[Home ] [Archive]    
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
IJRR Information::
For Authors::
For Reviewers::
Subscription::
News & Events::
Web Mail::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
ISSN
Hard Copy 2322-3243
Online 2345-4229
..
Online Submission
Now you can send your articles to IJRR office using the article submission system.
..

AWT IMAGE

AWT IMAGE

:: Volume 22, Issue 3 (7-2024) ::
Int J Radiat Res 2024, 22(3): 545-549 Back to browse issues page
Analysis of malignancy signs in breast magnetic resonance imaging
B. Feng , H. Chen
Department of Imaging, Maanshan General Hospital of Ranger-Duree Healthcare, Ma’anshan 243000, China , chenhuacai1791@163.com
Abstract:   (768 Views)
Background: To analyse the signs of malignant tumours in breast magnetic resonance imaging (MRI) and further improve the imaging diagnosis level of malignant breast tumours. Materials and Methods: The plain and enhanced MRI data of 60 patients who visited our hospital between January 2011 and January 2021 were analysed retrospectively, with 118 lesions in total. Malignant breast tumour signs were assessed. Results: A total of 96 lesions were pathologically confirmed as breast cancer, with 76 cases of single breast and single lesion, 10 cases of double breast and single lesion, 6 cases of single breast and two lesions, and 4 cases of single breast and three lesions. Regarding morphology, 58 lesions were regular in appearance and 60 were irregular, of which 50 had a burr sign or sharp angle sign. Strengthening methods included 52 cases of homogeneous strengthening, 3 of annular strengthening and 2 of cluster strengthening. Conclusion: A burr margin, local skin thickening, depression, adhesion and axillary lymph node enlargement are reliable MRI signs of breast cancer. When combined with Breast Imaging Reporting and Data System grading, these signs can effectively differentiate between benign and malignant breast tumours and constitute a key reference value for the diagnosis of breast cancer.
Keywords: breast cancer, focus, tumour, lymph gland and MRI.
Full-Text [PDF 917 kb]   (207 Downloads)    
Type of Study: Original Research | Subject: Radiation Biology
References
1. 1. Yang V, Gouveia MJ, Santos J, Koksch B, Amorim I, Gärtner F, Vale N (2020) Breast cancer: insights in disease and influence of drug methotrexate. RSC Medicinal Chemistry, 11(6):646-664. [DOI:10.1039/D0MD00051E]
2. Basu P and Maier C (2018) Phytoestrogens and breast cancer: In vitro anticancer activities of isoflavones, lignans, coumestans, stilbenes and their analogs and derivatives. Biomedecine & Pharmacotherapie, 107:1648-1666. [DOI:10.1016/j.biopha.2018.08.100]
3. Chen W, Zheng R, Baade P, Zhang S, Zeng H, Bray F, Jemal A, et al (2016) Cancer statistics in China, 2015. CA: a cancer journal for clinicians, 66(2): 115-132. [DOI:10.3322/caac.21338]
4. Fan L, Strasser-Weippl K, Li J, St Louis J, Finkelstein D, Yu K, Chen W, et al. (2014) Breast cancer in China. The Lancet Oncology, 15(7): e279-e289. [DOI:10.1016/S1470-2045(13)70567-9]
5. Sauter ER (2018) Breast Cancer Prevention: Current Approaches and Future Directions. Eur J Breast Health, 14(2): 64-71. [DOI:10.5152/ejbh.2018.3978]
6. Sequeira M, Luz R, Alvarez MJ (2022) The Practice of Physical Activity After Breast Cancer Treatments: A Qualitative Study Among Portuguese Women. Front Psychol, 2022, 13: 823139. [DOI:10.3389/fpsyg.2022.823139]
7. He H, Zhang G, Zhou H, Lin C, Xu Q, Liu R, Yu B, et al (2022) Differential Efficacy of B-Ultrasound Combined with Molybdenum Target Detection Mode for Breast Cancer Staging and Correlation of Blood Flow Parameters with IGF-1 and IGF-2 Expression Level and Prognosis. Contrast Media Mol Imaging, 2022: 9198626. [DOI:10.1155/2022/9198626]
8. Van-Baelen K, Geukens T, Maetens M, Tjan-Heijnen V, Lord CJ, Linn S, Bidard FC, et al. (2022) Current and future diagnostic and treatment strategies for patients with invasive lobular breast cancer. Ann Oncol, 33(8):769-785. [DOI:10.1016/j.annonc.2022.05.006]
9. Trinh L, Ikeda DM, Miyake KK, Trinh J, Lee KK, Dave H, Lipson J, et al (2019) Challenges in MRI detection of breast cancer: MRI features of benign and malignant conditions of the breast. Am J Roentgenol, 213(2): 269-276.
10. Mann RM, Cho N, Moy L (2019) Breast MRI: State of the Art. Radiology, 292(3): 520-536. [DOI:10.1148/radiol.2019182947]
11. Zhang L, Tang M, Min Z, Lu J, Lei X, Zhang X (2020) Multimodal 3-Dimensional Deep Learning for Automated Breast Tumor Detection and Classification Using Whole MR Volumes. Invest Radiol, 55(6): 363-372.
12. Agarwal S, Sharma U, Mathur S, Seenu V, Parshad R, Jagannathan NR (2018) Quantitative characterization of breast tissues using fast scan magnetic resonance spectroscopic imaging at 3T. Magn Reson Imaging, 50: 49-55. [DOI:10.1016/j.mri.2018.02.004]
