- Email: [email protected]
Diffusion-weighted imaging of breast tumors: Differentiation of benign and malignant tumors
The Egyptian Journal of Radiology and Nuclear Medicine (2011) 42, 93–99
Egyptian Society of Radiology and Nuclear Medicine
The Egyptian Journal of Radiology and Nuclear Medicine www.elsevier.com/locate/ejrnm www.sciencedirect.com
Diffusion-weighted imaging of breast tumors: Differentiation of benign and malignant tumors Ghada K. Gouhar *, El-Sayed H. Zidan Radiodiagnosis Department, Faculty of Medicine, Zagazig University, Sharkia, Egypt Received 6 September 2010; accepted 30 December 2010 Available online 8 March 2011
KEYWORDS DWI; DCE-MRI; Breast tumors
Abstract Objective: The aim of this study was to evaluate the role of diffusion-weighted images (DWI) in the differentiation between benign and malignant breast tumors. Patients and methods: This study included 62 females with focal breast lesions according to mammography or sonomamography. All patients underwent dynamic contrast enhanced MRI (DCEMRI), and DWI of the breast. The mean apparent diffusion coefficient (ADC) values were calculated for all lesions and were correlated with the final histopathological results. The sensitivity and specificity of DWI in the differentiation between benign and malignant breast tumors were calculated. Results: Seventy-eight lesions were detected in the examined 62 patients included in this study. Fifty one lesions were benign and 27 lesions were malignant according to the final histopathological results. (25/27) lesions were correctly diagnosed by ADC as malignant lesions with mean ADC value (0.92 ± 0.23 · 10 3 mm2/s) which was significantly lower than the mean ADC value for benign tumors (1.46 ± 0.48 · 10 3 mm2/s) and was correctly diagnosed in (50/51) lesions. The sensitivity and specificity of DWI in the differentiation between benign and malignant breast tumors were 92.6% and 98%, respectively.
* Corresponding author. Tel.: +20 0124038955. E-mail addresses: [email protected] (G.K. Gouhar), sayed. [email protected] (E.-S.H. Zidan). 0378-603X 2011 Egyptian Society of Radiology and Nuclear Medicine. Production and hosting by Elsevier B.V. All rights reserved. Peer review under responsibility of Egyptian Society of Radiology and Nuclear Medicine. doi:10.1016/j.ejrnm.2011.01.004
Production and hosting by Elsevier
94
G.K. Gouhar, E.-S.H. Zidan
Conclusion: DWI offers a useful method for differentiation of benign and malignant breast lesions with high sensitivity and specificity. Being a short unenhanced scan DWI can be safely added to the standard breast MRI protocol. 2011 Egyptian Society of Radiology and Nuclear Medicine. Production and hosting by Elsevier B.V. All rights reserved.
1. Introduction Dynamic contrast enhanced MRI (DCE-MRI) of the breast has been widely used for the diagnosis and characterization of breast lesions and it is a sensitive breast screening technique for women at risk; also it can accurately delineate the extent of the disease than mammography or sonomamography (1–3). Specific patterns of enhancement known as time-signal intensity curve (kinetic curve) has been proposed (4,5). These patterns are classified as: type (I), persistent enhancement (monotonic increase) and is suggestive of benign breast lesions, type (II), plateau enhancement (constant level) and can be seen in both benign and malignant lesions, type (III), washout enhancement (initial peak followed by an immediate decrease in the signal intensity) and is suggestive of malignant breast lesions (6). DCE-MRI has a sensitivity of about 85–99%, and a lower specificity of about 40–80% in detecting breast lesions; this lowered specificity is believed to be due to menstrual cycle, hormonal replacement therapy and proliferative alterations (7,8). DWI is an unenhanced MRI sequences that measures the mobility of water molecules in vivo which has a potential role in characterizing breast lesions (9,10). The apparent diffusion coefficient (ADC) value is an effective parameter for distinguishing between benign and malignant breast lesions, because tumor cellularity has a significant influence on ADC values (11,12). The high cellular density in the malignant lesions causes restriction of the extracellular matrix, and increased fraction of signal coming from intracellular water, this resulting in a lower ADC values in the malignant lesions (13–15). The aim of this study is to evaluate the role of DWI in differentiating benign from malignant breast lesions.
2. Patients and methods 2.1. Study population A total of 62 women (age range 18–72 years, mean 47 years) who underwent breast MRI due to suspicious breast lesions on mammography (BI-RADS, type 4&5) or sonomamography
Table 1
were included in this study. Purely cystic lesions (with no significant restriction within the lesion could be detected) were excluded from the study. All patients underwent subsequent core needle or surgical biopsy. 2.2. MRI protocol All the MRI studies were performed in a 1.5 T unit (Signa Excite HD; GE Healthcare, Milwaukee, USA), after obtaining prior consent, with a dedicated bilateral 16-channel phased-array breast coil, in which patient entered the magnetic bore head first and lied prone with both breasts freely suspended, Previously to the diffusion-weighted sequence, conventional and dynamic sequences were acquired. 2.3. Images acquisition All series were acquired in oblique axial plan in which long axis is parallel to nipple. Axial, T1-weighted fast spin-echo sequence (TR/TE: 783/10.6/EF,EC:1/1 35.7 kHz, FOV, 35 cm; NEX:2.00; slice thickness, 3.0 mm; interval, 1.0 mm), sagittal, T2-weighted fast spin-echo sequence (TR/TE, 3350/100.3/EF, EC:1/1 31.2khz, FOV, 20 cm, NEX:3.00, slice thickness, 3.0 mm; interval, 1.0 mm). Dynamic MRI was performed by hybrid technique using T1-weighted 3D fast spoiled gradientrecalled echo sequence with parallel image (VIBRANT.GE healthcare), (TR/TE: 5.2/2.5,EC:1/1 50 kHz, FOV, 33 cm; NEX:0.71; slice thickness, 1.8 mm; interval, 10.0 mm), for 5– 7 min after administration of contrast agent (gadolinium dimeglumin; magnivist, Schering, 1 mmol/kg) by power injector at rate of 2 ml/s, followed by a 20 ml isotonic sodium chloride flush. This technique is started by mask phase for good quality of image, subtraction phase during which contrast agent is injected at its last 15 s followed by six phases, each last from 1.20 to 1.30 min. DWI was performed after DCE-MRI acquisition using diffusion-weighted echo planer imaging (EPI) sequence with parallel imaging (ASSET.GE. Healthcare), (TR/TE: 3750/72.6/ EF,EC:1/1 250 kHz, FOV, 33 cm; NEX:16.00; slice thickness, 3.0 mm; interval, 1.0 mm), Diffusion gradient were applied at
Different ADC values for benign, and malignant breast lesions, and normal fibroglandular tissue.
