1 Introduction
Since the increased implementation of screening programs, approximately 20% to 25% of the screening-detected breast cancers have been ductal carcinoma in situ (DCIS).[1,2] [3] [4,5] [6] [7]
On dynamic contrast-enhanced (DCE) MR images, pure DCIS lesions often appear as nonmass clumped areas of enhancement with segmental or linear distribution.[8,9] [8,9] [10] breast MRI to predict occult invasion in biopsy-proven DCIS.[11–13] [11–13]
DCE MRI may be useful in primary surgical planning but visual assessment with DCE MRI has many inter- and intraobserver variations. Computer-aided diagnosis (CAD ) can reduce these variations with objective evaluation of breast lesions.[14,15] CAD to date for predicting occult invasion in biopsy-proven pure DCIS. Our hypothesis is that CAD findings can be used to predict occult invasive components in biopsy-proven pure DCIS.
This study aims to analyze kinetic and morphological features using DCE MRI with CAD for predicting invasive components in cases of biopsy-proven DCIS.
2 Material and methods
Institutional review board approval was obtained at Seoul National University Bundang Hospital (SNUBH) (IRB-B-2001-588-101) and informed consent was not required because of the study's retrospective nature.
2.1 Lesion and patient characteristics
From January 2009 to December 2012, 222 breasts of 209 patients diagnosed with DCIS via ultrasonography (US)-guided core needle biopsy at our institution were enrolled. Of those, 141 breast cancers of 138 patients (three patients had bilateral cancers) were finally included with the following inclusion criteria: patients who underwent a breast MRI before surgery; patients with an available CAD result associated with breast MRI ; patients with a surgically confirmed pathology; and patients who did not undergo preoperative chemotherapy.
All patients were women and their ages were in the range of 25 to 76 years, with an average age of 51.1 years. Their clinical symptoms were variable including palpable mass (n = 33), discharge (n = 8), and pain (n = 3). Asymptomatic screening MMG (n = 75) or US (n = 19) abnormalities were also present. All women underwent 2-view mammography (craniocaudal and mediolateral oblique views) using a full-field digital mammography system (Senographe 2000D FFDM; GE Medical Systems, Buc, France) and breast US (HDI 5000 or IU22, Philips-Advanced Technology Laboratories, Bothell, WA) before undergoing breast MRI , and the patients underwent MR examination after being diagnosed with DCIS based on the results of a US-guided core needle biopsy performed using a 14-gauge automated biopsy gun (STERICUT, TSK Laboratory, Tochigi, Japan). The mean number of cores for 14-G core needle biopsy was 5. In the case of calcified lesions, specimen radiography was obtained to confirm calcification retrieval. US-guided core needle biopsy of lesions was performed by one of the 3 radiologists (10–13, 3–6 years, and 1–4 years of breast imaging experience, respectively).
2.2 Breast MR protocol and CAD application
MRIs were performed with a 3 T Philips Achieva (Philips Medical Systems, Best, the Netherlands) with patients in the prone position and a dedicated phased-array breast coil was used. Bilateral unenhanced fat-suppressed (SPAIR) T2-weighted turbo spin-echo sagittal or axial images were obtained with the following parameters: TR/TE = 4502/77–4788/120, flip angle = 90 degree; field of view (FOV) = 200 × 200–300 × 300 mm; matrix size = 436 × 430–460 × 430; slice thickness = 1.0 mm. T1-weighted spin-echo images were acquired in the axial planes with the following parameters: TR/TE: 563/9, flip angle: 90 degree, 2 mm thickness, 3.2 mm gap, FOV = 350 × 350 mm. Administrated bolus injection of Gadolinium–DTPA (0.1 mmol/kg at a rate of 2 mL/s) was followed by a 20-mL saline flush using an automatic injector (Spectris Solaris; Nihon Medrad, Osaka, Japan). Multiphase dynamic contrast-enhanced T1 high-resolution isotropic volume examination (THRIVE) BLADE imaging in steady-state (BLISS) sequences were performed with 1 preenhanced and 5 post-enhanced series in sagittal images with the following parameters: TR/TE = 3.49/1.89–3.9/2 flip angle 12 degree; field of view (FOV) = 200 × 200–300 × 300 mm; matrix size = 200 × 200–300 × 300 cm; slice thickness = 1.0 mm, time of acquisition = 90 s. The post-processing process, including early subtraction (ie, first post-contrast images minus pre-contrast images) and maximum intensity projection imaging, was performed on the MRI console to evaluate the extent of breast cancer using second-phase dynamic images.
