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Non-Mass Enhancement of Breast MRI: The Comparison of Benign and Malignant Pathological Diagnosis and Association of Internal Enhancement Pattern and Distribution with Breast Cancer Molecular Sub-Types

Year 2022, Volume: 5 Issue: 3, 165 - 171, 15.10.2022

Hande Uslu Mesude Tosun Arzu Serpil Arslan

Abstract

Objective: The aim of our study is to investigate the distribution of lesions (focal, linear, segmental, regional, multiple regions, diffuse) and internal enhancement patterns (IEP) (homogeneous, heterogeneous, clumped, clustered ring) between benign and malignant type of NME and to evaluate the difference between Ki-67 and molecular subtypes (Luminal A, Luminal B, Basal-like, and HER2(+)) in malignant group.
Methods: A total of 923 women who underwent routine breast MRI between January 2015 and May 2018 were retrospectively reviewed. 88 MR images were included in the study. Histopathological results were 46 benign and 35 malignant lesions. We compared the distribution and IEPs between benign and malignant type of NME. In the malignant group, distribution and IEPs of different molecular subtypes and Ki-67 values were compared.
Results: Clustered ring internal enhancement were significantly associated with malignancy, while focal distribution and homogeneous enhancement pattern were associated with benignancy. A binomial logistic regression model explained 52.4% of the variance in benign-malignant status and correctly classified 77.3% of cases. Model sensitivity was 74.3%, specificity was 79.2%, positive predictive value was 70.2% and negative predictive value was 82.3%. There were not statistically significant differences in either distribution type of lesions or IEPs between molecular subtypes of malignant NME with different Ki-67 values.
Conclusion: 3-T MRI findings of focal distribution and homogeneous enhancement pattern were found to be a significant predictor of benign NME. Clustered ring enhancement can predict the probability of malignancy for non-mass like enhancement lesions.

Keywords

Breast MRI non-mass enhancement clustered-ring enhancement molecular sub-type Ki-67

