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Erschienen in: BMC Cancer 1/2020

Open Access 01.12.2020 | Research article

Value of digital mammography in predicting lymphovascular invasion of breast cancer

verfasst von: Zhuangsheng Liu, Ruqiong Li, Keming Liang, Junhao Chen, Xiangmeng Chen, Xiaoping Li, Ronggang Li, Xin Zhang, Lilei Yi, Wansheng Long

Erschienen in: BMC Cancer | Ausgabe 1/2020

Abstract

Background

Lymphovascular invasion (LVI) has never been revealed by preoperative scans. It is necessary to use digital mammography in predicting LVI in patients with breast cancer preoperatively.

Methods

Overall 122 cases of invasive ductal carcinoma diagnosed between May 2017 and September 2018 were enrolled and assigned into the LVI positive group (n = 42) and the LVI negative group (n = 80). Independent t-test and χ2 test were performed.

Results

Difference in Ki-67 between the two groups was statistically significant (P = 0.012). Differences in interstitial edema (P = 0.013) and skin thickening (P = 0.000) were statistically significant between the two groups. Multiple factor analysis showed that there were three independent risk factors for LVI: interstitial edema (odds ratio [OR] = 12.610; 95% confidence interval [CI]: 1.061–149.922; P = 0.045), blurring of subcutaneous fat (OR = 0.081; 95% CI: 0.012–0.645; P = 0.017) and skin thickening (OR = 9.041; 95% CI: 2.553–32.022; P = 0.001).

Conclusions

Interstitial edema, blurring of subcutaneous fat, and skin thickening are independent risk factors for LVI. The specificity of LVI prediction is as high as 98.8% when the three are used together.
Hinweise
Zhuangsheng Liu and Ruqiong Li contributed equally to this work.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abkürzungen
LVI
Lymphovascular invasion
DM
Digital mammography
RCC
Right craniocaudal
LCC
Left craniocaudal
RMLO
Right mediolateral oblique
LMLO
Left mediolateral oblique

Background

Breast cancer metastasizes through lymphatic and blood vessels, which makes the patients susceptible to distant metastasis, postoperative recurrence and even death. Lymphovascular invasion (LVI) has never been revealed by preoperative scans. Diagnostic histopathology is needed to reveal LVI of cancer cells. Preoperative identification of LVI can help to predict the prognosis of patients with breast cancer, especially those with axillary node-negative breast cancer, and to develop adjuvant treatment plans in clinical settings [1, 2].
Digital mammography is one of the important imaging tools for breast cancer screening and diagnosis. There have been many reports on prediction of axillary lymph node metastasis [35] and on digital mammography screening [69]. However, there has been no report on predicting LVI of breast cancer based on imaging patterns of digital mammography, except a little literature in which MRI findings were used for prediction [2, 1012].
It is necessary to use digital mammography, a more readily available imaging tool, in preoperative prediction of LVI in patients with breast cancer, and to evaluate the predictive specificity of the imaging findings and certain biomarkers detected by immunohistochemistry so as to better foresee disease progression and develop targeted treatment plans.

Methods

Clinical data

This single-center retrospective study enrolled 122 cases of invasive ductal carcinoma diagnosed between May 2017 and September 2018. Since the data were obtained from a picture archiving and communication system, patients’ informed consent was not required for this study. The inclusion criteria were: (1) modified radical mastectomy or breast-conserving surgery + axillary lymph node dissection; (2) diagnosis of invasive breast cancer confirmed by routine histopathological and immunohistochemical examinations; (3) no previous history of breast tumors or primary tumors in other locations; and (4) LVI status confirmed by immunohistochemistry. Patients were excluded if they had obscured lesions revealed by digital mammograms, were breastfeeding, had underwent lumbar puncture or radiotherapy prior to diagnosis, and had incomplete clinical data.
Mammographic lesions were confirmed either by core needle biopsies or by surgical pathology. All the patients underwent digital mammography preoperatively. All of them were female and aged between 26 and 77 with a median age of 45. They were assigned into the LVI positive group (n = 42) and the LVI negative group (n = 80).

