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Application of Abbreviated Protocol of Magnetic Resonance Imaging for Breast Cancer Screening in Dense Breast Tissue
ARTICLE IN PRESS
Original Investigation
Application of Abbreviated Protocol of Magnetic Resonance Imaging for Breast Cancer Screening in Dense Breast Tissue Shuang-Qing Chen, MD, Min Huang, MD, Yu-Ying Shen, MD, Chen-Lu Liu, MD, Chuan-Xiao Xu, MD Rationale and Objectives: The study aimed to evaluate the usefulness of an abbreviated protocol (AP) of magnetic resonance imaging (MRI) in comparison to a full diagnostic protocol (FDP) of MRI in the breast cancer screening with dense breast tissue. Materials and Methods: There are 478 female participants with dense breast tissue and negative mammography results, who were imaged with MRI using AP and FDP. The AP and FDP images were analyzed separately, and the sensitivity and specificity of breast cancer detection were calculated. The chi-square test and receiver operating characteristics curves were used to assess the breast cancer diagnostic capabilities of the two protocols. Results: Sixteen cases of breast cancer from 478 patients with dense breasts were detected using the FDP method, with pathologic confirmation of nine cases of ductal carcinoma in situ, six cases of invasive ductal carcinoma, and one case of mucinous carcinoma. Fifteen cases of breast cancer were successfully screened using the AP method. The sensitivity showed no obvious significant difference between AP and FDP (χ2 = 0.592, P = 0.623), but the specificity showed a statistically significant difference (χ2 = 4.619, P = 0.036). The receiver operating characteristics curves showed high efficacy of both methods in the detection of breast cancer in dense breast tissue (the areas under the curve were 0.931 ± 0.025 and 0.947 ± 0.024, respectively), and the ability to diagnose breast cancer was not statistically significantly different between the two methods. Conclusions: The AP of MRI may improve the detection rate of breast cancer in dense breast tissue, and it may be useful in efficient breast cancer screening. Key Words: Breast cancer; magnetic resonance imaging; abbreviated protocol; breast screening. © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
INTRODUCTION
B
reast cancer, the most common or second most common cancer in women worldwide (1,2), has gradually gained prevalence. Early detection of breast cancer can improve the duration of survival and quality of life in patients (3). Extensive screening can detect breast cancer early, thus screening plays an increasing important role in breast care. Mammography (MG) is the preferred method of screening for breast tissue because it is simple, convenient, affordable, and irreplaceable in the detection of microcalcifications (4). Studies have shown that, within groups of the same age, there are two to six times higher risk of breast cancer in dense breasts Acad Radiol 2016; ■:■■–■■ From the Department of Radiology, The Affiliated Suzhou Hospital, Nanjing Medical University, No.16, Bai-Ta-Xi Road, Suzhou 215001 (S.-Q.C., Y.-Y.S., C.-L.L.); Breast Imaging Screening Center, The Affiliated Suzhou Hospital, Nanjing Medical University, Suzhou, China (M.H., C.-X.X.). Received May 7, 2016; revised October 9, 2016; accepted October 10, 2016. Address correspondence to: S.-Q.C. e-mail: [email protected] © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.acra.2016.10.003
than in non-dense breasts, but MG detection sensitivity in dense breasts is much lower than that in fatty breasts (5–8). For example, Mendelson et al. found that the detection rate of breast cancer using MG was only 30% in dense breasts and 80% in fatty breasts (8). This clearly shows a limitation of using MG in breast screening. Magnetic resonance imaging (MRI) has outstanding soft tissue resolution and multiplanar imaging capability, thereby offering unique advantages in the detection and diagnosis of breast lesions. The American College of Radiology (ACR) included breast MRI in the fourth edition of the Breast Imaging Reporting and Data System (BI-RADS) in 2003. The use of MRI has been standardized in breast examination (9). Dynamic contrast-enhanced MRI (DCE-MRI), a more advanced technique for breast MRI, allows an analysis of breast lesions through both morphologic and hemodynamic changes, with a sensitivity of 100% and specificity of up to 97% for breast cancer detection (10). However, the lengthy inspection time and high medical cost incurred by DCE-MRI have limited its use in breast MRI screening. Currently, it is used as a supplementary examination of certain breast cancers in high-risk populations (11). 1
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From 2009 to 2010, Kuhl et al. of Aachen University Hospital (12) studied 443 cases of MG-negative and asymptomatic women, and found that by merely reviewing the first postcontrast subtracted (FAST) and maximum intensity projection (MIP) images, 11 cases of breast cancer were detected, with the detection rate increasing by 18.3 per 1000. This 3-minute abbreviated protocol (AP) of MRI had a high performance (100% sensitivity and 94.4% specificity) consistent with the 21-minute routine full diagnostic protocol (FDP). Morris at Sloan Kettering Cancer Center (USA) (13) found that the AP enabled a better detection performance than MG, and hence recommended that AP should become the standard protocol for breast cancer screening. In the present study, the use of AP in the screening of dense breasts was studied, and whether it can improve the detection rate of breast cancer in dense breast was investigated, with the aim of providing additional evidence for more effective and economical methods of breast screening. MATERIALS AND METHODS Participants
Female participants who had undergone MG from January 2013 to March 2015 were recruited to the study. Breast density was classified based on the ACR standards (9). In the present study, among 542 MG-negative women classified as having dense breasts, 478 underwent routine breast MRI. Women with a family history of breast cancer were excluded in this study. The subjects were 30 to 71 years old, with a mean age of 49.3 years. Premenopausal women were imaged 1 week after menstruation. MRI Examination Techniques