Type of lesions
No. of lesions according to ADC values (n = 78)
ADC values (mean ± SD · 10 mm2/s)
No. of lesions according to final histopathological results (n = 78)
Benign Malignant Fibroglandular tissue
52 26 62*
1.46 ± 0.48 0.92 ± 0.23 1.62 ± 0.27
51 27 _
*
Number of normal examined patients.
Diffusion-weighted imaging of breast tumors
Fig. 1 Forty-five year-old female patient presenting malignant mass in the left breast (invasive ductal carcinoma): delayed enhance-contrast axial T1-WI (A), DWI (b = 1000 s/mm2) in axial plane (B), and apparent diffusion coefficient (ADC) color map in axial plane (C), showed morphology and contrast enhancement of suspicious malignant lesion (arrow), the lesion presents high signal at DWI and low signal at ADC map denoting absence of water molecules and diffuse restriction ADC value = 0.91 · 10 3 mm2/s.
six direction with b = 0 and 1000 mm2/s, and scanning time was 4 min and 8 s. 2.4. Image analysis Each lesion was assessed using the American College of Radiology BI-RADS breast MRI lexicon incorporating morpho-
95
Fig. 2 Twenty-four year-old female patient presented with malignant lesion in the right breast (ductal carcinoma in situ): delayed enhance-contrast axial T1-WI (A), DWI (b = 1000 s/ mm2) in axial plane (B), and apparent diffusion coefficient (ADC) black/white map in axial plane (C), showed morphology and contrast enhancement of suspicious malignant lesion (arrow), it displays hyperintense signal at DWI and hypointense signal at ADC map denoting restriction of water ADC value = 0.89 · 10 3 mm2/s.
logical and kinetic features, then the DCE-MRI&DWI were analyzed retrospectively using a commercial software (Functool; GE Healthcare, Milwaukee, USA), for image post-processing, parametric map generation and ROI enhancement measurement, in most cases, correlation between the initial suspicious DCE-MRI findings and the DWI region of interest (ROI) were performed.
96
G.K. Gouhar, E.-S.H. Zidan
In this maps, lesions that are strongly enhanced, appear red, whereas slowly enhanced appear green, intermediate lesions are orange or yellow. A ROI was defined for each DEC/MRI detected lesion at the corresponding location on the combined DWI series, The signal enhancement ratio (SER) and apparent diffusion coefficient (ADC) values were automatically calculated by placing the ROI well within the confines of the lesion including the area of hyperintensity, when lesion was not hyperintense at DWI, the ROI was drawn at corresponding location and size as reflected on DCE-MRI. In order to achieve standardized conditions for results analysis and avoiding data contamination by adjacent structures, two regions of interest (ROI), with mean area of 61 mm2 (ranging from 40 to 94 mm2), were individually placed on the DCE-MRI or ADC map at the site of the target lesion and the signal enhancement ratio curves (SER) as well as mean ADC was calculated, in which the scanner software provides the mean value within the ROI, which equals the ADC value (multiplied by 10 3). 2.5. Quantification of enhancement The use of ROI temporal-enhancement curves has been strongly highlighted by proponents of dynamic MRM. Three basic curve shapes have been described by Kuhl & Co-investigator (16). Type I is persistently enhancing in which gradual steady enhancement occurs over about 5 min. This has been further classified into type Ia: slowly linearly progressive enhancement, type Ib: slow enhancement with a late plateau that produce a bow-like curve; type II plateau curve, and type III washout curve. 2.6. Statistical analysis Sensitivity and specificity for DWI in differentiating benign from malignant breast lesions were calculated. A P value < 0.05 was considered statistically significant.
3. Results Seventy-eight lesions were detected in the examined 62 patients included in this study. Fifty one lesions were benign and 27 lesions were malignant according to the final histopathological results. According to the ADC values (Table 1) 26 lesions were malignant (Figs. 1 and 2), and showed ADC values in the range of (0.92 ± 0.23 · 10 3 mm2/s). On DCE-MRI two lesions showed type 1 (persistent) curve, four lesions had type 2 (plateau) curve, and 19 lesions had type 3 (washout) curve. One lesion (1/26) had malignant ADC value and type 2 (plateau) curve, however proved to be benign lesion according to final histopathological results. Two lesions were falsely diagnosed as benign ones as these lesions showed a higher ADC values, one lesion had type 3 (washout) curve, and the second (Fig. 4) had type 2 (plateau) curve, these 2 lesions proved to be malignant according to the final results. A total of 52 lesions showed higher ADC values than malignant lesion (Table 1) and were in the range of (1.46 ± 0.48 · 10 3 mm2/s) and were diagnosed as benign lesions (Fig. 3).
