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ORIGINAL ARTICLE
Year : 2019  |  Volume : 15  |  Issue : 4  |  Page : 871-875

Diagnostic performance of minimum apparent diffusion coefficient value in differentiating the invasive breast cancer and ductal carcinoma in situ


1 Department of Radiology, The Second Hospital of Shandong University, Jinan, Shandong, China
2 Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, Shandong, China

Date of Web Publication14-Aug-2019

Correspondence Address:
Weihua Guo
Department of Radiology, The Second Hospital of Shandong University, No. 247, Beiyuan Road, Jinan 250033, Shandong
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jcrt.JCRT_607_18

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 > Abstract 


Background: This study is to explore the role of the minimum apparent diffusion coefficient (ADC-min) value in the diagnosis of invasive breast cancer and ductal carcinoma in situ (DCIS).
Materials and Methods: A total of 196 breast cancer patients with pathologically verified lesions were included. They received diffusion-weighted imaging and dynamic breast magnetic resonance imaging before the pathological confirmation. The ADC-min value and its relationship with invasive ductal carcinoma (IDC), IDC-DCIS, and DCIS were analyzed.
Results: Of the 196 breast cancer patients, there were 115 (58.67%) cases of IDC, 53 (27.04%) cases of IDC-DCIS, and 28 (14.29%) cases of DCIS. The mean ADC-min values for IDC, IDC-DCIS, and DCIS were (0.96 ± 0.16) × 10-3, (1.10 ± 0.13) × 10-3, and (1.24 ± 0.17) × 10-3 mm 2/s, respectively. The mean ADC-min value of IDC was significantly lower than that of IDC-DCIS and that of IDC-DCIS was significantly lower than that of DCIS (P < 0.01). The mean ADC-min value was also significantly different between invasive cancer and DCIS (P < 0.01). The mean ADC-min value can be used in the differential diagnosis of DCIS, with a cutoff point of 1.02 × 10-3 mm 2/s (sensitivity of 92.9% and specificity of 57.7%).
Conclusions: The ADC-min values are significantly different among IDC, IDC-DCIS, and DCIS, with the lowest ADC-min values in IDC, followed by IDC-DCIS and DCIS. The ADC-min maybe used as a promising parameter to differentiate DCIS and invasive cancer.

Keywords: Apparent diffusion coefficient, breast cancer, ductal carcinoma in situ, invasive ductal carcinoma, magnetic resonance imaging


How to cite this article:
Zhao S, Shao G, Chen P, Li L, Yang Y, Zhao X, Guo W. Diagnostic performance of minimum apparent diffusion coefficient value in differentiating the invasive breast cancer and ductal carcinoma in situ. J Can Res Ther 2019;15:871-5

How to cite this URL:
Zhao S, Shao G, Chen P, Li L, Yang Y, Zhao X, Guo W. Diagnostic performance of minimum apparent diffusion coefficient value in differentiating the invasive breast cancer and ductal carcinoma in situ. J Can Res Ther [serial online] 2019 [cited 2019 Sep 18];15:871-5. Available from: http://www.cancerjournal.net/text.asp?2019/15/4/871/264296




 > Introduction Top


Breast cancer is one of the most common malignant tumors in women worldwide.[1] Ductal carcinoma in situ (DCIS), which accounts for 20% of breast cancer, is a neoplastic lesion confined to ductal lobule of the breast and is characterized by malignant ductal epithelial cell proliferation.[2],[3] Early detection and treatment is the key to improve the prognosis of DCIS. Invasive ductal carcinoma (IDC) is the most common type of breast cancer, which is divided as pure IDC and IDC with DCIS (IDC-DCIS).[3] IDC may be generated from DCIS, or arise de novo.[4] IDC-DCIS has lower rate of proliferation, metastasis, local recurrence, and better prognosis when compared with pure IDC.[5],[6],[7] Therefore, preoperative diagnosis of DCIS, IDC-DCIS, and IDC is especially important for developing optimal treatment plan and predicting prognosis.

Diffusion-weighted imaging (DWI) can measure water diffusion in tissue. The apparent diffusion coefficient (ADC) is the quantized value of DWI, and low ADC values indicate restricted diffusion.[8],[9],[10] DWI is used in the detection and characterization of invasive breast tumors [11],[12],[13] and DCIS.[14],[15] The average ADC (ADC-mean) value was used in these studies. However, the minimum ADC (ADC-min) value can represent the most malignant parts of tumors.[16] So far, the correlation between ADC-min value and IDC, IDC-DCIS, and DCIS has not been fully established yet. Therefore, in this retrospective study, correlation of the ADC-min value with IDC, IDC-DCIS, and DCIS was investigated.