In this study, MRI was performed using an eight-channel dedicated phased-array breast coil on a 3.0T magnet (Area D13, Siemens, SHealthineers, Erlangen, Germany). The patients assumed a prone position with both breasts symmetrically positioned in the coil. The axial scans included fast spin echo (FSE) T1WI, T2WI + fat suppression, and the sagittal scans included FSE T2WI +fat suppression. For DCE-MRI, a Flash 3D sequence (transverse T1WI bilateral breast imaging with the following parameters: repetition time (TR) of 4 ms, echo time (TE) of 1.55 ms, thickness of 1.5 mm, no interval) was used. After the first dynamic scan (mask), contrast agent Gadolinium-diethylene triamine pentaacetic acids (Gd-DTPA) was injected via the cubital vein at a rate of 0.2 mL/s and a dose of 0.2 mmol/kg using a high-pressure syringe. The scanning started as soon as the contrast agent was injected, and eight phases were continuously scanned in a total scan time of 12 minutes and 32 seconds. Data Analysis
All of the raw images were processed in a syngo MR workplace, and subtraction images were automatically obtained. The 2
subtraction images at each phase were MIP reconstructed and time-signal intensity curves were rendered. Two senior radiologists, with experience in breast imaging of at least 10 years, independently read the films in two steps. They first drew a conclusion based on AP (FAST + MIP) images and then read all of the FDP images to draw the second conclusion, and the time to interpret the AP and FDP was measured. In order to avoid recall bias, two interpretation sessions were projected at least 1 month apart and cases were randomized. When the two radiologists’ assessments on either FDP or AP did not match, a third senior radiologist, with 15 years of specialized breast imaging experience, was called to independently analyze the material and determine the final conclusion. In this study, all MRI findings were retrospectively described using the BI-RADS MRI categories. The sensitivity, specificity, positive predictive value, and negative predictive values of the two methods were calculated. Statistical Analysis
The SPSS16.0 (SPSS Inc., Chicago, IL) statistical software was used for statistical analysis. The paired t test was used to assess differences of interpretation time between AP and FDP. The chi-square test and receiver operating characteristics (ROC) curves were used to compare the diagnostic capabilities of AP and FDP on breast cancer. A P value less than 0.05 was considered to indicate statistical significance. RESULTS When using the FDP as a diagnostic criterion, among the 478 cases of dense breasts, 41 lesions were detected in 39 patients. Subsequent biopsy and surgical pathology showed 16 breast cancers in 16 lesions and 23 cases of benign breast lesions in 25 lesions (Table 1). Malignant lesions were found in the upper outer quadrant in 10 cases, upper inner quadrant in 2 cases, lower outer quadrant in 3 cases, and lower inner quadrant in 1 case. Benign lesions were located in the upper outer quadrant in 12 cases, upper inner quadrant in 5 cases, lower outer quadrant in 5 cases, and lower inner quadrant in 3 cases. In this study, the average interpretation time of the AP was 42 ± 18 seconds, whereas the average interpretation time of
TABLE 1. Pathology of 41 Benign and Malignant Lesions Pathology Malignant (n = 16) Ductal carcinoma in situ Invasive ductal carcinoma Mucinous carcinoma Benign (n = 25) Hyperplasia Fibroadenoma Papilloma in situ of duct Cyst Granuloma
No 4 11 1 8 11 2 3 1
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ABBREVIATED BREAST MAGNETIC RESONANCE IMAGING
Figure 1. A 42-year-old woman with dense breast tissue. The abbreviated protocol of magnetic resonance imaging showed a 5-mm enhancing nodule (arrow) on the left, and pathology proved the presence of a 5-mm ductal carcinoma in situ. (a) First postcontrast dynamic acquisition (T1WI + fat suppression); (b) first postcontrast subtracted; and (c) maximum intensity projection.
Figure 2. A 37-year-old woman with dense breast tissue. The abbreviated protocol of magnetic resonance imaging showed a 10-mm enhancing nodule (arrow) on the left, and pathology proved the presence of a 10-mm invasive ductal carcinoma. (a) First postcontrast dynamic acquisition (T1WI + fat suppression); (b) first postcontrast subtracted; and (c) maximum intensity projection.
TABLE 2. Comparison of the Breast Cancer Diagnostic Capabilities of AP and FPD
Sensitivity Specificity PPV NPV
AP (%)
FDP (%)
93.8% (15/16) 88.3% (408/462) 21.7% (15/69) 99.8% (408/409)
100.0% (16/16) 94.6% (437/462) 41.0% (16/39) 100% (439/439)
AP, abbreviated protocol; FDP, full diagnostic protocol; NPV, negative predictive value; PPV, positive predictive value.
the FDP was 192 ± 44 seconds. A statistically significant difference was found between AP and FDP (P < 0.05). Among the 478 cases of patients with dense breasts, the AP-based MRI reading detected positive lesions in 54 cases and negative lesions in 424 cases, whereas the FDP-based reading detected positive lesions in 41 cases and negative lesions in 437 cases. Of the 16 cases of breast cancer, 14 cases were identified on AP by two radiologists, and two ductal carcinomas in situ were consistently missed by two radiologists. However, the remaining one invasive ductal carcinoma was only detected by one reader. According to the third senior radiologist, the APbased reading successfully detected 15 cases and the FDPbased successfully detected 16 cases (Figs 1 and 2). The sensitivity, specificity, positive predictive value, and negative predictive value of the two methods are summarized in Table 2. No significant difference in sensitivity was found between AP and FDP in the diagnosis of breast cancer (χ2 = 0.592, P = 0.623), but the specificity of AP was significantly lower than that of FDP (χ2 = 4.619, P = 0.036). The
Figure 3. The ROC curve of AP and FDP. The ROC curve showed the high efficacy of both AP and FDP in detection of breast cancer in dense breast tissue. AP, abbreviated protocol; FDP, full diagnostic protocol; ROC, receiver operating characteristics.