Precontrast and 5 consecutive post-contrast images were transferred to a commercially available CAD system (CadstreamTM version 4.1.3 Confirma, Inc., Kirkland, WA) and processed. The CAD systems compared the pixel intensity values between the pre-contrast and immediate post-contrast medium series with a 50% increase in enhancement as the minimum threshold. The initial phase determined by the signal change between the pre-contrast and second peak post-contrast series was categorized as either slow (<50% increase), medium (50%–100%), or rapid (>100%) enhancement. Delayed phase enhancement type after the peak post-contrast series was categorized as either persistent, plateau, or washout. A color overlay map was assigned to each pixel for different types of delayed enhancement pattern while comparing the immediate and delayed post-contrast medium series. If a pixel value on the delayed series decreased at a rate of >10% relative to the peak uptake value, the pixel is color coded as red, indicating a washout pattern. If a pixel value increases by >10%, the pixel is color coded as blue, indicating a persistent enhancement pattern. If there is a slope between these 2 values, the pixel is color coded as yellow for plateau enhancement. When >2 patterns of enhancement are mixed up in the same lesion, the most suspicious delayed curve type for malignancy (washout>plateau>persistent) was recorded. The peak enhancement percentage was calculated on the lesion at the second peak post-contrast series. Enhancing lesions detected by CAD can be automatically measured by clicking on the lesion (Fig. 1 ).
Figure 1: A 66-year-old woman with ductal carcinoma in situ in her left breast. (A) Post-contrast T1-weighted imaging with computer-aided diagnosis (CAD ) color overlay map showing a slow persistent mass (arrow) detected by CAD . (B) After clicking on the lesion, CAD automatically measured the mass for size, peak enhancement percentile, and early and delayed enhancement kinetics.
2.3 Image evaluation
All lesions detected by mammography, US, and MRI were retrospectively assessed and analyzed using a picture archiving and communication system by 2 radiologists with 15 years and 5 years of experience with breast MRI , respectively. At the time of the retrospective review, the radiologists were unaware of the histopathologic results for invasion and clinical information. Initial imaging analysis was performed independently and discrepant cases were discussed in consensus. Two image sets, that is, conventional MR images alone and MR images with MR CAD data, were evaluated. The first session of conventional MRI without CAD implementation was assessed according to the American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) Breast MRI Lexicon.[16] CAD data, the radiologist selected a specific lesion on an MRI scan and then program automatically generated the following details: initial (fast, medium, or slow) and delay (persistent, plateau, or washout) phase enhancement kinetic descriptor; peak enhancement percentage; lesion size calculated via CAD .
Mammographic and ultrasonographic images taken according to the locations of surgically confirmed enhancing lesions on MRI were also evaluated by ACR BI-RADS lexicon.[16]
2.4 Histopathologic evaluation
Lumpectomy or total mastectomy was performed by 1 of 2 surgeons who had 16 to 19 and 6 to 9 years of breast surgery experience. Histologic diagnosis was made by a pathologist with 16 to 19 years of experience in breast pathology. Pure DCIS meant no microinvasion and sentinel lymph node metastasis. Nuclear grade (1: low, 2: intermediate, and 3: high), presence of invasion, and largest tumor diameter were determined. The presence of comedonecrosis was also recorded.
2.5 Statistical analysis
Clinical, pathologic, and radiologic findings were reviewed. The data were entered into a commercially available computerized spreadsheet (Excel 2016; Microsoft, Redmond, WA). The final surgical histopathologic findings from either lumpectomy or mastectomy were used as the reference standard (pure DCIS vs DCIS with microinvasion or invasive cancer). The differences in radiologic findings and clinicopathologic factors according to the presence of invasiveness in continuous and categorical variables were analyzed using independent t test and χ 2 or Fisher exact test, respectively. A multivariate logistic regression model was used to analyze variables with at least a marginal predictive value (P < .05) on univariate analysis. All statistical analyses were performed using commercially available STATA software (version 14.0; StataCorp, College Station, TX) and SPSS (SPSS, version 17.0; SPSS, Chicago, IL). A P value of <.05 was considered to indicate a statistically significant difference.
3 Results
3.1 Subjects and lesions
Seventy-five (53.2%) of the 141 breasts underwent breast conservation surgery and 66 breasts (46.8%) underwent total mastectomy. Eighty-six (61%) breasts were finally diagnosed as pure DCIS and 55 (39%) were diagnosed as DCIS-associated invasive cancer. The invasive cancers consisted of 31 microinvasions, 23 invasive ductal carcinomas, and an invasive papillary carcinoma. The mean histologic diameter of tumor, including DCIS, was 3.5 ± 2.3 cm. In 47 breasts (33.3%), comedonecrosis was present. The nuclear grades of DCIS were 3 for 67 (47.5%), 2 for 61 (43.3%), and 1 for 13 (9.2%) breasts.
