[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 4 (10-2024) ::
Int J Radiat Res 2024, 22(4): 989-985 Back to browse issues page
Analysis of the application value of BI-RADS classification grading diagnosis based on imaging examinations for predicting atypical breast ductal hyperplasia and breast cancer
Z. Jiang , D. Xu , S. Wang , X. Chen , S. Gao , Y. Zhang , J. Ma
Department of General Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu ,210008, China , zhangyinglyy203@163.com
Abstract:   (615 Views)
Background: To investigate the application value of Breast Imaging Reporting and Data System (BI-RADS) classification grading diagnosis based on breast ultrasound, molybdenum target radiography mammography and MRI imaging for predicting atypicalbreast ductal hyperplasia (ADH) and breast cancer (BC). Materials and Methods: Retrospective analysis of patients who visited the Department of Mammary Gynecology and Obstetrics of Nanjing Medical University for breast lumps between January 2015 and July 2021, based on the pathological findings of breast lumps, included 150 patients with benign breast usual ductal hyperplasia (UDH), 100 patients with atypical breast hyperplasia ADH, and 100 patients with breast cancer BC. The masses were evaluated and graded according to the fifth edition of the BI-RADS criteria, and the receiver operating characteristic (ROC) curves) were drawn based on ultrasound, molybdenum target radiography mammography, and MRI for BI-RADS grading to identify atypical hyperplasia (ADH) and breast cancer and the feasibility of the three imaging methods for predicting breast atypical hyperplasia  ADH and breast cancer BC was compared. Results: The best cut-off value for breast ultrasound prediction of breast atypical hyperplasia ADH and breast cancer BC was BI-RADS grade 3 and the best cut-off value for molybdenum target radiography mammography and MRI prediction of breast atypical hyperplasia ADH and breast cancer BC was BI-RADS grade 4A, with corresponding area under the curve (AUC) of 0.691, 0.757, 0.866; the Jorden index was 0.363, 0.448, 0.662; the sensitivity was 56.30%, 48.20%, 71.20%; specificity 80.00%, 96.60%, 95.00%; positive predictive value 78.87%, 97.22%, 98.11%; negative predictive value 57.97%, 53.43%, 47.50%, respectively. Conclusion: BI-RADs classification grading diagnosis based on imaging examination has a high value in predicting breast dysplasia  ADH and breast cancer BC. BI-RADs classification grading can be given priority in clinical prediction of breast dysplasia ADH and breast cancer BC to reduce unnecessary invasive examination.
Keywords: Comprehensive nursing, lung cancer, radiotherapy, respiratory function test, quality of life, self-care ability.
Full-Text [PDF 577 kb]   (152 Downloads)    
Type of Study: Original Research | Subject: Radiation Biology
References
1. 1. Lei S, Zheng R, Zhang S, et al. (2021) Global patterns of breast cancer incidence and mortality: A population‐based cancer registry data analysis from 2000 to 2020. Cancer Communications, 41(11): 1183-1194. [DOI:10.1002/cac2.12207] [PMID] []
2. Eshaghi M (2020) The effect of pain management on pain reduction in women with breast cancer. Sjmshm, 2(2):1-5. [DOI:10.29252/sjmshm.2.2.1]
3. He Z, Chen Z, Tan M, et al. (2020) A review on methods for diagnosis of breast cancer cells and tissues. Cell Proliferation, 53(7): e12822. [DOI:10.1111/cpr.12822] [PMID] []
4. Liberman L and Menell JH (2002) Breast imaging reporting and data system (BI-RADS). Radiologic Clinics, 40(3): 409-430. [DOI:10.1016/S0033-8389(01)00017-3]
5. Orel S (2008) Who should have breast magnetic resonance imaging evaluation? Journal of Clinical Oncology, 26(5): 703-711. [DOI:10.1200/JCO.2007.14.3594] [PMID]
6. Magny SJ, Shikhman R and Keppke AL (2022) Breast imaging reporting and data system. In StatPearls [Internet]: StatPearls publishing.
