Original Research

Diagnostic Efficacy of the DiffusionWeighted Imaging in the Characterizationof Different Types of Breast Lesions

Sibel Kul, MD,* Ilker Eyuboglu, MD, Aysegul Cansu, MD, and Etem Alhan, MD

Purpose: To evaluate the diagnostic efficacy of quantita-tive Diffusion-weighted imaging (DWI) in the characteriza-tion of breast lesions of mass and non-massenhancement (NME) types.

Materials and Methods: After the institutional reviewboard gave approval, DWI exams of 267 women with 212suspicious masses, 73 NMEs were retrospectively ana-lyzed. Apparent diffusion coefficients (ADCs) of benignand malignant lesions were compared. Cutoff values wereobtained by receiver operating characteristics analysis.Diagnostic accuracies of DWI for masses and NMEs werecompared with the use of Chi-square test. The effect ofthe lesions histologic subtypes and size on diagnosticaccuracies was evaluated.

Results: ADCs were significantly lower in malignantsthan in benigns for both masses (0.75 versus 1.21 � 10�3

mm2/s,) and NMEs (0.79 versus 1.06 � 10�3 mm2/s)(P <

0.001). Cutoff value was 0.90 � 10�3 mm2/s for bothlesion types. The accuracy of DWI was lower in NMEs(76.7%) than masses (89.2%) (P ¼ 0.008) unrelated tolesion size. There was more overlap in ADCs of the benignand malignant NMEs due to the lower ADCs of the benignhistologies of this group.

Conclusion: Despite the lower diagnostic accuracy ofDWI in NMEs, it could be helpful in the characterizationof suspicious breast lesions of both mass and NME types.

Key Words: breast; diffusion-weighted imaging; apparentdiffusion coefficient; mass; non–mass-like enhancementJ. Magn. Reson. Imaging 2014;40:1158–1164.VC 2013 Wiley Periodicals, Inc.

MR imaging is a popular and established adjunctivetechnique to conventional imaging methods for theevaluation of the breast. It is widely used in a varietyof clinical settings, such as local staging in recentlydiagnosed breast cancer patients and screening highrisk women (1–5). As the most proposed breast MR

imaging method, dynamic contrast-enhanced (DCE)imaging has high sensitivity around 89–100% (6–11).However, the limited specificity of the method which isreported to be around 75% (ranging between 19% and95%) in a meta-analysis of 69 studies (12) continuesto be a significant problem, particularly in patientsreferred for the evaluation of inconclusive clinical andimaging findings.

On the other hand, DWI as an alternative methodreflects the molecular characteristics of the tissue bymeasuring the random motion of free water protons.It is available nowadays on most of the commercialMR scanners. It is noninvasive. It does not require theuse of gadolinium and has short scanning time.Quantitative evaluation is possible with the use ofapparent diffusion coefficient (ADC) value and is quiteeasy. It is mainly used in stroke imaging but also hasmany applications in oncologic imaging and can aidin tumor detection and characterization. The effective-ness of the method stems from the inverse correlationbetween the tumor cellularity and the ADC valuewhich is the quantitative measure of the diffusion.Hence, malignant tumors which generally exhibithigher cellularity than benign ones reveal lower ADCs.Thus, we can use this difference in the ADCs for thecharacterization of the tumors (13–18).

The method has been reported to be useful for thecharacterization of the breast tumors. A meta-analysis of 13 studies reported the overall sensitivityand specificity of DWI as 84% and 79%, respectively(19). Most of these studies tested the efficacy of DWIon mass type lesions. However, the efficacy of DWI inthe characterization of non-mass enhancement (NME)lesions is not clear. The purpose of the present studywas to investigate the probable difference in the diag-nostic efficacy of DWI between the breast mass andNME lesions.

MATERIALS AND METHODS

Subjects

We retrospectively reviewed 841 consecutive breastMR examinations performed between August 2008and November 2012, during which time DWI wasapplied as a part of our standard breast MR imaging

Karadeniz Technical University, School of Medicine, Trabzon, Turkey.

*Address reprint requests to: S.K., Karadeniz Technical University,Faculty of Medicine, Department of Radiology, 61080 Trabzon, Tur-key. E-mail: sibel_ozy@yahoo.com

Received April 30, 2013; Accepted September 11, 2013.

