ORIGINAL ARTICLE
The utility of diffusion weighted MRI and apparent
diffusion coefficient in characterization of breast
masses
Moustafa A. Kader A. Wahab
a,*, Hoda Abdel Kareem
b, Ebtesam Esmail Hassan
ca
Department of Radiology, El Minia University, Egypt
b
Department of Radiology, South Vally University, Egypt
c
Public Health and Preventive Medicine, El Minia University, Egypt Received 18 March 2015; accepted 23 June 2015
Available online 10 July 2015
KEYWORDS DW-MRI;
ADC map and value; Breast masses
Abstract Purpose: This study aimed to emphasize the value of DW-MRI, ADC values in differentiation of various breast masses.
Patients and methods: Between ‘‘June 2013 to January 2015’’, 50 consecutive patients with suspi-cious breast lesions underwent DW-MRI and ADC with the measurement of ADC values. All patients were examined with 1.5 Tesla MRI machine using breast coil. The images were obtained with b-values 0 and 750 s/mm2. The ADC values were calculated for breast lesions and axillary
LNs. The results were correlated with the histopathology results which were taken as gold standard. Results: In the studied 50 lesions, 20 were benign and 30 were malignant. The most frequent benign lesion was fibroadenoma (16%) and the most frequent malignant lesion was invasive duct carci-noma (36%). The mean ADC value for benign lesions was 1.6 ± 0.33· 10 3mm2/s while the mean ADC value for malignant lesions was 0.84 ± 0.25· 10 3
mm2/s. The ROC curve showed that the best ADC cut-off value between benign and malignant lesions was 1.02· 10 3
mm2/s with sensitiv-ity, specificsensitiv-ity, PPV, NPV and accuracy of 90%, 95%, 100%, 90.4% and 92% respectively. Conclusion: DW-MRI with ADC values measurement was considered a useful tool for accurate differentiation of various breast masses.
2015 The Authors. The Egyptian Society of Radiology and Nuclear Medicine. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction
Breast cancer is one of the leading causes of death from cancer in women(1). Methods such as X-ray mammography, ultra-sound and physical examination are often limited in sensitivity and specificity, especially in young women. MRI is being increasingly used for preoperative local staging, localization of multiple lesions and screening of high-risk patients (2).
* Corresponding author at: Department of Radiology, El Minia University, El Minia, Egypt. Tel.: +20 01123850453.
E-mail address:[email protected](M.A.K.A. Wahab). Peer review under responsibility of Egyptian Society of Radiology and Nuclear Medicine.
Egyptian Society of Radiology and Nuclear Medicine
The Egyptian Journal of Radiology and Nuclear Medicine
www.elsevier.com/locate/ejrnm
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http://dx.doi.org/10.1016/j.ejrnm.2015.06.016
0378-603X 2015 The Authors. The Egyptian Society of Radiology and Nuclear Medicine. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Breast MRI, as a different diagnostic tool from mammogra-phy and ultrasonogramammogra-phy (US), can show tissue perfusion characteristics of the masses on breast parenchyma, as well as morphologic features, such as the contour, size, and shape of the breast lesions. Although conventional MRI sequences have an important role in the differential diagnosis of breast masses, this technology has a low specificity, and thus requires the support of additional imaging techniques(3–5). Diffusion-Weighted MRI (DW-MRI) is an active field of research in MRI. In addition to diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) maps can be created and quantitative measurements can be performed. DW-MRI provides physiologic information about the movement of water in normal versus pathological tissue. The quantitative measure of DWI (ADC value) has been reported to be inver-sely correlated with tissue cellular density(6–9).
The aim of this study was to evaluate the role of DW-MRI and ADC values in the differentiation of various breast lesions.
2. Patients and methods 2.1. Patients
This study was approved by the ethics committee of our institutions during the period between ‘‘June 2013 to January 2015’’. It included 50 consecutive female patients with a suspi-cious breast mass diagnosed with mammography or US and considered for a biopsy procedure. The ages of the patients ranged from 28 to 71 years (median ± 49 years). Written informed consent was obtained from each patient.
2.2. Inclusion criteria
Any suspicious lesion on mammography or US according to Breast Imaging-Reporting and Data System (BI-RADS) crite-ria and who were recommended for biopsy procedure were included in the study.
