1. Mann RM, , Cho N, , Moy L. Breast MRI: state of the art. Radiology 2019; 292: 520–36. doi: https://doi.org/10.1148/radiol.2019182947

2. Riedl CC, , Luft N, , Bernhart C, , Weber M, , Bernathova M, , Tea M-KM, , et al.. Triple-modality screening trial for familial breast cancer underlines the importance of magnetic resonance imaging and questions the role of mammography and ultrasound regardless of patient mutation status, age, and breast density. J Clin Oncol 2015; 33: 1128–35. doi: https://doi.org/10.1200/JCO.2014.56.8626

3. Kuhl CK, , Strobel K, , Bieling H, , Leutner C, , Schild HH, , Schrading S. Supplemental breast MR imaging screening of women with average risk of breast cancer. Radiology 2017; 283: 361–70. doi: https://doi.org/10.1148/radiol.2016161444

4. van Zelst JCM, , Mus RDM, , Woldringh G, , Rutten MJCM, , Bult P, , Vreemann S, , et al.. Surveillance of women with the BRCA1 or BRCA2 mutation by using biannual automated breast us, MR imaging, and mammography. Radiology 2017; 285: 376–88. doi: https://doi.org/10.1148/radiol.2017161218

5. Vreeman S, , Gubern-Merida A, , Schlooz-vries MS, , Bult P, , Van GC, , Hoogerbrugge N, , et al.. Influence of risk category and screening round on the performance of an MR imaging mutation and other women at. Radiology [Internet] 2018; 286: 443–51. doi: https://doi.org/10.1148/radiol.2017170458

6. Bakker MF, , de Lange SV, , Pijnappel RM, , Mann RM, , Peeters PHM, , Monninkhof EM, , et al.. Supplemental MRI screening for women with extremely dense breast tissue. N Engl J Med 2019; 381: 2091–2102. doi: https://doi.org/10.1056/NEJMoa1903986

7. Geach R, , Jones LI, , Harding SA, , Marshall A, , Taylor-Phillips S, , McKeown-Keegan S, , et al.. The potential utility of abbreviated breast MRI (FAST MRI) as a tool for breast cancer screening: a systematic review and meta-analysis. Clin Radiol 2021; 76: 154. doi: https://doi.org/10.1016/j.crad.2020.08.032

8. Baxter GC, , Selamoglu A, , Mackay JW, , Bond S, , Gray E, , Gilbert FJ. A meta-analysis comparing the diagnostic performance of abbreviated MRI and A full diagnostic protocol in breast cancer. Clin Radiol 2021; 76: 154. doi: https://doi.org/10.1016/j.crad.2020.08.036

9. Hernández ML, , Osorio S, , Florez K, , Ospino A, , Díaz GM. Abbreviated magnetic resonance imaging in breast cancer: a systematic review of literature. Eur J Radiol Open 2021; 8: 100307. doi: https://doi.org/10.1016/j.ejro.2020.100307

10. Warner E, , Hill K, , Causer P, , Plewes D, , Jong R, , Yaffe M, , et al.. Prospective study of breast cancer incidence in women with a BRCA1 or BRCA2 mutation under surveillance with and without magnetic resonance imaging. J Clin Oncol 2011; 29: 1664–69. doi: https://doi.org/10.1200/JCO.2009.27.0835

11. Evans DG, , Harkness EF, , Howell A, , Wilson M, , Hurley E, , Holmen MM, , et al.. Intensive breast screening in BRCA2 mutation carriers is associated with reduced breast cancer specific and all cause mortality. Hered Cancer Clin Pract 2016; 14: 8. doi: https://doi.org/10.1186/s13053-016-0048-3

12. Saadatmand S, , Obdeijn I-M, , Rutgers EJ, , Oosterwijk JC, , Tollenaar RA, , Woldringh GH, , et al.. Survival benefit in women with BRCA1 mutation or familial risk in the MRI screening study (MRISC). Int J Cancer 2015; 137: 1729–38. doi: https://doi.org/10.1002/ijc.29534

13. Vinnicombe S. How I report breast magnetic resonance imaging studies for breast cancer staging and screening. Cancer Imaging 2016; 16: 17. doi: https://doi.org/10.1186/s40644-016-0078-0

