. Eur J Gynaecol Oncol 2014; 35:408-14.
Toplam 28 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Araştırma Makalesi
Yazarlar

Yasemin Durum Polat Bu kişi benim

Veli Süha Öztürk Bu kişi benim

Recep Özgür Bu kişi benim

İbrahim Halil Erdoğdu Bu kişi benim

Filiz Abacıgil Bu kişi benim

Füsun Taşkın Bu kişi benim

Yayımlanma Tarihi 1 Ocak 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 5 Sayı: 2

Kaynak Göster

Vancouver Durum Polat Y, Öztürk VS, Özgür R, Erdoğdu İH, Abacıgil F, Taşkın F. Can Breast MRI Findings Predict Molecular Subtypes of Breast Cancer?. Akd Tıp D. 2019;5(2):273-81.