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Breast MRI for prediction of lymphovascular invasion in breast cancer patients with clinically negative axillary lymph nodes
European Journal of Radiology 107 (2018) 111–118
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European Journal of Radiology journal homepage: www.elsevier.com/locate/ejrad
Research article
Breast MRI for prediction of lymphovascular invasion in breast cancer patients with clinically negative axillary lymph nodes
T
⁎
Takao Igarashi , Hisayo Furube, Hirokazu Ashida, Hiroya Ojiri Department of Radiology, The Jikei University School of Medicine, 3-25-8, Nishi-Shimbashi, Minato-ku, Tokyo 105-8461, Japan
A R T I C LE I N FO
A B S T R A C T
Keywords: Breast MRI Lymphovascular invasion
Objective: To retrospectively assess magnetic resonance imaging (MRI) findings that can predict lymphovascular invasion (LVI) in invasive breast cancer patients who were diagnosed with clinically negative axillary lymph nodes (LNs) preoperatively. Methods: This study included 140 lesions of 140 patients who underwent preoperative breast MRI and breast surgery, with omission of axillary LN dissection. Clinical characteristics and MRI findings were evaluated. The T2 signal intensity (SI) ratio (mean T2 SI of the tumor/mean T2 SI of the muscle), tumor apparent diffusion coefficient (ADC) value, peritumoral ADC value, peritumor-tumor ADC ratio (peritumoral maximum ADC value/ tumor mean ADC value), and ADC value of the contralateral breast parenchyma were retrospectively assessed. Statistical analyses were performed to identify significant factors for predicting LVI. Inter-observer variability was calculated. Results: The tumor ADC value (all ages: p = 0.005; age ≤ 55: p < 0.001), peritumoral ADC value (age ≤ 55: p = 0.04), and peritumor-tumor ADC ratio (all ages: p < 0.001; age ≤ 55: p < 0.001) were significantly associated with LVI on univariate analysis. Multivariate logistic regression analysis revealed significant differences in the pathological size of the invasive component and the tumor ADC value for predicting LVI (odds ratio [OR]: 3.43; 95% confidence interval [CI]: 1.41–8.32; p = 0.007; OR: 16.0; 95% CI: 1.89–136; p = 0.01, respectively). Inter-observer agreement was substantial for the tumor ADC value (intraclass correlation coefficient [ICC] = 0.77; 95% CI: 0.70–0.83) and the ADC value of the contralateral breast parenchyma (ICC = 0.68; 95% CI: 0.59–0.76). There was moderate agreement for the peritumoral ADC value (ICC = 0.53; 95% CI: 0.40–0.64) and the peritumor-tumor ADC ratio (ICC = 0.49; 95% CI: 0.35–0.61) and fair agreement for the T2 SI ratio (ICC = 0.30; 95% CI: 0.15–0.45). Conclusion: We found that the tumor ADC value, peritumoral ADC value, and peritumor-tumor ADC ratio were predictive MRI findings for LVI in patients aged ≤55. The tumor ADC value was the most significant predictor for LVI; moreover, inter-observer agreement for the tumor ADC value was substantial between two blinded observers with differences in interpretation experience.
1. Introduction Lymphovascular invasion (LVI) has been pathologically defined as the presence of tumor cells within both lymphatic and vascular space in the area surrounding an invasive carcinoma [1]. LVI has been accepted as sufficiently reliable to define risk of relapse and survival rate in lymph node (LN)-negative breast cancer patients [2–5]. A strong association between axillary nodal metastasis and LVI was found in a large study, in which positive LNs were detected in 51% of LVI-positive patients, compared with 19% of LVI-negative patients [6]. It is, therefore,
essential for breast cancer patients to undergo preoperative imaging of LVI and axillary LN in terms of prognostic prediction [3,7]. Since LVI is confirmed by histopathological examination, based on an excised specimen that contains primary lesion and perilesional breast tissue, it is difficult to confirm LVI by preoperative biopsy, which contains only primary lesion. Therefore, preoperative magnetic resonance imaging (MRI) is expected to provide an imaging biomarker that can predict LVI. Some recent studies have shown that apparent diffusion coefficient (ADC) value is a prognostic factor related to tumor aggressiveness in patients with breast cancer [8–10]. Recent retrospective cohort studies
Abbreviations: MRI, magnetic resonance imaging; LVI, lymphovascular invasion; LN, lymph node; SI, signal intensity; ADC, apparent diffusion coefficient; OR, odds ratio; CI, confidence interval ⁎ Corresponding author. E-mail addresses: [email protected] (T. Igarashi), [email protected] (H. Furube), [email protected] (H. Ashida), [email protected] (H. Ojiri). https://doi.org/10.1016/j.ejrad.2018.08.024 Received 2 May 2018; Received in revised form 1 August 2018; Accepted 26 August 2018 0720-048X/ © 2018 Elsevier B.V. All rights reserved.
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found that ADC values were significantly lower in the LVI-positive group than the -negative group [11,12]. A lower ADC value is associated with reduction in the speed of osmosis in tumor tissue and with greater tumor cell proliferation. LVI was associated with a high tumor cell proliferation level or high Ki-67 labeling index [13]. Peritumortumor ADC ratio has been reported to be a feasible method of MRI, and is device-independent. This method could objectively assess lymphedema caused by LVI [12]. Little has been reported regarding the combination of preoperative findings, including MRI, associated with prediction of LVI in breast cancer patients who were preoperatively diagnosed with negative axillary LNs (hereafter defined as “clinically negative nodes”). Identification of predictive findings that are associated with LVI has enabled us to determine the need for additional therapy. This study was undertaken to characterize preoperative MRI findings that can predict LVI in invasive breast cancer patients with clinically negative nodes.
the least squares method with all three images and b values of 0, 1000, and 1500 s/mm2. Dynamic contrast-enhanced MR (CEM) images were acquired with a three-dimensional fat-suppressed volumetric interpolated breath-hold examination sequence by using the following parameters: TR/TE, 5 ms/2.41 ms; flip angle, 15°; field of view, 340 mm; matrix, 768 × 768; receiver bandwidth, 340 kHz/pixel; mean partition thickness, 0.9 mm; time of acquisition, 60 s; NEX, 1. The section thickness varied depending on the size of the breast. Sections were acquired without a gap. Both breasts were included in the images. Three contrast-enhanced acquisitions were acquired at 60, 120, and 240 s after the start of the IV administration of 0.1 mmol/kg gadopentetate dimeglumine or gadobutrol (Magnevist or Gadovist; Bayer HealthCare, Berlin, Germany); administration was at a rate of 1 mL/s, followed by a 15 mL saline flush, and was performed with an automatic injector.
2. Material and methods
2.3. Image analysis
2.1. Patients
One radiologist with 16 years of experience retrospectively evaluated the clinical characteristics for which clinical and pathological information were available. Then, another radiologist with 16 years of experience in breast MR imaging (first blinded observer) re-evaluated the continuous variables of MRI findings on a PACS monitor while blinded to the clinical and pathological information. All cases were anonymized for re-evaluation. Another radiologist with 4 years of experience in breast MRI (second blinded observer) evaluated the continuous variables of the MRI findings to assess the reproducibility of the first observer’s evaluation. The second observer was blinded to the results of the first observer and to the clinical and histopathological information. Continuous variables of MRI findings included the T2 signal intensity (SI) ratio, tumor ADC value, peritumoral ADC value, peritumortumor ADC ratio, and ADC value of the contralateral breast parenchyma. ROIs were placed on targeted regions by referring to the findings of the dynamic CEM images. In a case of a multifocal or multicentric lesion, the largest tumor was accepted for analysis. For measurements of T2 SI of the tumor, the largest tumor cross section was selected, and an oval or round ROI, as large as possible, was placed inside the tumor. Another ROI was also placed on the pectoralis major muscle to measure the T2 SI of the muscle and calculate the T2 SI ratio between the lesion and the muscle. The T2 SI ratio was calculated according to the following formula:
This retrospective study was approved by the Committee on Clinical Studies at our institution (approval number, 29-268). The requirement for informed consent was waived. In total, 921 consecutive patients underwent breast MRI between July 17, 2015 and June 30, 2017 at our institution. The phase of the menstrual cycle of patients aged ≤55 was not considered because this was a retrospective study; therefore, it was not possible to analyze the phase of menstrual cycle during the MRI examination. The following inclusion criteria were used: (a) patients who had no suspicious findings, suggestive of metastatic LNs, on both preoperative breast ultrasonography and MRI; (b) patients who underwent both sentinel lymph node (SLN) biopsy and breast surgery, with omission of axillary LN dissection. Preoperative imaging findings suggestive of negative axillary LNs were evaluated based on a previous report [13], as follows: negative for round-shaped LNs with a completely or partially effaced fatty hilum; negative for LNs with irregular margins and/or cortical thickening (≥5 mm; focal or diffuse); negative for extra-hilar blood vessel flow on color doppler analysis. The following exclusion criteria were used: (a) patients who did not undergo US and/or MRI within the six-month period immediately preceding surgery (n = 47); (b) patients who had a past medical history of neoadjuvant chemotherapy and/or radiotherapy and/or breast surgery (n = 47); (c) patients who were diagnosed with ductal carcinoma in situ (n = 39), (d) intracystic papillary carcinoma (n = 2), (d) intraductal papilloma (n = 1), (e) Paget’s disease (n = 4), (f) invasive cancer of < 1 mm (n = 6) on histopathological examination; and (g) patients with small lesions in which an region of interest (ROI) could not be placed using a picture archiving and communication systems (PACS) monitor (n = 2). A total of 140 patients met the inclusion and exclusion criteria (Fig. 1).