DOI 10.1002/jmri.24491View this article online at wileyonlinelibrary.com.

JOURNAL OF MAGNETIC RESONANCE IMAGING 40:1158–1164 (2014)

VC 2013 Wiley Periodicals, Inc. 1158

protocol together with DCE-MR imaging. The indica-tions for MR imaging were mostly preoperative localstaging (%64) and clarification of suspicious conven-tional imaging or clinical findings (%18). The otherswere screening for high risk women (%10), searchingfor residual cancer in the early postoperative period(%5), follow-up after breast conservative surgery (%2)and detection of the occult primary breast cancer(%1).

After the review, suspicious mass and NME lesionswith definitive histologic diagnosis were identified andconstituted the study group. Patients were requirednot to be undergoing neoadjuvant chemotherapy. Focitypes of lesions and cysts were not included. Sixlesions were excluded when index lesion could not belocalized on ADC maps due to misregistration arti-facts. The final study group included 285 suspiciouslesions in 267 women (aged 20–75 years; mean age,45 years). Definite diagnoses were provided either bythe histopathologic examination of the surgicallyexcised or needle biopsied specimens or by at least2-year follow-up with mammography, ultrasound orMR imaging. The approval for the study was takenfrom the local ethical committee.

MR Imaging Protocol

All patients were examined by using a 1.5 Tesla (T)MR unit (Magnetom, Symphony; Siemens Healthcare,Erlangen, Germany) and two-channel dedicated dou-ble breast coil. If it was appropriate, we performedMR imagings during the second week of the menstrualcycle for premenopausal women. Patients were placedin the prone position. The conventional MR imagingprotocol included a non-fat suppressed T2-weightedturbo spin-echo sequence (repetition time/echo time[TR/TE], 4500/97; matrix, 384 � 512; slice thickness,3 mm), a T1-weighted non-fat suppressed sequenceand a T1-weighted fat suppressed dynamic contrast-enhanced sequence with one precontrast and sixpostcontrast acquisitions. T1-weighted imaging wasperformed with three-dimensional (3D) fast low angleshot (FLASH) sequence (TR/TE, 4.3/1.4; flip angle,12

�; field of view, 320 � 320; matrix, 307 � 512; sig-

nal average, 1; slice thickness, 1.5 mm), in the axialplane. Gadobutrol (Gadovist; Shering) of 0.1 mmol/kgbody weight was administered intravenously at a rateof 2 mL/s with a power injector followed by a 20 mLof saline flash for contrast-enhancement. Postcontrastimage acquisition was started immediately at the endof saline injection. Each postcontrast sequence lasted62 s.

Diffusion-weighted images were obtained beforedynamic images. Two-dimensional (2D) spin-echoecho-planar imaging (EPI) sequence (TR/TE, 5400/94; matrix, 192 � 192; signal average, 3; slice thick-ness, 3 mm; distance factor, 20%; acquisition voxelsize: 1.7 � 1.7 � 3 mm; band width, 1370 Hz/Px) inthe axial plane was used. Diffusion gradients in threeorthogonal directions with b-values of 50, 400, and1000 s/mm2 were applied. The apparent diffusioncoefficient (ADC) maps were created automatically by

the system from the trace-weighted images with theuse of all three b values.

Analysis of MR Images

All the MR images were interpreted on a workstation(Leonardo, Siemens Healthcare) by a trained radiolog-ist in breast imaging, with breast MR imaging experi-ence of 8 years (S.K.). During the interpretation,radiologist was blinded to the final diagnoses. Fat-suppressed precontrast images of the dynamic serieswere subtracted from the second series of postcontrastimages to selectively highlight the enhancing struc-tures. Subtracted and T2-weighted images were usedprimarily to identify and localize the sonographically ormammographically defined or incidentally found suspi-cious lesions. The types of the lesions were recorded aseither mass or NME according to BI-RADS assessment.Average tumor diameter measured at axial contrastenhanced or T2-weighted images was defined as lesionsize. ADC values of the lesions were measured on theADC maps from the corresponding locations by usingthe circular region of interest (ROI) with the size of atleast three pixels. Particular attention was paid forplacing the ROI to the solid and mostly enhancing por-tion of the lesion without fatty tissue contamination.At least three measurements were performed for eachlesion and the lowest mean value was selected. TheADCs of the normal fibroglandular tissue were alsomeasured from the contralateral breast, with the useof standard 20 pixels size ROI.