2.3. Exclusion criteria
The patients who had general contraindications for MRI examination and contrast-medium injections, patients who rejected MR examination, patients who had noisy or non-diagnostic DWI examinations due to motion artifacts and patients who refused to undergo a biopsy were excluded from the study.
2.4. The gold standard
All patients had MRI prior to the biopsy procedure. DWI and ADC values were compared with the histopathology results, which were taken as gold standard.
2.5. MRI protocol and technique
All MRIs were obtained using 1.5 Tesla superconducting unit (Toshiba Medical systems corporation, 1385, Shimoishi Gami, Otawara-Shi, Tochigi-Ken, Japan) with eight-channel CP breast Array coil. Conventional sequences of routine breast
MRI were performed for all patients, including axial fat-suppressed T2-weighted (TR/TE, 2500/60 ms; slice thickness 3 mm and matrix 340· 512), axial T1-weighted (TR/TE, 500/15 ms), axial STIR (TR/TE, 6500/84), fat saturation sequence (TR/TE, 4300/80) and contrast-enhanced three-dimensional dynamic fat-suppressed axial T1-weighted (TR/TE 4.4/1.6 ms and slice thickness 1 mm). One pre-contrast sequence was followed by six post-pre-contrast sequences for the dynamic contrast-enhanced images. Gad-DETPA (gadolinium-Diethylene triamine penta-acetic acid) was used as contrast media. The contrast media were given intra-venously over 20 s by an automatic MR-compatible injector. The doses were 0.2 mmol/kg (maximum dose 15 mmol).
The DWIs that formed the basis of our study were performed prior to contrast-enhanced examination. The DW-MRI sequences were performed with a two-dimensional echo-planar imaging (EPI) sequence (TR/TE, 8200/95 ms and slice thickness 3.5 mm) in the axial plane. The ADC map images were created automatically by the system at two different b values (b = 0 and 750 s/mm2).
2.6. Lesion assessment
All the lesions were evaluated by one radiologist according to size, location, shape, signal intensity and contrast enhance-ment patterns. The DW-MRIs were analyzed to observe any restriction of diffusion in the lesions, and the ADC maps were used for ADC value measurements. Each lesion was evaluated on T1, T2-weighted, STIR, fat saturation and contrast-enhanced images; the contrast-enhanced part of the lesion was preferred for evaluation on the corresponding DW-MRI; the region of interest (ROI) was placed manually on the corresponding area of the ADC map. The ROI was placed in the solid portion of the tumors and necrotic or cystic components were excluded from the measurement area.
2.7. Post-imaging processing
All image analysis were performed by one experienced Radiologist. ADC maps were constructed on a pixel by pixel basis. Multiple ROIs were placed on either the breast lesions or LNs on the ADC map and the average value was recorded. All detected lesions were reviewed for enhancement pattern and type of the time-intensity curve.
2.8. Surgical interference and pathological examination Radical and modified radical mastectomy with LN excision was done for 30 patients that proved pathologically to be malignant while lumpectomy was done for the benign proved lesions. Also radiotherapy and chemotherapy were additional treatment measures for the malignant lesions according to the pathology done after the excision.
2.9. Statistical analysis
Data entry and analysis were done with using the program Statistical Package for the Social Sciences (SPSS). Quantitative data were presented by mean and standard deviation, while qualitative data were presented by frequency
distribution. The ADC values between malignant and benign groups were compared using Student’s t test. The sensitivity, specificity, negative and positive predictive values (PPV) were assessed. Also, the ROC analysis was performed to distinguish between the thresholds ADC values of the benign and malig-nant lesions. P < 0.05 was considered statistically significant. 3. Results
This study included 50 consecutive female patients with 50 breast lumps, the clinical, radiological as well as pathological findings, all were represented in tables and statistical forms. 3.1. Histopathological diagnosis
Of the 50 lesions, 20 were benign; the most frequent of them was fibroadenoma (8/20), followed by intra-ductal papilloma (5/20), fat necrosis, fibrocystic changes and atypical ductal hyperplasia (2/20 for each) and the least frequent was granulo-matous mastitis (1/20). Thirty lesions were malignant; invasive duct carcinoma was the most frequent (18/30), followed by ductal carcinoma in-situ (5/30) and the least frequent was medullary carcinoma (3/30) (Table 1).