Digital mammography

GE (Senographe DS) and IMS (GIOTTO IMAGE) systems were used. Four standard body positions were imaged under automatic exposure conditions, and they were the right craniocaudal (RCC) view, left craniocaudal (LCC) view, right mediolateral oblique (RMLO) view and left mediolateral oblique (LMLO) view. When lesions were found in the axillary tail of Spence or near the cleavage, amplified imaging in these locations was done to reveal the lesions fully. The flat-panel detector of internal and external obliques was parallel to the pectoralis major muscle. According to the patients’ body shape, the projecting angle ranged from 40° to 65° and was usually 60°. The glands were fully unfolded, and the skin folds below the breasts and upper abdomen were within the mammographic field.

Image analysis

The imaging characteristics of breast cancer lesions were described according to the 5th edition of ACR BI-RADS® Atlas published in 2013 [13]. The lesions were classified into four types: mass, calcification, architectural distortion, and asymmetry. There could be one or more masses. The masses could be round, lobulated, and irregular. Clear and sharp edges meant well circumscribed margins, clear and sharp edges obscured by glands meant obscured margins, while obscured and spiculated edges meant indistinct margins. Amorphous and fine polymorphic calcifications were included, while typically benign calcifications were excluded. Architectural distortion referred to abnormal deformation of breasts without any mass clearly revealed by imaging. History of trauma and surgery must be ruled out under this circumstance. Focal asymmetry was seen in two images, but lacks the outward border or a mass. There were only few cases of architectural distortion and focal asymmetry (both n < 5). Those cases were excluded to avoid inaccurate statistical results. And the lesion type was classified as mass and calcification only.
Associated features included nipple discharge, interstitial edema, blurring of subcutaneous fat layer, skin thickening, and axillary adenopathy (lymph nodes measuring > 1 cm in the long axis diameter with absence of hilus. If enlarged lymph nodes are new, they need to be clinically combined and further examined). Due to its absence in the LVI negative group (n = 0), nipple discharge was not included as a variable. Thickening of the skin means that the affected breast has localized or diffuse thickening of the skin greater than 2 mm in thickness. Interstitial edema and subcutaneous fat layer blurring are caused by the filling and dilation of lymphatic vessels and blood vessels in the breast, while the performance of the whole breast including subcutaneous fat layer is blurring, and multiple cord shadows are seen.

Pathology

Surgically resected breast cancer specimens were fixed in 10% formaldehyde for 24 h, then were dehydrated and embedded in paraffin wax. Sections were prepared. Standard HE stain and streptavidin-peroxidase-biotin (SP) immunohistochemical method were performed. DAB detection systems were used. A score of 3 and more indicated Her-2 overexpression. Positive FISH result of Her-2 gene amplification also indicated overexpression when the score was 2 and more. Ki67 proliferative index (PI) of <10% indicated low expression level, while that of > 30% indicated high expression level. Ki67 PI of 10 to 30% indicated intermediate expression level [14].
The gold standard of this study was that LVI was defined as the intravenous tumor emboli and lymphatic tumor emboli detected by immunohistochemistry. These two kinds of tumor emboli were clinically referred to as intralymphovascular tumor emboli due to the difficulty of distinguishing them with pathological sections. The specimens were read by a senior pathologist who had been working on breast cancer for 21 years.

Statistical analysis

The data were analyzed using SPSS Version 19.0. The quantitative data were expressed as means ± SDs. The independent t-test was done for intergroup comparisons. The count data were expressed as frequencies or rates, and the χ2 test or Fisher’s method was performed. P < 0.05 indicated statistically significant difference. The count data whose values were 0 were excluded from statistical analysis and listed only in table(s).