14. Phi X-A, , Houssami N, , Obdeijn I-M, , Warner E, , Sardanelli F, , Leach MO, , et al.. Magnetic resonance imaging improves breast screening sensitivity in BRCA mutation carriers age ≥ 50 years: evidence from an individual patient data meta-analysis. J Clin Oncol 2015; 33: 349–56. doi: https://doi.org/10.1200/JCO.2014.56.6232

15. Phi X-A, , Houssami N, , Hooning MJ, , Riedl CC, , Leach MO, , Sardanelli F, , et al.. Accuracy of screening women at familial risk of breast cancer without a known gene mutation: individual patient data meta-analysis. Eur J Cancer 2017; 85: 31–38. doi: https://doi.org/10.1016/j.ejca.2017.07.055

16. Mahoney MC, , Gatsonis C, , Hanna L, , DeMartini WB, , Lehman C. Positive predictive value of BI-RADS MR imaging. Radiology 2012; 264: 51–58. doi: https://doi.org/10.1148/radiol.12110619

17. Gutierrez RL, , DeMartini WB, , Silbergeld JJ, , Eby PR, , Peacock S, , Javid SH, , et al.. High cancer yield and positive predictive value: outcomes at a center routinely using preoperative breast MRI for staging. American Journal of Roentgenology 2011; 196: W93–99. doi: https://doi.org/10.2214/AJR.10.4804

18. Smith H, , Chetlen AL, , Schetter S, , Mack J, , Watts M, , Zhu J (Jay). PPV3 of suspicious breast MRI findings. Academic Radiology 2014; 21: 1553–62. doi: https://doi.org/10.1016/j.acra.2014.07.013

19. Lee JM, , Ichikawa L, , Valencia E, , Miglioretti DL, , Wernli K, , Buist DSM, , et al.. Performance benchmarks for screening breast MR imaging in community practice. Radiology 2017; 285: 44–52. doi: https://doi.org/10.1148/radiol.2017162033

20. Strigel RM, , Rollenhagen J, , Burnside ES, , Elezaby M, , Fowler AM, , Kelcz F, , et al.. Screening breast MRI outcomes in routine clinical practice: comparison to BI-RADS benchmarks. Acad Radiol [Internet] 2018; 24: 411–17. doi: https://doi.org/10.1016/j.acra.2016.10.014

21. Royal College of Radiologists. Guidance on screening and symptomatic breast imaging. Fourth edition. 2019. Available from: https://www.rcr.ac.uk/system/files/publication/field_publication_files/bfcr199-guidance-on-screening-and-symptomatic-breast-imaging.pdf

22. NICE Guidelines. Familial breast cancer: classification, care and managing breast cancer and related risks in people with a family history of breast cancer. UK: National Institute for Health and Care Excellence; 2017.

23. Public Health England. Technical guidelines for magnetic resonance imaging (MRI) for the surveillance of women at higher risk of developing breast cancer. (NHSBSP Publication No 68). Gov.Uk. 2012. Available from: https://www.gov.uk/government/publications/nhs-breast-screening-using-mri-with-higher-risk-women

24. Mihalco SP, , Keeling SB, , Murphy SF, , O’Keeffe SA. Comparison of the utility of clinical breast examination and MRI in the surveillance of women with a high risk of breast cancer. Clin Radiol 2020; 75: 194–99. doi: https://doi.org/10.1016/j.crad.2019.09.145

25. Blanks RG, , Given-Wilson R, , Alison R, , Jenkins J, , Wallis MG. An analysis of 11.3 million screening tests examining the association between needle biopsy rates and cancer detection rates in the english NHS breast cancer screening programme. Clin Radiol 2019; 74: 384–89. doi: https://doi.org/10.1016/j.crad.2019.01.015

26. Veenhuizen SGA, , de Lange SV, , Bakker MF, , Pijnappel RM, , Mann RM, , Monninkhof EM, , et al.. Supplemental breast MRI for women with extremely dense breasts: results of the second screening round of the dense trial. Radiology 2021; 299: 278–86. doi: https://doi.org/10.1148/radiol.2021203633

27. Blanks RG, , Wallis MG, , Alison RJ, , Given-Wilson RM. An analysis of screen-detected invasive cancers by grade in the english breast cancer screening programme: are we failing to detect sufficient small grade 3 cancers? Eur Radiol 2021; 31: 2548–58. doi: https://doi.org/10.1007/s00330-020-07276-9

