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Diffusion tensor magnetic resonance imaging of the normal breast
Available online at www.sciencedirect.com
Magnetic Resonance Imaging 28 (2010) 320 – 328
Diffusion tensor magnetic resonance imaging of the normal breast☆ Savannah C. Partridge a,⁎, Revathi S. Murthy b , Ali Ziadloo b , Steven W. White c , Kimberly H. Allison d , Constance D. Lehman a a Department of Radiology, University of Washington, Seattle, WA 98195, USA Department of Bioengineering, University of Washington, Seattle, WA 98195, USA c Department of Computer Science, University of Washington, Seattle, WA 98195, USA d Department of Pathology, University of Washington, Seattle, WA 98195, USA Received 28 May 2009; revised 15 October 2009; accepted 27 October 2009 b
Abstract Purpose: The objective of this study was to evaluate diffusion anisotropy of the breast parenchyma and assess the range and repeatability of diffusion tensor imaging (DTI) parameters in normal breast tissue. Materials and Methods: The study was approved by our institutional review board and included 12 healthy females (median age, 36 years). Diffusion tensor imaging was performed at 1.5 T using a diffusion-weighted echo planar imaging sequence. Diffusion tensor imaging parameters including tensor eigenvalues (λ1, λ2, λ3), fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were measured for anterior, central and posterior breast regions. Results: Mean normal breast DTI measures were λ1=2.51×10−3 mm2/s, λ2=1.89×10−3 mm2/s, λ3=1.39×10−3 mm2/s, ADC=1.95±0.24×10−3 mm2/s and FA=0.29±0.05 for b=600 s/mm2. Significant regional differences were observed for both FA and ADC (Pb.05), with higher ADC in the central breast and higher FA in the posterior breast. Comparison of DTI values calculated using b=0, 600 s/mm2 vs. b=0, 1000 s/mm2, showed significant differences in ADC (Pb.001), but not FA. Repeatability assessment produced within-subject coefficient of variations of 4.5% for ADC and 11.4% for FA measures. Conclusion: This study demonstrates anisotropy of water diffusion in normal breast tissue and establishes a normative range of breast FA values. Attention to the influence of breast region and b value on breast DTI measurements may be important for clinical interpretation and standardization of techniques. © 2010 Elsevier Inc. All rights reserved. Keywords: Diffusion tensor imaging (DTI); Normal breast; Fractional anisotropy (FA); Apparent diffusion coefficient (ADC); Repeatability
1. Introduction Diffusion-weighted imaging (DWI) is an MRI technique that characterizes the three-dimensional (3D) mobility of water in vivo and probes tissue organization at the microscopic level. Recent studies have demonstrated the potential of DWI as a noncontrast technique for detecting breast cancer and characterizing breast lesions [1–5]. Standard DWI, based on diffusion encoding in three ☆ Supported by Susan G. Komen for the Cure grant BCTR0600618 and the Avon Breast Cancer Crusade Opportunity Fund. ⁎ Corresponding author. University of Washington School of Medicine, Seattle Cancer Care Alliance, Seattle, WA 98109-1023. Tel.: +1 206 288 1306; fax: +1 206 288 6473. E-mail address: [email protected] (S.C. Partridge).
0730–725X/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.mri.2009.10.003
orthogonal directions, is limited to quantifying only the apparent diffusion coefficient (ADC). Diffusion tensor imaging (DTI) extends standard DWI, with diffusion encoding in at least six directions, to measure the full diffusion tensor and characterize the motion of water in more detail. In addition to ADC, DTI enables calculation of the degree of diffusion anisotropy (or directionality) and the associated primary diffusion direction in each voxel. Diffusion tensor imaging can provide valuable information on tissue microstructure and pathophysiology that cannot be obtained by other imaging techniques. In the brain, diffusion anisotropy measures have been useful for elucidating white matter organization and development and identifying abnormalities [6–9].With recent advancements in MRI technology, DTI has also enabled unique microstructural characterization of normal and abnormal tissues in
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other areas of the body such as muscle [10], prostate [11–13] and kidney [14]. The general assumption in prior studies has been that water diffusion in breast tissue is isotropic, with equal mobility in all directions. However, in organized tissue such as breast parenchyma, which has a network of branching ducts and associated periductal fibrous stroma extending radially and posteriorly from the nipple, it is possible that water molecules may tend to follow a less restricted path and diffuse preferentially along or parallel to the ducts. The result may be anisotropic diffusion in normal breast tissue that can be detected by DTI. To our knowledge, no published studies have applied DTI to assess the levels of diffusion anisotropy in the breast or the diagnostic value provided by this information. Additionally, a challenge to a more widespread application of quantitative DTI for breast tumor assessment is the lack of standardization. A better understanding of the normative range of values and factors that may influence them would facilitate interpretation of breast DTI parameters in a clinical setting. The diffusion weighting, or b value, is known to directly affect ADC measures [15,16] and may also influence other breast DTI parameters. Furthermore, organization of the breast parenchyma (including the ductal network, terminal lobular units, stromal architecture and supporting ligaments) may cause anatomical variations in DTI measures. The purpose of this study was to (1) evaluate diffusion anisotropy of the breast parenchyma using DTI and (2) assess the range and repeatability of DTI parameters in normal breast tissue.