T2 SI ratio = mean T2 SI of the tumor/mean T2 SI of the muscle. (1) The tumor ADC value, peritumoral ADC value, and ADC value of the contralateral breast parenchyma measurements were calculated using ADC maps. To measure the tumor ADC value, ROIs were manually placed within the solid component of the tumor. To measure the peritumoral ADC value and the ADC value of the contralateral breast parenchyma, ROIs were manually placed in the breast parenchyma; fatty tissue was avoided to the extent possible. ROIs of the peritumoral ADC value were placed within 2 cm from the border between the tumor and the normal breast parenchyma. At least three measurements were taken for all continuous variables on MR images. The mean value among the three T2 SI ratios, the minimum value among the three mean tumor ADC values, the maximum value among the three maximum peritumoral ADC values, and the minimum value among the three mean ADC values of the contralateral breast parenchyma were accepted as the T2 SI ratio, tumor ADC value, peritumoral ADC value, and ADC value of the contralateral breast parenchyma, respectively. We calculated the peritumor-tumor ADC ratio, which has been reported to be a feasible method, according to the following formula [12]:
2.2. Image acquisition MRI was performed by using a 1.5-T system (Symphony, Siemens Medical Solutions, Erlangen, Germany) with a maximum gradient field strength of 30 m T/m and a 4-ch CP breast array coil. All patients were examined in the prone position. First, coronal T2-weighted spectral attenuated inversion recovery images of both breasts were obtained with the following parameters: repetition time (TR)/echo time (TE), 4000 ms/73 ms; flip angle, 150°; field of view, 35 × 35 cm; matrix size, 806 × 896; slice thickness, 4 mm; gap, 0; number of excitations (NEX), 1. Subsequently, coronal diffusion-weighted images of both breasts were obtained at b values of 0, 1000, and 1500 s/mm2 with the following parameters: TR/TE, 5600 ms/87 ms; field of view, 35 × 35 cm; matrix size, 234 × 320; slice thickness, 3.5 mm; slice gap, 0; NEX, 5. ADC maps were automatically generated on the operating console using
Peritumor-tumor ADC ratio = peritumoral maximum ADC value/tumor mean ADC value. (2) 112
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Fig. 1. Flow diagram for the patient selection process.
for the following cases: (a) SLNs had no metastatic cells or only isolated tumor cells; (b) SLNs had only 1-2 lymph nodes with metastatic cells, for patients who had undergone breast-conserving surgery. In this study, a positive SLN was defined as a LN with isolated tumor cells, micrometastases (diameter of metastatic deposit, 0.2–2 mm), or macrometastases (metastatic tumor with a maximum diameter > 2 mm). LVIs were classified into four grades: ly/v 0 (no LVI), ly/v 1 (minimal LVI), ly/v 2 (moderate LVI), and ly/v 3 (marked LVI). We divided LVIs into LVI-positive (ly/v 1-3) and LVI-negative groups (ly/v 0). The following variables were evaluated in all primary tumors: histopathological type; immunohistochemical staining for estrogen receptors (ER), progesterone receptors (PgR), and human epidermal growth factor receptor 2 (HER2); Ki-67 proliferation index, nuclear grade, size of the invasive component, and the presence of LVI. The size of the invasive component was defined as the maximum diameter of the focal invasion, excluding the intra-ductal component, on histopathological examination. Hormonal status was considered positive if > 1% of tumor cells were positive for ER or PgR [14]. HER2 positivity was defined as a score of 3+ on immunohistochemical staining, or as a score of 2+ with confirmation of HER2 gene amplification by fluorescence in situ hybridization. Ki-67 proliferation index was determined based on immunohistochemical analysis; an index of < 14% was considered low, and an index of ≥14% was considered high [15].
Inter-observer variability was assessed for each continuous variable. An age-dependent evaluation was conducted for the continuous variables with a cutoff at age 55, in consideration of the fact that natural menopause occurs at up to 55 years old for women worldwide. 2.4. Assessment of sentinel node SLN biopsy was performed with a radiocolloid and a dye. Mapping agents were injected into the subdermal plexus. 99mTC-labeled phytate colloid was injected on the day of surgery (0.25 mL, 15 MBq) or the day before surgery (0.5 mL, 30 MBq), and lymphoscintigraphy was performed. During the surgery, 5 mL of isosulfan blue dye (Lymphazurin; Covidien, Mansfield, MA, USA) or 3 mL of indocyanine green dye (Diagnogreen; Daiichi Sankyo, Tokyo, Japan) was injected. SLNs were identified as those with dye uptake, radiotracer uptake, or both. 2.5. Histopathological assessment All SLNs were sectioned along their short axis at 2-mm intervals. The nodal tissue was quickly frozen in liquid nitrogen, and a single 5μm-thick section, stained with hematoxylin and eosin (H & E), was examined intraoperatively (frozen-section analysis). In our institution, breast surgery with omission of axillary LN dissection was performed 113
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2.6. Statistical analysis
Table 1 Clinical characteristics.
All statistical analyses were performed with Ekuseru-Toukei 2015 (SSRI, Tokyo, Japan) and R (The R Project for Statistical Computing, www.r-project.org, version 3.3.0) software. Qualitative variables were analyzed with Fisher’s exact test. Fisher’s exact test with the BenjaminiHochberg method was used for multiple pairwise comparisons. Continuous variables were analyzed with the Mann-Whitney U test. Diagnostic performance was estimated by using receiver operating characteristic (ROC) analysis by calculating the area under the ROC curve (AUC) for each continuous variable that showed a significant difference on univariate analysis. A cutoff value differentiating the LVIpositive and -negative groups was chosen to maximize the Youden index. Based on the cutoff values, continuous variables were fit to the multivariate logistic regression analysis. Multivariate logistic regression analysis was performed with variables related to MRI findings that showed significant differences in univariate analyses. p < 0.05 was considered statistically significant. Inter-observer variability of the continuous variables was assessed by using intraclass correlation coefficients (ICCs). An ICC of 0.81–1.0 was considered to indicate almost perfect agreement; 0.61–0.80, substantial agreement; 0.41–0.60, moderate agreement; 0.21–0.40, fair agreement; and ≤0.20, slight agreement.