When using the conventional MRI sequences that were routinely done (T1WI, T2WI, STIR and fat saturation sequences), we found that (25/50) patients were diagnosed benign, (23/50) patients were diagnosed malignant and (2/50) were indeterminate. When correlated with the pathological diagnosis of these patients we found that among the 25 patients that were diagnosed benign by conventional MRI, 6 patients were diagnosed malignant by histopathology. One patient diagnosed malignant by conventional MRI and diag-nosed benign by pathological study. Also, the 2 patients that were indeterminate by MRI proved pathologically to be malignant (p-value was statistically significant 0.001) (Table 2). We measure the ADC values for all lesions and correlated with the pathology of these lesions. We found that the benign lesions had a mean ADC value of 1.6· 10 3
mm2/s and stan-dard of deviation 0.33 mm2/s; while the malignant lesions had
a mean ADC value of 0.84· 10 3
mm2/s and standard of devi-ation 0.25 mm2/s (Table 3).
When we used the DW MRI and ADC values for the evaluation of our patients we found that 21 patients were diag-nosed benign (one of them was diagdiag-nosed pathologically as
malignant). Twenty-seven patients were diagnosed malignant and all were proved pathologically to be malignant. Two patients were indeterminate by DW-MRI and proved patho-logically as one benign and one malignant with evident statis-tically significant P value 0.001 (Table 4).
Considering the ADC receiver operating characteristics curve (ROC curve), we found that the ADC value was diag-nostic for differentiation of breast masses as the area under the curve measured 0.87 ± 0.05 and confidence interval was from 0.77 to 0.96. The cut off value between benign and malig-nant lesions was found to be 1.02 mm2/s with significant P value < 0.001 (Table 5).
As regarding the differentiation of breast lesions, conven-tional MRI had a sensitivity of 73.3%, specificity of 90% with positive predictive value of 95.6%, negative predictive value of 76% and accuracy of 82%. While using the DW-MRI and ADC value had sensitivity of 90%, specificity of 95% with pos-itive predictive value of 100%, negative predictive value of 90.4% and higher accuracy for breast lesion differentiation that reached 92% (Table 6).
4. Discussion
DWI reflects changes in water molecule mobility caused by alterations of the tissue environment due to a pathological pro-cess. Therefore, measurement of the motion of water molecules can provide an additional feature that may further increase the specificity of the MRI classification of breast masses. Also, the measurement of the apparent diffusion coefficient plays a sig-nificant adjuvant role with DW-MRI in the differentiation of breast lesions as there is a direct relationship between ADC values and tumor cellular structure(10–13).
In this study we found that the invasive duct carcinoma was the most frequent malignant breast lesion and the fibroade-noma was the most frequent benign breast lesion. This was also stated on recent study by Sahin and Aribal(14). Also, this was proved by Blackledge et al.,(3)(Table 1) (Figs. 1–4).
Considering the ADC values we found that the high values were more toward benign lesions while the lower values were toward the malignant nature of the lesions. The mean ADC value for benign lesions was 1.60· 10 3
mm2/s with the stan-dard of deviation 0.33· 10 3mm2/s. While the mean ADC value for malignant lesions was 0.84· 10 3
mm2/s with the standard of deviation 0.25· 10 3
mm2/s with statistically significant P value 0.001 (Table 3). The ROC curve showed that, the cut off value for differentiation between benign and malignant lesions was 1.02· 10 3mm2/s and so that any
breast lesion with ADC value equal to or less than
Table 1 Histopathological types of breast lesions (n = 50).
Diagnosis Pathological type No % Benign (n = 20) Fibroadenoma 8 16
Intra-ductal papilloma 5 10 Fat necrosis 2 4 Fibrocystic changes 2 4 Atypical ductal hyperplasia 2 4 Granulomatous mastitis 1 2 Malignant (n = 30) Invasive duct carcinoma 18 36 Ductal carcinoma in-situ 5 10 Invasive tubular carcinoma 4 8 Medullary carcinoma 3 6
Total 50 100
Table 2 Correlation of conventional MRI findings to the histopathology in studied patients (n = 50).
Conventional MRI Pathology P Benign Malignant N= 20 N= 30
Benign (n = 25) 19(76%) 6(24%) 0.001* Malignant (n = 23) 1(4.3%) 22(95.7%)
Indeterminate (n = 2) 0 2(100%)
1.02· 10 3mm2/s, it should be considered malignant while any breast lesion with ADC value more than 1.02· 10 3
mm2/s, should be considered benign. Fernanda et al. (9) stated that the mean ADC values obtained from malignant lesions were 0.68–1.25 ± 0.25 with standard devia-tion 0.25–0.28· 10 3mm2/s while that observed from benign lesions 1.44–1.77 ± 0.31 with standard deviation 0.44· 10 3mm2/s. Also, Imamura et al. (15), reported that the most feasible ADC value to depict malignant lesions was found to be less than 1.10· 10 3mm2/s (seeFig. 5).
