The Diagnostic Value of MRI for Architectural Distortion Categorized As BI-RADS Category 3-4 by Mammography

Overview

Journal Gland Surg

Publisher AME Publishing Company

Specialty Endocrinology

Date 2020 Sep 21

PMID 32953609

Citations 5

Authors

Haibing Mei

Jian Xu

Gang Yao

Ying Wang

Affiliations

Soon will be listed here.

Abstract

Background: Architectural distortion is a common mammographic sign that can be benign or malignant. This study investigated the diagnostic value of magnetic resonance imaging (MRI) for architectural distortions that were category 3-4 under the breast imaging reporting and data system (BI-RADS) by mammography.

Methods: We retrospectively analyzed 219 pathologically confirmed lesions in 208 patients who had BI-RADS category 3-4 architectural distortion in mammography images. Two radiologists described and categorized the architectural distortion and assigned the BI-RADS categories to the corresponding lesions on MRI images. Using the postoperative pathological diagnosis as the gold standard, we performed receiver operating characteristic (ROC) analysis for the efficacy of mammography and MRI in differentiating patients with benign or malignant lesions.

Results: Totally 151 benign lesions and 68 malignant lesions were confirmed. According to the full-field digital mammography (FFDM), 82 lesions were in BI-RADS category 3, 104 lesions in 4A, 29 lesions in 4B, and 4 lesions in 4C. The positive predictive values of FFDM for BI-RADS categories 3, 4A, 4B, and 4C were 13.4% (11/82), 27.9% (29/104), 82.8% (24/29), and 100.0% (4/4), respectively. According to MRI, 59 lesions were in BI-RADS categories 1-2, 87 lesions in 3, 39 lesions in 4, and 34 lesions in 5, with their positive predictive values being 0.0% (0/58), 2.3% (2/87), 89.7% (35/39), and 100.0% (34/34), respectively. The area under the ROC curve (AUC) of breast benign and malignant lesions differentiated by FFDM was 0.647, and the diagnostic sensitivity, specificity, and Youden index were 86.3%, 41.7%, and 0.280, respectively. The AUC of FFDM combined with dynamic contrast-enhanced MRI (DCE-MRI) in differentiating breast benign malignant lesions was 0.851, and the diagnostic sensitivity, specificity, and Youden index were 89.2%, 80.7%, and 0.699, respectively. The AUC of FFDM combined with DCE-MRI and the apparent diffusion coefficient (ADC) in differentiating benign malignant lesions was 0.983, and the diagnostic sensitivity, specificity, and Youden index were 98.1%, 97.5%, and 0.956, respectively.

Conclusions: MRI can improve the diagnostic efficiency of mammography in diagnosing BI-RADS category 3-4 architectural distortions and can help in the qualitative diagnosis of architectural distortion lesions.

Citing Articles

A comprehensive analysis of imaging features and clinical characteristics to differentiate malignant from non-malignant mammographic architectural distortion.

Zhang S, Shao Z, Yi H, Liu P, Liu F, Lu H Gland Surg. 2024; 13(5):669-683.

PMID: 38845839 PMC: 11150194. DOI: 10.21037/gs-24-110.

Contrast-enhanced mammography in the management of breast architectural distortions and avoidance of unnecessary biopsies.

Bellini C, Pugliese F, Bicchierai G, Amato F, de Benedetto D, di Naro F Breast Cancer. 2024; 31(5):851-857.

PMID: 38811515 DOI: 10.1007/s12282-024-01599-x.

Unveiling the potential of breast MRI: a game changer for BI-RADS 4A microcalcifications.

Li S, Lin Y, Liu G, Shao Z, Yang Y Breast Cancer Res Treat. 2024; 206(2):425-435.

PMID: 38664289 DOI: 10.1007/s10549-024-07320-y.

Prediction of pathological complete response to neoadjuvant chemotherapy in patients with breast cancer using a combination of contrast-enhanced ultrasound and dynamic contrast-enhanced magnetic resonance imaging.

Han X, Yang H, Jin S, Sun Y, Zhang H, Shan M Cancer Med. 2022; 12(2):1389-1398.

PMID: 35822639 PMC: 9883403. DOI: 10.1002/cam4.5019.

Visualization positioning-guided biopsy of suspicious breast microcalcifications: a retrospective cohort study.

Zhang L, Cheng M, Chen Y, Zhuang X, Yang C, Ji F Ann Transl Med. 2021; 9(21):1620.

PMID: 34926664 PMC: 8640910. DOI: 10.21037/atm-21-4496.