Variable
Patient age (years) ≤55 > 55 Histopathological type Scirrhous carcinoma Papillotubular carcinoma Solid-tubular carcinoma Mucinous carcinoma (pure type) Mucinous carcinoma (mixed type) Apocrine carcinoma Metaplastic carcinoma Invasive micropapillary carcinoma Invasive lobular carcinoma Intrinsic subtype Luminal A Luminal B HER2 Triple-negative Ki-67 index All ages Age, ≤ 55 Age, > 55
3. Results Histopathological examination revealed patients with (n = 41) and without LVI (n = 99) among the 140 lesions. Univariate analyses of the qualitative and continuous variables are summarized in Tables 1 and 2. Results reported regarding continuous variables on MRI are based on assessments by the first blinded observer. The median (interquartile range, 25–75 percentile) of all ROIs was 20 mm2 (15–27) for the first observer and 28 mm2 (19–38) for the second observer. In the univariate analyses of clinical characteristics, the pathological size of the invasive component (all ages: p < 0.001; age ≤ 55: p < 0.001), Ki-67 index (all ages: p = 0.03; age ≤ 55: p = 0.02), and SLN positivity (p < 0.001) were significantly associated with LVI. For the intrinsic subtype and clinical stage, Luminal B tumor and clinical stage T2 are significantly more likely than luminal A and clinical stage T1 to exhibit LVI (adjusted p = 0.03 and adjusted p = 0.002, respectively). For continuous variables on MR images, the tumor ADC value (all ages: p = 0.005; age ≤ 55: p < 0.001), peritumoral ADC value (age ≤ 55: p = 0.04), and peritumor-tumor ADC ratio (all ages: p < 0.001; age ≤ 55: p < 0.001) were significantly associated with LVI (Figs. 2 and 3). The only significant variable identified in patients aged > 55 years was the ADC value of the contralateral breast parenchyma (p = 0.02). The AUC for the pathological size of the invasive component was 0.72, for the tumor ADC value it was 0.64, and for the peritumor-tumor ADC ratio it was 0.70. Multivariate logistic regression analysis revealed significant differences in the pathological size of the invasive component, SLN positivity and the tumor ADC value for the prediction of LVI (odds ratio [OR]: 3.43; 95% confidence interval [CI]: 1.41–8.32; p = 0.007; OR: 2.96; 95% CI: 1.15–7.62; p = 0.02; OR: 16.0; 95% CI: 1.89–136; p = 0.01, respectively; Table 3). The diagnostic performance, based on the data when applying the cutoff values of 2 cm for the pathological size of the invasive component and 0.862 × 10−3 mm2/s for the tumor ADC value, is summarized in Table 4. Inter-observer agreement was substantial for the tumor ADC value (ICC = 0.77; 95% CI: 0.70–0.83) and the ADC value of the contralateral breast parenchyma (ICC = 0.68; 95% CI: 0.59–0.76). There was moderate agreement for the peritumoral ADC value (ICC = 0.53; 95% CI: 0.40–0.64) and the peritumor-tumor ADC ratio (ICC = 0.49; 95% CI: 0.35–0.61) and fair agreement for the T2 SI ratio (ICC = 0.30; 95% CI: 0.15–0.45).
Nuclear grade Low or intermediate High Clinical stage T1 T2 T3
Patients with LVI (n = 41)
Patients without LVI (n = 99)
23 18
43 56
28 8 3
48 22 13 3
0.20
1 1 1 1 1
10
6 34 1 0
36 52 5 6
25 (16–40) 25.7 (18–42.55) 24.4 (15.08–30.75)
19.3 (10.2–30.6) 17.1 (9.7–32) 20 (11.5–30)
32 9
86 13
17 22 2
73 24 2
0.03
0.03 0.02 0.37 0.21
0.002
Pathological size of invasive component (mm) All ages 24 (16–32) Age, ≤ 55 25 (16.5–36) Age, > 55 23 (16.25–25) Lesion type Mass Non-mass SLN Positive Negative
p
15 (10–22) 12 (9.5–17) 16.5 (10.75–23.25)
< 0.001 < 0.001 0.06 0.11
40 1
87 12
21 20
19 80
< 0.001
Abbreviations: LVI: lymphovascular invasion; SLN: sentinel lymph node. The size of the invasive component and the Ki-67 index are expressed as the age-based median and interquartile range (25–75 percentile). In a multiple comparison of the intrinsic subtype and clinical stage, after performing the Fisher's exact test with the variables above, the results were corrected using the Benjamini-Hochberg method. Only the lowest adjusted p-values are shown. There were significant differences between Luminal A and Luminal B, and between clinical stage T1 and T2.
4. Discussion Our results are consistent with a recent retrospective cohort study that reported that breast cancers with LVI had significantly lower ADC values than breast cancers without LVI, independent of the histological subtype, grades of the ductal histological type, and mass lesions [11]. Our results also agree with a previous study that reported that the ADC value, peritumor-tumor ADC ratio, tumor diameter, Ki-67 index, and axillary LN metastasis were significantly different between patients with and without LVI [12]. The minimum-ADC value has been suggested as an effective parameter for the prediction of LVI status, and it was reported that LVI status had a strong positive correlation with LN status [16]. Thus, our results showed that the minimum mean tumor
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Table 2 Results of continuous variables on MR images. Variable
T2 SI ratio Tumor ADC value (×10−3 mm2/s) Peritumoral ADC value (×10−3 mm2/s) Peritumor-tumor ADC ratio ADC value of the contralateral breast parenchyma (×10−3 mm2/s)
Age ≤ 55
All ages
Age > 55
Patients with LVI (n = 41)
Patients without LVI (n = 99)
p
Patients with LVI (n = 23)
Patients without LVI (n = 43)
p
Patients with LVI (n = 18)
Patients without LVI (n = 56)
p
3.62 (2.75–4.57) 738.17 (664.6–814.87) 1849 (1661–2080)
3.45 (2.73–4.88) 785.26 (714.74–884.33) 1717 (1556–1967)
0.65 0.005
3.03 (2.78–4.02) 733.22 (665.14–790.42) 1985 (1795–2151)
3.33 (2.71–4.73) 808.85 (712.63–891.74) 1743 (1497–1939)
0.71 < 0.001
3.71 (2.93–5.27) 781.65 (718.60–842.51) 1707 (1581.5–1975.5)
0.90 0.20
0.04
4.19 (2.80–5.16) 753.51 (652.27–821.87) 1799 (1618–1936)
2.60 (2.25–2.72)
2.16 (1.91–2.50)
< 0.001
2.65 (2.40–3.02)
2.10 (1.88–2.49)
< 0.001
2.44 (2.12–2.67)
2.26 (1.94–2.50)
0.15
1761 (1547–1950)
1779 (1608–1883)
0.95
1941 (1747–2013)
1774 (1608–1898)
0.14
1579 (1424–1780)
1794 (1613–1881)
0.02
0.08
0.83
Abbreviations: MR: magnetic resonance; LVI: lymphovascular invasion; SI: signal intensity; ADC: apparent diffusion coefficient. Continuous variables are expressed as the median and interquartile range (25–75 percentile).
aggressiveness indicators, such as Ki-67, in ER-positive breast cancers [17,18]. Jacquemier et al. reported that higher Ki-67 values were associated with vascular and lymphatic invasion [19]. It has also been reported that premenopausal breast cancer patients tend to have higher Ki-67 values, while postmenopausal patients tend to have lower Ki-67
ADC value may contribute to the prediction of lymphatic invasion. Our results also showed that the measurement of the tumor ADC value could be conducted while ensuring reproducibility between blinded readers with differences in interpretation experience. Previous reports suggested that the tumor ADC value was correlated with tumor
Fig. 2. MR images of a 74-year-old woman with invasive ductal carcinoma (Luminal A) beneath the left nipple. Lymphovascular invasion and nodal macrometastasis were confirmed at the histopathological examination. (A) Coronal diffusion-weighted image (b = 1500) showing a margin-dominant high-intensity mass measuring approximately 20 mm. (B) Coronal apparent diffusion coefficient (ADC) map showing a mass with low signal suggestive of restricted diffusion (arrow). It can be confirmed visually that the region surrounding the mass shows higher signal intensity than the other region including the right mammary gland in the ADC map (arrowheads). The tumor ADC value was 0.680 (×10−3 mm2/s), the peritumor-tumor ADC ratio was 2.825.
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Fig. 3. MR images of a 60-year-old woman with invasive ductal carcinoma (Luminal B) in the medial upper region of the left breast. No lymphovascular invasion or nodal metastasis were confirmed on the histopathological examination. (A) Coronal diffusion-weighted image (b = 1500) showing a margin-dominant high-intensity mass measuring approximately 12 mm. (B) Coronal apparent diffusion coefficient (ADC) map showing a mass with low signal suggestive of restricted diffusion (arrow). The region surrounding the mass is iso-intensity compared to the other region including the right mammary gland in the ADC map (arrowhead). The tumor ADC value was 0.713 (×10−3 mm2/s), peritumor-tumor ADC ratio was 2.157.