Yoshikawa et al.(16)reported that the use of small b values increased the accuracy of differentiation between benign and malignant lesions. This was in contrast to Sinha and Sinha (17) that postulated, the use of high b-values decreased the SNR. Fernanda et al. (9) found that the use of 0 and 750 b-values combination was the most appropriate and we followed this protocol on this study. It was reported that the
DW-MRI with high b-values was more reliable in differentiat-ing between breast lesions, though signal loss more severe (3, 5 and 7). Bogner et al.,(18)reported that using variable b-values did not provide an advantage and reported ideal b-value as 850 s/mm2.
Correlating the results of conventional MRI with the pathological results, 25 lesions were diagnosed benign by MRI, 6 of them diagnosed pathologically malignant. On the other hand, 23 patients were diagnosed by MRI malignant, one of them was proved pathologically as benign. The other 2 lesions were in-determinate by conventional MRI and proved pathologically as malignant. The indeterminate lesions were the lesions that did not fulfil the criteria of either malig-nant or benign lesion, regarding the lesion shape, signal inten-sity, contrast enhancement, diffusion restriction or its ADC value. These results were statistically significant with P value 0.001 (Table 2). Nunes et al.,(19) and Houssami (20) stated that, despite of the high sensitivity of MRI, it showed low specificity ranging from 40% to 80% and there were many overlaps in the imaging findings for benign and malignant lesions. In this research, the sensitivity of conventional MRI
Table 3 The average apparent diffusion coefficient values of the malignant and benign lesions.
Bvalue combination (s/mm2)
ADC values (·10 3mm2/s) P
Benign Malignant
Mean SD Median Mean SD Median
0 and 750 1.60 0.33 1.55 0.84 0.25 0.81 0.001* * Statistically significant P value 0.001.
Table 4 Correlation of DW MRI and ADC values to the histopathology of our patients (n = 50).
DW MRI with ADC value measurement Pathology P Benign N= 20 Malignant N= 30 Benign (n = 21) 19(90.5%) 2(9.5%) 0.001* Malignant (n = 27) 0 27(100%) Indeterminate (n = 2) 1(50%) 1(50%)
* Statistically significant P value 0.001.
Table 5 Analysis of the ADC values of the breast lesions.
Item ADC
Classification variable Diagnose
Sample size 50
Positive group (malignant) 27 Negative group (benign and indeterminate) 23 Area under the ROC curve 0.87 ± 0.05 Confidence interval 0.77–0.96 P(area) <0.001 ROC: Receiver Operating Characteristics.
Table 6 Comparison between conventional MRI and DW-MRI with ADC value measurements in diagnosis of breast lesions.
MRI Sensitivity (%) Specificity (%) PPV (%) NPV (%) Accuracy (%)
Conventional 73.3 90 95.6 76 82
DW MRI with ADC value measurement. 90 95 100 90.4 92 Note: PPV = positive predictive value, NPV = negative predictive value.
Fig. 1 A receiver operating characteristic (ROC curve) analysis for the ADC values to differentiate various breast lesions.
Fig. 2 Female patient 58-year old complaining of Lt. breast swelling: Axial T1WI (A) revealed that a well-defined 37· 20 mm sized retro-areolar hypointense signal lesion. Fat saturation post Gad (B), the lesion appeared more defined with moderate heterogeneous enhancement and a Lt. axillary similar lesion is seen 32· 20 mm in size (C). On drawing the time intensity curve for the breast lesion, type I curve was resulted showing rapid enhancement and rapid wash out (D and D1). DWI at 0 and 750 b-values showed non-homogenous restriction of the lesion (E&E1) as well as the Lt. axillary lesion (F&F1) both lesions showed hyposignals on ADC map (E2 & F2). On measuring the mean ADC value for the breast lesion was found to be 0.854· 10 3mm2/s and that for the axillary lesion was found to be 0.781· 10 3mm2/s. Pathological diagnosis was medullary carcinoma.