Pathology reports were reviewed to determine thediagnoses and histologic subtypes of the lesions.Malignant lesions were grouped as invasive ductalcarcinoma (IDC), invasive lobular carcinoma (ILC),ductal carcinoma in situ (DCIS), and mucinous can-cers. Other uncommon cancer subtypes were catego-rized as other malignancies. Benign lesions weregrouped as fibroadenoma (FA) and fibrocystic changes(FCC). Epithelial hyperplasia, mastitis, papilloma,fibrosis, apocrine metaplasia and fat necrosis werecombined as a category of other benigns.

Statistical Analysis

ADCs of the benign tumors were compared with ADCsof the malignant tumors for each lesion type by usingindependent samples test for normally distributeddata and Mann Whitney test for not normally distrib-uted data. Receiver operating characteristics (ROC)analyses were used to determine the most effectivecutoff values of ADC for the differentiation of malig-nant from benign in each lesion group. Diagnosticperformances of DWI in the characterization of breastmasses and NMEs for the given cutoff values were cal-culated and accuracies were compared with eachother by using Chi-square test.

ADCs of the benign and malignant tumors for eachlesion type were compared with ADCs of the normalfibroglandular tissue by using the Paired-samples t-test for normally distributed data and Wilcoxonsigned-rank test for not normally distributed data.Mean ADCs were compared between specific benign

Efficacy of Breast DWI Compared for Mass and NME 1159

and malignant histologic subtypes by using analysisof variance (ANOVA) test and post hoc pairwise com-parisons by Turkey HSD tests. To evaluate the rela-tionship between lesion size and ADC values weclassified the lesions into two size groups of equal orless than 15 mm and greater than 15 mm. MeanADCs for benign and malignant lesions in each groupwere calculated and compared with the use of inde-pendent samples test for normally distributed dataand Mann Whitney test for not normally distributeddata. Afterward, the accuracy of DWI in different sizegroups was compared with each other usingChi-square test.

RESULTS

Two hundred sixty-seven women enrolled in the pres-ent study successfully underwent both DCE-MRI andDWI for their suspicious breast findings and had afinal diagnosis for their 285 lesions. Final diagnoseswere provided by histopathologic analysis in 263(92%) and by follow-up in 22 (8%) lesions. Of the 285lesions, 212 (74%) were masses and 73 (26%) wereNMEs. One hundred thirty-three (63%) of the 212masses and 28 (38%) of the 73 NMEs were malignant.The most common malignant diagnosis was IDC inboth groups of lesions. Most common benign diagno-ses were FA in masses and FCC in NMEs.

Mean ADCs of the benign and malignant masseswere 1.21 6 0.36 � 10�3 mm2/s and 0.75 6 0.19 �10�3 mm2/s, respectively. Mean ADCs of the benignand malignant NMEs were 1.06 6 0.24 � 10�3 mm2/sand 0.79 6 0.14 � 10�3 mm2/s, respectively. MeanADC of the normal breast tissue was 1.50 6 0.29 �10�3 mm2/s. Both for mass and NME, the ADCs weresignificantly lower in malignant compared with benignlesions (P < 0.001). In both lesion groups, ADCs ofthe benign and malignant tumors were significantlylower than those of the normal breast tissue (P �0.001) (Fig. 1).