Fig. 3 Sixty year-old female patient presented by left breast benign lesion (fibroadenoma): early enhance-contrast axial T1-WI (A), DWI (b = 1000 s/mm2) in axial plane (B), and apparent diffusion coefficient (ADC) black/white map in axial plane (C), showed small lesion of morphology and contrast enhancement of suspicious benign solid lesion (arrow), it displays hyperintense signal at DWI and ADC map denoting absence of restriction. ADC value = 1.42 · 10 3 mm2/s.
On DCE-MRI 41 lesions showed type 1 (persistent) curve, nine lesions had type 2 (plateau) curve, and three lesions had type 3 (washout) curve. The mean ADC values of the normal breast parenchyma were (1.62 ± 0.27 · 10 3 mm2/s).
Diffusion-weighted imaging of breast tumors
97
Fig. 4 Forty year-old female patient presented by large mass at left breast (cystsarcoma phylloid): early enhance-contrast axial T1-WI (A), dynamic enhanced curve (B), DWI (b = 1000 s/mm2) in axial plane (C), and apparent diffusion coefficient (ADC) color map in axial plane (D), showed large lesion of morphology and contrast enhancement of suspicious benign lesion (curved arrow) with cystic changes (straight arrow), however analysis of enhancement curve denotes rapid initial rinsing and a post-initial plateau curve (type II), it displays hyperintense signal at DWI and ADC map denoting absence of restriction. ADC value = 1.27 · 10 3 mm2/s.
The sensitivity, and specificity for DWI in the differentiating benign and malignant breast lesions were 92.6% and 98%, respectively. 4. Discussion DWI provides biologic information that are based on the molecular motion of water caused by the change in the tissue environment due to pathologic process (17). DWI is based on the ‘‘Brownian motion’’ of the molecules. Malignant breast lesions have higher cellularity and lower ADC values than benign lesions (18). So this sequence seems to be useful in differentiating benign and malignant lesions, and in monitoring the response to therapy. Cystic areas or high mucin content within the malignant tumor may show higher ADC values, so erroneously diagnosed as benign lesions (19,20). On the other hand, highly cellular benign lesions may have low ADC values leading to erroneous diagnosis as malignant lesions (21).
In this study the mean ADC value for benign breast lesions was 1.46 ± 0.48 · 10 3 mm/s, and 0.92 ± 0.23 · 10 3 mm/s for malignant breast lesions. The two false negative cases for malignancy presented in this study was due to the presence of cystic areas that were included in the ROI on ADC map leading to false high ADC values. One false positive case for malignancy was due to the high cellular content of the lesion, which was proved by histopathological study. These values agreed with the previous studies (22–26) regarding the mean ADC values in differentiating benign from malignant breast lesions. Previous studies (12,22,23,27,9,10,28,29) showed the sensitivity & specificity of DWI in the differentiation between benign and malignant breast lesions were ranging from 81% to 97%, and from 80% to 100% respectively. Our study agreed with these studies where the sensitivity & specificity were 92.6% and 98%, respectively.
98 DWI has some limitations, it can’t recognize lesions smaller than 1 cm, and therefore the exact localization of ROI on ADC map is difficult leading to the possibility of false sampling from adjacent tissue (21,22). However, a recent study found a low likelihood of cancer in lesions below 5 mm (30). Another limitation is the alteration of the ADC value if cystic or necrotic components were included in the ROI (18). Mi et al. (23) stated in their study that, data from previous studies showed discrepancies in the ADC values along the different b Values; hence they recommend that the ADC value of breast lesions be compared to that of normal fibroglandular tissue. In conclusion, DWI offers a useful method for differentiation between benign and malignant breast lesions with high sensitivity and specificity. The absence of contrast media in DWI reduces the cost of the examination and acts as a problem solving sequence in patients with allergy to contrast media. DWI is a short time screening scan that when added to the standard MRI examination of the breast leads to an increase in the overall accuracy of MRI, hence reducing the number of false positive results and consequently reducing the number of unnecessary biopsies.
References (1) Macura KJ, Ouwerkerk R, Jacobs MA, Bluemke DA. Patterns of enhancement on breast MR images: interpretation and imaging pitfalls. RadioGraphics 2006;26:1719–34. (2) Schnall MD, Rosten S, Englander S, Orel SG, Nunes LW. A combined architectural and kinetic interpretation model for breast MR images. Acad Radiol 2001;8:591–7. (3) Kuhl CK, Schrading S, Leutner CC, et al. Mammography, breast ultrasound, and magnetic resonance imaging for surveillance of women at high familial risk for breast cancer. J Clin Oncol 2005;23:8469–76. (4) Stoutjesdijk MJ, Futterer JJ, Boetes C, van Die LE, Jager G, Barentsz JO. Variability in the description of morphologic and contrast enhancement characteristics of breast lesions on magnetic resonance imaging. Invest Radiol 2005;40:355–62. (5) Jacobs Michael A, Barker Peter B, Ouwerkerk Pedram Argani Ronald, Bhujwalla Zaver M, Bluemke David A. Combined dynamic contrast enhanced breast MR and proton spectroscopic imaging: a feasibility study. J Magn Reson Imaging 2005;21:23–8. (6) El-Khouli Riham H, Macura Katarzyna J, Jacobs Michael A, Khalil Tarek H, Kamel Ihab R, Andrew Dwyer, et al. Dynamic contrast-enhanced MRI of the breast: quantitative method for kinetic curve type assessment. AJR 2009;193:295–300. (7) Wiener JI, Schilling KJ, Adami C, et al. Assessment of suspected breast cancer by MRI: a prospective clinical trial using a combined kinetic and morphologic analysis. AJR 2005;184:878–86. (8) Schnall MD, Blume J, Bluemke DA, et al. Diagnostic architectural and dynamic features at breast MR imaging: multicenter study. Radiology 2006;238:42–53. (9) Guo Y, Cai YQ, Cai ZL, et al. Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging. J Magn Reson Imaging 2002;16:172–8. (10) Rubesova E, Grell AS, De Maertelaer V, Metens T, Chao SL, Lemort M. Quantitative diffusion imaging in breast cancer: a clinical prospective study. J Magn Reson Imaging 2006;24:319–24. (11) Wenkel E, Geppert C, Schulz-Wendtland R, et al. Diffusion weighted imaging in breast MRI: comparison of two different pulse sequences. Acad Radiol 2007;14:1077–83.