Fig. 3 Female patient 35-year old complaining of Rt. breast mass: Axial T1 fat saturation (A) revealed 70· 34.5 mm sized mid-portion Rt. breast lesion that take heterogeneous enhancement after Gad injection (B). On drawing time intensity curve for this breast lesion, type II plateau curve was noted (C). DWI (D) revealed heterogeneous restriction on the Rt. breast lesion and appearance of Rt. axillary restricted lesion. On (D1) measuring the mean ADC value for the breast lesion 0.868· 10 3mm2/s and for the axillary lesion was found to be 1.104· 10 3
mm2/s. On (E & E1) DWI on 0 and 750 b-values revealed a restricted lesion on Rt. breast with mean ADC value 0.865· 10 3
Fig. 4 Female patient 55-year old presented by Rt. breast mass: Non-contrast axial T1 (A), revealed a 30· 25 mm sized lesion on Rt. breast at 10 & 11 O’clock displaying hypo signals and on T2WI (B), the lesion was seen heterogeneous hyper-intense. On post contrast axial T1WI (C), the lesion takes moderate heterogeneous enhancement. On plotting the time intensity curve, type III benign curve was seen. DWI at 0 and 750 b-values (E & E1), revealed hyper-intense lesion on Rt. breast that also noted hyper-intense on ADC map (G) denoting false restriction (T2 shinne through) and its ADC value was 1.851· 10 3
mm2/s. Pathological diagnosis was granulomatous mastitis.
in breast lesions differentiation was found to be 73.3%, and its specificity 90%, PPV 95.6%, NPV 76% with accuracy of 82% (Table 6). This was stated by Kim. et al.,(21).
Correlating the results of DW-MRI and ADC values with the pathological results, we found that 21 lesions diagnosed
benign by DW-MRI, 2 of them proved pathologically as malignant. On the other hand 27 lesions diagnosed as malig-nant by DW-MRI and all proved to be maligmalig-nant by histopathology. The remaining 2 lesions that were in-determinate by DW-MRI proved pathologically as one benign
Fig. 5 Female patient 20-year old presented by Rt. breast palpable mass: Axial T1W fat saturation (A) revealed 6.93· 5.86 cm sized lesion involving most of the Rt. breast parenchyma displaying hypointense signals. After Gad injection, the lesion takes patchy enhancement on (A1) and the enhancement increased gradually as in (A2). When plotting the time intensity curve and put the cursor on the region of interest (ROI) as in (B), type III pattern is identified as in (B1). DWI on 0 (c) and 750 b-value (C1), the lesion showed slight restriction on (C) and no significant restriction identified on (C1). ADC map (D) revealed non-homogenous hypersignals and measurement of the mean ADC value was 2.064· 10 3
mm2/s on (D1) and 1.812· 10 3
mm2/s (D2). Pathological diagnosis was intra-ductal papilloma.
and one malignant lesion. Marini et al.,(10)reported that the use of DW-MRI in differentiating between malignant and benign breast lesions had a sensitivity ranged from 81% to 93% and specificity from 80% to 88.5%; this was nearly stated by Yabouuchi et al.,(22)and Park et al.(23). In this study sen-sitivity of DW-MRI with ADC values in the differential diag-nosis of breast lesions reached 90% with specificity of 95%, PPV of 100%, NPV of 90.4 and accuracy of 92%.
Liu et al.,(24) postulated that the addition of DWI with measurements of ADC values to the conventional MRI, improved the detection and differentiation of various breast lesions. Hetta(25)stated that the use of DWI combined with breast MRI improved the detection and differentiation of breast lesions with sensitivity, specificity, PPV, NPV and accu-racy of 85%, 93.33%, 94.4%, 82.4% and 90.3% respectively. 5. Conclusion
According to the results of this study we concluded that the addition of DW-MRI and ADC value measurements to the conventional MRI of the breast increased the accuracy of diag-nosis and characterization of different breast masses. Also, the use of DW-MRI with ADC value measurements was found to be a valuable quantitative analysis.
Conflict of interest
All authors have materially participated in the research prepa-ration and agree for the submission.
We have no conflict of interest to declare. Disclosure
No disclosure of funding received for this work from any organization.
Authors’ contribution
All authors have apprised the article and actively contributed to the work
Moustafa A. Kader A. Wahab: Data collection, Image revision and final editing.
Hoda Abdel Kareem: Final editing and revision.