area under the ROC curve was 0.931 ± 0.025 (P = 0.000) for AP and 0.947 ± 0.024 (P = 0.000) for FDP (Fig 3). Both methods demonstrated statistically significant differences in the ability to diagnose breast cancer, and the diagnostic accuracy was high. The 95% confidence interval (95% CI) of AP was 0.881–0.980, and the 95% CI of FDP was 0.900–0.994. The CIs overlapped substantially, indicating that the difference 3
CHEN ET AL
in the ability to diagnose breast cancer was not statistically significant between the two methods.
DISCUSSION Breast tissues on MG images were divided into four categories based on the relative content of mammary glands and fibers and the fifth edition of ACR BI-RADS (14), wherein breasts in which fibroglandular tissues make up more than 75% of the gland are considered dense. Many researchers believe that the increase in breast density is an independent risk factor for breast cancer: the denser the breast tissue is, the higher risk of breast cancer will be (15,16). Some reports have indicated that the possibility of dense breast tissue developing into dysplasia or carcinoma in situ is 9.7 times higher than that of non-dense breast (17,18). Asian women generally have smaller breasts and less fat content but a higher proportion of fibroglandular tissue than people in non-Asian countries, so dense breasts are significantly more common in Asian populations than in European, North American, and African populations (17,19). In China, statistics have shown that more than one third of women have dense breasts, and the incidence of breast cancer is significantly higher than that of nondense breasts (20). MG is the preferred method of screening breasts for cancer, but its sensitivity and specificity are significantly affected by gland density. Because of the overlap between normal breast tissues and lesions, MG reading may miss lesions hidden deep in the breast tissues, or even mistake some overlapping tissues artifacts as false positives. It has been reported in the literature that 15–50% of the breast lumps in dense breast tissues palpable during physical examination cannot be displayed on MG (21). Typically, the denser the breast, the lower the detection rate of breast cancer by reading MG (22,23). Even the widely used full-field digital mammography that demonstrates poor resolution on the structure of dense breast tissues may lead to easy miss of deep lesions or lesions under the axilla (24,25). Past research has shown that 50% of the lesions in dense breast tissues cannot be displayed clearly on full-field digital mammography (26). Digital breast tomosynthesis is available for breast screening and can increase the cancer detection rate. However, additional cancer detection rates still are lower than demonstrated by MRI (27). Because of its ability to produce high-resolution images, MRI has become another important modality for early detection of breast cancer, especially for high-risk women (11). It is often used after MG. Not affected by breast density, MRI with multiparameter and multidirectional imaging clearly shows the morphology of the lesions, internal features, and surrounding structures, thereby allowing better lesion detection. It is particularly effective in the detection of tiny hidden nodules in the breast tissues. Berg et al. have shown that, even in patients found to be negative under MG and ultrasonography (US), MRI can still detect an additional 15 per 1000 cases of breast cancer (28). 4
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DCE-MRI is the most commonly used MRI technology for breast cancer diagnosis. It is highly sensitive and specific (10,29). Digital subtraction imaging can remove the interference signals caused by the fat and increase the contrast between the lesion and its surrounding tissues. MIP can clearly display surrounding distorted large vessels and abnormally proliferated small blood vessels. In this way, DCE-MRI enables accurately localizing the lesions from both morphologic and hemodynamic aspects. However, it takes a long time to perform a conventional DCE-MRI scan, typically requiring at least five to eight dynamic phases, and to process the time-signal intensity curve images. In addition, high costs and other issues restrict the wide use of MRI in breast screening. Moore et al. used the Markov model to compare the cost-effectiveness of MRI to that of MG (30). The results showed that, although breast MRI has many advantages, it is not cost-effective. In DCE-MRI, when the positive contrast agent GdDTPA passes over the tumor tissue the first time, the signal intensity increases, reflecting the abundant tumor blood supply and high vascular permeability. Therefore, the enhanced contrast between the breast lesions and normal breast parenchyma during the early stages is particularly important for breast cancer diagnosis (31). Kuhl et al. argued that the images created during the early arterial phase after contrast injection are the most suitable for visual enhancement of breast cancer, and images created during other phases are mainly used to observe the structural features after the injection of contrasting agent, and showed that FAST and subsequent MIP are better for breast cancer screening than other methods (12). In the present study, FAST + MIP images of the 478 dense breast cases were reviewed, and 15 of 16 breast cancer cases were detected, with a high sensitivity rate (93.8%) and negative predictive value (99.8%) with statistical significance. The ROC curves also showed that AP, a time-saving protocol, demonstrated no significant differences from FDP, a more lengthy program, not to mention that it is more time-consuming to review all FDP images than AP images. Our results also showed that the specificity of AP-based breast cancer detection was less pronounced than that of FDPbased. It is because FDP images taken during other phases can demonstrate more prominent structural features during postlesion enhancement, providing the corresponding strengthening curve. This indicates that the AP-based screening method may not work for clinical diagnosis or differential diagnosis. In addition, several benign lesions were incorrectly found using AP, and the false-positive diagnoses may lead to high indirect costs (eg, US, biopsy, or short-term follow-up was performed). However, AP still enables a significant detection rate for patients with negative MG. Because AP requires significantly less examination time, it can screen more patients during the same period and save cost. These features may play an important role in further promoting MRI in breast screening. Breast cancer is one of the few cancers for which mortality can be reduced by cancer screening, so experts in the field are committed to addressing early detection of breast cancer,