2. Materials and methods 2.1. Subjects This prospective study was institutional review board approved and Health Insurance Portability and Accountability Act compliant, and subjects provided informed consent. The study included 12 healthy female volunteers with no known or prior breast abnormalities. Subject ages spanned 25 to 72 years, with a median of 36 years. Each subject underwent multiple DTI acquisitions during a single examination, with acquisitions at different b values and after repositioning (in nine subjects) to assess measurement variability. 2.2. Magnetic resonance imaging acquisition All MRI was performed on a GE 1.5-T Signa HD scanner using a dedicated 8-channel bilateral breast coil (General Electric Medical Systems, Milwaukee, WI, USA). Each MR examination included a T1-weighted sequence for anatomical reference and a DTI sequence with matching slice prescription; both sequences contained 24 slices in the axial orientation, with field of view of 36 cm and slice thickness of 4 to 5 mm. The T1-weighted sequence was acquired with a 3D fast spoiled gradient-recalled echo sequence with parallel
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imaging (Volume Imaging for Breast Assessment, VIBRANT); repetition time (TR)=6.2 ms, echo time (TE)=3 ms; flip angle=10°; 350×350 matrix, and 90-s scan time. Diffusion tensor imaging was performed using a diffusionweighted echo planar imaging sequence with Array Spatial Sensitivity Encoding Technique (ASSET) parallel imaging (reduction factor=2); TR/TE=7 s/71.5 ms, three averages, 192×192 matrix, zero gap between slices and 160-s scan time. Diffusion gradients were applied in six directions with b=0, 600 and 1000 s/mm2 in all cases. One subject was additionally scanned with b=50, 100, 200, 300, 400 and 500, 600 and 1000 s/mm2 in order to investigate the influence of b value on DTI measures in more detail. To assess the repeatability of DTI measures, we removed each subject from the MRI scanner and repositioned them during the examination, and the b=0 and 600 s/mm2 scans were repeated. A water phantom was scanned for reference. 2.3. Image analysis Diffusion tensor imaging images were retrospectively analyzed offline using in-house software written in MATLAB (The Mathworks, Natick, MA) and Java programming language for use with ImageJ (National Institutes of Health, public domain). Prior to processing, the DTI images were spatially registered to the b=0 s/mm2 reference images to minimize artifacts due to motion and eddy current-induced image distortion using a nonlinear-based two-dimensional registration algorithm (CADstream; Confirma, Seattle, WA). The algorithm employs an adaptive approach in which images are aligned from course to fine resolutions [17]. Transformations steps are rigid, affine and a local deformation, which allows for nonlinear spatial correction. The sum of squared differences (SSD) is minimized at each step using a Gauss–Newton optimization for five iterations. To reduce influence from signal intensity on the SSD metric, the algorithm filters the images with a Laplacian kernel. While the distortion artifacts in this study of normal volunteers were observed to be minor, we have previously found the registration algorithm to improve data quality for DWI scans in patients and apply it as a preliminary step in all cases. Parametric maps were generated for the five rotationally invariant DTI parameters: the directionally averaged diffusion coefficient (ADC), fractional anisotropy (FA) and the maximum, intermediate and minimum eigenvalues (λ1, λ2, and λ3, respectively) and their associated eigenvectors, based on the methods proposed by Basser and Pierpaoli [18]. The eigenvalues describe the magnitude or rate of diffusion along each of the three principal axes of the diffusion tensor ellipsoid (in mm2/s). Apparent diffusion coefficient (also known as the mean diffusivity, Dav) describes the degree of mobility or restriction of water molecules and is given by
ADC =
k1 + k2 + k3 3
ð1Þ
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Fig. 1. Methodology for ROI measurement illustrated in a 34-year-old female volunteer. The T1-weighted image was used for anatomical reference and to distinguish fibroglandular from adipose tissue (A). Bilateral ROIs defined in the anterior, central and posterior regions of the breast (outlined in white) were defined on the T2-weighted b=0 s/mm2 image (B). ROIs were typically 6×6 pixels, placed within areas of fibroglandular tissue in each region with care taken to exclude regions of adipose tissue as identified on the T1-weighted image (A). Measurements were then taken from the same ROI locations on the DTI maps, as shown on the ADC map (C) and FA map (D).