 > Materials and Methods Top


Study patients

A total of 362 cases of breast cancer patients who underwent breast magnetic resonance (MR) examinations from May 2014 to February 2018 were retrospectively reviewed. Among them, 23 cases with other type malignant tumors, 87 cases with benign lesions, and 18 cases with no surgical confirmation were excluded. Moreover, 38 patients who underwent chemotherapy or radiotherapy were also excluded. Finally, a total of 196 patients (mean age: 47.01 ± 9.20 years) were included in the analysis. The diagnosis was confirmed by pathology. This study was approved by the Ethics Committee of the Second Hospital of Shandong University. Due to the retrospective nature of the study, informed consent was waived.

Magnetic resonance imaging

The 3.0-T system (GE Discovery MR750; GE Healthcare, Milwaukee, WI, USA) with an eight-channel dedicated breast coil was used. Both breasts were imaged simultaneously. Premenopausal females were examined at day 7 to day 14 of the menstrual cycle.

MR imaging (MRI) was performed in the following procedures: (1) Axial T2-weighted single shot fast spin-echo sequence (repetition time TR, 2500 ms; echo time TE, 53.5 ms; slice thickness, 6 mm; layer spacing, 1.0 mm; field of view, 360 mm × 360 mm; matrix size, 320 × 192; and NEX, 3). (2) Axial T1FSE (TR, 569 ms; TE, 15.6 ms; slice thickness, 6 mm; layer spacing, 1.0 mm; field of view, 360 mm × 360 mm; matrix size, 256 × 192; NEX, 4). (3) Axial single shot fat suppressed echo-planar diffusion-weighted sequence (TR, 3000 ms; TE, 49.5 ms; slice thickness, 6 mm; layer spacing, 1.0 mm; field of view, 360 mm × 360 mm; matrix size, 128 × 96; and NEX, 4), with the diffusion-sensitizing gradient applied along the x, y, z axes and with the b-values of 0 and 800 s/mm 2. (4) Axial T1-weighted three-dimensional dynamic gradient echo fat sequence (VIBRANT) (TR/TE, 3.9/1.7; flip angle, 5°; field of view, 360 mm × 360 mm; matrix size, 348 × 348; and slice thickness, 1.8 mm). Dynamic contrast-enhanced image acquisition started immediately after the Gadodiamide (0.2 mmol/kg body weight, rate of 2 ml/s) and the saline injection in turn. There were 7 sequences without time gaps, and each sequence lasted for 60 s.

Image analysis

MRI analysis was carried out by two experienced radiologists independently in a blinded way. Each final decision was made based on the agreement of these two radiologists.

GE workstation software (Advantage Windows Workstation 4.6; GE Healthcare) was used for ADC measurement. Single region of interest (ROI) was placed on the ADC images. ADC values were automatically calculated on the ADC maps, with the location identical to that of the DWI image and dynamic contrast-enhanced image. We placed a single ROI smaller than lesion in the solid part of lesion and avoided the necrotic and hemorrhagic regions as indicated by T2-weighted image and T1-weighted image. The ROI size was consistent among multiple measurements. The minimum ADC (ADC-min) value was defined as the lowest one of three values [Figure 1]c, [Figure 3]c. The mean ADC value was defined as the average of three measurements.
Figure 1: A 53-year-old female with invasive ductal carcinoma. (a) Axial contrast-enhanced image showed a 1.4-cm oval mass with homogeneous enhancement in the upper-outer quadrant of the left breast. (b) Axial apparent diffusion coefficient map of the breast showed low signal of the tumor (arrow). (c) For measurement of apparent diffusion coefficient values, a single region of interest of 47 mm2 (circle) was manually placed within the mass lesion on apparent diffusion coefficient map. The measurement was repeated three times and the apparent diffusion coefficient values were automatically generated, which were 0.84 × 10−3 mm2/s, 1.05 × 10−3 mm2/s, and 1.20 × 10−3 mm2/s, respectively. The apparent diffusion coefficient-min value for this patient was determined as 0.84 × 10−3 mm2/s