28. Lynge E, , Bak M, , Von EM, , Kroman N, , Lernevall A, , Mogensen NB, , et al.. Denmark. BMC Cancer 2017; 17: 1–9. doi: https://doi.org/10.1186/s12885-017-3929-6

29. American College of Radiology. III. REPORTING SYSTEM. In: American College of Radiology, editor. In: ACR BI-RADS Atlas - Breast MRI. ; 2013., pp. 125–43. Available from: https://www.acr.org/-/media/ACR/Files/RADS/BI-RADS/MRI-Reporting.pdf

30. Macura KJ, , Ouwerkerk R, , Jacobs MA, , Bluemke DA. Patterns of enhancement on breast Mr images: interpretation and imaging pitfalls. Radiographics 2006; 26: 1719–34. doi: https://doi.org/10.1148/rg.266065025

31. Gilbert FJ, , Warren RML, , Kwan-Lim G, , Thompson DJ, , Eeles RA, , Evans DG, , et al.. Cancers in BRCA1 and BRCA2 carriers and in women at high risk for breast cancer: MR imaging and mammographic features. Radiology 2009; 252: 358–68. doi: https://doi.org/10.1148/radiol.2522081032

32. Maxwell AJ, , Lim YY, , Hurley E, , Evans DG, , Howell A, , Gadde S. False-negative MRI breast screening in high-risk women. Clin Radiol 2017; 72: 207–16. doi: https://doi.org/10.1016/j.crad.2016.10.020

33. Luo J, , Hippe DS, , Rahbar H, , Parsian S, , Rendi MH, , Partridge SC. Diffusion tensor imaging for characterizing tumor microstructure and improving diagnostic performance on breast MRI: a prospective observational study. Breast Cancer Res 2019; 21: 102. doi: https://doi.org/10.1186/s13058-019-1183-3

34. Rahbar H, , Zhang Z, , Chenevert TL, , Romanoff J, , Kitsch AE, , Hanna LG, , et al.. Utility of diffusion-weighted imaging to decrease unnecessary biopsies prompted by breast MRI: A trial of the ECOG-ACRIN cancer research group (A6702). Clin Cancer Res 2019; 25: 1756–65. doi: https://doi.org/10.1158/1078-0432.CCR-18-2967

35. Baltzer P, , Mann RM, , Iima M, , Sigmund EE, , Clauser P, , Gilbert FJ, , et al.. Diffusion-weighted imaging of the breast-a consensus and mission statement from the EUSOBI international breast diffusion-weighted imaging working group. Eur Radiol 2020; 30: 1436–50. doi: https://doi.org/10.1007/s00330-019-06510-3

36. Frank L, , Brolund-Napier C, , Sidebottom R, , Lyburn I, , Vinnicombe S. High risk screening breast MRI: is adequate sensitivity possible with acceptable recall rates? Breast Cancer Res 2021; 23: 98. doi: https://doi.org/10.1186/s13058-021-01471-2

37. Dietzel M, , Baltzer PAT. How to use the Kaiser score as a clinical decision rule for diagnosis in multiparametric breast MRI: a pictorial essay. Insights Imaging 2018; 9: 325–35. doi: https://doi.org/10.1007/s13244-018-0611-8

38. Kawai M, , Kataoka M, , Kanao S, , Iima M, , Onishi N, , Ohashi A, , et al.. The value of lesion size as an adjunct to the BI-RADS-MRI 2013 descriptors in the diagnosis of solitary breast masses. Magn Reson Med Sci 2018; 17: 203–10. doi: https://doi.org/10.2463/mrms.mp.2017-0024

39. Woitek R, , Spick C, , Schernthaner M, , Rudas M, , Kapetas P, , Bernathova M, , et al.. A simple classification system (the tree flowchart) for breast MRI can reduce the number of unnecessary biopsies in MRI-only lesions. Eur Radiol 2017; 27: 3799–3809. doi: https://doi.org/10.1007/s00330-017-4755-6

40. Dietzel M, , Krug B, , Clauser P, , Burke C, , Hellmich M, , Maintz D, , et al.. A multicentric comparison of apparent diffusion coefficient mapping and the Kaiser score in the assessment of breast lesions. Invest Radiol 2021; 56: 274–82. doi: https://doi.org/10.1097/RLI.0000000000000739