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although controversies still exist regarding breast cancer screening technology and platforms. US can improve the detection rate of breast cancer. Varga et al. had proposed to combine US and MG, which are the two pillars of modern breast cancer detection (32). However, the false-positive rate of US is still significantly higher than that of MRI (28). MG performance is poor for imaging of dense glands, and excessive repeated MG leads to radiation damage and higher costs, thereby reducing the cost-benefit ratio. The U.S. Preventive Services Task Force published new breast cancer screening recommendations in Annals of Internal Medicine in November 2009, in which they no longer recommended MG screening every 1~2 years for women aged 40~49 years but instead recommended MG screening every 2 years for women aged 50~74 (33). For younger women, especially those with dense breasts, MRI AP may be a more appropriate screening protocol. Of course, extensive use of AP for breast screening still needs further clinical study. CONCLUSION We suggest that breast density should be classified based on gland density after the initial MG screening. For abundant and dense glands, the AP of MRI should be recommended to help improve the detection rate of breast cancer and costeffectiveness of screening programs. REFERENCES 1. Aberle DR, Chiles C, Gatsonis C, et al. Imaging and cancer: research strategy of the American College of Radiology Imaging Network. Radiology 2005; 235:741–751. 2. Jemal A, Siegel R, Xu J, et al. Cancer statistics, 2010. CA Cancer J Clin 2010; 60:277–300. 3. Game JP, Aspegren K, Balldin G, et al. Increasing incidence of and declining mortality from breast carcinoma. Trends in Malmö, Sweden, 1961– 1992. Cancer 1997; 79:69–74. 4. Graf O, Berg WA, Sickle EA. Large rodlike calcifications at mammography: analysis of morphologic features. AJR Am J Roentgenol 2013; 200:299–303. 5. Pollán M, Ascunce N, Ederra M, et al. Mammographic density and risk of breast cancer according to tumor characteristics and mode of detection: a Spanish population-based case-control study. Breast Cancer Res 2013; 15:R9. 6. Boyd NF, Guo H, Martin LJ, et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med 2007; 356:227–236. 7. McCormack VA, dos Santos Silva I. Breast density and parenchymal as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev 2006; 15:1159–1169. 8. Mendelson MT, Oestreicher N, Porter PL, et al. Breast density as a predictor of mammographic detection: comparison of interval- and screendetected cancers. J Natl Cancer Inst 2000; 92:1081–1087. 9. Oeffinger KC, Fontham ET, Etzioni R, et al. Breast cancer screening for women at average risk: 2015 guideline update from the American Cancer Society. JAMA 2015; 314:1599–1614. 10. Harnett A, Smallwood J, Titshall V, et al. Diagnosis and treatment of early breast cancer, including locally advanced disease-summary of NICE guidance. BMJ 2009; 338:b438.
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11. Berg WA. How well does supplemental screening magnetic resonance imaging work in high-risk women? J Clin Oncol 2014; 32:2193–2196. 12. Kuhl CK, Schrading S, Strobel K, et al. Abbreviated breast magnetic resonance imaging (MRI): first postcontrast subtracted images and maximumintensity projection-a novel approach to breast cancer screening with MRI. J Clin Oncol 2014; 32:2304–2310. 13. Morris EA. Rethinking breast cancer screening: ultra fast breast magnetic resonance imaging. J Clin Oncol 2014; 32:2281–2283. 14. Kim SY, Kim HY, Kim EK, et al. Evaluation of malignancy risk stratification of microcalcifications detected on mammography: a study based on the 5th edition of BI-RADS. Ann Surg Oncol 2015; 22:2895–2901. 15. Brower V. Homing in on mechanisms linking breast density to breast cancer risk. J Natl Cancer Inst 2010; 102:843–845. 16. Kerlikowske K. The mammogram that cried Wolfe. N Engl J Med 2007; 356:297–300. 17. Harvey JA, Bovbjerg VE. Quantitative assessment of mammographic breast density: relationship with breast cancer risk. Radiology 2004; 230:29– 41. 18. Boyd NF, Rommens JM, Vogt K, et al. Mammographic breast density as an intermediate phenotype for breast cancer. Lancet Oncol 2005; 6:798– 808. 19. del Carmen MG, Halpern EF, Kopans DB, et al. Mammographic breast density and race. AJR 2007; 188:1147–1150. 20. Carney PA, Miglioretti DL, Yankaskas BC, et al. Individual and combined effects of age, breast density, and hormone replacement therapy use on the accuracy of screening mammography. Ann Intern Med 2003; 138:168–175. 21. Mandelson MT, Oestreicher N, Porter PL, et al. Breast density as a predictor of mammographic detection: comparison of interval- and screendetected cancers. J Natl Cancer Inst 2000; 92:1081–1087. 22. Kerlikowske K, Grady D, Barclay J, et al. Effect of age, breast density, and family history on the sensitivity of first screening mammography. JAMA 1996; 276:33–38. 23. Kolb TM, Lichy J, Newhouse JH. Comparison of the performance of screening mammography, physical examination, and breast us and evaluation of factors that influence them: an analysis of 27,825 patient evaluations. Radiology 2002; 225:165–175. 