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Figure 3: A 49-year-old female with ductal carcinoma in situ. (a) Axial contrast-enhanced image showed a 1.7-cm irregular mass with heterogeneous enhancement in the lower-inner quadrant of the left breast. (b) Axial apparent diffusion coefficient map of the breast showed low signal of the tumor (arrow). (c) For measurement of apparent diffusion coefficient values, a single region of interest of 47 mm2 (circle) was manually placed within the mass lesion on apparent diffusion coefficient map. The measurement was repeated three times, and the apparent diffusion coefficient values were automatically generated, which were 1.20 × 10−3 mm2/s, 1.35 × 10−3 mm2/s, and 1.26 × 10−3 mm2/s, respectively. The apparent diffusion coefficient-min value for this patient was determined as 1.20 × 10−3 mm2/s

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Statistical analysis

Data were expressed as mean ± standard deviation. The statistical analysis was performed using SPSS software (IBM SPSS Statistics 25.0, Chicago, IL, USA). The one-way ANOVA and LSD test were used to compare the difference in ADC-min value. The diagnostic value of ADC-min value in differentiating DCIS and invasive cancer was analyzed using student-t test for independent samples and receiver operating characteristic (ROC) analysis. P < 0.05 was considered as statistically significant.


 > Results Top


Pathological type and apparent diffusion coefficient-min values

The relationship of pathological types with ADC-min values was analyzed. In these 196 breast cancer cases, there were 115 (58.67%) cases of IDC, 53 (27.04%) cases of IDC-DCIS, and 28 (14.29%) cases of DCIS [Figure 1], [Figure 2], [Figure 3]. Moreover, the mean ADC-min value of breast cancer was (1.04 ± 0.18) ×10−3 mm 2/s. According to the pathological type, the minimum, maximum, and mean ADC-min values of breast cancer were presented in [Table 1].
Figure 2: A 44-year-old female with invasive ductal carcinoma-ductal carcinoma in situ. (a) Axial contrast-enhanced image showed the 1.3-cm irregular mass with heterogeneous enhancement in the upper-outer quadrant of the right breast. (b) Axial apparent diffusion coefficient map of the breast showed low signal of the tumor (arrow). (c) For measurement of apparent diffusion coefficient values, a single region of interest of 47 mm2 (circle) was manually placed within the mass lesion on apparent diffusion coefficient map. The measurement was repeated three times, and the automatically generated apparent diffusion coefficient values were 1.05 × 10−3 mm2/s, 1.09 × 10−3 mm2/s, and 1.11 × 10−3 mm2/s, respectively. The apparent diffusion coefficient-min value for this patient was determined as 1.05 × 10−3 mm2/s

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Table 1: The range and mean values of minimum apparent diffusion coefficient of breast cancer (×10-3 mm2/s)

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Mean ADC-min values for IDC, IDC-DCIS, and DCIS were (0.96 ± 0.16) ×10−3 (range (0.52–1.40) ×10−3), (1.10 ± 0.13) ×10−3 (range (0.79–1.39) ×10−3), and (1.24 ± 0.17) ×10−3 (range (0.92–1.50) ×10−3) mm 2/s, respectively. [Table 1] showed that the mean ADC-min values of IDC, IDC-DCIS, and DCIS were significantly different (P < 0.01), in ascending order of IDC, IDC-DCIS, and DCIS. In particular, significant difference was found in mean ADC-min value between IDC and DCIS (P < 0.01).

Apparent diffusion coefficient-min value in ductal carcinoma in situ diagnosis

To assess the role of ADC-min in diagnosis of the DCIS, the cases were divided into the DCIS and invasive cancer (IDC and IDC-DCIS) groups. It was showed that the mean ADC-min value in the DCIS was (1.24 ± 0.17) ×10−3 mm 2/s, while the mean ADC-min value in the invasive cancer group was (1.0 ± 0.16) ×10−3 mm 2/s (P < 0.01) [Figure 4]. ROC analysis showed that both the ADC-min value and mean ADC value had great significance in the differential diagnosis of DCIS, with the area under the curve (AUC) of 0.85 and 0.84, respectively (both P < 0.01). The ADC-min threshold value was 1.02 × 10−3 mm 2/s, with sensitivity of 92.9% and specificity of 57.7%. The threshold for mean ADC value was 1.11 × 10−3 mm 2/s, with sensitivity of 78.6% and specificity of 71.4% [Figure 5] and [Table 2]. These results suggest that the ADC-min values have diagnostic value for DCIS.
Figure 4: Box plot showed the apparent diffusion coefficient-min values of invasive cancer (invasive ductal carcinoma and invasive ductal carcinoma-ductal carcinoma in situ) and ductal carcinoma in situ. Apparent diffusion coefficient-min values were significantly different between invasive cancer and ductal carcinoma in situ (P < 0.01)