13. Pinker K, Shitano F, Sala E, Do RK, Young RJ, Wibmer AG, Hricak H, et al (2018) Background, Incidence, and Predictors of Anti-VEGF Therapy-Induced Complications in Breast Cancer: A Systematic Review and Meta-analysis. Radiology, 286(2): 471-482.
14. Gubern-Mérida A, Martí R, Melendez J, Hauth JLM, Mann RM, Karssemeijer N, Platel B (2016) Automated localization of breast cancer in DCE-MRI. Med Image Anal, 31: 46-57.
15. Tan PH, Ellis I, Allison K, Brogi E, Fox SB, Lakhani S, Lazar AJ, et al (2020) WHO Classification of Tumours Editorial Board. The 2019 World Health Organization classification of tumours of the breast. Histopathology, 77(2):181-185. [DOI:10.1111/his.14091]
16. Aiello M, Cavaliere C, D'Alise AM, D'Amico P, Basso G, Salvatore M, Avallone A, et al (2018) A fully automatic approach in breast cancer diagnosis from MRI images: Clinical validation. Journal of Digital Imaging, 31(6): 896-904.
17. Bahrami N, Hartman SJ, Chang YH, Naranjo A, Meric-Bernstam F, Buchholz TA, Woodward W, et al (2019) Predictive value of dynamic contrast-enhanced magnetic resonance imaging during neoadjuvant chemotherapy for breast cancer. Oncotarget, 10(58): 6189-6199.
18. Grimm LJ, Zhang J, Baker JA, Soo MS, Johnson KS, Mazurowski MA (2018) Relationships Between MRI Breast Imaging-Reporting and Data System (BI-RADS) Lexicon Descriptors and Breast Cancer Molecular Subtypes: Internal Enhancement is Associated with Luminal B Subtype. Breast Journal, 24(5): 715-718. [DOI:10.1111/tbj.12799]
19. Onishi N, Kanao S, Kataoka M, Iima M, Sakaguchi R, Kawai M, Kataoka TR, et al (2019) Apparent diffusion coefficient as a potential surrogate marker for Ki-67 index in mucinous breast carcinoma. Journal of Magnetic Resonance Imaging, 49(4): 1180-1186.
20. Preibsch H, Wanner L, Bahrs SD, Wietek BM, Siegmann-Luz KC, Oberlecher E, Hahn M, et al (2017) Size matters: The influence of training on qualitative lesion characterization with breast MRI. European Radiology, 27(5): 1940-1947.
21. Agarwal S, Sharma U, Mathur S, Seenu V, Parshad R, Jagannathan NR (2021) Role of textural features in the differential diagnosis of malignant and benign breast lesions on DCE-MRI. Magnetic Resonance Imaging, 76: 49-58.
22. Drukker K, Giger ML, Joe BN, Kerlikowske K, Greenwood H, Drukteinis JS, Niell B, et al (2019) Combined Benefit of Quantitative Three-Compartment Breast Image Analysis and Mammography Radiomics in the Classification of Breast Masses in a Clinical Data Set. Radiology, 290(3): 621-628. [DOI:10.1148/radiol.2018180608]
23. Thompson JL, Wright GP (2021) The role of breast MRI in newly diagnosed breast cancer: An evidence-based review. Am J Surg, 221(3):525-528. [DOI:10.1016/j.amjsurg.2020.12.018]
24. Choi JS (2023) Breast Imaging Reporting and Data System (BI-RADS): Advantages and Limitations. J Korean Soc Radiol, 84(1): 3-14. [DOI:10.3348/jksr.2022.0142]
25. Spak DA, Plaxco JS, Santiago L, Dryden MJ, Dogan BE (2017) BI-RADS® fifth edition: A summary of changes. Diagn Interv Imaging, 98(3): 179-190. [DOI:10.1016/j.diii.2017.01.001]
26. Han M, Kim TH, Kang DK, Kim KS, Yim H (2012) Prognostic role of MRI enhancement features in patients with breast cancer: value of adjacent vessel signs and increased ipsilateral whole-breast vascularity. AJR Am J Roentgenol, 2012,199(4): 921-928. [DOI:10.2214/AJR.11.7895]
27. Rauch GM, Adrada BE (2018) Comparison of Breast MR Imaging with Molecular Breast Imaging in Breast Cancer Screening, Diagnosis, Staging, and Treatment Response Evaluation. Magn Reson Imaging Clin N Am, 26(2):273-280. [DOI:10.1016/j.mric.2017.12.009]
28. Lugano R, Ramachandran M, Dimberg A (2020) Tumor angiogenesis: causes, consequences, challenges and opportunities. Cell Mol Life Sci, 77(9): 1745-1770. [DOI:10.1007/s00018-019-03351-7]
29. Majidpoor J, Mortezaee K (2021) Angiogenesis as a hallmark of solid tumors - clinical perspectives. Cell Oncol (Dordr), 44(4):715-737. [DOI:10.1007/s13402-021-00602-3]
30. Penault-Llorca F, Radosevic-Robin N (2017) Ki67 assessment in breast cancer: an update. Pathology, 2017, 49(2): 166-171. [DOI:10.1016/j.pathol.2016.11.006]
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA



XML     Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Feng B, Chen H. Analysis of malignancy signs in breast magnetic resonance imaging. Int J Radiat Res 2024; 22 (3) :545-549
URL: http://ijrr.com/article-1-5549-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 22, Issue 3 (7-2024) Back to browse issues page
International Journal of Radiation Research
Persian site map - English site map - Created in 0.05 seconds with 49 queries by YEKTAWEB 4660