G.K. Gouhar, E.-S.H. Zidan (12) Woodhams R, Matsunaga K, Iwabuchi K, et al. Diffusionweighted imaging of malignant breast tumors: the usefulness of apparent diffusion coefficient (ADC) value and ADC-map for the detection of malignant breast tumors and evaluation of cancer extension. J Comput Assist Tomogr 2005;29:644–9. (13) Hatakenaka M, Soeda H, Yabuuchi H, et al. Apparent diffusion coefficients of breast tumors: clinical application. Magn Reson Med Sci 2008;7:23–9. (14) Lyng H, Haraldseth O, Rofstad EK. Measurement of cell density and necrotic fraction in human melanoma xenografts by diffusion weighted magnetic resonance imaging. Magn Reson Med 2000;43:828–36. (15) Partridge Savannah C, DeMartini Wendy B, Kurland Brenda F, Eby Peter R, White Steven W, Lehman Constance D. Quantitative diffusion-weighted imaging as an adjunct to conventional breast MRI for improved positive predictive value. AJR 2009;193:1716–22. (16) Kuhl CK, Mielcareck P, Klaschik S, et al. Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions? Radiology 1999;211:101–10. (17) Pereira Fernanda Philadelpho Arantes, Martins Gabriela, Figueiredo Eduardo, Domingues Marisa Nassar Aidar, Domingues Romeu Cortes, da Fonseca Lea Mirian Barbosa, et al. Assessment of breast lesions with diffusion-weighted MRI: comparing the use of different b values. AJR 2009;193:1030–5. (18) Odoguari F, Cilotti A, Marini C, Moretti M, Mazzotta D, Vaccro A, et al. Role of diffusion-weighted imaging (DWI) in magnetic resonance (MR) of the breast. Italy: University of PISA; 2005. (19) Kawashima M, Tamaki Y, Nonaka T, et al. MR imaging of mucinous carcinoma of the breast. AJR Am J Roentgenol 2002;179:179–83. (20) Hatakenaka M, Soeda H, Yabuuchi H, et al. Apparent diffusion coefficients of breast tumors: clinical application. Magn Reson Med Sci 2008;7:23–9. (21) Pereira Fernanda Philadelpho Arantes, Martins Gabriela, Figueiredo Eduardo, Domingues Marisa Nassar Aidar, Romeu Coˆrtes Domingues, da Fonseca Lea Mirian Barbosa. The use of diffusion-weighted magnetic resonance imaging in the differentiation between benign and malignant breast lesions. Radiol Bras 2009;42(5):283–8. (22) Palle Lalitha, Reddy Balaji. Role of diffusion MRI in characterizing benign and malignant breast lesions. Indian J Radiol Imag 2009;19(4):287–90. (23) Park Mi Jung, Cha Eun Suk, Kang Bong Joo, Ihn Yon Kwon, Baik Jun Hyun. The role of diffusion-weighted imaging and the apparent diffusion coefficient(ADC) values for breast tumors. Korean J Radiol 2007;8:390–6. (24) Stadlbauer Andreas, Bernt Reinhard, Gruber Stephan, Bogner Wolfgang, Pinker Katja, van der Riet Wilma, Haller J, et al. Diffusion-weighted MR imaging with background body signal suppression (DWIBS) for the diagnosis of malignant and benign breast lesions. Eur Radiol 2009;19:2349–56. (25) Bogner Wolfgang, Gruber Stephan, Pinker Katja, Grabner Gu¨nther, Stadlbauer Andreas, Weber Michael, et al. Diffusionweighted MR for differentiation of breast lesions at 3.0 T: how does selection of diffusion protocols affect diagnosis? Radiology 2009;253:341–51. (26) Yili Z, Xiaoyan H, Hongwen D, Yun Z, Xin C, Peng W, et al. The value of diffusion weighted imaging in assessing changes of tissues adjacent to breast carcinoma. BMC Cancer 2009;9:18. (27) Marini C, Iacconi C, Giannelli M, Cilotti A, Moretti M, Bartolozzi C. Quantitative diffusion weighted MR imaging in the differential diagnosis of breast lesion. Eur Radiol 2007;17:2646–55. (28) Kuroki Y, Nasu K, Kuroki S, et al. Diffusion weighted imaging of breast cancer with the sensitivity encoding technique: analysis of the apparent diffusion coefficient value. Magn Reson Med Sci 2004;3:79–85.
Diffusion-weighted imaging of breast tumors (29) Yabuuchi H, Matsuo Y, Okafuji T, et al. Enhanced mass on contrast-enhanced breast MR imaging: lesion characterization using combination of dynamic contrast-enhanced and diffusion weighted MR images. J Magn Reson Imaging 2008;28:1157–65. (30) Baltzer PAT, Renz DM, Errmann K-H, Dietzel M, Krumbein I, Gajda M, et al. Diffusion-weighted imaging (DWI) in MR
99 mammography (MRM): clinical comparison of echo planar imaging (EPI) and half-Fourier single-shot turbo spin echo (HASTE) diffusion techniques. Eur Radiol 2009;19:1612–20.