Results

General data and biomarkers

Table 1 presents the data about childbearing history, miscarriage history, history of other breast diseases, nipple discharge, CA153, age, ER, PR, HER-2, E-CAD, P53, and Ki-67. Difference in Ki-67 between the LVI positive group and the LVI negative group was statistically significant (P = 0.012), while no statistically significant differences were observed in the other factors mentioned.
Table 1
Comparison of patient characteristics according to lymphovascular invasion
Characteristics
Total
LVI = 0 (Negative)
LVI = 1 (Positive)
P
Age
122
49.99(10.17)
48.93(9.34)
0.566
History of giving birth
122
80
42
0.488
 No
5
4(80.00)
1(20.00)
 
 Yes
117
76(64.96)
41(35.04)
 
History of abortion
122
80
42
0.560
 No
86
55(63.95)
31(36.05)
 
 Yes
36
25(69.44)
11(30.56)
 
nipple discharge
122
80
42
 
 No
120
80(66.67)
40(33.33)
 
 Yes
2
0(0.00)
2(100.00)
 
CA153a
121
79
42
0.514
 Negative
117
77(65.81)
40(34.19)
 
 Positive
4
2(50.00)
2(50.00)
 
History of related illness
122
80
42
0.488
 No
117
76(64.96)
41(35.04)
 
 Yes
5
4(80.00)
1(20.00)
 
ER
122
80
42
0.062
 Negative
39
21(53.85)
18(46.15)
 
 Positive
83
59(71.08)
24(28.92)
 
PR
122
80
42
0.0591
 Negative
47
26(55.32)
21(44.68)
 
 Positive
75
54(72.00)
21(28.00)
 
HER-2
122
80
42
0.994
 Negative
32
21(65.63)
11(34.38)
 
 Positive
90
59(65.56)
31(34.44)
 
E-cada
87
56
31
0.100
 Negative
6
2(33.33)
4(66.67)
 
 Positive
81
54(66.67)
27(33.33)
 
Ki-67
122
80
42
0.012
 Low
27
20(74.07)
7(25.93)
 
 Moderate
36
29(80.56)
7(19.44)
 
 High
59
31(52.54)
28(47.46)
 
P53
122
80
42
0.126
 Negative
40
30(75.00)
10(25.00)
 
 Positive
82
50(60.98)
32(39.02)
 
Amount of fibroglandular tissue
122
80
42
0.431
 Almost entirely fat/Scattered fibroglandular tissue
49
33(67.35)
16(32.65)
 
 Heterogeneous fibroglandular tissue
54
37(68.52)
17(31.48)
 
 Extreme fibroglandular tissue
19
10(52.63)
9(47.37)
 
Size
122
80
42
0.094
 ≤2cm
79
56(70.89)
23(29.11)
 
 >2cm
43
24(55.81)
19(44.19)
 
Single/multiple
122
80
42
0.746
 Single
95
63(66.32)
32(33.68)
 
 Multiple
27
17(62.96)
10(37.04)
 
Lesions
122
80
42
0.8855
 Mass
65
43(66.15)
22(33.85)
 
 Mass/calcification
57
37(64.91)
20(35.09)
 
Location
122
80
42
0.879
 Outer upper
73
49(67.12)
24(32.88)
 
 Outer lower
5
4(80.00)
1(20.00)
 
 Lower inner
15
10(66.67)
5(33.33)
 
 Upper inner
15
9(60.00)
6(40.00)
 
 Central area
14
8(57.14)
6(42.86)
 
Mass shape
122
80
42
0.160
 Lobulated
16
8(50.00)
8(50.00)
 
 Irregular
106
72(67.92)
34(32.08)
 
Mass Margin
122
80
42
0.088
 Smooth
6
2(33.33)
4(66.67)
 
 Rough
116
78(67.24)
38(32.76)
 
Boundary
122
80
42
0.714
 Clear
69
47(68.12)
22(31.88)
 
 Obscure
27
16(59.26)
11(40.74)
 
 Shield
26
17(65.38)
9(34.62)
 
Calcificationa
56
36
20
0.279
 Vague and amorphous
25
18(72.00)
7(28.00)
 
 Fine polymorphous
31
18(58.06)
13(41.94)
 
Interstitial edema
122
80
42
0.013
 No
110
76(69.09)
34(30.91)
 
 Yes
12
4(33.33)
8(66.67)
 
Subcutaneous fat
122
80
42
0.697
 Clear
101
67(66.34)
34(33.66)
 
 Muddy
21
13(61.90)
8(38.10)
 
Thicken Skin
122
80
42
< 0.001
 No
86
65(75.58)
21(24.42)
 
 Yes
36
15(41.67)
21(58.33)
 