References

Pereira F, Martins G, Figueiredo E, Domingues M, Domingues R, Barbosa da Fonseca L . Assessment of breast lesions with diffusion-weighted MRI: comparing the use of different b values. AJR Am J Roentgenol. 2009; 193(4):1030-5. DOI: 10.2214/AJR.09.2522. View

Partridge S, Rahbar H, Murthy R, Chai X, Kurland B, DeMartini W . Improved diagnostic accuracy of breast MRI through combined apparent diffusion coefficients and dynamic contrast-enhanced kinetics. Magn Reson Med. 2011; 65(6):1759-67. PMC: 3201817. DOI: 10.1002/mrm.22762. View

Schueller G, Riedl C, Mallek R, Eibenberger K, Langenberger H, Kaindl E . Image quality, lesion detection, and diagnostic efficacy in digital mammography: full-field digital mammography versus computed radiography-based mammography using digital storage phosphor plates. Eur J Radiol. 2007; 67(3):487-96. DOI: 10.1016/j.ejrad.2007.08.016. View

Stadlbauer A, Bernt R, Gruber S, Bogner W, Pinker K, van der Riet W . Diffusion-weighted MR imaging with background body signal suppression (DWIBS) for the diagnosis of malignant and benign breast lesions. Eur Radiol. 2009; 19(10):2349-56. DOI: 10.1007/s00330-009-1426-2. View

Ong E . Preoperative imaging for breast conservation surgery-do we need more than conventional imaging for local disease assessment?. Gland Surg. 2019; 7(6):554-559. PMC: 6323257. DOI: 10.21037/gs.2018.08.05. View

Pijnappel R, Peeters P, Hendriks J, Mali W . Reproducibility of mammographic classifications for non-palpable suspect lesions with microcalcifications. Br J Radiol. 2004; 77(916):312-4. DOI: 10.1259/bjr/84593467. View

Kul S, Cansu A, Alhan E, Dinc H, Gunes G, Reis A . Contribution of diffusion-weighted imaging to dynamic contrast-enhanced MRI in the characterization of breast tumors. AJR Am J Roentgenol. 2010; 196(1):210-7. DOI: 10.2214/AJR.10.4258. View

Ei Khouli R, Jacobs M, Mezban S, Huang P, Kamel I, Macura K . Diffusion-weighted imaging improves the diagnostic accuracy of conventional 3.0-T breast MR imaging. Radiology. 2010; 256(1):64-73. PMC: 2897691. DOI: 10.1148/radiol.10091367. View

Boyer B, Russ E . Anatomical-radiological correlations: architectural distortions. Diagn Interv Imaging. 2014; 95(2):134-40. DOI: 10.1016/j.diii.2014.01.003. View

10.

Raichand S, Dunn A, Ong M, Bourgeois F, Coiera E, Mandl K . Conclusions in systematic reviews of mammography for breast cancer screening and associations with review design and author characteristics. Syst Rev. 2017; 6(1):105. PMC: 5441061. DOI: 10.1186/s13643-017-0495-6. View

11.

Mendez A, Cabanillas F, Echenique M, Malekshamran K, Perez I, Ramos E . Mammographic features and correlation with biopsy findings using 11-gauge stereotactic vacuum-assisted breast biopsy (SVABB). Ann Oncol. 2004; 15(3):450-4. DOI: 10.1093/annonc/mdh088. View

12.

Lo G, Ai V, Chan J, Li K, Cheung P, Wong T . Diffusion-weighted magnetic resonance imaging of breast lesions: first experiences at 3 T. J Comput Assist Tomogr. 2009; 33(1):63-9. DOI: 10.1097/RCT.0b013e318165dc6b. View

13.

Brnic D, Brnic D, Simundic I, Vanjaka Rogosic L, Tadic T . MRI and comparison mammography: a worthy diagnostic alliance for breast microcalcifications?. Acta Radiol. 2015; 57(4):413-21. DOI: 10.1177/0284185115585036. View

14.

Shaheen R, Schimmelpenninck C, Stoddart L, Raymond H, Slanetz P . Spectrum of diseases presenting as architectural distortion on mammography: multimodality radiologic imaging with pathologic correlation. Semin Ultrasound CT MR. 2011; 32(4):351-62. DOI: 10.1053/j.sult.2011.03.008. View

15.

Chopier J, Roedlich M, Mathelin C . [Breast imaging of mass, architectural distortion and asymmetry: Clinical practice guidelines]. J Gynecol Obstet Biol Reprod (Paris). 2015; 44(10):947-59. DOI: 10.1016/j.jgyn.2015.09.056. View

16.

Durand M, Wang S, Hooley R, Raghu M, Philpotts L . Tomosynthesis-detected Architectural Distortion: Management Algorithm with Radiologic-Pathologic Correlation. Radiographics. 2016; 36(2):311-21. DOI: 10.1148/rg.2016150093. View

17.

Liberman L, Menell J . Breast imaging reporting and data system (BI-RADS). Radiol Clin North Am. 2002; 40(3):409-30, v. DOI: 10.1016/s0033-8389(01)00017-3. View

18.

Yili Z, Xiaoyan H, Hongwen D, Yun Z, Xin C, Peng W . The value of diffusion-weighted imaging in assessing the ADC changes of tissues adjacent to breast carcinoma. BMC Cancer. 2009; 9:18. PMC: 2633008. DOI: 10.1186/1471-2407-9-18. View

19.

Rangayyan R, Banik S, Desautels J . Computer-aided detection of architectural distortion in prior mammograms of interval cancer. J Digit Imaging. 2010; 23(5):611-31. PMC: 3046672. DOI: 10.1007/s10278-009-9257-x. View