values [20]; that is, postmenopausal patients tend to have low proliferative activity. Both the tumor ADC value and the Ki-67 index of patients aged ≤55 years showed significant differences regarding the LVI status, but there were no significant differences in patients aged > 55 years on univariate analysis. Our study indicated that the lower tumor ADC value and higher Ki-67 index in patients aged ≤55 years were predictors of LVI positivity. Considering previous reports that showed tumor ADC value did not correlate with LN status [11,9], our results therefore infer predicting LVI status with measurements of tumor ADC value can be useful for prognostic prediction. Mori et al. reported that there was a significant difference between the tumor ADC values of LVI-positive and -negative postmenopausal patients [12], while in our study, they were not significantly different in patients aged > 55 years. Considering the correlation of ADC with Ki-67 index [17,18], our findings, which showed that tumor ADC value and Ki-67 index in patients aged > 55 years were not significantly different, are theoretically consistent. Peritumoral ADC values of patients aged ≤55 years showed a significant difference between patients with and without LVI. However, no similar results were identified in patients of all ages or in those aged > 55 years. Mori et al. reported that the peritumoral ADC values of all patients and of postmenopausal patients showed a significant difference regarding the presence of LVI [12]. It is conceivable that the reason our results were different from those of Mori et al. is that we did not exclude cases with scattered and fatty breast tissue surrounding the tumor. Although ROIs were placed in the peritumoral breast parenchyma and avoided fat to the extent possible, they might have contained fat components. Mori et al. excluded patients who had no breast
Table 3 Results of multivariate logistic regression analysis. Variable
OR
95% CI
p
Pathological size of invasive component (> 2 cm vs. ≤ 2 cm) Ki 67 index (> 14.9 vs. ≤ 14.9) SLN (positive vs. negative) Tumor ADC value (≤0.862 vs. > 0.862) (×10−3 mm2/s) Peritumor-tumor ADC ratio (> 2.372 vs. ≤ 2.372)
3.43
1.41–8.32
0.007
1.39 2.96 16.0
0.51–3.85 1.15–7.62 1.89–136
0.52 0.02 0.01
1.48
0.59–3.72
0.41
Abbreviations: OR: odds ratio; CI: confidence interval; SLN: sentinel lymph node; ADC: apparent diffusion coefficient. Table 4 The diagnostic performance of the pathological size of the invasive component and the tumor ADC value.
Pathological size of the invasive component (> 2 cm vs. ≤ 2 cm) Tumor ADC value (≤0.862 vs. > 0.862) (×10−3 mm2/s)
Sensitivity
Specificity
PPV
NPV
Accuracy
61
74
49
82
70
98
30
37
97
50
Abbreviations: PPV: positive predictive value; NPV: negative predictive values; ADC: apparent diffusion coefficient. Data are expressed as percentages.
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Funding sources
parenchyma surrounding the tumor. Accordingly, measurements of the peritumoral ADC value might have affected the results of our study. With aging, the breast parenchyma is replaced with fatty tissue [21]. It has been reported that postmenopausal breast tissue has a significantly lower ADC than premenopausal tissue [22]. Age-related fatty replacement of breast tissue is associated with decreasing serum estradiol and progesterone. Hence, ADC values are likely to be reduced due to a reduction in the speed of osmosis as breast tissue becomes fatty in postmenopausal patients. Although the value of the peritumoral-tumoral ADC ratio for the prediction of LVI and peritumoral edema as a prognostic factor associated with disease recurrence were reported [12,23], method limitations should be considered when assessing the status of the peritumoral region in breast cancer patients with scattered or fatty breast tissue. Several limitations of our study must be considered. First, this retrospective study included several special histological types. Hence, it is difficult to compare our results with previous reports that included only luminal type cancers [17,18]. An additional, prospective study is necessary to confirm our results. Second, we did not assess correlation of measurement values for the size of the invasive component between MRI and histopathological results. Further studies are needed to investigate whether radiological size measurement could be a predictor of LVI status, especially in the case of a mass forming lesion, which is relatively easy to measure. This may be less feasible in the case of a non-mass lesion, as it is difficult to measure the size of the invasive component. Third, it is possible that the peritumoral ADC and ADC values of the contralateral breast parenchyma did not accurately reflect the true conditions, because the ROIs of some cases may have contained fat components. Fourth, we included patients with mucinous carcinoma. Since the ADC value of mucinous carcinoma is different from that of ordinary invasive ductal carcinoma, it may have been appropriate to consider excluding those cases. Fifth, we did not consider fibrocystic breast changes. Previous studies have reported that the ADC value of normal fibroglandular tissues was not significantly affected by the menstrual cycle [22]. However, the effects of fibrocystic changes on the ADC values of normal breast tissue have not been clarified. The pathophysiology of fibrocystic breast change is determined by estrogen predominance and progesterone deficiency, which results in the hyperproliferation of connective tissue, followed by facultative epithelial proliferation [24]. Izumori et al. reported that the thickness of the normal breast stroma surrounding lobules and ducts was not always uniform [25], and we speculate that this non-uniformity could be affected by fibrocystic breast changes. As a result, fibrocystic breast changes might affect the measurement of ADC values of the breast parenchyma, especially in patients aged ≤55 years. Sixth, we could not investigate the history of hormone replacement therapy (HRT) of all patients at any time in their lives; this should be considered because normal fibroglandular tissues could be affected by HRT.
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Ellis, Improved methods of detection of lymphovascular invasion demonstrate that it is the predominant method of vascular invasion in breast cancer and has important clinical consequences, Am. J. Surg. Pathol. 31 (2007) 1825–1833. [5] E.A. Rakha, S. Martin, A.H. Lee, D. Morgan, P.D. Pharoah, Z. Hodi, D. Macmillan, I.O. Ellis, The prognostic significance of lymphovascular invasion in invasive breast carcinoma, Cancer 118 (2012) 3670–3680. [6] C. Gajdos, P.I. Tartter, I.J. Bleiweiss, Lymphatic invasion, tumor size, and age are independent predictors of axillary lymph node metastases in women with T1 breast cancers, Ann. Surg. 230 (1999) 692–696. [7] A.H. Lee, S.E. Pinder, R.D. Macmillan, M. Mitchell, I.O. Ellis, C.W. Elston, R.W. Blamey, Prognostic value of lymphovascular invasion in women with lymph node negative invasive breast carcinoma, Eur. J. Cancer 42 (2006) 357–362. [8] L. Martincich, V. Deantoni, I. Bertotto, S. Redana, F. Kubatzki, I. Sarotto, V. Rossi, M. Liotti, R. Ponzone, M. Aglietta, D. Regge, F. Montemurro, Correlations between diffusion-weighted imaging and breast cancer biomarkers, Eur. Radiol. 22 (2012) 1519–1528. [9] S.H. Park, H.Y. Choi, S.Y. Hahn, Correlations between apparent diffusion coefficient values of invasive ductal carcinoma and pathologic factors on diffusion-weighted MRI at 3.0 Tesla, J. Magn. Reson. Imaging 41 (2015) 175–182. [10] S.B. Thakur, M. Durando, S. Milans, G.Y. Cho, L. Gennaro, E.J. Sutton, D. Giri, E.A. Morris, Apparent diffusion coefficient in estrogen receptor-positive and lymph node-negative invasive breast cancers at 3.0T DW-MRI: a potential predictor for an oncotype Dx test recurrence score, J. Magn. Reson. Imaging 47 (2) (2018) 401–409. [11] M. Durando, L. Gennaro, G.Y. Cho, D.D. Giri, M.M. Gnanasigamani, S. Patil, E.J. Sutton, J.O. Deasy, E.A. Morris, S.B. Thakur, Quantitative apparent diffusion coefficient measurement obtained by 3.0 Tesla MRI as a potential noninvasive marker of tumor aggressiveness in breast cancer, Eur. J. Radiol. 85 (2016) 1651–1658. [12] N. Mori, S. Mugikura, C. Takasawa, M. Miyashita, A. Shimauchi, H. Ota, T. Ishida, A. Kasajima, K. Takase, T. Kodama, S. Takahashi, Peritumoral apparent diffusion coefficients for prediction of lymphovascular invasion in clinically node-negative invasive breast cancer, Eur. Radiol. 26 (2016) 331–339. [13] H. Abe, R.A. Schmidt, K. Kulkarni, C.A. Sennett, J.S. Mueller, G.M. Newstead, Axillary lymph nodes suspicious for breast cancer metastasis: sampling with USguided 14-gauge core-needle biopsy—clinical experience in 100 patients, Radiology 250 (2009) 41–49. [14] H. Yaziji, C.R. Taylor, N.S. Goldstein, D.J. Dabbs, E.H. Hammond, B. Hewlett, A.D. Floyd, T.S. Barry, A.W. Martin, S. Badve, F. Baehner, R.W. Cartun, R.N. Eisen, P.E. Swanson, S.M. Hewitt, M. Vyberg, D.G. Hicks, Members of the Standardization Ad-Hoc Consensus Committee, Consensus recommendations on estrogen receptor testing in breast cancer by immunohistochemistry, Appl. Immunohistochem. Mol. Morphol. 16 (2008) 513–520. [15] M.C. Cheang, S.K. Chia, D. Voduc, D. Gao, S. Leung, J. Snider, M. Watson, S. Davies, P.S. Bernard, J.S. Parker, C.M. Perou, M.J. Ellis, T.O. Nielsen, Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer, J. Natl. Cancer Inst. 101 (2009) 736–750. [16] W. Yang, J.M. Qiang, H.P. Tian, B. Chen, A.J. Wang, J.G. Zhao, Minimum apparent diffusion coefficient for predicting lymphovascular invasion in invasive cervical cancer, J. Magn. Reson. Imaging 45 (2017) 1771–1779. [17] N. Mori, H. Ota, S. Mugikura, C. Takasawa, T. Ishida, G. Watanabe, H. Tada, M. Watanabe, K. Takase, S. Takahashi, Luminal-type breast cancer: correlation of apparent diffusion coefficients with the Ki-67 labeling index, Radiology 274 (2015) 66–73. [18] H.J. Shin, S.H. Kim, H.J. Lee, G. Gong, S. Baek, E.Y. Chae, W.J. Choi, J.H. Cha, H.H. Kim, Tumor apparent diffusion coefficient as an imaging biomarker to predict tumor aggressiveness in patients with estrogen receptor-positive breast cancer, NMR Biomed. 29 (2016) 1070–1078. [19] J. Jacquemier, E. Charafe-Jauffret, F. Monville, B. Esterni, J.M. Extra, G. Houvenaeghel, L. Xerri, F. Bertucci, D. Birnbaum, Association of GATA3, P53, Ki67 status and vascular peritumoral invasion are strongly prognostic in luminal breast cancer, Breast Cancer Res. 11 (2009) R23. [20] E.C. Inwald, M. Klinkhammer-Schalke, F. Hofstädter, F. Zeman, M. Koller, M. Gerstenhauer, O. Ortmann, Ki-67 is a prognostic parameter in breast cancer patients: results of a large population-based cohort of a cancer registry, Breast Cancer Res. Treat. 139 (2013) 539–552. [21] J.N. Wolfe, Breast parenchymal patterns and their changes with age, Radiology (1976) 545–552.