7. Said SM, Visscher DW, Nassar A, et al. (2015) Flat epithelial atypia and risk of breast cancer: a Mayo cohort study. Cancer, 121(10):1548-1555. [DOI:10.1002/cncr.29243] [PMID] []
8. Rudin AV, Hoskin TL, Fahy A, et al. (2017) Flat epithelial atypia on core biopsy and upgrade to cancer: a systematic review and meta-analysis. Annals of Surgical Oncology, 24: 3549-3558. [DOI:10.1245/s10434-017-6059-0] [PMID]
9. Rageth CJ, O'Flynn EA, Pinker K, et al. (2019) Second international consensus conference on lesions of uncertain malignant potential in the breast (B3 lesions). Breast Cancer Research and Treatment, 174: 279-296. [DOI:10.1007/s10549-018-05071-1] [PMID] []
10. Pinder S, Shaaban A, Deb R, et al. (2018) NHS Breast Screening multidisciplinary working group guidelines for the diagnosis and management of breast lesions of uncertain malignant potential on core biopsy (B3 lesions). Clinical radiology, 73(8): 682-692. [DOI:10.1016/j.crad.2018.04.004] [PMID]
11. Zubor P, Kubatka P, Kajo K, et al. (2019) Why the gold standard approach by mammography demands extension by multiomics? Application of liquid biopsy miRNA profiles to breast cancer disease management. International Journal of Molecular Sciences, 20(12): 2878. [DOI:10.3390/ijms20122878] [PMID] []
12. Cykowska A, Marano L, D'Ignazio A, et al. (2020) New technologies in breast cancer sentinel lymph node biopsy; from the current gold standard to artificial intelligence. Surgical Oncology, 34: 324-335. [DOI:10.1016/j.suronc.2020.06.005] [PMID]
13. Hartmann LC, Degnim AC, Santen RJ, et al. (2015) Atypical hyperplasia of the breast-risk assessment and management options. New England Journal of Medicine, 372(1): 78-89. [DOI:10.1056/NEJMsr1407164] [PMID] []
14. Jung HK, Kuzmiak CM, Kim KW, et al. (2017) Potential use of American College of Radiology BI-RADS mammography atlas for reporting and assessing lesions detected on dedicated breast CT imaging: preliminary study. Academic Radiology, 24(11): 1395-1401. [DOI:10.1016/j.acra.2017.06.003] [PMID]
15. D'Orsi C, Bassett L, Feig S (2018) Breast imaging reporting and data system (BI-RADS). Breast imaging atlas, 4th edn. American College of Radiology, Reston. [DOI:10.1093/med/9780190270261.003.0005]
16. Berg WA, Campassi C, Langenberg P, et al. (2000) Breast imaging reporting and data system: Inter-and intraobserver variability in feature analysis and final assessment. American Journal of Roentgenology, 174(6): 1769-1777. [DOI:10.2214/ajr.174.6.1741769] [PMID]
17. Sirous M, Shahnani PS, Sirous A (2018) Investigation of frequency distribution of breast imaging reporting and data system (BIRADS) Classification and epidemiological factors related to breast cancer in Iran: A 7-year Study (2010-2016). Advanced Biomedical Research, 7. [DOI:10.4103/abr.abr_161_17] [PMID] []
18. Eghtedari M, Chong A, Rakow-Penner R, et al. (2021) Current status and future of BI-RADS in multimodality imaging, from the AJR special series on radiology reporting and data systems. American Journal of Roentgenology, 216(4): 860-873. [DOI:10.2214/AJR.20.24894] [PMID]
19. Tollens F, Baltzer PA, Dietzel M, et al. (2021) Cost-effectiveness of MR-mammography in breast cancer screening of women with extremely dense breasts after two rounds of screening. Frontiers in Oncology, 11: 724543. [DOI:10.3389/fonc.2021.724543] [PMID] []
20. Hu Y, Zhang Y, Cheng J (2019) Diagnostic value of molybdenum target combined with DCE-MRI in different types of breast cancer. Oncology Letters, 18(4): 4056-4063. [DOI:10.3892/ol.2019.10746] [PMID] []
21. Gu WQ, Cai SM, Liu WD, et al. (2022) Combined molybdenum target X-ray and magnetic resonance imaging examinations improve breast cancer diagnostic efficacy. World Journal of Clinical Cases, 10(2): 485. [DOI:10.12998/wjcc.v10.i2.485] [PMID] []
22. Kaiser CG, Dietzel M, Vag T, et al. (2021) Cost-effectiveness of MR-mammography vs. conventional mammography in screening patients at intermediate risk of breast cancer-A model-based economic evaluation. European Journal of Radiology, 136: 109355. [DOI:10.1016/j.ejrad.2020.109355] [PMID]
23. Tollens F, Baltzer PA, Dietzel M, et al. (2021) Cost-effectiveness of digital breast tomosynthesis vs. abbreviated breast MRI for screening women with intermediate risk of breast cancer-how low-cost must MRI be? Cancers, 13(6): 1241. [DOI:10.3390/cancers13061241] [PMID] []
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:

Jiang Z, Xu D, Wang S, Chen X, Gao S, Zhang Y et al . Analysis of the application value of BI-RADS classification grading diagnosis based on imaging examinations for predicting atypical breast ductal hyperplasia and breast cancer. Int J Radiat Res 2024; 22 (4) :989-985
URL: http://ijrr.com/article-1-5780-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 4 (10-2024) Back to browse issues page
International Journal of Radiation Research
Persian site map - English site map - Created in 0.11 seconds with 50 queries by YEKTAWEB 4710