Nipple retraction
122
80
42
0.073
 No
98
68(69.39)
30(30.61)
 
 Yes
24
12(50.00)
12(50.00)
 
Axillary lymph node enlargement
122
80
42
0.166
 No
77
54(70.13)
23(29.87)
 
 Yes
45
26(57.78)
19(42.22)
 
aMissing value exists
LVI Lymphovascular invasion

Digital mammography findings

Details are shown in Table 1. Differences in interstitial edema (P = 0.013, Figs. 1 and 2) and skin thickening (P = 0.000, Figs. 1 and 2) between the two groups were statistically significant. No statistically significant intergroup differences were seen in other imaging features, such as fibroglandular tissue density (P = 0.431), radiological diameter (P = 0.094), mass number (P = 0.746), lesion number (P = 0.8855), location (P = 0.879), mass shape (P = 0.160), mass margin (P = 0.088), boundary (P = 0.714), calcification (P = 0.279), subcutaneous fat (P = 0.697), nipple retraction (P = 0.073) and axillary adenopathy (P = 0.166).
Risk factor analysis results are shown in Table 2. Multiple factor analysis showed that there are three independent risk factors for LVI: interstitial edema (odds ratio [OR] = 12.610; 95% confidence interval [CI]: 1.061–149.922; P = 0.045), subcutaneous fat (OR = 0.081; 95% CI: 0.012–0.645; P = 0.017) and skin thickening (OR = 9.041; 95% CI: 2.553–32.022; P = 0.001).
Table 2
Univariate and multivariate analysis
Factors
Univariate analysis
Multivariate analysis
OR (95% CI)
P
OR (95% CI)
P
Interstitial edema
4.471(1.260,15.864)
0.020
12.610(1.061,149.922)
0.045
Subcutaneous fat
1.213(0.458,3.207)
0.698
0.081(0.012,0.645)
0.017
Thicken Skin
4.333(1.899,9.891)
0.000
9.041(2.553,32.022)
0.001
ER
0.475(0.216,1.044)
0.064
1.595(0.252,10.084)
0.62
PR
0.481(0.224,1.034)
0.061
0.508(0.085,3.035)
0.458
HER-2
1.003(0.429,2.345)
0.994
1.436(0.462,4.466)
0.532
Ki-67
 Moderate
0.690(0.209,2.273)
0.541
0.382(0.094,1.551)
0.178
 High
2.581(0.948,7.022)
0.063
1.298(0.350,4.809)
0.696
 P53
1.920(0.827,4.457)
0.129
2.115(0.739,6.050)
0.163
Amount of fibroglandular tissue
 Heterogeneous fibroglandular tissue
0.948(0.414,2.179)
0.899
1.439(0.491,4.215)
0.507
 Extreme fibroglandular tissue
1.856(0.630,5.469)
0.262
3.773(0.707,20.154)
0.12
Size
1.928(0.890,4176)
0.096
0.921(0.294,2.891)
0.889
Nipple retraction
2.267(0.914,5.621)
0.077
1.299(0.281,5.991)
0.738
Single/multiple
1.158(0.476,2.819)
0.746
1.183(0.336,4.165)
0.793
Lesions
1.057(0.500,2.233)
0.885
0.712(0.256,1.979)
0.514
Mass shape
0.472(0.163,1.365)
0.166
0.624(0.128,3.047)
0.56
Margin
0.224(0.043,1.389)
0.112
0.424(0.032,5.630)
0.516
Boundary
 Obscure
1.469(0.586,3.684)
0.413
1.483(0.439,5.007)
0.526
 Shield
1.131(0.436,2.935)
0.800
0.997(0.246,4.043)
0.997
Axillary lymph node enlargement
1.716(0.797,3.694)
0.168
0.909(0.295,2.805)
0.868
E-cad
0.250(0.043,1.452)
0.122
  