The area under the ROC curve (AUC) was 0.88 (95%confidence interval [CI]: 0.83–0.92) for masses and0.84 (95% CI: 0.74–0.92) for NMEs (Fig. 2). Cutofflevel for ADC derived from the ROC analysis was 0.90� 10�3 mm2/s for both types of lesion. One hundredeighty-nine (89.2%) of the 212 masses (Fig. 3) and 56(76.7%) of the 73 NMEs (Fig. 4) were classified cor-rectly with the use of the ADC cutoff. The resultingdiagnostic performances of DWI for both types oflesions were documented in Table 1. The accuracy ofDWI was significantly higher for masses than forNMEs (89.2% versus 76.7%, P ¼ 0.008). The meanADCs of the malignant NMEs (0.79 � 10�3 mm2/s)was slightly higher than those of the malignantmasses (0.75 � 10�3 mm2/s) (P ¼ 0.067). However,

Figure 1. ADC values of malignant and benign breast lesionsof mass and NME types and normal fibroglandular tissue.ADCs of the benign and malignant tumors were significantlylower than those of the normal breast tissue (P � 0.001)ADCs were significantly lower in malignant compared withbenign lesions for both type of lesions (P < 0.001). However,the difference between the ADCs of the benign and malignantlesions was smaller for NMEs than for masses.

Figure 2. ROC curves for the ADC values of the mass and NME lesions. AUC, which represents the probability that a lesionwill be classified accurately as benign or malignant, was higher for masses (0.88) than for NMEs (0.84). Cutoff ADC value of0.90 provided 95% sensitivity and 80% specificity for masses and 86% sensitivity and 71% specificity for NMEs.

1160 Kul et al.

the mean ADCs of the benign NMEs (1.06 � 10�3

mm2/s) were significantly lower than those of thebenign masses (1.21 � 10�3 mm2/s) (P ¼ 0.005).

Mean ADCs of the histologic subtypes were given inTable 2. Benign subtype with highest ADCs was FA(1.41 � 10�3 mm2/s). In pairwise comparison, FAdemonstrated significantly higher ADC than FCC (P ¼0.022) and other benign histologies—mastitis, papil-loma, epithelial hyperplasia—(P < 0.001) (Fig. 5). FAconstituted 28% of the benign masses and FCC con-stituted 40% of the benign NMEs. Malign subtypeswith lowest ADCs were IDC, ILC and noncategorizedinvasive cancers (0.74 � 10�3 mm2/s). Mucinous car-cinomas demonstrated higher ADCs (1.76 � 10�3

mm2/s) than all other malignancies. In the study, 8(%5) of the 161 malignant lesions were pure ductalcarcinoma in situ (DCIS). They constituted 18% ofmalignant NMEs and 2% of malignant masses. Thedifference between the ADCs of the IDC (0.74 � 10�3

mm2/s) and DCIS (0.83 � 10�3 mm2/s) was not sig-nificant (P ¼ 0.388).

Lesion size was significantly larger in malignantand benign NMEs (33 6 15 mm and 31 6 19 mm)compared with mass counterparts (22 6 14 mm and15 6 9 mm) (P < 0.001). For the masses, the ADC val-ues were independent of size. However, for the NMEs,

Figure 3. Invasive ductal carcinoma in a 39-year-old premenopausal woman. a: Axial postcontrast subtracted image of theleft breast shows a well-marginated, rim enhancing mass of 16 mm in the upper outer quadrant (arrow). b: On ADC map, theenhancing part of the mass had a low ADC value (0.78 � 10�3 mm2/s).

Figure 4. Invasive lobular carcinoma in a 51-year-oldwoman. a: Axial subtracted image of the dynamic studyshows regional, heterogeneous, non-mass enhancement(arrows) of 23 � 52 mm in the outer half of the right breast.b: On ADC map, the lesion had low ADC values (0.69 � 10�3

mm2/s and 0.75 � 10�3 mm2/s).

Table 1

Diagnostic Performances of ADC in the Characterization of Mass

and NME Lesions

Results Mass NME

True-positive* 126 24

True-negative* 63 32

False-positive* 16 13

False-negative* 7 4

Sensitivity (%) 94.7 85.7

Specificity (%) 79.8 71.1

Accuracy (%) 89.2 76.7

*Data are number of lesions.

Efficacy of Breast DWI Compared for Mass and NME 1161

ADC values were higher in the small size groups ofboth malignant (P ¼ 0.012) and benign lesions (P ¼0.023) compared with the large size groups (Table 3).The accuracy of DWI was significantly higher in thelarge size group (95%) compared with the small sizegroup (83%) of the masses (P ¼ 0.006). However, forthe NME lesions, the difference between the accura-cies in the large (74%) and small size groups (84%)was not significant (P ¼ 0.369).