3.2 MRI and CAD findings of DCIS groups
Table 1 shows MRI findings for DCIS with or without an invasive component. In the pure DCIS group, lesion size on MRI was smaller than that in the DCIS with an invasive component group (2.9 ± 1.9 cm vs 4.1 ± 2.1 cm, P = .002); the pure DCIS group also showed more homogenous (42.4% [14/33] vs 14.3% [3/21], P = .03) internal enhancement characteristics in mass and focal (15.1% [8/53] vs 0% (0/34), P = .02) distribution in NME that those shown by the DCIS with an invasive component group. With regard to CAD application, the enhancing mass or NME of the pure DCIS group was less frequently detected (86.1% [74/86] vs 100% [55/55], P = .004) (Fig. 2 ), smaller (2.1 ± 1.6 cm vs 3.4 ± 2.3 cm, p = .001), and showed lesser delay washout kinetics (19.8% [17/86] vs 63.6% [35/55], P = .001) (Fig. 3 ).
Table 1: Comparison of MRI and CAD findings between pure DCIS and DCIS combined with an invasive component.
Figure 2: A 41-year-old woman with ductal carcinoma in situ (DCIS) in her right breast confirmed via ultrasonography-guided core biopsy. Post-contrast T1-weighted imaging with computer-aided diagnosis (CAD ) color overlay map showing a 3-cm regional heterogeneous nonmass lesion (arrows) that was not detected by CAD . Final pathology, as confirmed by lumpectomy, revealed a nuclear grade 1 DCIS measuring 3.4 cm in diameter.
Figure 3: A 50-year-old woman with ductal carcinoma in situ (DCIS) in her left breast confirmed via ultrasonography-guided core biopsy. (A) Post-contrast T1-weighted imaging (T1WI) showing a 6.5-cm segmental heterogeneous non-mass lesion (arrows). (B) T2-weighted imaging showing an indistinctive lesion with iso-signal intensity to the adjacent gland. (C) Post-contrast T1WI with computer-aided diagnosis (CAD ) color overlay map showing a slow persistent mass (arrows) detected by CAD . The final pathology revealed nuclear grade 3 with comedonecrosis DCIS measuring 6 cm in diameter, as confirmed by mastectomy.
3.3 Clinicopathologic and other radiologic findings of DCIS groups
Table 2 shows other clinicopathologic factors, mammographic, and ultrasonographic findings according to DCIS with and without an invasive component. The DCIS with an invasive component group was more symptomatic (43.6% [24/55] vs. 23.3% [20/86], P = .01); underwent mastectomy more frequently (60% [33/55] vs 38.4% [33/86], P = .01); more commonly showed as mass or asymmetry-associated calcifications (27.3% [15/55] vs 11.6% [10/86], P = .02) on mammography and mass on US (92.7% [51/55] vs 76.1% [68/86], P = .02); and had a larger pathologic tumor size including DCIS (4.5 ± 2.3 cm vs 2.9 ± 2 cm, P < .001), higher prevalence of comedonecrosis (50.9% [28/55] vs 22.1% [19/86], P < .001), higher (2 or 3) nuclear grade (2: 29.1% [16/55] vs 52.3% [45/86], P = .007; 3: 67.3% [37/55] vs 34.9% [30/86], P < .001), and a higher frequency of abnormality detection on mammography (89.1% [49/55] vs 73.3% [63/86], P = .02) than the pure DCIS group.
Table 2: Comparison of variables other than MRI findings between pure DCIS and DCIS combined with an invasive component.
3.4 Multivariate analysis
Using multivariate logistic regression analysis, the delay washout kinetics on CAD and pathologic tumor size were independent predictors of the histologic upgrade after adjusting for multiple clinicoradiologic factors (Table 3 ). The probability of the presence of invasive components in delay washout kinetics was approximately 4-fold higher (Fig. 4 ) than that in delay persistent or plateau kinetics (odds ratio [OR], 4.36; 95% confidence interval [CI], 1.96–9.69; P = .0003) and increased 1.29-fold according to a 1-cm increase in pathologic size (OR, 1.29; 95% CI 1.05–1.57; P = .014) (Fig. 5 ).
Table 3: Multivariate analysis results of clinicoradiologic factors for predicting the invasive component.
Figure 4: A 61-year-old woman with ductal carcinoma in situ (DCIS) in her left breast confirmed via ultrasonography-guided core biopsy. (A) Post-contrast T1-weighted imaging (T1WI) showing a 5.5-cm regional heterogeneous nonmass lesion (arrows). (B) T2-weighted imaging showing that an indistinctive lesion with iso-signal intensity at the adjacent gland. (C) Post-contrast T1WI with computer-aided diagnosis (CAD ) color overlay map showing an early enhancing component (arrowhead) with a background of slow persistent enhancement (arrows) detected by CAD . Final pathology revealed a 0.5-cm invasive cancer with 5.5-cm DCIS, as confirmed by mastectomy.