Fractional anisotropy is a unitless measure of the degree of directionality of intravoxel diffusivity, calculated by qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðk1 − k2 Þ2 + ðk2 − k3 Þ2 + ðk3 − k1 Þ2 ffi FA = ð2Þ pffiffiffiqffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 k12 + k22 + k32 For isotropic diffusion (λ1=λ2=λ3), FA is zero, and in the case of high anisotropy where there is a strongly preferred direction of diffusion (λ1≫λ2≥λ3), FA approaches one. Diffusion tensor imaging parameters were measured for six bilateral regions of interest (ROIs) in each subject. The T1-weighted image was used as an anatomical reference in each case, and the ROIs were drawn to include only fibroglandular tissue and exclude regions of adipose tissue
or cyst. The breasts were visually divided into three regions, representing the anterior, central and posterior thirds of the breast, and the ROIs were positioned on the b=0 s/mm 2 image at the level of the nipple, as illustrated in Fig. 1. ROIs were placed bilaterally in anterior (near the nipple), central (midway between anterior/posterior and lateral/medial) and lateral posterior regions. If there was not sufficient breast tissue visible in a region of the breast, that region was omitted from the analysis. Each ROI was 6×6 pixels square, except in areas of sparse tissue, where it was drawn freehand. The median value of the voxels in each ROI was calculated from both the FA and ADC maps. Fig. 1 illustrates the typical ROI size and placement. In general, the same ROIs were used for the b=600 and 1000 s/mm 2 acquisitions prior to subject repositioning, and the ROIs
Table 1 Mean breast DTI parameters measured at b=600 s/mm2 Volunteer
Age
λ1 (×10−3 mm2/s)
λ2 (×10−3 mm2/s)
λ3 (×10−3 mm2/s)
ADC (×10−3 mm2/s)
FA
1 2 3 4 5 6 7 8 9 10 11 12 Mean S.D.
25 29 30 34 34 35 37 38 45 45 51 72 40 12
2.61 3.04 2.48 2.41 2.77 2.58 2.44 2.46 2.30 2.83 2.27 1.99 2.51 0.28
1.91 2.29 1.86 1.60 2.28 1.98 1.99 1.84 1.80 1.96 1.67 1.45 1.89 0.25
1.33 1.70 1.37 1.14 1.90 1.55 1.49 1.37 1.35 1.29 1.27 0.90 1.39 0.26
2.00 2.34 1.90 1.72 2.34 2.07 1.98 1.89 1.86 2.06 1.72 1.53 1.95 0.24
0.32 0.28 0.29 0.36 0.20 0.26 0.26 0.28 0.27 0.36 0.29 0.36 0.29 0.05
Data for each subject are average of right and left breast measures (mean of all six ROI locations). λ1=primary eigenvalue, λ2=second eigenvalue, λ3=third eigenvalue.
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were then redefined for the repeated b=0 and 600 s/mm2 image acquisitions.
Table 2 Diffusion tensor imaging parameters by location in the breast for b=600 s/mm2
2.4. Statistical analysis
Volunteer
Normative values were calculated for each DTI parameter as the mean and S.D. of all subjects. Additionally, DTI measures were compared by breast region and by b value. Mean ADC and FA values for the anterior, central and posterior regions of the breast were compared within each b value by Wilcoxon signed-rank test for paired data. In addition, overall ADC and FA values (average of all locations) for each subject were compared between b values by Wilcoxon signedrank test. Descriptive and reproducibility statistics were calculated for repeated DTI measures in nine subjects based on previously described methods [19–21]: withinsubject S.D., repeatability and within-subject coefficient of variation. Data were first assessed to verify there was no relationship between the measurement error and magnitude of the parameter values (by Kendall's τ), and there were no statistically significant differences between the repeated examinations (by Wilcoxon signed-rank test). Analyses were conducted using R version 2.7.1 (R Foundation for Statistical Computing, Vienna, Austria) and JMP 7.0 (SAS, Cary, NC). 3. Results Diffusion tensor imaging parameters including ADC and FA were measured bilaterally in the breasts of 12 healthy volunteers. One subject only had sufficient breast tissue for measurement in the anterior region of the breast. A water phantom was scanned for reference using the same DTI technique. The mean ADC for the water phantom at room temperature was 2.22×10−3 mm2/s at both b=600 and
1 2 3 4 5 6 7 8 9 10 11 12 Mean S.D.