41. Lunkiewicz M, , Forte S, , Freiwald B, , Singer G, , Leo C, , Kubik-Huch RA. Interobserver variability and likelihood of malignancy for fifth edition BI-RADS MRI descriptors in non-mass breast lesions. Eur Radiol 2020; 30: 77–86. doi: https://doi.org/10.1007/s00330-019-06312-7

42. Onishi N, , Kataoka M, , Kanao S, , Sagawa H, , Iima M, , Nickel MD, , et al.. Ultrafast dynamic contrast-enhanced MRI of the breast using compressed sensing: breast cancer diagnosis based on separate visualization of breast arteries and veins. J Magn Reson Imaging 2018; 47: 97–104. doi: https://doi.org/10.1002/jmri.25747

43. Machida Y, , Shimauchi A, , Kuroki Y, , Tozaki M, , Kato Y, , Hoshi K, , et al.. Single focus on breast magnetic resonance imaging: diagnosis based on kinetic pattern and patient age. Acta Radiol 2017; 58: 652–59. doi: https://doi.org/10.1177/0284185116668212

44. Nunes LW, , Schnall MD, , Orel SG, , Hochman MG, , Langlotz CP, , Reynolds CA, , et al.. Correlation of lesion appearance and histologic findings for the nodes of a breast MR imaging interpretation model. Radiographics 1999; 19: 79–92. doi: https://doi.org/10.1148/radiographics.19.1.g99ja0379

45. Nunes LW, , Schnall MD, , Orel SG. Update of breast MR imaging architectural interpretation model. Radiology 2001; 219: 484–94. doi: https://doi.org/10.1148/radiology.219.2.r01ma44484

46. Clauser P, , Dietzel M, , Weber M, , Kaiser CG, , Baltzer PAT. Motion artifacts, lesion type, and parenchymal enhancement in breast MRI: what does really influence diagnostic accuracy? Acta Radiol 2019; 60: 19–27. doi: https://doi.org/10.1177/0284185118770918

47. Ray KM, , Kerlikowske K, , Lobach IV, , Hofmann MB, , Greenwood HI, , Arasu VA, , et al.. Effect of background parenchymal enhancement on breast MR imaging interpretive performance in community-based practices. Radiology 2018; 286: 822–29. doi: https://doi.org/10.1148/radiol.2017170811

48. Dontchos BN, , Rahbar H, , Partridge SC, , Korde LA, , Lam DL, , Scheel JR, , et al.. Are qualitative assessments of background parenchymal enhancement, amount of fibroglandular tissue on Mr images, and mammographic density associated with breast cancer risk? Radiology 2015; 276: 371–80. doi: https://doi.org/10.1148/radiol.2015142304

49. Liao GJ, , Henze Bancroft LC, , Strigel RM, , Chitalia RD, , Kontos D, , Moy L, , et al.. Background parenchymal enhancement on breast MRI: a comprehensive review. J Magn Reson Imaging 2020; 51: 43–61. doi: https://doi.org/10.1002/jmri.26762

50. Millet I, , Pages E, , Hoa D, , Merigeaud S, , Curros Doyon F, , Prat X, , et al.. Pearls and pitfalls in breast MRI. Br J Radiol 2012; 85: 197–207. doi: https://doi.org/10.1259/bjr/47213729

51. Li J, , Dershaw DD, , Lee CH, , Lee CF, , Joo S, , Morris EA. Breast MRI after conservation therapy: usual findings in routine follow-up examinations. AJR Am J Roentgenol 2010; 195: 799–807. doi: https://doi.org/10.2214/AJR.10.4305

52. Dialani V, , Lai KC, , Slanetz PJ. Mr imaging of the reconstructed breast: what the radiologist needs to know. Insights Imaging 2012; 3: 201–13. doi: https://doi.org/10.1007/s13244-012-0150-7

53. Kim MY, , Suh YJ, , An YY. Imaging surveillance for the detection of ipsilateral local tumor recurrence in patients who underwent oncoplastic breast-conserving surgery with acellular dermal matrix: abbreviated MRI versus conventional mammography and ultrasonography. World J Surg Oncol 2021; 19: 1–10: 290. doi: https://doi.org/10.1186/s12957-021-02403-2

