Comparison of Diagnostic Accuracies of USG, MG and MRI Modalities
Defined with BI-RADS Classification System

Serdar      Serinsöz; Remzi      Akturk

doi:10.2174/1573405618666220322112133

Abstract

Background: BI-RADS classification facilitates the information related to diagnosis for radiologists. It allows radiologists to interpret mammograms accurately.

Objective: We aimed to compare the diagnostic accuracy of the three modalities, USG, MG and MRI, with the BI-RADS classification system according to their imaging findings.

Methods: This study included 82 patients who underwent Tru-Cut biopsy under the guidance of USG, MG, and MRI. Mammography, sonography and MRI were performed in the prone position.

Results: Of the patients, 46.3%, 14.6%, and 39.0% were assessed in 4A, 4B, and 5 MRI BI-RADS categories, respectively. Based on the variable surgical/pathological diagnosis, 50%, 28.0%, and 22.0% of the patients were categorized as having malignant findings, benign findings, and infectioninflammation- mastitis, respectively. The determination of the endpoints for the parameter of long-axis diameter (mm) was found to be statistically significant according to ROC analysis as a gold standard based on specificity levels of benign and malignant findings (p<0.05). A significant correlation was detected between the gold standard and the categorical variable MRI BI-RADS (χ²=46.380, p<0.01).

Conclusion: When the specificity and sensitivity of all three modalities in surgical/pathological diagnosis were compared, MRI was concluded to be superior to the other modalities and a valuable method for the prediction of lesion malignancy and determination of biopsy prediction and priority.

Keywords: BI-RADS, mammography, USG, MRI, modalities, malignancy.

[1] 
Pesce K, Orruma MB, Hadad C, Bermúdez Cano Y, Secco R, Cernadas A. BI-RADS terminology for mammography reports: What residents need to know. Radiographics  2019; 39(2): 319-20.
[http://dx.doi.org/10.1148/rg.2019180068] [PMID:  30844352] 
[2] 
Mercado CL. BI-RADS update. Radiol Clin North Am  2014; 52(3): 481-7.
[http://dx.doi.org/10.1016/j.rcl.2014.02.008] [PMID:  24792650] 
[3] 
Spak DA, Plaxco JS, Santiago L, et al. BI-RADS((R)) fifth edition: A
summary of changes. Diagn Interv Imaging  2017; 98(3): 179-90.
[http://dx.doi.org/10.1016/j.diii.2017.01.001] 
[4] 
Shin K, Phalak K, Hamame A, et al. Interpretation of breast MRI
utilizing the BI-RADS fifth edition lexicon: How are we doing and
where are we headed? Curr Probl Diagn Radiol 2017; 46(1): 26-34.
[http://dx.doi.org/10.1067/j.cpradiol.2015.12.001] 
[5] 
Magny SJ, Shikhman R, Keppke AL. Breast Imaging Reporting and Data System. Treasure Island, FL: StatPearls Publishing 2021.
[6] 
Patenaude Y, Pugash D, Lim K, et al. The use of magnetic resonance imaging in the obstetric patient. J Obstet Gynaecol Can  2014; 36(4): 349-63.
[http://dx.doi.org/10.1016/S1701-2163(15)30612-5] [PMID:  24798674] 
[7] 
Liberman L, Mason G, Morris EA, Dershaw DD. Does size matter? Positive predictive value of MRI-detected breast lesions as a function of lesion size. AJR Am J Roentgenol  2006; 186(2): 426-30.
[http://dx.doi.org/10.2214/AJR.04.1707] [PMID:  16423948] 
[8] 
Smith H, Chetlen AL, Schetter S, Mack J, Watts M, Zhu JJ. PPV(3) of suspicious breast MRI findings. Acad Radiol  2014; 21(12): 1553-62.
[http://dx.doi.org/10.1016/j.acra.2014.07.013] [PMID:  25262952] 
[9] 
de Almeida JR, Gomes AB, Barros TP, Fahel PE, Rocha Mde S. Predictive performance of BI-RADS magnetic resonance imaging descriptors in the context of suspicious (category 4) findings. Radiol Bras  2016; 49(3): 137-43.
[http://dx.doi.org/10.1590/0100-3984.2015.0021] [PMID:  27403012] 
[10] 
Liberman L, Morris EA, Lee MJ, et al. Breast lesions detected on MR imaging: Features and positive predictive value. AJR Am J Roentgenol  2002; 179(1): 171-8.
[http://dx.doi.org/10.2214/ajr.179.1.1790171] [PMID:  12076929] 
[11] 
Tozaki M, Igarashi T, Fukuda K. Positive and negative predictive values of BI-RADS-MRI descriptors for focal breast masses. Magn Reson Med Sci  2006; 5(1): 7-15.
[http://dx.doi.org/10.2463/mrms.5.7] [PMID:  16785722] 
[12] 
Stomper P, Leibowich S, Meyer J. The prevalence and distribution of well-circumscribed nodules on screening mammography: Analysis of 1500 mammograms. Breast Dis  1991; 4: 197-203.
[13] 
Sarica O, Uluc F. Additional diagnostic value of MRI in patients with suspicious breast lesions based on ultrasound. Br J Radiol  2014; 87(1041): 20140009.
[http://dx.doi.org/10.1259/bjr.20140009] [PMID:  24983629] 
[14] 
Dorrius MD, Pijnappel RM, Sijens PE, van der Weide MC, Oudkerk M. The negative predictive value of breast magnetic resonance imaging in noncalcified BIRADS 3 lesions. Eur J Radiol  2012; 81(2): 209-13.
[http://dx.doi.org/10.1016/j.ejrad.2010.12.046] [PMID:  21251784] 
[15] 
Gökalp G, Topal U. MR imaging in probably benign lesions (BI-RADS category 3) of the breast. Eur J Radiol  2006; 57(3): 436-44.
[http://dx.doi.org/10.1016/j.ejrad.2005.10.004] [PMID:  16316732] 
[16] 
Borders MH. Breast MRI and BI-RADS category 3: Is it appropriate? Breast J  2018; 24(2): 107-8.
[http://dx.doi.org/10.1111/tbj.12869] [PMID:  29508933] 
[17] 
Panigrahi B, Harvey SC, Mullen LA, et al. Characteristics and outcomes of BI-RADS 3 lesions on breast MRI. Clin Breast Cancer  2019; 19(1): e152-9.
[http://dx.doi.org/10.1016/j.clbc.2018.08.011] [PMID:  30268764] 
[18] 
Edmonds CE, Lamb LR, Mercaldo SF, Sippo DA, Burk KS, Lehman CD. Frequency and cancer yield of BI-RADS category 3 lesions de-tected at high-risk screening breast MRI. AJR Am J Roentgenol  2020; 214(2): 240-8.
[http://dx.doi.org/10.2214/AJR.19.21778] [PMID:  31799867] 
[19] 
D’Orsi CJ. 2013 ACR BI-RADS Atlas: Breast Imaging Reporting and Data System.  5th ed. Reston, VA: American College of Radiology 2014.
[20] 
Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1). Eur J Cancer  2009; 45(2): 228-47.
[http://dx.doi.org/10.1016/j.ejca.2008.10.026] [PMID:  19097774] 

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DOI https://dx.doi.org/10.2174/1573405618666220322112133	Print ISSN 1573-4056
Publisher Name Bentham Science Publisher	Online ISSN 1875-6603

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Comparison of Diagnostic Accuracies of USG, MG and MRI Modalities Defined with BI-RADS Classification System

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