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• Clinical Article •
Comparative assessment of MRI BI-RADS 4 breast lesions with Kaiser score and apparent diffusion coefficient value
REN Xiaomeng  LIU Xiaochun  DAI Tianzi  ZHANG Hui  ZHENG Guona  HAN Lina 

Cite this article as: Ren XM, Liu XC, Dai TZ, et al. Comparative assessment of MRI BI-RADS 4 breast lesions with Kaiser score and apparent diffusion coefficient value[J]. Chin J Magn Reson Imaging, 2022, 13(9): 25-29, 34. DOI:10.12015/issn.1674-8034.2022.09.005.


[Abstract] Objective To investigate the diagnostic performance of the Kaiser score and apparent diffusion coefficient (ADC) to Breast Imaging Reporting and Data System (BI-RADS) Category 4 lesions at dynamic contrast-enhanced MRI (DCE-MRI).Materials and Methods The cases who underwent breast MRI and were classified as BI-RADS category 4 with clear pathological findings in Hebei General Hospital from June 2020 to February 2022 were retrospectively analyzed. The measurement of ADC value was designated by experienced physicians to designate a region of interest (ROI) and measured. Using logistic regression combined Kaiser score and ADC value to obtain the predictor Kaiser+. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of Kaiser score, Kaiser+ and ADC. The area under the curve (AUC) values were calculated and compared by using the Delong test.Results The study involved 128 women with 165 lesions. Overall diagnostic performance for Kaiser score (AUC=0.882) was significantly higher than for ADC (AUC=0.582; P＜0.05). There were no significant differences in AUCs between Kaiser score and Kaiser+ (P=0.885). Compared with ADC value, the Kaiser score is independent of background parenchymal enhancement when making a lesion diagnosis.Conclusions For BI-RADS 4 breast lesions, the Kaiser score is superior to ADC mapping and may help to avoid unnecessary biopsies. However, the combination of both indicators did not significantly contribute to breast cancer diagnosis.
[Keywords] breast cancer；Kaiser score；magnetic resonance imaging；apparent diffusion coefficient

REN Xiaomeng1, 2   LIU Xiaochun2, 3   DAI Tianzi1, 2   ZHANG Hui2*   ZHENG Guona4   HAN Lina5  

1 Graduate School, Hebei Medical University, Shijiazhuang 050017, China

2 Department of Radiology, Hebei General Hospital, Shijiazhuang 050051, China

3 Graduate School, Hebei North University, Zhangjiakou 075000, China

4 Department of Pathology, Hebei General Hospital, Shijiazhuang 050051, China

5 Department of Neurology, Hebei General Hospital, Shijiazhuang 050051, China

*Zhang H, E-mail: wszzzhui@163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Hebei Province Talent Training Project (No. A201901017).
Received  2022-05-31
Accepted  2022-09-14
DOI: 10.12015/issn.1674-8034.2022.09.005
Cite this article as: Ren XM, Liu XC, Dai TZ, et al. Comparative assessment of MRI BI-RADS 4 breast lesions with Kaiser score and apparent diffusion coefficient value[J]. Chin J Magn Reson Imaging, 2022, 13(9): 25-29, 34. DOI:10.12015/issn.1674-8034.2022.09.005.