54. Garvey PB, , Buchel EW, , Pockaj BA, , Casey WJ 3rd, , Gray RJ, , Hernández JL, , et al.. DIEP and pedicled TRAM flaps: a comparison of outcomes. Plast Reconstr Surg 2006; 117: 1711–19. doi: https://doi.org/10.1097/01.prs.0000210679.77449.7d

55. Margolis NE, , Morley C, , Lotfi P, , Shaylor SD, , Palestrant S, , Moy L, , et al.. Update on imaging of the postsurgical breast. Radiographics 2014; 34: 642–60. doi: https://doi.org/10.1148/rg.343135059

56. Santen RJ, , Mansel R. Benign breast disorders. N Engl J Med 2005; 353: 275–85. doi: https://doi.org/10.1056/NEJMra035692

57. Guray M, , Sahin AA. Benign breast diseases: classification, diagnosis, and management. Oncologist 2006; 11: 435–49. doi: https://doi.org/10.1634/theoncologist.11-5-435

58. Rosen M, , Siegelman E. Body MRI (Chapter 10: MRI of the Breast). Internet]. WB Saunders. 2005. doi: https://doi.org/10.1016/B978-0-7216-3740-2.50015-7

59. Hines N, , Slanetz PJ, , Eisenberg RL. Cystic masses of the breast. AJR Am J Roentgenol 2010; 194: W122–33. doi: https://doi.org/10.2214/AJR.09.3688

60. Daimiel Naranjo I, , Gibbs P, , Reiner JS, , Lo Gullo R, , Sooknanan C, , Thakur SB, , et al.. Radiomics and machine learning with multiparametric breast MRI for improved diagnostic accuracy in breast cancer diagnosis. Diagnostics (Basel) 2021; 11: 1–13. doi: https://doi.org/10.3390/diagnostics11060919

61. Maglione KD, , Lee AY, , Ray KM, , Joe BN, , Balassanian R. Radiologic-pathologic correlation for benign results after MRI-guided breast biopsy. American Journal of Roentgenology 2017; 209: 442–53. doi: https://doi.org/10.2214/AJR.16.17048

62. Wurdinger S, , Herzog AB, , Fischer DR, , Marx C, , Raabe G, , Schneider A, , et al.. Differentiation of phyllodes breast tumors from fibroadenomas on MRI. American Journal of Roentgenology 2005; 185: 1317–21. doi: https://doi.org/10.2214/AJR.04.1620

63. Schnall MD, , Blume J, , Bluemke DA, , DeAngelis GA, , DeBruhl N, , Harms S, , et al.. Diagnostic architectural and dynamic features at breast MR imaging: multicenter study. Radiology 2006; 238: 42–53. doi: https://doi.org/10.1148/radiol.2381042117

64. Rodrigues MF, , Truong PT, , McKevitt EC, , Weir LM, , Knowling MA, , Wai ES. Phyllodes tumors of the breast: the British Columbia cancer agency experience. Cancer/Radiothérapie 2018; 22: 112–19. doi: https://doi.org/10.1016/j.canrad.2017.08.112

65. Lakhani S, , Ellis I, , Schnitt S, , Tan P, , Vijver van de M. World Health Organization (WHO) Classification of Tumours of the Breast. 4th edn. IARC Press; 2012.

66. Chu B, , Crystal P. Imaging of fibroepithelial lesions: a pictorial essay. Can Assoc Radiol J 2012; 63: 135–45. doi: https://doi.org/10.1016/j.carj.2010.08.004

67. Eiada R, , Chong J, , Kulkarni S, , Goldberg F, , Muradali D. Papillary lesions of the breast: MRI, ultrasound, and mammographic appearances. AJR Am J Roentgenol 2012; 198: 264–71. doi: https://doi.org/10.2214/AJR.11.7922

68. Wang L-J, , Wu P, , Li X-X, , Luo R, , Wang D-B, , Guan W-B. Magnetic resonance imaging features for differentiating breast papilloma with high-risk or malignant lesions from benign papilloma: a retrospective study on 158 patients. World J Surg Oncol 2018; 16: 1–9. doi: https://doi.org/10.1186/s12957-018-1537-9