References

  • 1. Ikeda D, Hylton N, Kuhl C. BI-RADS: Magnetic resonance imaging. In: D’Orsi CJ, Mendelson EB, Ikeda DM, et al, editors. Breast Imaging Reporting and Data System: ACR BI-RADS - Breast imaging atlas. 1st ed. Virginia: American College of Radiology; 2003.pp. 1-114.
  • 2. Lee SM, Nam KJ, Choo KS, Kim JY, Jeong DW, Kim HY, et al. Patterns of malignant non-mass enhancement on 3-T breast MRI help predict invasiveness: using the BI-RADS lexicon fifth edition. Acta Radiol. 2018;59(11):1292-9.
  • 3. Perou CM, Sørlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747-52.
  • 4. Sorlie T, Tibshirani R, Parker J, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA. 2003;100(14):8418-23.
  • 5. Sakamoto N, Tozaki M, Higa K, et al. Categorization of non-mass-like breast lesions detected by MRI. Breast Cancer. 2008;15(3):241-6.
  • 6. Wirapati P, Sotiriou C, Kunkel S, et al. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res. 2008;10(4):1-11.
  • 7. Inwald E, Klinkhammer-Schalke M, Hofstädter F, et al. Ki-67 is a prognostic parameter in breast cancer patients: results of a large population-based cohort of a cancer registry. Breast Cancer Res. Treat. 2013;139(2):539-52.
  • 8. Yuen S, Uematsu T, Masako K, Uchida Y, Nishimura T. Segmental enhancement on breast MR images: Differential diagnosis and diagnostic strategy. Eur. Radiol. 2008;18(10):2067-75.
  • 9. Tozaki M, Igarashi T, Fukuda K. Breast MRI using the VIBE sequence: clustered ring enhancement in the differential diagnosis of lesions showing non-masslike enhancement. AJR Am J Roentgenol. 2006;187(2):313-21.
  • 10. Shimauchi A, Ota H, Machida Y, et al. Morphology evaluation of nonmass enhancement on breast MRI: Effect of a three-step interpretation model for readers’ performances and biopsy recommendations. Eur. J. Radiol. 2016;85(2):480-8.
  • 11. Yang Q-X, Ji X, Feng L-L, et al. Significant MRI indicators of malignancy for breast non-mass enhancement. J. X-Ray Sci. Technol. 2017;25(6):1033-44.
  • 12. Uematsu T, Kasami M. High-spatial-resolution 3-T breast MRI of nonmasslike enhancement lesions: an analysis of their features as significant predictors of malignancy. AJR Am J Roentgenol. 2012;198(5):1223-30.
  • 13. Asada T, Yamada T, Kanemaki Y, Fujiwara K, Okamoto S, Nakajima Y. Grading system to categorize breast MRI using BI-RADS 5th edition: a statistical study of non-mass enhancement descriptors in terms of probability of malignancy. Jpn J. Radiol. 2018;36(3):200-8.
  • 14. Mahoney MC, Gatsonis C, Hanna L, DeMartini WB, Lehman C. Positive predictive value of BI-RADS MR imaging. Radiology. 2012;264(1):51-8.
  • 15. Machida Y, Tozaki M, Shimauchi A, Yoshida T. Two distinct types of linear distribution in nonmass enhancement at breast MR imaging: difference in positive predictive value between linear and branching patterns. Radiology. 2015;276(3):686-94.
  • 16. Baltzer PA, Benndorf M, Dietzel M, Gajda M, Runnebaum IB, Kaiser WA. False-positive findings at contrast-enhanced breast MRI: a BI-RADS descriptor study. AJR Am J Roentgenol. 2010;194(6):1658-63.
  • 17. Liberman L, Morris EA, Lee MJ-Y, et al. Breast lesions detected on MR imaging: features and positive predictive value. AJR Am J Roentgenol. 2002;179(1):171-8.
  • 18. Morakkabati-Spitz N, Leutner C, Schild H, Traeber F, Kuhl C. Diagnostic usefulness of segmental and linear enhancement in dynamic breast MRI. Eur. Radiol. 2005;15(9):2010-7.
  • 19. Wilhelm A, McDonough MD, DePeri ER. Malignancy Rates of Non‐masslike Enhancement on Breast Magnetic Resonance Imaging Using American College of Radiology Breast Imaging Reporting and Data System Descriptors. Breast J. 2012;18(6):523-6.
  • 20. Ko ES, Lee BH, Kim H-A, Noh W-C, Kim MS, Lee S-A. Triple-negative breast cancer: correlation between imaging and pathological findings. Eur. Radiol. 2010;20(5):1111-7.
  • 21. Youk JH, Son EJ, Chung J, Kim J-A, Kim E-k. Triple-negative invasive breast cancer on dynamic contrast-enhanced and diffusion-weighted MR imaging: comparison with other breast cancer subtypes. Eur. Radiol. 2012;22(8):1724-34.
  • 22. Yamada T, Mori N, Watanabe M, et al. Radiologic-pathologic correlation of ductal carcinoma in situ. Radiographics. 2010;30(5):1183-98.
  • 23. Tse G, Tan PH, Pang AL, Tang AP, Cheung HS. Calcification in breast lesions: pathologists’ perspective. J. Clin. Pathol. 2008;61(2):145-51.

Meme MRG’de Kitlesel Olmayan Kontrastlanma: Benign-Malign Patolojik Tanı ve Meme Kanserinde Moleküler Alt Grupların Dağılım ve Kontrastlanma Paternleri ile Karşılaştırılması