Egyptian Society of Radiology and Nuclear Medicine
The Egyptian Journal of Radiology and Nuclear Medicine www.elsevier.com/locate/ejrnm www.sciencedirect.com
Diffusion-weighted imaging of breast tumors: Differentiation of benign and malignant tumors Ghada K. Gouhar *, El-Sayed H. Zidan Radiodiagnosis Department, Faculty of Medicine, Zagazig University, Sharkia, Egypt Received 6 September 2010; accepted 30 December 2010 Available online 8 March 2011
KEYWORDS DWI; DCE-MRI; Breast tumors
Abstract Objective: The aim of this study was to evaluate the role of diffusion-weighted images (DWI) in the differentiation between benign and malignant breast tumors. Patients and methods: This study included 62 females with focal breast lesions according to mammography or sonomamography. All patients underwent dynamic contrast enhanced MRI (DCEMRI), and DWI of the breast. The mean apparent diffusion coefficient (ADC) values were calculated for all lesions and were correlated with the final histopathological results. The sensitivity and specificity of DWI in the differentiation between benign and malignant breast tumors were calculated. Results: Seventy-eight lesions were detected in the examined 62 patients included in this study. Fifty one lesions were benign and 27 lesions were malignant according to the final histopathological results. (25/27) lesions were correctly diagnosed by ADC as malignant lesions with mean ADC value (0.92 ± 0.23 · 10 3 mm2/s) which was significantly lower than the mean ADC value for benign tumors (1.46 ± 0.48 · 10 3 mm2/s) and was correctly diagnosed in (50/51) lesions. The sensitivity and specificity of DWI in the differentiation between benign and malignant breast tumors were 92.6% and 98%, respectively.
* Corresponding author. Tel.: +20 0124038955. E-mail addresses: [email protected] (G.K. Gouhar), sayed. [email protected] (E.-S.H. Zidan). 0378-603X 2011 Egyptian Society of Radiology and Nuclear Medicine. Production and hosting by Elsevier B.V. All rights reserved. Peer review under responsibility of Egyptian Society of Radiology and Nuclear Medicine. doi:10.1016/j.ejrnm.2011.01.004
Production and hosting by Elsevier
94
G.K. Gouhar, E.-S.H. Zidan
Conclusion: DWI offers a useful method for differentiation of benign and malignant breast lesions with high sensitivity and specificity. Being a short unenhanced scan DWI can be safely added to the standard breast MRI protocol. 2011 Egyptian Society of Radiology and Nuclear Medicine. Production and hosting by Elsevier B.V. All rights reserved.
1. Introduction Dynamic contrast enhanced MRI (DCE-MRI) of the breast has been widely used for the diagnosis and characterization of breast lesions and it is a sensitive breast screening technique for women at risk; also it can accurately delineate the extent of the disease than mammography or sonomamography (1–3). Specific patterns of enhancement known as time-signal intensity curve (kinetic curve) has been proposed (4,5). These patterns are classified as: type (I), persistent enhancement (monotonic increase) and is suggestive of benign breast lesions, type (II), plateau enhancement (constant level) and can be seen in both benign and malignant lesions, type (III), washout enhancement (initial peak followed by an immediate decrease in the signal intensity) and is suggestive of malignant breast lesions (6). DCE-MRI has a sensitivity of about 85–99%, and a lower specificity of about 40–80% in detecting breast lesions; this lowered specificity is believed to be due to menstrual cycle, hormonal replacement therapy and proliferative alterations (7,8). DWI is an unenhanced MRI sequences that measures the mobility of water molecules in vivo which has a potential role in characterizing breast lesions (9,10). The apparent diffusion coefficient (ADC) value is an effective parameter for distinguishing between benign and malignant breast lesions, because tumor cellularity has a significant influence on ADC values (11,12). The high cellular density in the malignant lesions causes restriction of the extracellular matrix, and increased fraction of signal coming from intracellular water, this resulting in a lower ADC values in the malignant lesions (13–15). The aim of this study is to evaluate the role of DWI in differentiating benign from malignant breast lesions.
2. Patients and methods 2.1. Study population A total of 62 women (age range 18–72 years, mean 47 years) who underwent breast MRI due to suspicious breast lesions on mammography (BI-RADS, type 4&5) or sonomamography
Table 1
were included in this study. Purely cystic lesions (with no significant restriction within the lesion could be detected) were excluded from the study. All patients underwent subsequent core needle or surgical biopsy. 2.2. MRI protocol All the MRI studies were performed in a 1.5 T unit (Signa Excite HD; GE Healthcare, Milwaukee, USA), after obtaining prior consent, with a dedicated bilateral 16-channel phased-array breast coil, in which patient entered the magnetic bore head first and lied prone with both breasts freely suspended, Previously to the diffusion-weighted sequence, conventional and dynamic sequences were acquired. 2.3. Images acquisition All series were acquired in oblique axial plan in which long axis is parallel to nipple. Axial, T1-weighted fast spin-echo sequence (TR/TE: 783/10.6/EF,EC:1/1 35.7 kHz, FOV, 35 cm; NEX:2.00; slice thickness, 3.0 mm; interval, 1.0 mm), sagittal, T2-weighted fast spin-echo sequence (TR/TE, 3350/100.3/EF, EC:1/1 31.2khz, FOV, 20 cm, NEX:3.00, slice thickness, 3.0 mm; interval, 1.0 mm). Dynamic MRI was performed by hybrid technique using T1-weighted 3D fast spoiled gradientrecalled echo sequence with parallel image (VIBRANT.GE healthcare), (TR/TE: 5.2/2.5,EC:1/1 50 kHz, FOV, 33 cm; NEX:0.71; slice thickness, 1.8 mm; interval, 10.0 mm), for 5– 7 min after administration of contrast agent (gadolinium dimeglumin; magnivist, Schering, 1 mmol/kg) by power injector at rate of 2 ml/s, followed by a 20 ml isotonic sodium chloride flush. This technique is started by mask phase for good quality of image, subtraction phase during which contrast agent is injected at its last 15 s followed by six phases, each last from 1.20 to 1.30 min. DWI was performed after DCE-MRI acquisition using diffusion-weighted echo planer imaging (EPI) sequence with parallel imaging (ASSET.GE. Healthcare), (TR/TE: 3750/72.6/ EF,EC:1/1 250 kHz, FOV, 33 cm; NEX:16.00; slice thickness, 3.0 mm; interval, 1.0 mm), Diffusion gradient were applied at
Different ADC values for benign, and malignant breast lesions, and normal fibroglandular tissue.