Figure 5: A 59-year-old woman with ductal carcinoma in situ (DCIS) in her right breast confirmed via ultrasonography-guided core biopsy. (A) Post-contrast T1-weighted imaging (T1WI) showing a 6.3-cm irregular irregular heterogeneous enhancing mass (arrows). (B, C) Post-contrast T1WI with computer-aided diagnosis color overlay map (B) and maximun intensity projection (C) showing multifocal early fast and delayed washout enhancing components (red colors). Final pathology revealed multifocal invasive ductal cancers with 5.7-cm DCIS, as confirmed by mastectomy.
4 Discussion
Here, the CAD application of preoperative MRI findings including detectability on CAD , detected lesion size, and delay washout kinetics were significantly associated with the invasive component in biopsy-proven DCIS. Of the MRI findings, smaller lesion size, homogeneous internal mass enhancement, and focal distribution of NME were significantly associated with pure DCIS. In addition, among the other clinicoradiologic findings, abnormality detection on an ultrasound scan or mammogram, symptomatic condition, patients who underwent total mastectomy, high nuclear grade, and presence of comedonecrosis were significantly correlated with the DCIS-associated invasive component. On multivariate analysis, the probability of the presence of an invasive component was approximately 4-fold higher in delay washout kinetics and had increased 1.29-fold according to 1-cm increase in pathologic tumor size.
The final histologic findings from our study revealed 55 invasive lesions of 141 biopsy-proven DCIS and the rate of prevalence of invasive components was 39%. Once DCIS had been diagnosed pathologically during biopsy, knowledge of occult invasion was crucial because it influenced treatment decisions. It has been well known that SLNB should be considered for axillary management in invasive breast cancer patients.[6] [7]
Mammography is a useful screening tool for DCIS but it can only detect calcified portions of DCIS and underestimates the disease extent as opposed to histologic findings.[17] [18] [19,20] breast lesion underwent noninvasive imaging study, particularly breast MRI , to evaluate the contralateral or multicentric breast lesion . MRI reflects the biology of breast lesions and reveals visual differentiation regarding increased vascularity and capillary permeability of breast lesions. Breast MRI is an emerging complementary work-up tool because of its high sensitivity in the detection of breast lesions and because it provides additional 3-dimensional spatial and temporal information on breast cancer. Recent studies on DCIS have reported the sensitivity values of breast MRI as 97% for 33 patients and 92% for 167 patients.[18,21]
In terms of MRI findings, several previous studies found that lesion size on MRI scans and enhancement pattern of lesions correlated with the co-existence of invasive components in biopsy-proven DCIS. Goto et al and Lamb et al reported that large-size lesions on MRI scans could be associated with an invasive component.[11,12] [22,23] CAD systems in this study to correctly diagnose invasive cancer. Among the findings, presence of a delayed washout, detectability, or lesion size on CAD were individually correlated with invasive cancer; the presence of delayed washout was the most predictive MR feature with the highest OR in this study (OR, 4.36; 95% CI, 1.96–9.69; P = .0003).
Many previous studies have investigated the predictive factors for an occult invasive component in biopsy-proven DCIS. In a meta-analysis, the authors described how large tumor size, high nuclear grade, presence of symptoms such as palpability, and presence of mammographic abnormalities could be significantly associated with a risk of invasive disease in biopsy-proven DCIS.[24] [23] [12,25] [13]
Our study had several limitations. First, it was performed retrospectively with a small sample size and only included cases of US-guided biopsy-proven DCIS. In addition, we included the patients for about 4 years; therefore, a potential selection bias could have occurred during that period. Second, variable management techniques could have been adopted by different physicians; for instance, there is a potential for variability among the radiologists for deciding whether US-guided core needle biopsy needs to be performed. Third, our study focused on MR features, and thus, we included limited ultrasonographic and mammographic findings in our analysis.
In conclusion, with the application of CAD systems, MRI can be more useful for diagnosing invasive component in patients with biopsy-proven DCIS. As opposed to pure DCIS, DCIS with an invasive component showed a larger pathologic size and a more frequent delayed washout kinetic feature in the CAD system. Therefore, SLNB could be considered for patients selectively.
Author contributions
Conceptualization: Sun Mi Kim.
Data curation: Hye Shin Ahn, Bo La Yun, Mijung Jang, Eunyoung Kang, Eun-Kyu Kim, Mi Sun Kim.
Formal analysis: Eunyoung Kang, Eun-Kyu Kim.
Investigation: So Yeon Park.
Methodology: Sun Mi Kim, Bohyoung Kim.
Project administration: Sun Mi Kim.
Validation: So Yeon Park.
Writing – original draft: Hye Shin Ahn, Mi Sun Kim
Writing – review & editing: Bo La Yun, Mijung Jang, Bohyoung Kim.
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