5. Conclusions We found that the tumor ADC value, peritumoral ADC value, and peritumor-tumor ADC ratio were predictive MRI findings for LVI in patients aged ≤55. The tumor ADC value showed a significant association with LVI, and the inter-observer agreement for tumor ADC value was substantial between two blinded observers with differences in interpretation experience. Our study suggests that, even when breast cancer patients show clinically negative nodes, if positive LVI is suspected on preoperative MRI, a more aggressive management strategy should be considered; this might include the addition of postoperative adjuvant chemotherapy and/or radiation therapy. Conflicts of interest None. 117
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[24] H. Vorherr, Fibrocystic breast disease: pathophysiology, pathomorphology, clinical picture, and management, Am. J. Obstet. Gynecol. 154 (1986) 161–179. [25] A. Izumori, R. Horii, F. Akiyama, T. Iwase, Proposal of a novel method for observing the breast by high-resolution ultrasound imaging: understanding the normal breast structure and its application in an observational method for detecting deviations, Breast Cancer 20 (2013) 83–91.
[22] J.Y. Kim, H.B. Suh, H.J. Kang, J.K. Shin, K.S. Choo, K.J. Nam, S.W. Lee, Y.L. Jung, Y.T. Bae, Apparent diffusion coefficient of breast cancer and normal fibroglandular tissue in diffusion-weighted imaging: the effects of menstrual cycle and menopausal status, Breast Cancer Res. Treat. 157 (2016) 31–40. [23] H. Cheon, H.J. Kim, T.H. Kim, H.K. Ryeom, J. Lee, G.C. Kim, J.S. Yuk, W.H. Kim, Invasive breast cancer: prognostic value of peritumoral edema identified at preoperative MR imaging, Radiology 9 (2018) 171157.
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European Journal of Radiology journal homepage: www.elsevier.com/locate/ejrad
Research article
Breast MRI for prediction of lymphovascular invasion in breast cancer patients with clinically negative axillary lymph nodes
T
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Takao Igarashi , Hisayo Furube, Hirokazu Ashida, Hiroya Ojiri Department of Radiology, The Jikei University School of Medicine, 3-25-8, Nishi-Shimbashi, Minato-ku, Tokyo 105-8461, Japan
A R T I C LE I N FO
A B S T R A C T
Keywords: Breast MRI Lymphovascular invasion
Objective: To retrospectively assess magnetic resonance imaging (MRI) findings that can predict lymphovascular invasion (LVI) in invasive breast cancer patients who were diagnosed with clinically negative axillary lymph nodes (LNs) preoperatively. Methods: This study included 140 lesions of 140 patients who underwent preoperative breast MRI and breast surgery, with omission of axillary LN dissection. Clinical characteristics and MRI findings were evaluated. The T2 signal intensity (SI) ratio (mean T2 SI of the tumor/mean T2 SI of the muscle), tumor apparent diffusion coefficient (ADC) value, peritumoral ADC value, peritumor-tumor ADC ratio (peritumoral maximum ADC value/ tumor mean ADC value), and ADC value of the contralateral breast parenchyma were retrospectively assessed. Statistical analyses were performed to identify significant factors for predicting LVI. Inter-observer variability was calculated. Results: The tumor ADC value (all ages: p = 0.005; age ≤ 55: p < 0.001), peritumoral ADC value (age ≤ 55: p = 0.04), and peritumor-tumor ADC ratio (all ages: p < 0.001; age ≤ 55: p < 0.001) were significantly associated with LVI on univariate analysis. Multivariate logistic regression analysis revealed significant differences in the pathological size of the invasive component and the tumor ADC value for predicting LVI (odds ratio [OR]: 3.43; 95% confidence interval [CI]: 1.41–8.32; p = 0.007; OR: 16.0; 95% CI: 1.89–136; p = 0.01, respectively). Inter-observer agreement was substantial for the tumor ADC value (intraclass correlation coefficient [ICC] = 0.77; 95% CI: 0.70–0.83) and the ADC value of the contralateral breast parenchyma (ICC = 0.68; 95% CI: 0.59–0.76). There was moderate agreement for the peritumoral ADC value (ICC = 0.53; 95% CI: 0.40–0.64) and the peritumor-tumor ADC ratio (ICC = 0.49; 95% CI: 0.35–0.61) and fair agreement for the T2 SI ratio (ICC = 0.30; 95% CI: 0.15–0.45). Conclusion: We found that the tumor ADC value, peritumoral ADC value, and peritumor-tumor ADC ratio were predictive MRI findings for LVI in patients aged ≤55. The tumor ADC value was the most significant predictor for LVI; moreover, inter-observer agreement for the tumor ADC value was substantial between two blinded observers with differences in interpretation experience.
1. Introduction Lymphovascular invasion (LVI) has been pathologically defined as the presence of tumor cells within both lymphatic and vascular space in the area surrounding an invasive carcinoma [1]. LVI has been accepted as sufficiently reliable to define risk of relapse and survival rate in lymph node (LN)-negative breast cancer patients [2–5]. A strong association between axillary nodal metastasis and LVI was found in a large study, in which positive LNs were detected in 51% of LVI-positive patients, compared with 19% of LVI-negative patients [6]. It is, therefore,
essential for breast cancer patients to undergo preoperative imaging of LVI and axillary LN in terms of prognostic prediction [3,7]. Since LVI is confirmed by histopathological examination, based on an excised specimen that contains primary lesion and perilesional breast tissue, it is difficult to confirm LVI by preoperative biopsy, which contains only primary lesion. Therefore, preoperative magnetic resonance imaging (MRI) is expected to provide an imaging biomarker that can predict LVI. Some recent studies have shown that apparent diffusion coefficient (ADC) value is a prognostic factor related to tumor aggressiveness in patients with breast cancer [8–10]. Recent retrospective cohort studies
Abbreviations: MRI, magnetic resonance imaging; LVI, lymphovascular invasion; LN, lymph node; SI, signal intensity; ADC, apparent diffusion coefficient; OR, odds ratio; CI, confidence interval ⁎ Corresponding author. E-mail addresses: [email protected] (T. Igarashi), [email protected] (H. Furube), [email protected] (H. Ashida), [email protected] (H. Ojiri). https://doi.org/10.1016/j.ejrad.2018.08.024 Received 2 May 2018; Received in revised form 1 August 2018; Accepted 26 August 2018 0720-048X/ © 2018 Elsevier B.V. All rights reserved.