24. Svane G, Azavedo E, Lindman K, et al. Clinical experience of photon counting breast tomosynthesis: comparison with traditional mammography. Acta Radiol 2014; 52:134–142. 25. Gennaro G, Toledano A, di Maggio C, et al. Digital breast tomosynthesis versus digital mammography: a clinical performance study. Eur Radiol 2010; 20:1545–1553. 26. Roubidoux MA, Bailey JE, Wray LA, et al. Invasive cancers detected after breast cancer screening yielded a negative result: relationship of mammographic density to tumor prognostic factors. Radiology 2004; 230:42– 48. 27. Clauser P, Carbonaro LA, Pancot M, et al. Additional findings at preoperative breast MRI: the value of second-look digital breast tomosynthesis. Eur Radiol 2015; 25:2830–2839. 28. Berg WA, Zhang Z, Lehrer D, et al. Detection of breast cancer with addition of annual screening ultrasound or a single screening MRI to mammography in women with elevated breast cancer risk. JAMA 2012; 307:1394–1404. 29. Tudorica LA, Oh KY, Roy N, et al. A feasible high spatiotemporal resolution breast DCE-MRI protocol for clinical settings. Magn Reson Imaging 2012; 30:1257–1267. 30. Moore SG, Shenoy PJ, Fanucchi L, et al. Cost-effectiveness of MRI compared to mammography for breast cancer screening in a high risk population. BMC Health Serv Res 2009; 9:9. 31. Heywang SH, Wolf A, Pruss E, et al. MR imaging of the breast with GdDTPA: use and limitations. Radiology 1987; 171:95–103. 32. Varga D, Wöckel A, Wagner J, et al. Value of ultrasound in preoperative local staging in early breast cancer. Ultraschall Med 2011; 32:387– 392. 33. U.S. Preventive Services Task Force. Screening for breast cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med 2009; 151:716–726.
5
Original Investigation
Application of Abbreviated Protocol of Magnetic Resonance Imaging for Breast Cancer Screening in Dense Breast Tissue Shuang-Qing Chen, MD, Min Huang, MD, Yu-Ying Shen, MD, Chen-Lu Liu, MD, Chuan-Xiao Xu, MD Rationale and Objectives: The study aimed to evaluate the usefulness of an abbreviated protocol (AP) of magnetic resonance imaging (MRI) in comparison to a full diagnostic protocol (FDP) of MRI in the breast cancer screening with dense breast tissue. Materials and Methods: There are 478 female participants with dense breast tissue and negative mammography results, who were imaged with MRI using AP and FDP. The AP and FDP images were analyzed separately, and the sensitivity and specificity of breast cancer detection were calculated. The chi-square test and receiver operating characteristics curves were used to assess the breast cancer diagnostic capabilities of the two protocols. Results: Sixteen cases of breast cancer from 478 patients with dense breasts were detected using the FDP method, with pathologic confirmation of nine cases of ductal carcinoma in situ, six cases of invasive ductal carcinoma, and one case of mucinous carcinoma. Fifteen cases of breast cancer were successfully screened using the AP method. The sensitivity showed no obvious significant difference between AP and FDP (χ2 = 0.592, P = 0.623), but the specificity showed a statistically significant difference (χ2 = 4.619, P = 0.036). The receiver operating characteristics curves showed high efficacy of both methods in the detection of breast cancer in dense breast tissue (the areas under the curve were 0.931 ± 0.025 and 0.947 ± 0.024, respectively), and the ability to diagnose breast cancer was not statistically significantly different between the two methods. Conclusions: The AP of MRI may improve the detection rate of breast cancer in dense breast tissue, and it may be useful in efficient breast cancer screening. Key Words: Breast cancer; magnetic resonance imaging; abbreviated protocol; breast screening. © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
INTRODUCTION
B
reast cancer, the most common or second most common cancer in women worldwide (1,2), has gradually gained prevalence. Early detection of breast cancer can improve the duration of survival and quality of life in patients (3). Extensive screening can detect breast cancer early, thus screening plays an increasing important role in breast care. Mammography (MG) is the preferred method of screening for breast tissue because it is simple, convenient, affordable, and irreplaceable in the detection of microcalcifications (4). Studies have shown that, within groups of the same age, there are two to six times higher risk of breast cancer in dense breasts Acad Radiol 2016; ■:■■–■■ From the Department of Radiology, The Affiliated Suzhou Hospital, Nanjing Medical University, No.16, Bai-Ta-Xi Road, Suzhou 215001 (S.-Q.C., Y.-Y.S., C.-L.L.); Breast Imaging Screening Center, The Affiliated Suzhou Hospital, Nanjing Medical University, Suzhou, China (M.H., C.-X.X.). Received May 7, 2016; revised October 9, 2016; accepted October 10, 2016. Address correspondence to: S.-Q.C. e-mail: [email protected] © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.acra.2016.10.003
than in non-dense breasts, but MG detection sensitivity in dense breasts is much lower than that in fatty breasts (5–8). For example, Mendelson et al. found that the detection rate of breast cancer using MG was only 30% in dense breasts and 80% in fatty breasts (8). This clearly shows a limitation of using MG in breast screening. Magnetic resonance imaging (MRI) has outstanding soft tissue resolution and multiplanar imaging capability, thereby offering unique advantages in the detection and diagnosis of breast lesions. The American College of Radiology (ACR) included breast MRI in the fourth edition of the Breast Imaging Reporting and Data System (BI-RADS) in 2003. The use of MRI has been standardized in breast examination (9). Dynamic contrast-enhanced MRI (DCE-MRI), a more advanced technique for breast MRI, allows an analysis of breast lesions through both morphologic and hemodynamic changes, with a sensitivity of 100% and specificity of up to 97% for breast cancer detection (10). However, the lengthy inspection time and high medical cost incurred by DCE-MRI have limited its use in breast MRI screening. Currently, it is used as a supplementary examination of certain breast cancers in high-risk populations (11). 1