Location
 Outer lower
0.510(0.054,4.819)
0.557
  
 Lower inner
1.021(0.314,3.320)
0.973
  
 Upper inner
1.361(0.434,4.267)
0.597
  
 Central area
1.531(0.477,4.913)
0.474
  
Calcification
1.857(0.601,5.734)
0.166
  
Family history
1.927(0.117,31.602)
0.646
  
History of giving birth
2.158(0.233,19.947)
0.498
  
History of abortion
0.781(0.339,1.799)
0.561
  
CA15–3
1.925(0.261,14.179)
0.52
  
History of related illness
0.463(0.050,4.284)
0.498
  
Table 3 shows the sensitivity, specificity, accuracy, positive predictive value and negative predictive value of the three independent risk factors in LVI prediction. The specificity of LVI prediction was as high as 98.8% when they were applied together.
Table 3
Diagnostic performance
Methods
Sensitivity
Specificity
Accuracy
PPV
NPV
Interstitial edema
19.0(8/42)
95.0(76/80)
68.9(84/122)
66.7(8/12)
69.1(76/110)
Thicken Skin
50.0(21/42)
81.3(65/80)
70.5(86/122)
58.3(21/36)
75.6(65/86)
Subcutaneous fat
19.0(8/42)
83.8(67/80)
61.2(75/122)
38.1(8/21)
66.3(67/101)
All factors
14.3(6/42)
98.8(79/80)
69.7(85/122)
85.7(6/7)
68.7(79/115)

Discussion

LVI or intralymphovascular tumor emboli is closely related to the adverse outcome of many malignant tumors [1517]. As a risk factor for recurrent breast cancer following modified radical mastectomy, lymphovascular tumor emboli, especially lymphatic tumor emboli, has been included in the St Gallen consensus for breast cancer [18]. Karlsson et al. [19] reported that the failure rate of chemotherapy was higher in breast cancer patients with LVI than those without. Shen et al. [20] found that lymphovascular tumor emboli promoted recurrence and distant metastasis of local tumors. Therefore, presence of lymphovascular tumor emboli is a reliable indicator for distant metastasis of breast cancer and an important factor influencing overall survival. This article aimed to predict the risk of LVI of breast cancer using various digital mammography features.
There are no statistically significant differences in age, childbearing history, miscarriage history, family history and other medical history between the LVI positive group and the LVI negative group. Nulliparity, miscarriage, and family history of breast cancer are not associated with increase of LVI occurrence.
CA153 is a tumor marker first discovered in breast cancer cells. Its specificity is relatively high in diagnosis of breast cancer. Diagnostic sensitivity of CA153 increases from 66 to 80% as breast cancer advances [21]. However, in this study, there are only 4 cases of positive CA153 (3.3%). Though there are no statistical significant differences in ER, PR, Her-2, E-cad, and P53 between the two groups, the LVI positive group have more cases of high Ki-67 expression level (> 30%) than the LVI negative group and the difference is statistically significant (P = 0.012). Some literature have confirmed that Ki-67 is associated with tumor differentiation, LVI, metastasis, and recurrence [2224].
There are no statistically significant differences between the two groups in mammographic density, location, number, radiological diameter, shape, margin, boundary, calcification. Therefore, the above factors cannot be used to predict LVI. However, intergroup differences in interstitial edema and skin thickening are statistically significant (P = 0.013 and 0.000, respectively). In addition, multivariate analysis demonstrates that interstitial edema, blurring of subcutaneous fat, and skin thickening are independent risk factors for LVI (P = 0.045, 0.017 and 0.001, respectively). In clinical work-up, physicians should be highly alerted about LVI occurrence when digital mammography reveals the above three phenomena. Even if lymph node metastasis is negative in sentinel lymph node and axillary lymph node biopsies, there is possibility that breast cancer cells has infiltrated surrounding vessels but not metastasized upwards to the axillary lymph nodes yet. Besides, modification of postoperative adjuvant therapy should be considered to reduce risk of recurrence and distant metastasis, and thus to prolong survival.
We believed that the axillary lymph nodes shown on digital mammography could be used to predict LVI. However, there are no differences between the two groups in axillary lymph nodes (P = 0.166). One possible explanation might be that digital mammography failed to reveal axillary lymph nodes. In addition, an enlarged (> 1 cm) or complete lymph node does not always suggest metastasis. There is possibility of reactive hyperplasia.