DISCUSSION

In this large series we found that the effectiveness ofDWI was lower for the NMEs as compared with themasses. The difference between the ADCs of benignand malignant lesions was smaller for NMEs. Thelower diagnostic accuracy of DWI in NMEs was notrelated to lesion size.

Many studies have tested the effectiveness of DWIin the benign-malignant differentiation of breastlesions especially that of the mass types with promis-ing results (14–18). However, there are just a fewstudies (20–22) on the effectiveness of DWI in NMEtype lesions with inconsistent results. Only one study(23) comparing the effectiveness of DWI in masses

Table 2

ADC Values of the Specific Histologic Subtypes and Normal Fibro-

glandular Tissue

Histology No. of lesions (%)

Mean ADC 6

SD � 10�3 mm2/s

IDC 123 (43%) 0.74 6 0.14

ILC 17 (6%) 0.74 6 0.12

DCIS 8 (2%) 0.83 6 0.15

Mucinous cancer 2 (1%) 1.76 6 0.09

Other malignants 11 (4%) 0.74 6 0.16

FA 22 (8%) 1.41 6 0.27

FCC 28 (10%) 1.19 6 0.33

Mastitis 17 (6%) 0.91 6 0.17

EH 7 (2%) 0.83 6 0.18

Papillomas 8 (3%) 0.97 6 0.21

Other benigns 20 (7%) 1.03 6 0.30

Followed 22 (8%) 1.35 6 0.27

Normal tissue 267 (100%)* 1.46 6 0.27

*Given as number of patients.

EH ¼ epithelial hyperplasia.

Figure 5. Postcontrast subtracted and ADC map images of three most common benign histologies. Regional, heterogeneous,non-mass enhancement (arrows) due to fibrocystic changes in the subtracted image of a 52-year-old woman (a) had an ADCvalue of 0.97 � 10�3 mm2/s (b). Segmental, stippled, non-mass enhancement (arrows) belong to chronic granulomatous mas-titis in the subtracted image of a 44-year-old woman (c) had an ADC value of 0.74 � 10�3 mm2/s (d). Small, homogeneouslyenhancing, round mass (arrow) belong to fibroadenoma in the left breast of a 48-year-old woman (e) had an ADC value of1.66 � 10�3 mm2/s) (f).

Table 3

Comparison of ADC Values of Benign and Malignant Lesions of

Mass and NME Separately for Small and Large Size Groups

Lesion

type Pathology

Size

group*

No. of

lesions

Mean ADC

(�10�3

mm2/sn) P-value

Mass Benign 1 54 1.21 0.961

2 25 1.21

Malignant 1 54 0.78 0.079

2 79 0.72

NME Benign 1 14 1.17 0.012

2 31 1.00

Malignant 1 5 0.92 0.023

2 23 0.76

*Size group: 1, � 15 mm; 2, > 15 mm.

1162 Kul et al.

and NMEs is available. In the earlier two studies(20,21) of around 20 NMEs, the authors were not ableto identify a significant difference of ADCs betweenbenign and malignant lesions. Yabuuchi et al in theirstudy (22) of 45 NMEs obtained 81% sensitivity and71% specificity and reported the low ADC as one ofthe strongest predictors of malignancy. Lastly, Par-tridge et al, in their study (23) including 71 massesand 45 NMEs obtained comparable diagnostic accura-cies for both lesion types (66% for masses and 60%for NMEs). In the present study including 212 massesand 73 NMEs, we have found that as in the case ofmasses, DWI is also significantly effective in the char-acterization of the NMEs. However, the diagnosticaccuracy of DWI for the selected cutoff value is signifi-cantly lower for NMEs (77%) as compared to masses(89%) (P ¼ 0.008).