Academic Radiology, Vol ■, No ■■, 2016
CHEN ET AL
From 2009 to 2010, Kuhl et al. of Aachen University Hospital (12) studied 443 cases of MG-negative and asymptomatic women, and found that by merely reviewing the first postcontrast subtracted (FAST) and maximum intensity projection (MIP) images, 11 cases of breast cancer were detected, with the detection rate increasing by 18.3 per 1000. This 3-minute abbreviated protocol (AP) of MRI had a high performance (100% sensitivity and 94.4% specificity) consistent with the 21-minute routine full diagnostic protocol (FDP). Morris at Sloan Kettering Cancer Center (USA) (13) found that the AP enabled a better detection performance than MG, and hence recommended that AP should become the standard protocol for breast cancer screening. In the present study, the use of AP in the screening of dense breasts was studied, and whether it can improve the detection rate of breast cancer in dense breast was investigated, with the aim of providing additional evidence for more effective and economical methods of breast screening. MATERIALS AND METHODS Participants
Female participants who had undergone MG from January 2013 to March 2015 were recruited to the study. Breast density was classified based on the ACR standards (9). In the present study, among 542 MG-negative women classified as having dense breasts, 478 underwent routine breast MRI. Women with a family history of breast cancer were excluded in this study. The subjects were 30 to 71 years old, with a mean age of 49.3 years. Premenopausal women were imaged 1 week after menstruation. MRI Examination Techniques
In this study, MRI was performed using an eight-channel dedicated phased-array breast coil on a 3.0T magnet (Area D13, Siemens, SHealthineers, Erlangen, Germany). The patients assumed a prone position with both breasts symmetrically positioned in the coil. The axial scans included fast spin echo (FSE) T1WI, T2WI + fat suppression, and the sagittal scans included FSE T2WI +fat suppression. For DCE-MRI, a Flash 3D sequence (transverse T1WI bilateral breast imaging with the following parameters: repetition time (TR) of 4 ms, echo time (TE) of 1.55 ms, thickness of 1.5 mm, no interval) was used. After the first dynamic scan (mask), contrast agent Gadolinium-diethylene triamine pentaacetic acids (Gd-DTPA) was injected via the cubital vein at a rate of 0.2 mL/s and a dose of 0.2 mmol/kg using a high-pressure syringe. The scanning started as soon as the contrast agent was injected, and eight phases were continuously scanned in a total scan time of 12 minutes and 32 seconds. Data Analysis
All of the raw images were processed in a syngo MR workplace, and subtraction images were automatically obtained. The 2
subtraction images at each phase were MIP reconstructed and time-signal intensity curves were rendered. Two senior radiologists, with experience in breast imaging of at least 10 years, independently read the films in two steps. They first drew a conclusion based on AP (FAST + MIP) images and then read all of the FDP images to draw the second conclusion, and the time to interpret the AP and FDP was measured. In order to avoid recall bias, two interpretation sessions were projected at least 1 month apart and cases were randomized. When the two radiologists’ assessments on either FDP or AP did not match, a third senior radiologist, with 15 years of specialized breast imaging experience, was called to independently analyze the material and determine the final conclusion. In this study, all MRI findings were retrospectively described using the BI-RADS MRI categories. The sensitivity, specificity, positive predictive value, and negative predictive values of the two methods were calculated. Statistical Analysis
The SPSS16.0 (SPSS Inc., Chicago, IL) statistical software was used for statistical analysis. The paired t test was used to assess differences of interpretation time between AP and FDP. The chi-square test and receiver operating characteristics (ROC) curves were used to compare the diagnostic capabilities of AP and FDP on breast cancer. A P value less than 0.05 was considered to indicate statistical significance. RESULTS When using the FDP as a diagnostic criterion, among the 478 cases of dense breasts, 41 lesions were detected in 39 patients. Subsequent biopsy and surgical pathology showed 16 breast cancers in 16 lesions and 23 cases of benign breast lesions in 25 lesions (Table 1). Malignant lesions were found in the upper outer quadrant in 10 cases, upper inner quadrant in 2 cases, lower outer quadrant in 3 cases, and lower inner quadrant in 1 case. Benign lesions were located in the upper outer quadrant in 12 cases, upper inner quadrant in 5 cases, lower outer quadrant in 5 cases, and lower inner quadrant in 3 cases. In this study, the average interpretation time of the AP was 42 ± 18 seconds, whereas the average interpretation time of
TABLE 1. Pathology of 41 Benign and Malignant Lesions Pathology Malignant (n = 16) Ductal carcinoma in situ Invasive ductal carcinoma Mucinous carcinoma Benign (n = 25) Hyperplasia Fibroadenoma Papilloma in situ of duct Cyst Granuloma
No 4 11 1 8 11 2 3 1
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ABBREVIATED BREAST MAGNETIC RESONANCE IMAGING
Figure 1. A 42-year-old woman with dense breast tissue. The abbreviated protocol of magnetic resonance imaging showed a 5-mm enhancing nodule (arrow) on the left, and pathology proved the presence of a 5-mm ductal carcinoma in situ. (a) First postcontrast dynamic acquisition (T1WI + fat suppression); (b) first postcontrast subtracted; and (c) maximum intensity projection.