Conclusions

There is statistically significant difference in Ki-67 between the LVI positive group and the LVI negative group. Interstitial edema, blurring of subcutaneous fat and skin thickening are independent risk factors for LVI (P = 0.045, 0.017, and 0.001, respectively). When the three imaging features are applied together, the specificity of LVI prediction is as high as 98.8%.

Acknowledgements

We would like to thank the study teams from Jiangmen Central Hospital and Foshan Hospital of Traditional Chinese Medicine for their continuous support.
The study was approved by the Jiangmen Central Hospital and the requirement for signed informed consent was waived.
Not applicable.

Competing interests

The authors declare that they have no competing interests.
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Literatur
1.
Zurück zum Zitat Rezaianzadeh A, Talei A, Rajaeefard A, et al. Lymphovascular invasion as an independent prognostic factor in lymph node negative invasive breast cancer. Asian Pac J Cancer Prev. 2012;13(11):5767–72.CrossRef Rezaianzadeh A, Talei A, Rajaeefard A, et al. Lymphovascular invasion as an independent prognostic factor in lymph node negative invasive breast cancer. Asian Pac J Cancer Prev. 2012;13(11):5767–72.CrossRef
2.
Zurück zum Zitat Oy F, Bl G, Xy H, et al. A nomogram for individual prediction of lymphovascular invasion in primary breast cancer. Eur J Radiol. 2019;110:30–8.CrossRef Oy F, Bl G, Xy H, et al. A nomogram for individual prediction of lymphovascular invasion in primary breast cancer. Eur J Radiol. 2019;110:30–8.CrossRef
3.
Zurück zum Zitat Yang JB, Wang T, Yang LF, et al. Preoperative prediction of axillary lymph node metastasis in breast cancer using mammography-based Radiomics method. Sci Rep. 2019;9:4429.CrossRef Yang JB, Wang T, Yang LF, et al. Preoperative prediction of axillary lymph node metastasis in breast cancer using mammography-based Radiomics method. Sci Rep. 2019;9:4429.CrossRef
4.
Zurück zum Zitat Cen DZ, Xu L, Zhang SW, et al. BI-RADS 3–5 microcalcifications: prediction of lymph node metastasis of breast cancer. Oncotarget. 2017;8(18):30190–8.CrossRef Cen DZ, Xu L, Zhang SW, et al. BI-RADS 3–5 microcalcifications: prediction of lymph node metastasis of breast cancer. Oncotarget. 2017;8(18):30190–8.CrossRef
5.
Zurück zum Zitat Karahallı Ö, Acar T, Atahan MK, et al. Clinical and pathological factors affecting the sentinel lymph node metastasis in patients with breast cancer. Indian J Surg. 2017;79(5):418–22.CrossRef Karahallı Ö, Acar T, Atahan MK, et al. Clinical and pathological factors affecting the sentinel lymph node metastasis in patients with breast cancer. Indian J Surg. 2017;79(5):418–22.CrossRef
6.
Zurück zum Zitat Hubbard RA, Zhu W, Horblyuk R, et al. Diagnostic imaging and biopsy pathways following abnormal screen-film and digital screening mammography. Breast Cancer Res Treat. 2013;138(3):879–87.CrossRef Hubbard RA, Zhu W, Horblyuk R, et al. Diagnostic imaging and biopsy pathways following abnormal screen-film and digital screening mammography. Breast Cancer Res Treat. 2013;138(3):879–87.CrossRef
7.
Zurück zum Zitat Lee CI, Cevik M, Alagoz O, et al. Comparative effectiveness of combined digital mammography and Tomosynthesis screening for women with dense breasts. Radiology. 2015;274(3):772–80.CrossRef Lee CI, Cevik M, Alagoz O, et al. Comparative effectiveness of combined digital mammography and Tomosynthesis screening for women with dense breasts. Radiology. 2015;274(3):772–80.CrossRef
8.