Ebtesam Esmail Hasan: Statistical performance and revision.
References
(1)Siegel R, Ward E, Brawley O, Jemal A. Cancer statistics, 2011: the impact of eliminating socioeconomic and racial disparities on premature cancer deaths. CA Cancer J Clin 2011;61:212–36. (2)Jagannathan NR, Breast MR. NMR Biomed 2009;22:1. (3)Blackledge MD, Leach MO, Collins DJ, Koh DM. Computed
diffusion-weighted MR imaging may improve tumor detection. Radiology 2011;261:573–81.
(4)Kul S, Cansu A, Alhan E, Dinc H, Reis A, Can G. Contrast-enhanced MR angiography of the breast: evaluation of ipsilateral increased vascularity and adjacent vessel sign in the characteri-zation of breast lesions. AJR Am J Roentgenol 2010;195:1250–4. (5)Orguc S, Basara I, Coskun T. Diffusion-weighted MR imaging of the breast: comparison of apparent diffusion coefficient values of
normal breast tissue with benign and malignant breast lesions. Singapore Med J 2012;53:737–43.
(6)El Khouli RH, Jacobs MA, Mezban SD, et al. Diffusion-weighted imaging improves the diagnostic accuracy of conven-tional 3.0-T breast MR imaging. Radiology 2010;256:64–73. (7)Woodhams R, Ramadan S, Stanwell P, et al. Diffusion-weighted
imaging of the breast: principles and clinical applications. Radiographics 2011;31:1059–84.
(8)Koh DM, Collins DJ. Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR 2007;188:1622–35. (9)Pereira Fernanda Philadelpho Arantes, Gabriela Martins, et al. Assessment of breast lesions with diffusion-weighted MRI: comparing the use of different b values. AJR 2009;193(October). (10)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.
(11)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.
(12)Woodhams R, Matsunaga K, Iwabuchi K, et al. Diffusion-weighted 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. Apparent diffusion coefficients of breast tumors: clinical application. Magn Reson Med Sci 2008;1:23–9.
(14)Sahin Cennet, Aribal Erkin. The role of apparent diffusion coefficient values in the differential diagnosis of breast lesions in diffusion-weighted MRI. Diagn Interv Radiol 2013;19:457–62. (15)Imamura T, Isomoto I, Sueyoshi E, et al. Diagnostic
perfor-mance of ADC for non mass like breast lesions on MR imaging. Magn Reson Med Sci 2010;9(4):217–25.
(16)Yoshikawa MI, Ohsumi O, Sugata S, et al. Comparison of breast cancer detection by diffusion weighted magnetic resonance imaging and mammography. Radiat Med 2007;25:218–23. (17)Sinha S, Sinha U. Functional magnetic resonance of human
breast tumors: diffusion and perfusion imaging. Ann N Y Acad Sci 2002;980:95–115.
(18)Bogner W, Gruber S, Pinker K, et al. Dif-fusion-weighted MR for differentiation of breast lesions at 3.0 T: how does selection of diffusion protocols affect diagnosis? Radiology 2009;253:341–51. (19)Nunes LW, Schnall MD, Orel SG. Update of breast MR imaging architectural interpretation model. Radiology 2001;219:484–94. (20)Houssami N, Hayes DF. Review of preoperative magnetic
resonance imaging (MRI) in breast cancer: should MRI be performed on all women with newly diagnosed, early stage breast cancer? CA Cancer J Clin 2009;59:290–302.
(21)Kim Tae Hee, Kang Doo Kyoung, Jung Yong Sik, Kim Ku Sang, yunee Yim. Contralateral enhancing lesions on magnetic reso-nance imaging in patients with breast cancer. J Ultrasound Med 2012;31:903–13.
(22)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.
(23)Park MJ, Cha ES, Kang BJ, Ihn YK, Baik JH. The role of diffusion-weighted imaging and the apparent diffusion coefficient (ADC) values for breast tumors. Korean J Radiol 2007;8:390–6. (24)Liu C, Liang C, Liu Z, et al. Intravoxel incoherent motion (IVIM) in evaluation of breast lesions: comparison with conven-tional DWI. Eur J Radiol 2013;82(12):782–9.
(25)Hetta Walled. Role of diffusion weighted images combined with breast MRI in improving the detection and differentiation of breast lesions. Egypt J Radiol Nucl Med 2015;46:259–70.