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found that ADC values were significantly lower in the LVI-positive group than the -negative group [11,12]. A lower ADC value is associated with reduction in the speed of osmosis in tumor tissue and with greater tumor cell proliferation. LVI was associated with a high tumor cell proliferation level or high Ki-67 labeling index [13]. Peritumortumor ADC ratio has been reported to be a feasible method of MRI, and is device-independent. This method could objectively assess lymphedema caused by LVI [12]. Little has been reported regarding the combination of preoperative findings, including MRI, associated with prediction of LVI in breast cancer patients who were preoperatively diagnosed with negative axillary LNs (hereafter defined as “clinically negative nodes”). Identification of predictive findings that are associated with LVI has enabled us to determine the need for additional therapy. This study was undertaken to characterize preoperative MRI findings that can predict LVI in invasive breast cancer patients with clinically negative nodes.
the least squares method with all three images and b values of 0, 1000, and 1500 s/mm2. Dynamic contrast-enhanced MR (CEM) images were acquired with a three-dimensional fat-suppressed volumetric interpolated breath-hold examination sequence by using the following parameters: TR/TE, 5 ms/2.41 ms; flip angle, 15°; field of view, 340 mm; matrix, 768 × 768; receiver bandwidth, 340 kHz/pixel; mean partition thickness, 0.9 mm; time of acquisition, 60 s; NEX, 1. The section thickness varied depending on the size of the breast. Sections were acquired without a gap. Both breasts were included in the images. Three contrast-enhanced acquisitions were acquired at 60, 120, and 240 s after the start of the IV administration of 0.1 mmol/kg gadopentetate dimeglumine or gadobutrol (Magnevist or Gadovist; Bayer HealthCare, Berlin, Germany); administration was at a rate of 1 mL/s, followed by a 15 mL saline flush, and was performed with an automatic injector.
2. Material and methods
2.3. Image analysis
2.1. Patients
One radiologist with 16 years of experience retrospectively evaluated the clinical characteristics for which clinical and pathological information were available. Then, another radiologist with 16 years of experience in breast MR imaging (first blinded observer) re-evaluated the continuous variables of MRI findings on a PACS monitor while blinded to the clinical and pathological information. All cases were anonymized for re-evaluation. Another radiologist with 4 years of experience in breast MRI (second blinded observer) evaluated the continuous variables of the MRI findings to assess the reproducibility of the first observer’s evaluation. The second observer was blinded to the results of the first observer and to the clinical and histopathological information. Continuous variables of MRI findings included the T2 signal intensity (SI) ratio, tumor ADC value, peritumoral ADC value, peritumortumor ADC ratio, and ADC value of the contralateral breast parenchyma. ROIs were placed on targeted regions by referring to the findings of the dynamic CEM images. In a case of a multifocal or multicentric lesion, the largest tumor was accepted for analysis. For measurements of T2 SI of the tumor, the largest tumor cross section was selected, and an oval or round ROI, as large as possible, was placed inside the tumor. Another ROI was also placed on the pectoralis major muscle to measure the T2 SI of the muscle and calculate the T2 SI ratio between the lesion and the muscle. The T2 SI ratio was calculated according to the following formula:
This retrospective study was approved by the Committee on Clinical Studies at our institution (approval number, 29-268). The requirement for informed consent was waived. In total, 921 consecutive patients underwent breast MRI between July 17, 2015 and June 30, 2017 at our institution. The phase of the menstrual cycle of patients aged ≤55 was not considered because this was a retrospective study; therefore, it was not possible to analyze the phase of menstrual cycle during the MRI examination. The following inclusion criteria were used: (a) patients who had no suspicious findings, suggestive of metastatic LNs, on both preoperative breast ultrasonography and MRI; (b) patients who underwent both sentinel lymph node (SLN) biopsy and breast surgery, with omission of axillary LN dissection. Preoperative imaging findings suggestive of negative axillary LNs were evaluated based on a previous report [13], as follows: negative for round-shaped LNs with a completely or partially effaced fatty hilum; negative for LNs with irregular margins and/or cortical thickening (≥5 mm; focal or diffuse); negative for extra-hilar blood vessel flow on color doppler analysis. The following exclusion criteria were used: (a) patients who did not undergo US and/or MRI within the six-month period immediately preceding surgery (n = 47); (b) patients who had a past medical history of neoadjuvant chemotherapy and/or radiotherapy and/or breast surgery (n = 47); (c) patients who were diagnosed with ductal carcinoma in situ (n = 39), (d) intracystic papillary carcinoma (n = 2), (d) intraductal papilloma (n = 1), (e) Paget’s disease (n = 4), (f) invasive cancer of < 1 mm (n = 6) on histopathological examination; and (g) patients with small lesions in which an region of interest (ROI) could not be placed using a picture archiving and communication systems (PACS) monitor (n = 2). A total of 140 patients met the inclusion and exclusion criteria (Fig. 1).
T2 SI ratio = mean T2 SI of the tumor/mean T2 SI of the muscle. (1) The tumor ADC value, peritumoral ADC value, and ADC value of the contralateral breast parenchyma measurements were calculated using ADC maps. To measure the tumor ADC value, ROIs were manually placed within the solid component of the tumor. To measure the peritumoral ADC value and the ADC value of the contralateral breast parenchyma, ROIs were manually placed in the breast parenchyma; fatty tissue was avoided to the extent possible. ROIs of the peritumoral ADC value were placed within 2 cm from the border between the tumor and the normal breast parenchyma. At least three measurements were taken for all continuous variables on MR images. The mean value among the three T2 SI ratios, the minimum value among the three mean tumor ADC values, the maximum value among the three maximum peritumoral ADC values, and the minimum value among the three mean ADC values of the contralateral breast parenchyma were accepted as the T2 SI ratio, tumor ADC value, peritumoral ADC value, and ADC value of the contralateral breast parenchyma, respectively. We calculated the peritumor-tumor ADC ratio, which has been reported to be a feasible method, according to the following formula [12]:
2.2. Image acquisition MRI was performed by using a 1.5-T system (Symphony, Siemens Medical Solutions, Erlangen, Germany) with a maximum gradient field strength of 30 m T/m and a 4-ch CP breast array coil. All patients were examined in the prone position. First, coronal T2-weighted spectral attenuated inversion recovery images of both breasts were obtained with the following parameters: repetition time (TR)/echo time (TE), 4000 ms/73 ms; flip angle, 150°; field of view, 35 × 35 cm; matrix size, 806 × 896; slice thickness, 4 mm; gap, 0; number of excitations (NEX), 1. Subsequently, coronal diffusion-weighted images of both breasts were obtained at b values of 0, 1000, and 1500 s/mm2 with the following parameters: TR/TE, 5600 ms/87 ms; field of view, 35 × 35 cm; matrix size, 234 × 320; slice thickness, 3.5 mm; slice gap, 0; NEX, 5. ADC maps were automatically generated on the operating console using
Peritumor-tumor ADC ratio = peritumoral maximum ADC value/tumor mean ADC value. (2) 112
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Fig. 1. Flow diagram for the patient selection process.
for the following cases: (a) SLNs had no metastatic cells or only isolated tumor cells; (b) SLNs had only 1-2 lymph nodes with metastatic cells, for patients who had undergone breast-conserving surgery. In this study, a positive SLN was defined as a LN with isolated tumor cells, micrometastases (diameter of metastatic deposit, 0.2–2 mm), or macrometastases (metastatic tumor with a maximum diameter > 2 mm). LVIs were classified into four grades: ly/v 0 (no LVI), ly/v 1 (minimal LVI), ly/v 2 (moderate LVI), and ly/v 3 (marked LVI). We divided LVIs into LVI-positive (ly/v 1-3) and LVI-negative groups (ly/v 0). The following variables were evaluated in all primary tumors: histopathological type; immunohistochemical staining for estrogen receptors (ER), progesterone receptors (PgR), and human epidermal growth factor receptor 2 (HER2); Ki-67 proliferation index, nuclear grade, size of the invasive component, and the presence of LVI. The size of the invasive component was defined as the maximum diameter of the focal invasion, excluding the intra-ductal component, on histopathological examination. Hormonal status was considered positive if > 1% of tumor cells were positive for ER or PgR [14]. HER2 positivity was defined as a score of 3+ on immunohistochemical staining, or as a score of 2+ with confirmation of HER2 gene amplification by fluorescence in situ hybridization. Ki-67 proliferation index was determined based on immunohistochemical analysis; an index of < 14% was considered low, and an index of ≥14% was considered high [15].