Zurück zum Zitat Jewett PI, Gangnon RE, Elkin E, et al. Geographic access to mammography facilities and frequency of mammography screening. Ann Epidemiol. 2018;28(2):65–71.CrossRef Jewett PI, Gangnon RE, Elkin E, et al. Geographic access to mammography facilities and frequency of mammography screening. Ann Epidemiol. 2018;28(2):65–71.CrossRef
9.
Zurück zum Zitat O’Donoghue C, Eklund M, Elissa M, et al. Aggregate cost of mammography screening in the United States: comparison of current practice and advocated guidelines. Ann Intern Med. 2014;160(3):145.CrossRef O’Donoghue C, Eklund M, Elissa M, et al. Aggregate cost of mammography screening in the United States: comparison of current practice and advocated guidelines. Ann Intern Med. 2014;160(3):145.CrossRef
10.
Zurück zum Zitat Hyejin C, Hye JK, So ML, et al. Preoperative MRI features associated with Lymphovascular invasion in node-negative invasive breast cancer: a propensity-matched analysis. J Magn Reson Imaging. 2017;46(4):1037–44.CrossRef Hyejin C, Hye JK, So ML, et al. Preoperative MRI features associated with Lymphovascular invasion in node-negative invasive breast cancer: a propensity-matched analysis. J Magn Reson Imaging. 2017;46(4):1037–44.CrossRef
11.
Zurück zum Zitat Mori N, Mugikura S, Takasawa C, et al. Peritumoral apparent diffusion coefficients for prediction of lymphovascular invasion in clinically node-negative invasive breast cancer. Eur Radiol. 2016;26:331–9.CrossRef Mori N, Mugikura S, Takasawa C, et al. Peritumoral apparent diffusion coefficients for prediction of lymphovascular invasion in clinically node-negative invasive breast cancer. Eur Radiol. 2016;26:331–9.CrossRef
12.
Zurück zum Zitat Liu ZS, Bao F, Li CL, et al. Preoperative prediction of Lymphovascular invasion in invasive breast cancer with dynamic contrast-enhanced-MRI-based Radiomics. J Magn Reson Imaging. 2019;50(3):847 [Epub ahead of print].CrossRef Liu ZS, Bao F, Li CL, et al. Preoperative prediction of Lymphovascular invasion in invasive breast cancer with dynamic contrast-enhanced-MRI-based Radiomics. J Magn Reson Imaging. 2019;50(3):847 [Epub ahead of print].CrossRef
13.
Zurück zum Zitat American College of Radiology (ACR). Breast imaging reporting and data system (BI-RADS). 5th ed. Reston: Ameirican College of Radiology; 2013. p. 133. American College of Radiology (ACR). Breast imaging reporting and data system (BI-RADS). 5th ed. Reston: Ameirican College of Radiology; 2013. p. 133.
14.
Zurück zum Zitat Barbashina V, Adriana D, Corben MD. Mucinous micropapillary carcinoma of the breast:an aggressive counterpart to conventional pure mucinous tumors. Hum Pathol. 2013;44:1577–85.CrossRef Barbashina V, Adriana D, Corben MD. Mucinous micropapillary carcinoma of the breast:an aggressive counterpart to conventional pure mucinous tumors. Hum Pathol. 2013;44:1577–85.CrossRef
15.
Zurück zum Zitat Liang JW, Gao P, Wang ZN, et al. The integration of macroscopic tumor invasionof adjacent organs into TNM staging system for colorectal cancer. PLoS One. 2012;7(12):52269.CrossRef Liang JW, Gao P, Wang ZN, et al. The integration of macroscopic tumor invasionof adjacent organs into TNM staging system for colorectal cancer. PLoS One. 2012;7(12):52269.CrossRef
16.
Zurück zum Zitat Lai JH, Zhou YJ, Bin D, et al. Clinical significance of detecting lymphatic and blood vessel invasion in stage II colon cancer using markers D2–40 and CD34 in combination. Asian Pac J Cancer Prev. 2014;15(3):1363–7.CrossRef Lai JH, Zhou YJ, Bin D, et al. Clinical significance of detecting lymphatic and blood vessel invasion in stage II colon cancer using markers D2–40 and CD34 in combination. Asian Pac J Cancer Prev. 2014;15(3):1363–7.CrossRef
17.