[1]
Leithner D, Wengert G, Helbich T, et al. MRI in the assessment of BI-RADS® 4 lesions[J]. Top Magn Reson Imaging, 2017, 26(5): 191-199. DOI: 10.1097/RMR.0000000000000138.
[2]
Bickel H, Pinker K, Polanec S, et al. Diffusion-weighted imaging of breast lesions: region-of-interest placement and different ADC parameters influence apparent diffusion coefficient values[J]. Eur Radiol, 2017, 27(5): 1883-1892. DOI: 10.1007/s00330-016-4564-3.
[3]
Clauser P, Krug B, Bickel H, et al. Diffusion-weighted imaging allows for downgrading MR BI-RADS 4 lesions in contrast-enhanced MRI of the breast to avoid unnecessary biopsy[J]. Clin Cancer Res, 2021, 27(7): 1941-1948. DOI: 10.1158/1078-0432.CCR-20-3037.
[4]
Zhang M, Horvat JV, Bernard-Davila B, et al. Multiparametric MRI model with dynamic contrast-enhanced and diffusion-weighted imaging enables breast cancer diagnosis with high accuracy[J]. J Magn Reson Imaging, 2019, 49(3): 864-874. DOI: 10.1002/jmri.26285.
[5]
Strigel RM, Burnside ES, Elezaby M, et al. Utility of BI-RADS assessment category 4 subdivisions for screening breast MRI[J]. AJR Am J Roentgenol, 2017, 208(6): 1392-1399. DOI: 10.2214/AJR.16.16730.
[6]
An YY, Liu C, Zhang HX, et al. Diagnostic value of Kaiser score for BI-RADS 4 lesions on MRI[J]. Zhejiang Med J, 2021, 43(5): 511-515. DOI: 10.12056/j.issn.1006-2785.2021.43.5.2020-3139.
[7]
Grippo C, Jagmohan P, Helbich TH, et al. Correct determination of the enhancement curve is critical to ensure accurate diagnosis using the Kaiser score as a clinical decision rule for breast MRI[J/OL]. Eur J Radiol, 2021 [2022-05-30]. https://doi.org/10.1016/j.ejrad.2021.109630. DOI: 10.1016/j.ejrad.2021.109630.
[8]
Wengert GJ, Pipan F, Almohanna J, et al. Impact of the Kaiser score on clinical decision-making in BI-RADS 4 mammographic calcifications examined with breast MRI[J]. Eur Radiol, 2020, 30(3): 1451-1459. DOI: 10.1007/s00330-019-06444-w.
[9]
Milos RI, Pipan F, Kalovidouri A, et al. The Kaiser score reliably excludes malignancy in benign contrast-enhancing lesions classified as BI-RADS 4 on breast MRI high-risk screening exams[J]. Eur Radiol, 2020, 30(11): 6052-6061. DOI: 10.1007/s00330-020-06945-z.
[10]
Iima M, Honda M, Sigmund EE, et al. Diffusion MRI of the breast: current status and future directions[J]. J Magn Reson Imaging, 2020, 52(1): 70-90. DOI: 10.1002/jmri.26908.
[11]
Dijkstra H, Dorrius MD, Wielema M, et al. Quantitative DWI implemented after DCE-MRI yields increased specificity for BI-RADS 3 and 4 breast lesions[J]. J Magn Reson Imaging, 2016, 44(6): 1642-1649. DOI: 10.1002/jmri.25331.
[12]
Istomin A, Masarwah A, Okuma H, et al. A multiparametric classification system for lesions detected by breast magnetic resonance imaging[J/OL]. Eur J Radiol, 2020 [2022-05-30]. https://doi.org/10.1016/j.ejrad.2020.109322. DOI: 10.1016/j.ejrad.2020.109322.
[13]
Bitencourt AG, Graziano L, Osório CA, et al. MRI features of mucinous cancer of the breast: correlation with pathologic findings and other imaging methods[J]. AJR Am J Roentgenol, 2016, 206(2): 238-246. DOI: 10.2214/AJR.15.14851.
[14]
Baltzer PAT, Dietzel M, Kaiser WA. A simple and robust classification tree for differentiation between benign and malignant lesions in MR-mammography[J]. Eur Radiol, 2013, 23(8): 2051-2060. DOI: 10.1007/s00330-013-2804-3.
[15]
Woitek R, Spick C, Schernthaner M, et al. A simple classification system (the Tree flowchart) for breast MRI can reduce the number of unnecessary biopsies in MRI-only lesions[J]. Eur Radiol, 2017, 27(9): 3799-3809. DOI: 10.1007/s00330-017-4755-6.