Year 2022, Volume: 5 Issue: 3, 165 - 171, 15.10.2022

Hande Uslu Mesude Tosun Arzu Serpil Arslan

Abstract

Amaç: Çalışmamızın amacı, benign ve malign tip kitlesel olmayan kontrastlanma (KOK) ile malign grupta farklı Ki-67 değerleri ve moleküler alt gruplar (Luminal A, Luminal B, Bazal-benzeri ve HER2 (+)) arasında lezyonların dağılımı (fokal, lineer, segmental, rejyonel, multiple alanlar, diffüz) ve internal kontrastlanma paternleri (İKP) (homojen, heterojen, kümeli, kümelenmiş halka) açısından farklılık olup olmadığını değerlendirmektir.
Yöntemler: Ocak 2015-Mayıs 2018 tarihleri arasında rutin meme MRG uygulanan toplam 923 kadın retrospektif olarak incelendi. Çalışmaya 88 MR görüntüsü dahil edildi. Histopatolojik sonuçlarda 46 benign ve 35 malign lezyon vardı. Benign ve malign KOK tipleri arasındaki dağılım ve İKP'leri karşılaştırdık. Malign grupta farklı moleküler alt gruplar ve Ki-67 değerleri dağılım ve İKP’leri ile karşılaştırıldı.
Bulgular: Kümelenmiş halka internal kontrastlanma paterni malignite ile anlamlı olarak ilişkiliyken, fokal dağılım ve homojen internal kontrastlanma paterni benignite ile ilişkiliydi. Binominal lojistik regresyon modeli, benign-malign durumdaki varyansın % 52.4'ünü açıklamış ve olguların % 77.3'ünü doğru sınıflandırmıştır. Model duyarlılığı %74.3, özgüllük %79.2, pozitif prediktif değer %70.2 ve negatif prediktif değer %82.3 idi. Farklı Ki-67 değerlerine sahip malign KOK’ların moleküler alt grupları arasında lezyonların dağılımı veya İKP’lerinde istatistiksel olarak anlamlı fark yoktu.
Sonuç: 3 Tesla (T) MRG’de fokal dağılım ve homojen internal kontrastlanma paterninin benign KOK’ların anlamlı bir belirleyicisi olduğu bulundu. Kümelenmiş halka internal kontrastlanma paterni, KOK’larda malignite olasılığını tahmin edebilir.

Keywords

Meme MRG kitlesel olmayan kontrastlanma dağılım internal kontrastlanma paterni moleküler alt grup Ki-67