Type of lesions
No. of lesions according to ADC values (n = 78)
ADC values (mean ± SD · 10 mm2/s)
No. of lesions according to final histopathological results (n = 78)
Benign Malignant Fibroglandular tissue
52 26 62*
1.46 ± 0.48 0.92 ± 0.23 1.62 ± 0.27
51 27 _
*
Number of normal examined patients.
Diffusion-weighted imaging of breast tumors
Fig. 1 Forty-five year-old female patient presenting malignant mass in the left breast (invasive ductal carcinoma): delayed enhance-contrast axial T1-WI (A), DWI (b = 1000 s/mm2) in axial plane (B), and apparent diffusion coefficient (ADC) color map in axial plane (C), showed morphology and contrast enhancement of suspicious malignant lesion (arrow), the lesion presents high signal at DWI and low signal at ADC map denoting absence of water molecules and diffuse restriction ADC value = 0.91 · 10 3 mm2/s.
six direction with b = 0 and 1000 mm2/s, and scanning time was 4 min and 8 s. 2.4. Image analysis Each lesion was assessed using the American College of Radiology BI-RADS breast MRI lexicon incorporating morpho-
95
Fig. 2 Twenty-four year-old female patient presented with malignant lesion in the right breast (ductal carcinoma in situ): delayed enhance-contrast axial T1-WI (A), DWI (b = 1000 s/ mm2) in axial plane (B), and apparent diffusion coefficient (ADC) black/white map in axial plane (C), showed morphology and contrast enhancement of suspicious malignant lesion (arrow), it displays hyperintense signal at DWI and hypointense signal at ADC map denoting restriction of water ADC value = 0.89 · 10 3 mm2/s.
logical and kinetic features, then the DCE-MRI&DWI were analyzed retrospectively using a commercial software (Functool; GE Healthcare, Milwaukee, USA), for image post-processing, parametric map generation and ROI enhancement measurement, in most cases, correlation between the initial suspicious DCE-MRI findings and the DWI region of interest (ROI) were performed.
96
G.K. Gouhar, E.-S.H. Zidan
In this maps, lesions that are strongly enhanced, appear red, whereas slowly enhanced appear green, intermediate lesions are orange or yellow. A ROI was defined for each DEC/MRI detected lesion at the corresponding location on the combined DWI series, The signal enhancement ratio (SER) and apparent diffusion coefficient (ADC) values were automatically calculated by placing the ROI well within the confines of the lesion including the area of hyperintensity, when lesion was not hyperintense at DWI, the ROI was drawn at corresponding location and size as reflected on DCE-MRI. In order to achieve standardized conditions for results analysis and avoiding data contamination by adjacent structures, two regions of interest (ROI), with mean area of 61 mm2 (ranging from 40 to 94 mm2), were individually placed on the DCE-MRI or ADC map at the site of the target lesion and the signal enhancement ratio curves (SER) as well as mean ADC was calculated, in which the scanner software provides the mean value within the ROI, which equals the ADC value (multiplied by 10 3). 2.5. Quantification of enhancement The use of ROI temporal-enhancement curves has been strongly highlighted by proponents of dynamic MRM. Three basic curve shapes have been described by Kuhl & Co-investigator (16). Type I is persistently enhancing in which gradual steady enhancement occurs over about 5 min. This has been further classified into type Ia: slowly linearly progressive enhancement, type Ib: slow enhancement with a late plateau that produce a bow-like curve; type II plateau curve, and type III washout curve. 2.6. Statistical analysis Sensitivity and specificity for DWI in differentiating benign from malignant breast lesions were calculated. A P value < 0.05 was considered statistically significant.
3. Results Seventy-eight lesions were detected in the examined 62 patients included in this study. Fifty one lesions were benign and 27 lesions were malignant according to the final histopathological results. According to the ADC values (Table 1) 26 lesions were malignant (Figs. 1 and 2), and showed ADC values in the range of (0.92 ± 0.23 · 10 3 mm2/s). On DCE-MRI two lesions showed type 1 (persistent) curve, four lesions had type 2 (plateau) curve, and 19 lesions had type 3 (washout) curve. One lesion (1/26) had malignant ADC value and type 2 (plateau) curve, however proved to be benign lesion according to final histopathological results. Two lesions were falsely diagnosed as benign ones as these lesions showed a higher ADC values, one lesion had type 3 (washout) curve, and the second (Fig. 4) had type 2 (plateau) curve, these 2 lesions proved to be malignant according to the final results. A total of 52 lesions showed higher ADC values than malignant lesion (Table 1) and were in the range of (1.46 ± 0.48 · 10 3 mm2/s) and were diagnosed as benign lesions (Fig. 3).