Inter-observer variability was assessed for each continuous variable. An age-dependent evaluation was conducted for the continuous variables with a cutoff at age 55, in consideration of the fact that natural menopause occurs at up to 55 years old for women worldwide. 2.4. Assessment of sentinel node SLN biopsy was performed with a radiocolloid and a dye. Mapping agents were injected into the subdermal plexus. 99mTC-labeled phytate colloid was injected on the day of surgery (0.25 mL, 15 MBq) or the day before surgery (0.5 mL, 30 MBq), and lymphoscintigraphy was performed. During the surgery, 5 mL of isosulfan blue dye (Lymphazurin; Covidien, Mansfield, MA, USA) or 3 mL of indocyanine green dye (Diagnogreen; Daiichi Sankyo, Tokyo, Japan) was injected. SLNs were identified as those with dye uptake, radiotracer uptake, or both. 2.5. Histopathological assessment All SLNs were sectioned along their short axis at 2-mm intervals. The nodal tissue was quickly frozen in liquid nitrogen, and a single 5μm-thick section, stained with hematoxylin and eosin (H & E), was examined intraoperatively (frozen-section analysis). In our institution, breast surgery with omission of axillary LN dissection was performed 113
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2.6. Statistical analysis
Table 1 Clinical characteristics.
All statistical analyses were performed with Ekuseru-Toukei 2015 (SSRI, Tokyo, Japan) and R (The R Project for Statistical Computing, www.r-project.org, version 3.3.0) software. Qualitative variables were analyzed with Fisher’s exact test. Fisher’s exact test with the BenjaminiHochberg method was used for multiple pairwise comparisons. Continuous variables were analyzed with the Mann-Whitney U test. Diagnostic performance was estimated by using receiver operating characteristic (ROC) analysis by calculating the area under the ROC curve (AUC) for each continuous variable that showed a significant difference on univariate analysis. A cutoff value differentiating the LVIpositive and -negative groups was chosen to maximize the Youden index. Based on the cutoff values, continuous variables were fit to the multivariate logistic regression analysis. Multivariate logistic regression analysis was performed with variables related to MRI findings that showed significant differences in univariate analyses. p < 0.05 was considered statistically significant. Inter-observer variability of the continuous variables was assessed by using intraclass correlation coefficients (ICCs). An ICC of 0.81–1.0 was considered to indicate almost perfect agreement; 0.61–0.80, substantial agreement; 0.41–0.60, moderate agreement; 0.21–0.40, fair agreement; and ≤0.20, slight agreement.
Variable
Patient age (years) ≤55 > 55 Histopathological type Scirrhous carcinoma Papillotubular carcinoma Solid-tubular carcinoma Mucinous carcinoma (pure type) Mucinous carcinoma (mixed type) Apocrine carcinoma Metaplastic carcinoma Invasive micropapillary carcinoma Invasive lobular carcinoma Intrinsic subtype Luminal A Luminal B HER2 Triple-negative Ki-67 index All ages Age, ≤ 55 Age, > 55
3. Results Histopathological examination revealed patients with (n = 41) and without LVI (n = 99) among the 140 lesions. Univariate analyses of the qualitative and continuous variables are summarized in Tables 1 and 2. Results reported regarding continuous variables on MRI are based on assessments by the first blinded observer. The median (interquartile range, 25–75 percentile) of all ROIs was 20 mm2 (15–27) for the first observer and 28 mm2 (19–38) for the second observer. In the univariate analyses of clinical characteristics, the pathological size of the invasive component (all ages: p < 0.001; age ≤ 55: p < 0.001), Ki-67 index (all ages: p = 0.03; age ≤ 55: p = 0.02), and SLN positivity (p < 0.001) were significantly associated with LVI. For the intrinsic subtype and clinical stage, Luminal B tumor and clinical stage T2 are significantly more likely than luminal A and clinical stage T1 to exhibit LVI (adjusted p = 0.03 and adjusted p = 0.002, respectively). For continuous variables on MR images, the tumor ADC value (all ages: p = 0.005; age ≤ 55: p < 0.001), peritumoral ADC value (age ≤ 55: p = 0.04), and peritumor-tumor ADC ratio (all ages: p < 0.001; age ≤ 55: p < 0.001) were significantly associated with LVI (Figs. 2 and 3). The only significant variable identified in patients aged > 55 years was the ADC value of the contralateral breast parenchyma (p = 0.02). The AUC for the pathological size of the invasive component was 0.72, for the tumor ADC value it was 0.64, and for the peritumor-tumor ADC ratio it was 0.70. Multivariate logistic regression analysis revealed significant differences in the pathological size of the invasive component, SLN positivity and the tumor ADC value for the prediction of LVI (odds ratio [OR]: 3.43; 95% confidence interval [CI]: 1.41–8.32; p = 0.007; OR: 2.96; 95% CI: 1.15–7.62; p = 0.02; OR: 16.0; 95% CI: 1.89–136; p = 0.01, respectively; Table 3). The diagnostic performance, based on the data when applying the cutoff values of 2 cm for the pathological size of the invasive component and 0.862 × 10−3 mm2/s for the tumor ADC value, is summarized in Table 4. Inter-observer agreement was substantial for the tumor ADC value (ICC = 0.77; 95% CI: 0.70–0.83) and the ADC value of the contralateral breast parenchyma (ICC = 0.68; 95% CI: 0.59–0.76). There was moderate agreement for the peritumoral ADC value (ICC = 0.53; 95% CI: 0.40–0.64) and the peritumor-tumor ADC ratio (ICC = 0.49; 95% CI: 0.35–0.61) and fair agreement for the T2 SI ratio (ICC = 0.30; 95% CI: 0.15–0.45).
Nuclear grade Low or intermediate High Clinical stage T1 T2 T3
Patients with LVI (n = 41)
Patients without LVI (n = 99)
23 18
43 56
28 8 3
48 22 13 3
0.20
1 1 1 1 1
10
6 34 1 0
36 52 5 6
25 (16–40) 25.7 (18–42.55) 24.4 (15.08–30.75)
19.3 (10.2–30.6) 17.1 (9.7–32) 20 (11.5–30)
32 9
86 13
17 22 2
73 24 2
0.03
0.03 0.02 0.37 0.21
0.002
Pathological size of invasive component (mm) All ages 24 (16–32) Age, ≤ 55 25 (16.5–36) Age, > 55 23 (16.25–25) Lesion type Mass Non-mass SLN Positive Negative
p
15 (10–22) 12 (9.5–17) 16.5 (10.75–23.25)
< 0.001 < 0.001 0.06 0.11
40 1
87 12
21 20
19 80
< 0.001
Abbreviations: LVI: lymphovascular invasion; SLN: sentinel lymph node. The size of the invasive component and the Ki-67 index are expressed as the age-based median and interquartile range (25–75 percentile). In a multiple comparison of the intrinsic subtype and clinical stage, after performing the Fisher's exact test with the variables above, the results were corrected using the Benjamini-Hochberg method. Only the lowest adjusted p-values are shown. There were significant differences between Luminal A and Luminal B, and between clinical stage T1 and T2.
4. Discussion Our results are consistent with a recent retrospective cohort study that reported that breast cancers with LVI had significantly lower ADC values than breast cancers without LVI, independent of the histological subtype, grades of the ductal histological type, and mass lesions [11]. Our results also agree with a previous study that reported that the ADC value, peritumor-tumor ADC ratio, tumor diameter, Ki-67 index, and axillary LN metastasis were significantly different between patients with and without LVI [12]. The minimum-ADC value has been suggested as an effective parameter for the prediction of LVI status, and it was reported that LVI status had a strong positive correlation with LN status [16]. Thus, our results showed that the minimum mean tumor
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Table 2 Results of continuous variables on MR images. Variable
T2 SI ratio Tumor ADC value (×10−3 mm2/s) Peritumoral ADC value (×10−3 mm2/s) Peritumor-tumor ADC ratio ADC value of the contralateral breast parenchyma (×10−3 mm2/s)
Age ≤ 55
All ages
Age > 55
Patients with LVI (n = 41)
Patients without LVI (n = 99)
p
Patients with LVI (n = 23)
Patients without LVI (n = 43)
p
Patients with LVI (n = 18)
Patients without LVI (n = 56)
p
3.62 (2.75–4.57) 738.17 (664.6–814.87) 1849 (1661–2080)
3.45 (2.73–4.88) 785.26 (714.74–884.33) 1717 (1556–1967)
0.65 0.005
3.03 (2.78–4.02) 733.22 (665.14–790.42) 1985 (1795–2151)
3.33 (2.71–4.73) 808.85 (712.63–891.74) 1743 (1497–1939)
0.71 < 0.001
3.71 (2.93–5.27) 781.65 (718.60–842.51) 1707 (1581.5–1975.5)
0.90 0.20
0.04
4.19 (2.80–5.16) 753.51 (652.27–821.87) 1799 (1618–1936)
2.60 (2.25–2.72)
2.16 (1.91–2.50)
< 0.001
2.65 (2.40–3.02)
2.10 (1.88–2.49)
< 0.001
2.44 (2.12–2.67)
2.26 (1.94–2.50)
0.15
1761 (1547–1950)
1779 (1608–1883)
0.95
1941 (1747–2013)
1774 (1608–1898)
0.14
1579 (1424–1780)
1794 (1613–1881)
0.02
0.08
0.83
Abbreviations: MR: magnetic resonance; LVI: lymphovascular invasion; SI: signal intensity; ADC: apparent diffusion coefficient. Continuous variables are expressed as the median and interquartile range (25–75 percentile).