References

  • 1. Ikeda D, Hylton N, Kuhl C. BI-RADS: Magnetic resonance imaging. In: D’Orsi CJ, Mendelson EB, Ikeda DM, et al, editors. Breast Imaging Reporting and Data System: ACR BI-RADS - Breast imaging atlas. 1st ed. Virginia: American College of Radiology; 2003.pp. 1-114.
  • 2. Lee SM, Nam KJ, Choo KS, Kim JY, Jeong DW, Kim HY, et al. Patterns of malignant non-mass enhancement on 3-T breast MRI help predict invasiveness: using the BI-RADS lexicon fifth edition. Acta Radiol. 2018;59(11):1292-9.
  • 3. Perou CM, Sørlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747-52.
  • 4. Sorlie T, Tibshirani R, Parker J, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA. 2003;100(14):8418-23.
  • 5. Sakamoto N, Tozaki M, Higa K, et al. Categorization of non-mass-like breast lesions detected by MRI. Breast Cancer. 2008;15(3):241-6.
  • 6. Wirapati P, Sotiriou C, Kunkel S, et al. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res. 2008;10(4):1-11.
  • 7. Inwald E, Klinkhammer-Schalke M, Hofstädter F, et al. Ki-67 is a prognostic parameter in breast cancer patients: results of a large population-based cohort of a cancer registry. Breast Cancer Res. Treat. 2013;139(2):539-52.
  • 8. Yuen S, Uematsu T, Masako K, Uchida Y, Nishimura T. Segmental enhancement on breast MR images: Differential diagnosis and diagnostic strategy. Eur. Radiol. 2008;18(10):2067-75.
  • 9. Tozaki M, Igarashi T, Fukuda K. Breast MRI using the VIBE sequence: clustered ring enhancement in the differential diagnosis of lesions showing non-masslike enhancement. AJR Am J Roentgenol. 2006;187(2):313-21.
  • 10. Shimauchi A, Ota H, Machida Y, et al. Morphology evaluation of nonmass enhancement on breast MRI: Effect of a three-step interpretation model for readers’ performances and biopsy recommendations. Eur. J. Radiol. 2016;85(2):480-8.
  • 11. Yang Q-X, Ji X, Feng L-L, et al. Significant MRI indicators of malignancy for breast non-mass enhancement. J. X-Ray Sci. Technol. 2017;25(6):1033-44.
  • 12. Uematsu T, Kasami M. High-spatial-resolution 3-T breast MRI of nonmasslike enhancement lesions: an analysis of their features as significant predictors of malignancy. AJR Am J Roentgenol. 2012;198(5):1223-30.
  • 13. Asada T, Yamada T, Kanemaki Y, Fujiwara K, Okamoto S, Nakajima Y. Grading system to categorize breast MRI using BI-RADS 5th edition: a statistical study of non-mass enhancement descriptors in terms of probability of malignancy. Jpn J. Radiol. 2018;36(3):200-8.
  • 14. Mahoney MC, Gatsonis C, Hanna L, DeMartini WB, Lehman C. Positive predictive value of BI-RADS MR imaging. Radiology. 2012;264(1):51-8.
  • 15. Machida Y, Tozaki M, Shimauchi A, Yoshida T. Two distinct types of linear distribution in nonmass enhancement at breast MR imaging: difference in positive predictive value between linear and branching patterns. Radiology. 2015;276(3):686-94.
  • 16. Baltzer PA, Benndorf M, Dietzel M, Gajda M, Runnebaum IB, Kaiser WA. False-positive findings at contrast-enhanced breast MRI: a BI-RADS descriptor study. AJR Am J Roentgenol. 2010;194(6):1658-63.
  • 17. Liberman L, Morris EA, Lee MJ-Y, et al. Breast lesions detected on MR imaging: features and positive predictive value. AJR Am J Roentgenol. 2002;179(1):171-8.
  • 18. Morakkabati-Spitz N, Leutner C, Schild H, Traeber F, Kuhl C. Diagnostic usefulness of segmental and linear enhancement in dynamic breast MRI. Eur. Radiol. 2005;15(9):2010-7.
  • 19. Wilhelm A, McDonough MD, DePeri ER. Malignancy Rates of Non‐masslike Enhancement on Breast Magnetic Resonance Imaging Using American College of Radiology Breast Imaging Reporting and Data System Descriptors. Breast J. 2012;18(6):523-6.
  • 20. Ko ES, Lee BH, Kim H-A, Noh W-C, Kim MS, Lee S-A. Triple-negative breast cancer: correlation between imaging and pathological findings. Eur. Radiol. 2010;20(5):1111-7.
  • 21. Youk JH, Son EJ, Chung J, Kim J-A, Kim E-k. Triple-negative invasive breast cancer on dynamic contrast-enhanced and diffusion-weighted MR imaging: comparison with other breast cancer subtypes. Eur. Radiol. 2012;22(8):1724-34.
  • 22. Yamada T, Mori N, Watanabe M, et al. Radiologic-pathologic correlation of ductal carcinoma in situ. Radiographics. 2010;30(5):1183-98.
  • 23. Tse G, Tan PH, Pang AL, Tang AP, Cheung HS. Calcification in breast lesions: pathologists’ perspective. J. Clin. Pathol. 2008;61(2):145-51.
There are 23 citations in total.

Details

Primary Language English
Subjects Radiology and Organ Imaging
Journal Section Research Articles
Authors

Hande Uslu 0000-0003-1530-2573

Mesude Tosun 0000-0001-8278-108X

Arzu Serpil Arslan 0000-0002-4993-4010

Publication Date October 15, 2022
Submission Date June 9, 2022
Acceptance Date September 9, 2022
Published in Issue Year 2022 Volume: 5 Issue: 3

Cite

AMA Uslu H, Tosun M, Arslan AS. Non-Mass Enhancement of Breast MRI: The Comparison of Benign and Malignant Pathological Diagnosis and Association of Internal Enhancement Pattern and Distribution with Breast Cancer Molecular Sub-Types. Acta Med Nicomedia. October 2022;5(3):165-171. doi:10.53446/actamednicomedia.1128352
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