Figure 2. A 37-year-old woman with dense breast tissue. The abbreviated protocol of magnetic resonance imaging showed a 10-mm enhancing nodule (arrow) on the left, and pathology proved the presence of a 10-mm invasive ductal carcinoma. (a) First postcontrast dynamic acquisition (T1WI + fat suppression); (b) first postcontrast subtracted; and (c) maximum intensity projection.
TABLE 2. Comparison of the Breast Cancer Diagnostic Capabilities of AP and FPD
Sensitivity Specificity PPV NPV
AP (%)
FDP (%)
93.8% (15/16) 88.3% (408/462) 21.7% (15/69) 99.8% (408/409)
100.0% (16/16) 94.6% (437/462) 41.0% (16/39) 100% (439/439)
AP, abbreviated protocol; FDP, full diagnostic protocol; NPV, negative predictive value; PPV, positive predictive value.
the FDP was 192 ± 44 seconds. A statistically significant difference was found between AP and FDP (P < 0.05). Among the 478 cases of patients with dense breasts, the AP-based MRI reading detected positive lesions in 54 cases and negative lesions in 424 cases, whereas the FDP-based reading detected positive lesions in 41 cases and negative lesions in 437 cases. Of the 16 cases of breast cancer, 14 cases were identified on AP by two radiologists, and two ductal carcinomas in situ were consistently missed by two radiologists. However, the remaining one invasive ductal carcinoma was only detected by one reader. According to the third senior radiologist, the APbased reading successfully detected 15 cases and the FDPbased successfully detected 16 cases (Figs 1 and 2). The sensitivity, specificity, positive predictive value, and negative predictive value of the two methods are summarized in Table 2. No significant difference in sensitivity was found between AP and FDP in the diagnosis of breast cancer (χ2 = 0.592, P = 0.623), but the specificity of AP was significantly lower than that of FDP (χ2 = 4.619, P = 0.036). The
Figure 3. The ROC curve of AP and FDP. The ROC curve showed the high efficacy of both AP and FDP in detection of breast cancer in dense breast tissue. AP, abbreviated protocol; FDP, full diagnostic protocol; ROC, receiver operating characteristics.
area under the ROC curve was 0.931 ± 0.025 (P = 0.000) for AP and 0.947 ± 0.024 (P = 0.000) for FDP (Fig 3). Both methods demonstrated statistically significant differences in the ability to diagnose breast cancer, and the diagnostic accuracy was high. The 95% confidence interval (95% CI) of AP was 0.881–0.980, and the 95% CI of FDP was 0.900–0.994. The CIs overlapped substantially, indicating that the difference 3
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in the ability to diagnose breast cancer was not statistically significant between the two methods.
DISCUSSION Breast tissues on MG images were divided into four categories based on the relative content of mammary glands and fibers and the fifth edition of ACR BI-RADS (14), wherein breasts in which fibroglandular tissues make up more than 75% of the gland are considered dense. Many researchers believe that the increase in breast density is an independent risk factor for breast cancer: the denser the breast tissue is, the higher risk of breast cancer will be (15,16). Some reports have indicated that the possibility of dense breast tissue developing into dysplasia or carcinoma in situ is 9.7 times higher than that of non-dense breast (17,18). Asian women generally have smaller breasts and less fat content but a higher proportion of fibroglandular tissue than people in non-Asian countries, so dense breasts are significantly more common in Asian populations than in European, North American, and African populations (17,19). In China, statistics have shown that more than one third of women have dense breasts, and the incidence of breast cancer is significantly higher than that of nondense breasts (20). MG is the preferred method of screening breasts for cancer, but its sensitivity and specificity are significantly affected by gland density. Because of the overlap between normal breast tissues and lesions, MG reading may miss lesions hidden deep in the breast tissues, or even mistake some overlapping tissues artifacts as false positives. It has been reported in the literature that 15–50% of the breast lumps in dense breast tissues palpable during physical examination cannot be displayed on MG (21). Typically, the denser the breast, the lower the detection rate of breast cancer by reading MG (22,23). Even the widely used full-field digital mammography that demonstrates poor resolution on the structure of dense breast tissues may lead to easy miss of deep lesions or lesions under the axilla (24,25). Past research has shown that 50% of the lesions in dense breast tissues cannot be displayed clearly on full-field digital mammography (26). Digital breast tomosynthesis is available for breast screening and can increase the cancer detection rate. However, additional cancer detection rates still are lower than demonstrated by MRI (27). Because of its ability to produce high-resolution images, MRI has become another important modality for early detection of breast cancer, especially for high-risk women (11). It is often used after MG. Not affected by breast density, MRI with multiparameter and multidirectional imaging clearly shows the morphology of the lesions, internal features, and surrounding structures, thereby allowing better lesion detection. It is particularly effective in the detection of tiny hidden nodules in the breast tissues. Berg et al. have shown that, even in patients found to be negative under MG and ultrasonography (US), MRI can still detect an additional 15 per 1000 cases of breast cancer (28). 4