69. Sarica O, , Uluc F, , Tasmali D. Magnetic resonance imaging features of papillary breast lesions. Eur J Radiol 2014; 83: 524–30. doi: https://doi.org/10.1016/j.ejrad.2013.12.007

70. Chadashvili T, , Ghosh E, , Fein-Zachary V, , Mehta TS, , Venkataraman S, , Slanetz PJ. Nonmass enhancement on breast MRI: review of patterns with. Am J Roentgenol [Internet] 2015; 204: 219–27. doi: https://doi.org/10.2214/AJR.14.12656

71. Renz DM, , Baltzer PAT, , Böttcher J, , Thaher F, , Gajda M, , Camara O, , et al.. Magnetic resonance imaging of inflammatory breast carcinoma and acute mastitis. A comparative study. Eur Radiol 2008; 18: 2370–80. doi: https://doi.org/10.1007/s00330-008-1029-3

72. Wolfrum A, , Kümmel S, , Theuerkauf I, , Pelz E, , Reinisch M. Granulomatous mastitis: A therapeutic and diagnostic challenge. Breast Care (Basel) 2018; 13: 413–18. doi: https://doi.org/10.1159/000495146

73. Wu JM, , Turashvili G. Cystic neutrophilic granulomatous mastitis: an update. J Clin Pathol 2020; 73: 445–53. doi: https://doi.org/10.1136/jclinpath-2019-206180

74. Fazzio RT, , Shah SS, , Sandhu NP, , Glazebrook KN. Idiopathic granulomatous mastitis: imaging update and review. Insights Imaging 2016; 7: 531–39. doi: https://doi.org/10.1007/s13244-016-0499-0

75. Altunkeser A, , Arslan FZ, , Eryılmaz MA. Magnetic resonance imaging findings of idiopathic granulomatous mastitis: can it be an indirect sign of treatment success or fail? BMC Med Imaging 2019; 19: 1–5. doi: https://doi.org/10.1186/s12880-019-0397-2

76. Tan PH, , Lai LM, , Carrington EV, , Opaluwa AS, , Ravikumar KH, , Chetty N, , et al.. Fat necrosis of the breast—A review. The Breast 2006; 15: 313–18. doi: https://doi.org/10.1016/j.breast.2005.07.003

77. Daly CP, , Jaeger B, , Sill DS. Variable appearances of fat necrosis on breast MRI. American Journal of Roentgenology 2008; 191: 1374–80. doi: https://doi.org/10.2214/AJR.07.4051

78. Ha SM, , Cha JH, , Shin HJ, , Chae EY, , Choi WJ, , Kim HH, , et al.. Radial scars/complex sclerosing lesions of the breast: radiologic and clinicopathologic correlation. BMC Med Imaging 2018; 18(1. doi: https://doi.org/10.1186/s12880-018-0279-z

79. Bacci J, , MacGrogan G, , Alran L, , Labrot‐Hurtevent G. Management of radial scars/complex sclerosing lesions of the breast diagnosed on vacuum‐assisted large‐core biopsy: is surgery always necessary? Histopathology 2019; 75: 900–915. doi: https://doi.org/10.1111/his.13950

80. Bargallo X, , Ubeda B, , Ganau S, , Gonzalez B, , Macedo M, , Alonso I, , et al.. Magnetic resonance imaging assessment of radial scars/complex sclerosing lesions of the breast. CMIR 2022; 18: 242–48. doi: https://doi.org/10.2174/1573405616666201231095918

81. Raj SD, , Sahani VG, , Adrada BE, , Scoggins ME, , Albarracin CT, , Woodtichartpreecha P, , et al.. Pseudoangiomatous stromal hyperplasia of the breast: multimodality review with pathologic correlation. Current Problems in Diagnostic Radiology 2017; 46: 130–35. doi: https://doi.org/10.1067/j.cpradiol.2016.01.005

82. Jones KN, , Glazebrook KN, , Reynolds C. Pseudoangiomatous stromal hyperplasia: imaging findings with pathologic and clinical correlation. American Journal of Roentgenology 2010; 195: 1036–42. doi: https://doi.org/10.2214/AJR.09.3284

83. Schwarz GS, , Drotman M, , Rosenblatt R, , Milner L, , Shamonki J, , Osborn