Fig. 3 Sixty year-old female patient presented by left breast benign lesion (fibroadenoma): early enhance-contrast axial T1-WI (A), DWI (b = 1000 s/mm2) in axial plane (B), and apparent diffusion coefficient (ADC) black/white map in axial plane (C), showed small lesion of morphology and contrast enhancement of suspicious benign solid lesion (arrow), it displays hyperintense signal at DWI and ADC map denoting absence of restriction. ADC value = 1.42 · 10 3 mm2/s.
On DCE-MRI 41 lesions showed type 1 (persistent) curve, nine lesions had type 2 (plateau) curve, and three lesions had type 3 (washout) curve. The mean ADC values of the normal breast parenchyma were (1.62 ± 0.27 · 10 3 mm2/s).
Diffusion-weighted imaging of breast tumors
97
Fig. 4 Forty year-old female patient presented by large mass at left breast (cystsarcoma phylloid): early enhance-contrast axial T1-WI (A), dynamic enhanced curve (B), DWI (b = 1000 s/mm2) in axial plane (C), and apparent diffusion coefficient (ADC) color map in axial plane (D), showed large lesion of morphology and contrast enhancement of suspicious benign lesion (curved arrow) with cystic changes (straight arrow), however analysis of enhancement curve denotes rapid initial rinsing and a post-initial plateau curve (type II), it displays hyperintense signal at DWI and ADC map denoting absence of restriction. ADC value = 1.27 · 10 3 mm2/s.
The sensitivity, and specificity for DWI in the differentiating benign and malignant breast lesions were 92.6% and 98%, respectively. 4. Discussion DWI provides biologic information that are based on the molecular motion of water caused by the change in the tissue environment due to pathologic process (17). DWI is based on the ‘‘Brownian motion’’ of the molecules. Malignant breast lesions have higher cellularity and lower ADC values than benign lesions (18). So this sequence seems to be useful in differentiating benign and malignant lesions, and in monitoring the response to therapy. Cystic areas or high mucin content within the malignant tumor may show higher ADC values, so erroneously diagnosed as benign lesions (19,20). On the other hand, highly cellular benign lesions may have low ADC values leading to erroneous diagnosis as malignant lesions (21).
In this study the mean ADC value for benign breast lesions was 1.46 ± 0.48 · 10 3 mm/s, and 0.92 ± 0.23 · 10 3 mm/s for malignant breast lesions. The two false negative cases for malignancy presented in this study was due to the presence of cystic areas that were included in the ROI on ADC map leading to false high ADC values. One false positive case for malignancy was due to the high cellular content of the lesion, which was proved by histopathological study. These values agreed with the previous studies (22–26) regarding the mean ADC values in differentiating benign from malignant breast lesions. Previous studies (12,22,23,27,9,10,28,29) showed the sensitivity & specificity of DWI in the differentiation between benign and malignant breast lesions were ranging from 81% to 97%, and from 80% to 100% respectively. Our study agreed with these studies where the sensitivity & specificity were 92.6% and 98%, respectively.
98 DWI has some limitations, it can’t recognize lesions smaller than 1 cm, and therefore the exact localization of ROI on ADC map is difficult leading to the possibility of false sampling from adjacent tissue (21,22). However, a recent study found a low likelihood of cancer in lesions below 5 mm (30). Another limitation is the alteration of the ADC value if cystic or necrotic components were included in the ROI (18). Mi et al. (23) stated in their study that, data from previous studies showed discrepancies in the ADC values along the different b Values; hence they recommend that the ADC value of breast lesions be compared to that of normal fibroglandular tissue. In conclusion, DWI offers a useful method for differentiation between benign and malignant breast lesions with high sensitivity and specificity. The absence of contrast media in DWI reduces the cost of the examination and acts as a problem solving sequence in patients with allergy to contrast media. DWI is a short time screening scan that when added to the standard MRI examination of the breast leads to an increase in the overall accuracy of MRI, hence reducing the number of false positive results and consequently reducing the number of unnecessary biopsies.
References (1) Macura KJ, Ouwerkerk R, Jacobs MA, Bluemke DA. Patterns of enhancement on breast MR images: interpretation and imaging pitfalls. RadioGraphics 2006;26:1719–34. (2) Schnall MD, Rosten S, Englander S, Orel SG, Nunes LW. A combined architectural and kinetic interpretation model for breast MR images. Acad Radiol 2001;8:591–7. (3) Kuhl CK, Schrading S, Leutner CC, et al. Mammography, breast ultrasound, and magnetic resonance imaging for surveillance of women at high familial risk for breast cancer. J Clin Oncol 2005;23:8469–76. (4) Stoutjesdijk MJ, Futterer JJ, Boetes C, van Die LE, Jager G, Barentsz JO. Variability in the description of morphologic and contrast enhancement characteristics of breast lesions on magnetic resonance imaging. Invest Radiol 2005;40:355–62. (5) Jacobs Michael A, Barker Peter B, Ouwerkerk Pedram Argani Ronald, Bhujwalla Zaver M, Bluemke David A. Combined dynamic contrast enhanced breast MR and proton spectroscopic imaging: a feasibility study. J Magn Reson Imaging 2005;21:23–8. (6) El-Khouli Riham H, Macura Katarzyna J, Jacobs Michael A, Khalil Tarek H, Kamel Ihab R, Andrew Dwyer, et al. Dynamic contrast-enhanced MRI of the breast: quantitative method for kinetic curve type assessment. AJR 2009;193:295–300. (7) Wiener JI, Schilling KJ, Adami C, et al. Assessment of suspected breast cancer by MRI: a prospective clinical trial using a combined kinetic and morphologic analysis. AJR 2005;184:878–86. (8) Schnall MD, Blume J, Bluemke DA, et al. Diagnostic architectural and dynamic features at breast MR imaging: multicenter study. Radiology 2006;238:42–53. (9) Guo Y, Cai YQ, Cai ZL, et al. Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging. J Magn Reson Imaging 2002;16:172–8. (10) Rubesova E, Grell AS, De Maertelaer V, Metens T, Chao SL, Lemort M. Quantitative diffusion imaging in breast cancer: a clinical prospective study. J Magn Reson Imaging 2006;24:319–24. (11) Wenkel E, Geppert C, Schulz-Wendtland R, et al. Diffusion weighted imaging in breast MRI: comparison of two different pulse sequences. Acad Radiol 2007;14:1077–83.