Despite the different diagnostic criteria used for thecharacterization of mass and NMEs on DCE-MRI, diag-nostic criteria are same for all lesion types at DWI. TheADCs of the lesions are evaluated. So, the evaluation ofbreast lesions of any type with DWI is simpler whencompared with dynamic method. However, due to thetechnical and protocol differences in scanning, resultsof the DWI studies vary greatly (6). A meta-analysis of13 articles reported that mean ADC values of thebenign and malignant tumors ranged from 1.00 to 1.82� 10�3 mm2/s and from 0.87 to 1.36 � 10�3 mm2/s(19). Our ADC values obtained for malignant andbenign lesions and cutoffs are among the lowest onesgiven in the literature. We have used small ROIs andanalyzed the lowest ADCs measured from the tumors.This is likely the main reason of the relatively lowerADC values obtained in our study. By the way, Hiranoet al (24) compared the diagnostic performances of dif-ferent ADC parameters and found the minimum ADCsuperior to average ADC. There is no consensus amongdifferent research groups regarding the optimal DWItechnique, scanning parameters and even ROI size andplacement (6). This is one of the main challenges of thetechnique. Until all imaging and postprocessing param-eters are unified, the variations in the obtained ADCvalues and cutoffs will continue.

Moreover, we do not know if the same ADC cutoffvalue is suitable for all type of lesions. Partridge et alin their study (23) found similar ADC cutoffs formasses and NMEs. Consistently, we obtained identi-cal ADC cutoffs for both types of lesions in our study.It seems that the use of the same ADC cutoff value forboth masses and NMEs might be feasible, whichmakes the evaluation of DWI easier.

As expected, malignant lesions revealed significantlylower ADCs than benign ones. Mean ADCs of the malig-nant NMEs was slightly higher than those of the masses(P ¼ 0.067). That might be the result of the volumeaveraging effect of the background breast parenchymain NMEs. Additionally, DCIS more commonly appearsas NME (14) and shows higher ADC values comparedwith other malignancies (25). This might also have aneffect on the higher ADCs obtained from NMEs. On theother hand, the mean ADC of the benign NMEs was sig-nificantly lower than that of the benign masses (P ¼0.005). As reported by Partridge et al, the difference

between the ADCs of the benign and malignant lesionswas smaller for NMEs than for masses (23). We are notsure if this can be explained by the more partial volumeaveraging with normal tissue in case of NMEs. NMEshave distribution patterns reminiscent of ducts or glan-dular tissues. So, partial volume averaging is possible.However, normal fibroglandular tissue provides thehighest ADC whereas the fat tissue provides the lowestone when compared with breast tumors of both benignand malignant nature. If it was the case, partial volumeaveraging should either decreased or increased theADCs of the benign and malignant NMEs togetherrelated to the averaged tissue, but not reduce the differ-ence. It is well known that, smaller lesions are moreprone to partial volume effect. ADCs were significantlyhigher in the small size groups of NMEs, than in thelarge size groups. It means that partial volume effectpossibly causes the ADCs to be measured higher thannormal for NMEs. Hence, partial volume averaging isnot a reasonable explanation for the smaller differencebetween the ADCs of the benign and malignant lesionsin NMEs compared with masses.

Recently, the difference between the ADCs of someof the benign breast lesion subtypes was documentedby Parsian et al (26). Although they did not make theirdetailed evaluation according to lesion types, theyreported the FA as most prevalent lesion subtype withADCs above the threshold. Similarly, FAs had signifi-cantly higher ADCs when compared with other benignlesions in our study. FAs and other benign histologieswere unevenly distributed in the lesion groups and asthe most common mass type lesions FAs were occu-pied nearly one-third of the masses. We think that,greater difference between the benign and malignantADC values in the masses compared with NMEs mightstem from higher ADC value of FAs.

In the present study, lesion size was significantlylarger in NMEs compared with the masses. Besides,we could not identify any association between thelesion size and accuracy of DWI for NMEs. Therefore,lower diagnostic accuracy of DWI in NMEs could notbe explained with the size factor. We think that, thesmaller difference between the ADCs of benign andmalignant NME lesions might cause more overlap inthe ADCs of the benign and malignant lesions andreduce the accuracy of DWI.

In the study, ADC values of the masses were inde-pendent of size. However, the accuracy of DWI washigher in the large size group of the masses. Most ofthe initial DWI studies did not include the lesions lessthan 10 mm due the limited ability of ADC maps todemonstrate them (15,17,27). Therefore, the effect oflesion size on the diagnostic efficacy of DWI was notevaluated until a later study (23) of Partridge et al.Unlike our result, they did not identify any effects oflesion size in differentiating benign and malignantmasses. Further studies to clarify the effect of lesionsize on the efficacy of DWI are needed.