Zurück zum Zitat Matloff E. Cancer principles and practice of oncology: handbook of clinical cancer genetics. J Am Med Assoc. 1990;248(15):1904–5. Matloff E. Cancer principles and practice of oncology: handbook of clinical cancer genetics. J Am Med Assoc. 1990;248(15):1904–5.
18.
Zurück zum Zitat Mignatiadis MB, Sotiriou C. St Gallen international expert consensus on the primary therapy of early breast cancer: an invaluable tool for physicians, and scientists. Ann Oncl. 2012;26(8):1519–20.CrossRef Mignatiadis MB, Sotiriou C. St Gallen international expert consensus on the primary therapy of early breast cancer: an invaluable tool for physicians, and scientists. Ann Oncl. 2012;26(8):1519–20.CrossRef
19.
Zurück zum Zitat Karlsson P, Cole BF, Price KN, et al. The role of the number of uninvolved lymph nodes in predicting locoregional recurrence in breast cancer. J Clin Oncol. 2007;25(15):2019–26.CrossRef Karlsson P, Cole BF, Price KN, et al. The role of the number of uninvolved lymph nodes in predicting locoregional recurrence in breast cancer. J Clin Oncol. 2007;25(15):2019–26.CrossRef
20.
Zurück zum Zitat Shen S, Zhong S, Lu H, et al. A meta-analysis of lymphatic vessel invasion correlated with pathologic factors in invasive breast cancer. J Cancer Ther. 2015;6:315–21.CrossRef Shen S, Zhong S, Lu H, et al. A meta-analysis of lymphatic vessel invasion correlated with pathologic factors in invasive breast cancer. J Cancer Ther. 2015;6:315–21.CrossRef
21.
Zurück zum Zitat Choi JW, Moon BI, Lee JW, et al. Use of CA15-3 for screening breast cancer: an antibody-lectin sandwich assay for detecting glycosylation of CA15-3 in sera. Oncol Rep. 2018;40(1):145–54.PubMedPubMedCentral Choi JW, Moon BI, Lee JW, et al. Use of CA15-3 for screening breast cancer: an antibody-lectin sandwich assay for detecting glycosylation of CA15-3 in sera. Oncol Rep. 2018;40(1):145–54.PubMedPubMedCentral
22.
Zurück zum Zitat Menon SS, Guruvayoorappan C, Sakthivel KM, et al. Ki-67 protein as a tumour proliferation marker. Clin Chim Acta. 2019;491:39–45.CrossRef Menon SS, Guruvayoorappan C, Sakthivel KM, et al. Ki-67 protein as a tumour proliferation marker. Clin Chim Acta. 2019;491:39–45.CrossRef
23.
Zurück zum Zitat Zhang H, Sui X, Zhou S, et al. About “correlation of conventional ultrasound characteristics of breast tumors with axillary lymph node metastasis and ki-67 expression in patients with breast cancer”. J Ultrasound Med. 2019;38(7):1833. https://doi.org/10.1002/jum.14930 [Epub ahead of print].CrossRefPubMed Zhang H, Sui X, Zhou S, et al. About “correlation of conventional ultrasound characteristics of breast tumors with axillary lymph node metastasis and ki-67 expression in patients with breast cancer”. J Ultrasound Med. 2019;38(7):1833. https://​doi.​org/​10.​1002/​jum.​14930 [Epub ahead of print].CrossRefPubMed
24.
Zurück zum Zitat Peng JH, Zhang X, Song JL, et al. Neoadjuvant chemotherapy reduces the expression rates of ER, PR, HER2, Ki67, and P53 of invasive ductal carcinoma. Medicine (Baltimore). 2019;98(2):e13554.CrossRef Peng JH, Zhang X, Song JL, et al. Neoadjuvant chemotherapy reduces the expression rates of ER, PR, HER2, Ki67, and P53 of invasive ductal carcinoma. Medicine (Baltimore). 2019;98(2):e13554.CrossRef
Metadaten
Titel
Value of digital mammography in predicting lymphovascular invasion of breast cancer
verfasst von
Zhuangsheng Liu
Ruqiong Li
Keming Liang
Junhao Chen
Xiangmeng Chen
Xiaoping Li
Ronggang Li
Xin Zhang
Lilei Yi
Wansheng Long
Publikationsdatum
01.12.2020
Verlag
BioMed Central
Erschienen in
BMC Cancer / Ausgabe 1/2020
Elektronische ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-020-6712-z

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