G.K. Gouhar, E.-S.H. Zidan (12) Woodhams R, Matsunaga K, Iwabuchi K, et al. Diffusionweighted imaging of malignant breast tumors: the usefulness of apparent diffusion coefficient (ADC) value and ADC-map for the detection of malignant breast tumors and evaluation of cancer extension. J Comput Assist Tomogr 2005;29:644–9. (13) Hatakenaka M, Soeda H, Yabuuchi H, et al. Apparent diffusion coefficients of breast tumors: clinical application. Magn Reson Med Sci 2008;7:23–9. (14) Lyng H, Haraldseth O, Rofstad EK. Measurement of cell density and necrotic fraction in human melanoma xenografts by diffusion weighted magnetic resonance imaging. Magn Reson Med 2000;43:828–36. (15) Partridge Savannah C, DeMartini Wendy B, Kurland Brenda F, Eby Peter R, White Steven W, Lehman Constance D. Quantitative diffusion-weighted imaging as an adjunct to conventional breast MRI for improved positive predictive value. AJR 2009;193:1716–22. (16) Kuhl CK, Mielcareck P, Klaschik S, et al. Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions? Radiology 1999;211:101–10. (17) Pereira Fernanda Philadelpho Arantes, Martins Gabriela, Figueiredo Eduardo, Domingues Marisa Nassar Aidar, Domingues Romeu Cortes, da Fonseca Lea Mirian Barbosa, et al. Assessment of breast lesions with diffusion-weighted MRI: comparing the use of different b values. AJR 2009;193:1030–5. (18) Odoguari F, Cilotti A, Marini C, Moretti M, Mazzotta D, Vaccro A, et al. Role of diffusion-weighted imaging (DWI) in magnetic resonance (MR) of the breast. Italy: University of PISA; 2005. (19) Kawashima M, Tamaki Y, Nonaka T, et al. MR imaging of mucinous carcinoma of the breast. AJR Am J Roentgenol 2002;179:179–83. (20) Hatakenaka M, Soeda H, Yabuuchi H, et al. Apparent diffusion coefficients of breast tumors: clinical application. Magn Reson Med Sci 2008;7:23–9. (21) Pereira Fernanda Philadelpho Arantes, Martins Gabriela, Figueiredo Eduardo, Domingues Marisa Nassar Aidar, Romeu Coˆrtes Domingues, da Fonseca Lea Mirian Barbosa. The use of diffusion-weighted magnetic resonance imaging in the differentiation between benign and malignant breast lesions. Radiol Bras 2009;42(5):283–8. (22) Palle Lalitha, Reddy Balaji. Role of diffusion MRI in characterizing benign and malignant breast lesions. Indian J Radiol Imag 2009;19(4):287–90. (23) Park Mi Jung, Cha Eun Suk, Kang Bong Joo, Ihn Yon Kwon, Baik Jun Hyun. The role of diffusion-weighted imaging and the apparent diffusion coefficient(ADC) values for breast tumors. Korean J Radiol 2007;8:390–6. (24) Stadlbauer Andreas, Bernt Reinhard, Gruber Stephan, Bogner Wolfgang, Pinker Katja, van der Riet Wilma, Haller J, et al. Diffusion-weighted MR imaging with background body signal suppression (DWIBS) for the diagnosis of malignant and benign breast lesions. Eur Radiol 2009;19:2349–56. (25) Bogner Wolfgang, Gruber Stephan, Pinker Katja, Grabner Gu¨nther, Stadlbauer Andreas, Weber Michael, et al. Diffusionweighted MR for differentiation of breast lesions at 3.0 T: how does selection of diffusion protocols affect diagnosis? Radiology 2009;253:341–51. (26) Yili Z, Xiaoyan H, Hongwen D, Yun Z, Xin C, Peng W, et al. The value of diffusion weighted imaging in assessing changes of tissues adjacent to breast carcinoma. BMC Cancer 2009;9:18. (27) Marini C, Iacconi C, Giannelli M, Cilotti A, Moretti M, Bartolozzi C. Quantitative diffusion weighted MR imaging in the differential diagnosis of breast lesion. Eur Radiol 2007;17:2646–55. (28) Kuroki Y, Nasu K, Kuroki S, et al. Diffusion weighted imaging of breast cancer with the sensitivity encoding technique: analysis of the apparent diffusion coefficient value. Magn Reson Med Sci 2004;3:79–85.
Diffusion-weighted imaging of breast tumors (29) Yabuuchi H, Matsuo Y, Okafuji T, et al. Enhanced mass on contrast-enhanced breast MR imaging: lesion characterization using combination of dynamic contrast-enhanced and diffusion weighted MR images. J Magn Reson Imaging 2008;28:1157–65. (30) Baltzer PAT, Renz DM, Errmann K-H, Dietzel M, Krumbein I, Gajda M, et al. Diffusion-weighted imaging (DWI) in MR
99 mammography (MRM): clinical comparison of echo planar imaging (EPI) and half-Fourier single-shot turbo spin echo (HASTE) diffusion techniques. Eur Radiol 2009;19:1612–20.