Our study had some limitations. Although it is oneof the larger studies on breast DWI including bothmass and NMEs, a relatively small number of lesionsof some sizes and histologic diagnoses limited ourcomparisons. Therefore, the effect of the lesion size on

Efficacy of Breast DWI Compared for Mass and NME 1163

the accuracy of DWI and ADCs of specific histologiesshould be investigated with larger studies. Secondlimitation was the lack of histopathologic correlationfor 22 (8%) of our lesions. Third, we speculated thatlower diagnostic accuracy of DWI in NMEs might berelated to the lower ADCs of some of the specificbenign histologies in this group. However, our studyincluded some uncommon, specific, benign histologieslike granulomatous mastitis which might create bias.Hence, our hypothesis needs to be verified with furtherstudies. Fourth, due to the limited spatial resolutionas current limitation of DWI, we could not include focito our study. The fifth limitation was that the areas ofsignal loss created by fat suppression and inherentsusceptibility and ghosting artifacts formed during thedata acquisition together with limited resolution com-plicated the localization of the small lesions on ADCmaps which may have affected the accuracy of ADCmeasurements. Use of high field strength MR unitsand new technical developments on DWI might allowsmall lesions to be evaluated better with DWI in thefuture. Another limitation was that DWI is not suitablefor stand-alone use at the present. In the presentstudy, we evaluated the diagnostic accuracy of thatadjunct technique but not evaluated its contribution toDCE-MR imaging in different types of lesions. It mightbe the topic of future investigations.

In conclusion, despite the lower diagnostic accuracyof quantitative DWI in NMEs, it is effective in thecharacterization of breast masses and NMEs and asingle ADC cutoff value might be used effectively forboth types of lesion. Our results are encouraging forthe use of DWI in the characterization of breastlesions including both mass and non-mass types.More detailed studies are needed to evaluate the con-tribution of DWI in different types of lesions as anadjunct to conventional DCE-MR imaging and toassess the diagnostic utility of DWI as an alternativenoncontrast breast MR technique. In addition, theeffect of lesion size on the accuracy of DWI and thedifferences in the ADCs of specific histologies shouldbe documented with further studies.

REFERENCES

1. Bloom S, Morrow M. A clinical oncologic perspective on breastmagnetic resonance imaging. Magn Reson Imaging Clin N Am2010;18:277–294.

2. DeMartini W, Lehman C. A review of current evidence-based clini-cal applications for breast magnetic resonance imaging. TopMagn Reson Imaging 2008;19:143–150.

3. Berg WA, Gutierrez L, NessAiver MS, et al. Diagnostic accuracy ofmammography, clinical examination, US, and MR imaging in pre-operative assessment of breast cancer. Radiology 2004;233:830–849.

4. Morakkabati N, Leutner CC, Schmiedel A, et al. Breast MR imag-ing during or soon after radiation therapy Radiology 2003;229:893–901.

5. Ikeda DM, Baker DR, Daniel BL. Magnetic resonance imaging ofbreast cancer: clinical indications and breast MRI reporting sys-tem. J Magn Reson Imaging 2000;12:975–983.

6. Pereira FP, Martins G, Carvalhaes de Oliveira Rde V. Diffusionmagnetic resonance imaging of the breast. Magn Reson ImagingClin N Am 2011;19:95–110.

7. Huang W, Fisher PR, Dulaimy K, Tudorica LA, O’Hea B. Detectionof breast malignancy: diagnostic MR protocol for improved speci-ficity. Radiology 2004;232:585–591.

8. Heywang-Kobrunner SH, Viehweg P, Heinig A, Kuchler C. Con-trast enhanced MRI of the breast: accuracy, value, controversies,solutions. Eur J Radiol 1997;24:94–108.

9. Schnall MD, Rosten S, Englander S, Orel SG, Nunes LW. A com-bined architectural and kinetic interpretation model for breastMR images. Acad Radiol 2001;8:591–597.