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DCE-MRI is the most commonly used MRI technology for breast cancer diagnosis. It is highly sensitive and specific (10,29). Digital subtraction imaging can remove the interference signals caused by the fat and increase the contrast between the lesion and its surrounding tissues. MIP can clearly display surrounding distorted large vessels and abnormally proliferated small blood vessels. In this way, DCE-MRI enables accurately localizing the lesions from both morphologic and hemodynamic aspects. However, it takes a long time to perform a conventional DCE-MRI scan, typically requiring at least five to eight dynamic phases, and to process the time-signal intensity curve images. In addition, high costs and other issues restrict the wide use of MRI in breast screening. Moore et al. used the Markov model to compare the cost-effectiveness of MRI to that of MG (30). The results showed that, although breast MRI has many advantages, it is not cost-effective. In DCE-MRI, when the positive contrast agent GdDTPA passes over the tumor tissue the first time, the signal intensity increases, reflecting the abundant tumor blood supply and high vascular permeability. Therefore, the enhanced contrast between the breast lesions and normal breast parenchyma during the early stages is particularly important for breast cancer diagnosis (31). Kuhl et al. argued that the images created during the early arterial phase after contrast injection are the most suitable for visual enhancement of breast cancer, and images created during other phases are mainly used to observe the structural features after the injection of contrasting agent, and showed that FAST and subsequent MIP are better for breast cancer screening than other methods (12). In the present study, FAST + MIP images of the 478 dense breast cases were reviewed, and 15 of 16 breast cancer cases were detected, with a high sensitivity rate (93.8%) and negative predictive value (99.8%) with statistical significance. The ROC curves also showed that AP, a time-saving protocol, demonstrated no significant differences from FDP, a more lengthy program, not to mention that it is more time-consuming to review all FDP images than AP images. Our results also showed that the specificity of AP-based breast cancer detection was less pronounced than that of FDPbased. It is because FDP images taken during other phases can demonstrate more prominent structural features during postlesion enhancement, providing the corresponding strengthening curve. This indicates that the AP-based screening method may not work for clinical diagnosis or differential diagnosis. In addition, several benign lesions were incorrectly found using AP, and the false-positive diagnoses may lead to high indirect costs (eg, US, biopsy, or short-term follow-up was performed). However, AP still enables a significant detection rate for patients with negative MG. Because AP requires significantly less examination time, it can screen more patients during the same period and save cost. These features may play an important role in further promoting MRI in breast screening. Breast cancer is one of the few cancers for which mortality can be reduced by cancer screening, so experts in the field are committed to addressing early detection of breast cancer,
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although controversies still exist regarding breast cancer screening technology and platforms. US can improve the detection rate of breast cancer. Varga et al. had proposed to combine US and MG, which are the two pillars of modern breast cancer detection (32). However, the false-positive rate of US is still significantly higher than that of MRI (28). MG performance is poor for imaging of dense glands, and excessive repeated MG leads to radiation damage and higher costs, thereby reducing the cost-benefit ratio. The U.S. Preventive Services Task Force published new breast cancer screening recommendations in Annals of Internal Medicine in November 2009, in which they no longer recommended MG screening every 1~2 years for women aged 40~49 years but instead recommended MG screening every 2 years for women aged 50~74 (33). For younger women, especially those with dense breasts, MRI AP may be a more appropriate screening protocol. Of course, extensive use of AP for breast screening still needs further clinical study. CONCLUSION We suggest that breast density should be classified based on gland density after the initial MG screening. For abundant and dense glands, the AP of MRI should be recommended to help improve the detection rate of breast cancer and costeffectiveness of screening programs. REFERENCES 1. Aberle DR, Chiles C, Gatsonis C, et al. Imaging and cancer: research strategy of the American College of Radiology Imaging Network. Radiology 2005; 235:741–751. 2. Jemal A, Siegel R, Xu J, et al. Cancer statistics, 2010. CA Cancer J Clin 2010; 60:277–300. 3. Game JP, Aspegren K, Balldin G, et al. Increasing incidence of and declining mortality from breast carcinoma. Trends in Malmö, Sweden, 1961– 1992. Cancer 1997; 79:69–74. 4. Graf O, Berg WA, Sickle EA. Large rodlike calcifications at mammography: analysis of morphologic features. AJR Am J Roentgenol 2013; 200:299–303. 5. Pollán M, Ascunce N, Ederra M, et al. Mammographic density and risk of breast cancer according to tumor characteristics and mode of detection: a Spanish population-based case-control study. Breast Cancer Res 2013; 15:R9. 6. Boyd NF, Guo H, Martin LJ, et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med 2007; 356:227–236. 7. McCormack VA, dos Santos Silva I. Breast density and parenchymal as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev 2006; 15:1159–1169. 8. Mendelson MT, Oestreicher N, Porter PL, et al. Breast density as a predictor of mammographic detection: comparison of interval- and screendetected cancers. J Natl Cancer Inst 2000; 92:1081–1087. 9. Oeffinger KC, Fontham ET, Etzioni R, et al. Breast cancer screening for women at average risk: 2015 guideline update from the American Cancer Society. JAMA 2015; 314:1599–1614. 10. Harnett A, Smallwood J, Titshall V, et al. Diagnosis and treatment of early breast cancer, including locally advanced disease-summary of NICE guidance. BMJ 2009; 338:b438.
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