aggressiveness indicators, such as Ki-67, in ER-positive breast cancers [17,18]. Jacquemier et al. reported that higher Ki-67 values were associated with vascular and lymphatic invasion [19]. It has also been reported that premenopausal breast cancer patients tend to have higher Ki-67 values, while postmenopausal patients tend to have lower Ki-67
ADC value may contribute to the prediction of lymphatic invasion. Our results also showed that the measurement of the tumor ADC value could be conducted while ensuring reproducibility between blinded readers with differences in interpretation experience. Previous reports suggested that the tumor ADC value was correlated with tumor
Fig. 2. MR images of a 74-year-old woman with invasive ductal carcinoma (Luminal A) beneath the left nipple. Lymphovascular invasion and nodal macrometastasis were confirmed at the histopathological examination. (A) Coronal diffusion-weighted image (b = 1500) showing a margin-dominant high-intensity mass measuring approximately 20 mm. (B) Coronal apparent diffusion coefficient (ADC) map showing a mass with low signal suggestive of restricted diffusion (arrow). It can be confirmed visually that the region surrounding the mass shows higher signal intensity than the other region including the right mammary gland in the ADC map (arrowheads). The tumor ADC value was 0.680 (×10−3 mm2/s), the peritumor-tumor ADC ratio was 2.825.
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Fig. 3. MR images of a 60-year-old woman with invasive ductal carcinoma (Luminal B) in the medial upper region of the left breast. No lymphovascular invasion or nodal metastasis were confirmed on the histopathological examination. (A) Coronal diffusion-weighted image (b = 1500) showing a margin-dominant high-intensity mass measuring approximately 12 mm. (B) Coronal apparent diffusion coefficient (ADC) map showing a mass with low signal suggestive of restricted diffusion (arrow). The region surrounding the mass is iso-intensity compared to the other region including the right mammary gland in the ADC map (arrowhead). The tumor ADC value was 0.713 (×10−3 mm2/s), peritumor-tumor ADC ratio was 2.157.
values [20]; that is, postmenopausal patients tend to have low proliferative activity. Both the tumor ADC value and the Ki-67 index of patients aged ≤55 years showed significant differences regarding the LVI status, but there were no significant differences in patients aged > 55 years on univariate analysis. Our study indicated that the lower tumor ADC value and higher Ki-67 index in patients aged ≤55 years were predictors of LVI positivity. Considering previous reports that showed tumor ADC value did not correlate with LN status [11,9], our results therefore infer predicting LVI status with measurements of tumor ADC value can be useful for prognostic prediction. Mori et al. reported that there was a significant difference between the tumor ADC values of LVI-positive and -negative postmenopausal patients [12], while in our study, they were not significantly different in patients aged > 55 years. Considering the correlation of ADC with Ki-67 index [17,18], our findings, which showed that tumor ADC value and Ki-67 index in patients aged > 55 years were not significantly different, are theoretically consistent. Peritumoral ADC values of patients aged ≤55 years showed a significant difference between patients with and without LVI. However, no similar results were identified in patients of all ages or in those aged > 55 years. Mori et al. reported that the peritumoral ADC values of all patients and of postmenopausal patients showed a significant difference regarding the presence of LVI [12]. It is conceivable that the reason our results were different from those of Mori et al. is that we did not exclude cases with scattered and fatty breast tissue surrounding the tumor. Although ROIs were placed in the peritumoral breast parenchyma and avoided fat to the extent possible, they might have contained fat components. Mori et al. excluded patients who had no breast
Table 3 Results of multivariate logistic regression analysis. Variable
OR
95% CI
p
Pathological size of invasive component (> 2 cm vs. ≤ 2 cm) Ki 67 index (> 14.9 vs. ≤ 14.9) SLN (positive vs. negative) Tumor ADC value (≤0.862 vs. > 0.862) (×10−3 mm2/s) Peritumor-tumor ADC ratio (> 2.372 vs. ≤ 2.372)
3.43
1.41–8.32
0.007
1.39 2.96 16.0
0.51–3.85 1.15–7.62 1.89–136
0.52 0.02 0.01
1.48
0.59–3.72
0.41
Abbreviations: OR: odds ratio; CI: confidence interval; SLN: sentinel lymph node; ADC: apparent diffusion coefficient. Table 4 The diagnostic performance of the pathological size of the invasive component and the tumor ADC value.
Pathological size of the invasive component (> 2 cm vs. ≤ 2 cm) Tumor ADC value (≤0.862 vs. > 0.862) (×10−3 mm2/s)
Sensitivity
Specificity
PPV
NPV
Accuracy
61
74
49
82
70
98
30
37
97
50
Abbreviations: PPV: positive predictive value; NPV: negative predictive values; ADC: apparent diffusion coefficient. Data are expressed as percentages.
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Funding sources
parenchyma surrounding the tumor. Accordingly, measurements of the peritumoral ADC value might have affected the results of our study. With aging, the breast parenchyma is replaced with fatty tissue [21]. It has been reported that postmenopausal breast tissue has a significantly lower ADC than premenopausal tissue [22]. Age-related fatty replacement of breast tissue is associated with decreasing serum estradiol and progesterone. Hence, ADC values are likely to be reduced due to a reduction in the speed of osmosis as breast tissue becomes fatty in postmenopausal patients. Although the value of the peritumoral-tumoral ADC ratio for the prediction of LVI and peritumoral edema as a prognostic factor associated with disease recurrence were reported [12,23], method limitations should be considered when assessing the status of the peritumoral region in breast cancer patients with scattered or fatty breast tissue. Several limitations of our study must be considered. First, this retrospective study included several special histological types. Hence, it is difficult to compare our results with previous reports that included only luminal type cancers [17,18]. An additional, prospective study is necessary to confirm our results. Second, we did not assess correlation of measurement values for the size of the invasive component between MRI and histopathological results. Further studies are needed to investigate whether radiological size measurement could be a predictor of LVI status, especially in the case of a mass forming lesion, which is relatively easy to measure. This may be less feasible in the case of a non-mass lesion, as it is difficult to measure the size of the invasive component. Third, it is possible that the peritumoral ADC and ADC values of the contralateral breast parenchyma did not accurately reflect the true conditions, because the ROIs of some cases may have contained fat components. Fourth, we included patients with mucinous carcinoma. Since the ADC value of mucinous carcinoma is different from that of ordinary invasive ductal carcinoma, it may have been appropriate to consider excluding those cases. Fifth, we did not consider fibrocystic breast changes. Previous studies have reported that the ADC value of normal fibroglandular tissues was not significantly affected by the menstrual cycle [22]. However, the effects of fibrocystic changes on the ADC values of normal breast tissue have not been clarified. The pathophysiology of fibrocystic breast change is determined by estrogen predominance and progesterone deficiency, which results in the hyperproliferation of connective tissue, followed by facultative epithelial proliferation [24]. Izumori et al. reported that the thickness of the normal breast stroma surrounding lobules and ducts was not always uniform [25], and we speculate that this non-uniformity could be affected by fibrocystic breast changes. As a result, fibrocystic breast changes might affect the measurement of ADC values of the breast parenchyma, especially in patients aged ≤55 years. Sixth, we could not investigate the history of hormone replacement therapy (HRT) of all patients at any time in their lives; this should be considered because normal fibroglandular tissues could be affected by HRT.
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5. Conclusions We found that the tumor ADC value, peritumoral ADC value, and peritumor-tumor ADC ratio were predictive MRI findings for LVI in patients aged ≤55. The tumor ADC value showed a significant association with LVI, and the inter-observer agreement for tumor ADC value was substantial between two blinded observers with differences in interpretation experience. Our study suggests that, even when breast cancer patients show clinically negative nodes, if positive LVI is suspected on preoperative MRI, a more aggressive management strategy should be considered; this might include the addition of postoperative adjuvant chemotherapy and/or radiation therapy. Conflicts of interest None. 117
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