10. Kinkel K, Helbich TH, Esserman LJ, et al. Dynamic high-spatial-resolution MR imaging of suspicious breast lesions: diagnosticcriteria and interobserver variability. AJR Am J Roentgenol 2000;175:35–43.

11. Warren RML, Pointon L, Thompson D, et al. Reading protocol fordynamic contrast-enhanced MR images of the breast: sensitivityand specificity analysis. Radiology 2005;236:779–788.

12. Medeiros LR, Duarte CS, Rosa DD, et al. Accuracy of magneticresonance in suspicious breast lesions: a systematic quantitativereview and meta-analysis. Breast Cancer Res Treat 2011;126:273–285.

13. Martincich L, Deantoni V, Bertotto I, et al. Correlations betweendiffusion-weighted imaging and breast cancer biomarkers. EurRadiol 2012;22:1519–1528.

14. Rahbar H, Partridge SC, Eby PR. Characterization of ductal carci-noma in situ on diffusion weighted breast MRI. Eur Radiol 2011;21:2011–2019.

15. Marini C, Iacconi C, Giannelli M, Cilotti A, Moretti M, BartolozziC. Quantitative diffusion-weighted MR imaging in the differentialdiagnosis of breast lesion. Eur Radiol 2007;17:2646–2655.

16. Guo Y, Cai YQ, Cai ZL, et al. Differentiation of clinically benignand malignant breast lesions using diffusion-weighted imaging. JMagn Reson Imaging 2002;16:172–178.

17. Rubesova E, Grell AS, De Maertelaer V, Metens T, Chao SL,Lemort M. Quantitative diffusion imaging in breast cancer: a clin-ical prospective study. J Magn Reson Imaging 2006;24:319–324.

18. Kul S, Cansu A, Alhan E, Dinc H, Gunes G, Reis A. Contributionof diffusion-weighted imaging to dynamic contrast-enhanced MRIin the characterization of breast tumors. AJR Am J Roentgenol2011;196:210–217.

19. Chen X, Li WL, Zhang YL, Wu Q, Guo YM, Bai ZL. Meta-analysisof quantitative diffusion-weighted MR imaging in the differentialdiagnosis of breast lesions. BMC Cancer 2010;10:693–704.

20. Baltzer PA, Renz DM, Herrmann KH, et al. Diffusion-weightedimaging (DWI) in MR mammography (MRM): clinical comparisonof echo planar imaging (EPI) and half-Fourier single-shot turbospin echo (HASTE) diffusion techniques. Eur Radiol 2009;19:1612–1620.

21. Imamura T, Isomoto I, Sueyoshi E, et al. Diagnostic performanceof ADC for non-mass-like breast lesions on MR imaging. MagnReson Med Sci 2010;9:2172–2125.

22. Yabuuchi H, Matsuo Y, Kamitani T, et al. Non-mass-like enhance-ment non contrast-enhanced breast MR imaging: lesion charac-terization using combination of dynamic contrast-enhanced anddiffusion-weighted MR images. Eur J Radiol 2010;75:126–132.

23. Partridge SC, Mullins CD, Kurland BF, et al. Apparent diffusioncoefficient values for discriminating benign and malignant breastMRI lesions: effects of lesion type and size. AJR Am J Roentgenol2010;194:1664–1673.

24. Hirano M, Satake H, Ishigaki S, Ikeda M, Kawai H, Naganawa S.Diffusion-weighted Imaging of breast masses: comparison of diag-nostic performance using various apparent diffusion coefficientparameters. AJR Am J Roentgenol 2012;198:717–722.

25. Choi SY, Chang YW, Park HJ, Kim HJ, Hong SS, Seo DY. Correla-tion of the apparent diffusion coefficiency values on diffusion-weighted imaging with prognostic factors for breast cancer. Br JRadiol 2012;85:474–479.

26. Parsian S, Rahbar H, Allison KH, et al. Nonmalignant breastlesions: ADCs of benign and high-risk subtypes assessed asfalse-positive at Dynamic enhanced MR imaging. Radiology 2012;265:696–706.

27. Hatakenaka M, Soeda H, Yabuuchi H, et al. Apparent diffusioncoefficients of breast tumors: clinical application. Magn ResonMed Sci 2008;7:23–29.

1164 Kul et al.