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Figure 5: Receiver operating characteristic curve analysis. The receiver operating characteristic curve for minimum apparent diffusion coefficient and mean apparent diffusion coefficient value in ductal carcinoma in situ diagnosis was shown

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Table 2: Receiver operating characteristic analysis for minimum apparent diffusion coefficient and mean apparent diffusion coefficient value in ductal carcinoma in situ diagnosis

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 > Discussion Top


Breast cancer is a heterogeneous tumor.[4],[16] The lowest cellular zone has the maximum ADC value, while the highest cellular zone has the minimum ADC value.[16] In addition, the components of fibrosis and necrosis in tumors may also affect the ADC values.[16] Thus, the mean ADC value cannot reflect the malignancy of tumors. In this study, we used the ADC-min value, which may represent the most malignant parts of tumors.[16] The application of the ADC-min values in breast cancer has been reported.[16],[17],[18],[19],[20] Most of these mentioned studies used multiple ROI method in breast MRI, and the lowest mean ADC value with multiple small ROIs in the lesion was defined as the ADC-min value. However, the multiple ROI method is time-consuming and thus has limited clinical application.[16],[17],[18],[20] In the present study, we placed a single ROI smaller than lesion in the solid tumor and avoided the necrotic and fibrotic regions. The ROI size was consistent among multiple measurements, and ADC-min value was obtained from each lesion. This method has feasibility in clinical settings and has been previously reported.[19]

In this study, we did not statistically analyze the ADC-min minimum or maximum. The ADC-min values of all the patients were averaged. The results showed that mean ADC-min values of IDC, IDC-DCIS, and DCIS were (0.96 ± 0.16) ×10−3, (1.10 ± 0.13) ×10−3, and (1.24 ± 0.17) ×10−3 mm 2/s, respectively, and the corresponding ranges were (0.52–1.40) ×10−3, (0.79–1.39) ×10−3, and (0.92–1.50) ×10−3 mm 2/s. The ADC-min values among IDC, IDC-DCIS, and DCIS showed significant differences. The lower ADC values of IDC may be caused by the higher cellular density and smaller extracellular space.[21] There was overlapping of the ADC-min for the three types of breast cancer, which is probably caused by tumor heterogeneity.[4] So far, only one study reported the differentiation among IDC, IDC-DCIS, and DCIS.[22] It showed that volume-based ADC values could distinguish between IDC, IDC-DCIS, and DCIS; however, this method needs additional time and effort. Our study showed consistent results [22] but with simpler and more feasible method.

Early detection and management of DCIS is of high importance because DCIS can develop into invasive breast cancer, which is lethal.[23] In recent years, there have been only two reports on the clinical value of DWI in the differentiation between DCIS and invasive cancer in breast cancer patients.[24],[25] These studies showed that ADC could be used as an imaging marker for breast cancer diagnosis. In this study, the ADC-min value of DCIS and invasive cancer were (1.24 ± 0.17) ×10−3 and (1.0 ± 0.16) ×10−3 mm 2/s, respectively. The mean ADC-min value of DCIS was higher than invasive cancer probably because cancer cells of DCIS mainly spread in the duct, and the cell density is lower than invasive cancer, while the invasive cancer is a densely packed tumor and has smaller extracellular space.[21] There were significant differences in mean ADC-min value between the DCIS and invasive groups, consistent with previous studies.[24],[25] The cutoff ADC-min (1.02 × 10−3 mm 2/s) was used to differentiate DCIS and invasive cancer, with sensitivity of 92.9.0% and specificity of 57.7%. Our results from the ROC analysis showed that ADC-min value had great significance in the diagnosis of DCIS, with the AUC of 0.85. Interestingly, the cutoff value, diagnostic sensitivity, and diagnostic specificity of ADC-min were similar to those of mean ADC value. This may be caused by the small sample size of this study. However, the measurement method for ADC-min is simpler and more practical. Further study is warranted.

There are several limitations of our study. First, there is a relatively small sample size. Therefore, enlarged sample sizes are needed in the future. Second, the ADC-min measurement was to some extent subjective, which may cause observational bias. Third, in the research, we applied only two b-values (0 and 800 mm 2/s) according to clinical practice and previous report.[26] Further studies with more b values are needed.

In summary, the ADC-min value showed significant differences among IDC, IDC-DCIS, and DCIS, in ascending order of IDC, IDC-DCIS, and DCIS. The ADC-min may be used as a promising parameter to differentiate DCIS and invasive cancer.

Financial support and sponsorship

This work was supported by the Key Research and Development Plan of Shandong Province (grant number 2015GSF119034).

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
 
 
    Tables

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