[16]
Baltzer P, Krug KB, Dietzel M. Evidence-based and structured diagnosis in breast MRI using the Kaiser score[J/OL]. Rofo, 2022 [2022-05-30]. https://www.thieme-connect.com. DOI: 10.1055/a-1829-5985.
[17]
Dietzel M, Baltzer PAT. How to use the Kaiser score as a clinical decision rule for diagnosis in multiparametric breast MRI: a pictorial essay[J]. Insights Imaging, 2018, 9(3): 325-335. DOI: 10.1007/s13244-018-0611-8.
[18]
Marino MA, Clauser P, Woitek R, et al. A simple scoring system for breast MRI interpretation: does it compensate for reader experience?[J]. Eur Radiol, 2016, 26(8): 2529-2537. DOI: 10.1007/s00330-015-4075-7.
[19]
Istomin A, Masarwah A, Vanninen R, et al. Diagnostic performance of the Kaiser score for characterizing lesions on breast MRI with comparison to a multiparametric classification system[J/OL]. Eur J Radiol, 2021 [2022-05-30]. https://doi.org/10.1016/j.ejrad.2021.109659. DOI: 10.1016/j.ejrad.2021.109659.
[20]
Rong X, Kang Y, Xue J, et al. Value of contrast-enhanced mammography combined with the Kaiser score for clinical decision-making regarding tomosynthesis BI-RADS 4A lesions[J/OL]. Eur Radiol, 2022 [2022-05-30]. https://doi.org/10.1007/s00330-022-08810-7. DOI: 10.1007/s00330-022-08810-7.
[21]
Wang S, Li JY, Zheng H, et al. Analysis on Kaiser sore in diagnostic value of BI-RADS 4 types of breast non-masses enhancement[J]. J Clin Radiol, 2021, 40(12): 2282-2286. DOI: 10.13437/j.cnki.jcr.2021.12.010.
[22]
Jajodia A, Sindhwani G, Pasricha S, et al. Application of the Kaiser score to increase diagnostic accuracy in equivocal lesions on diagnostic mammograms referred for MR mammography[J/OL]. Eur J Radiol, 2021[2022-05-30] https://doi.org.10.1016/j.ejrad.2020.109413. DOI: 10.1016/j.ejrad.2020.109413.
[23]
Telegrafo M, Rella L, Stabile Ianora AA, et al. Effect of background parenchymal enhancement on breast cancer detection with magnetic resonance imaging[J]. Diagn Interv Imaging, 2016, 97(3): 315-320. DOI: 10.1016/j.diii.2015.12.006.
[24]
Jung Y, Jeong S, Kim JY, et al. Correlations of female hormone levels with background parenchymal enhancement and apparent diffusion coefficient values in premenopausal breast cancer patients: effects on cancer visibility[J/OL]. Eur J Radiol, 2020 [2022-05-30] https://doi.org/10.1016/j.ejrad.2020.108818. DOI: 10.1016/j.ejrad.2020.108818.
[25]
Zhang H, Guo LL, Tao WJ, et al. Possible breast cancer risk related to background parenchymal enhancement at breast MRI: a meta-analysis study[J]. Nutr Cancer, 2021, 73(8): 1371-1377. DOI: 10.1080/01635581.2020.1795211.
[26]
Zhang B, Feng LL, Wang L, et al. Kaiser score for diagnosis of breast lesions presenting as non-mass enhancement on MRI[J]. Nan Fang Yi Ke Da Xue Xue Bao, 2020, 40(4): 562-566. DOI: 10.12122/j.issn.1673-4254.2020.04.18.
[27]
Nadrljanski MM, Marković BB, Milošević ZČ. Breast ductal carcinoma in situ: morphologic and kinetic MRI findings[J]. Iran J Radiol, 2013, 10(2): 99-102. DOI: 10.5812/iranjradiol.4876.
[28]
Lee JM, Ichikawa L, Valencia E, et al. Performance benchmarks for screening breast MR imaging in community practice[J]. Radiology, 2017, 285(1): 44-52. DOI: 10.1148/radiol.2017162033.
[29]
Dietzel M, Krug B, Clauser P, et al. A multicentric comparison of apparent diffusion coefficient mapping and the Kaiser score in the assessment of breast lesions[J]. Invest Radiol, 2021, 56(5): 274-282. DOI: 10.1097/RLI.0000000000000739.019-06444-w.}

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