ADC (×10−3 mm2/s)
FA
Anterior
Central
Posterior
Anterior
Central
Posterior
1.91 2.12 1.78 1.59 2.34 2.07 1.76 1.78 2.46 1.83 1.38 1.41 1.87 0.33
2.06 2.72 1.98 1.78 2.41 n/a 2.29 2.07 1.61 2.27 1.76 1.62 2.07 0.34
2.02 2.18 1.95 1.80 2.26 n/a 1.90 1.84 1.50 2.07 2.03 1.56 1.92 0.23
0.22 0.27 0.33 0.31 0.18 0.26 0.27 0.28 0.21 0.33 0.28 0.24 0.27 0.05
0.32 0.23 0.23 0.33 0.21 n/a 0.20 0.21 0.32 0.39 0.28 0.38 0.28 0.07
0.42 0.33 0.32 0.44 0.21 n/a 0.28 0.36 0.28 0.34 0.33 0.44 0.34 0.07
Data for each subject are average of right and left breast measures.
1000 s/mm2, which compared well to established measures [22]. The isotropic water phantom exhibited very low mean FA at both b values (0.06 at b=600 s/mm2 and 0.04 at b=1000 s/mm2). Breast DTI parameters for each subject measured at b=600 s/mm2 are given in Table 1. The mean eigenvalues measured for normal fibroglandular tissue were λ1=2.51±0.28×10−3 mm2/s, λ2=1.89±0.25×10−3 mm2/s and λ3=1.39±0.26×10−3 mm2/s. The mean breast ADC for the normal subjects was 1.95±0.24×10−3 mm2/s, and the mean FA was 0.29±0.05. The FA in breast fibroglandular tissue was substantially higher than that of the isotropic water phantom. A cyst identified in one subject exhibited very low anisotropy compared to surrounding fibroglandular tissue (Fig. 2).
Fig. 2. Example DTI images for a 34-year-old study subject. A cyst (arrow) was identified on the T2-weighted b=0 s/mm2 image (A). Compared to surrounding fibroglandular tissue, the cyst is hyperintense on the b=600 s/mm2 diffusion-weighted image (B), isointense on the ADC map (C) and hypointense on the FA map (D). Diffusion tensor imaging measures in this subject were mean ADC 1.72×10−3 mm2/s and mean FA of 0.36 in fibroglandular tissue, compared with ADC of 2.09×10−3 mm2/s and FA of 0.09 in the cyst.
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breast ADC (Fig. 3A). Apparent diffusion coefficient measures in the central breast (mean ADC, 2.07±0.34×10−3 mm2/s) were significantly higher than the posterior breast (mean ADC, 1.92±0.23×10−3 mm2/s, P=.042) in the same subjects, with a mean ADC difference of 0.13±0.21×10−3 mm2/s. Apparent diffusion coefficient in the central breast also tended to be higher than the anterior breast (mean ADC, 1.87±0.33×10−3 mm2/s), although the difference was not significant (P=.054). There was no significant difference in ADC between the anterior and posterior breast regions (P=.10). There were also regional differences in FA (Fig. 3B). Fractional anisotropy values in the posterior breast (mean FA, 0.34±0.07) were significantly higher than the anterior (mean FA, 0.27±0.05, P=.005) and central breast (mean FA, 0.28±0.07, P=.019). The mean difference between posterior and anterior breast FA was 0.08±0.07, and the mean difference between posterior and central breast was 0.06± 0.06. There was no significant difference in FA between the anterior and central breast regions (P=.52). 3.2. Comparison of DTI measures between b values The DTI measures calculated from the bilateral central, anterior and posterior ROIs were averaged to form one overall ADC and FA value for each subject. The overall ADC and FA values by b value are reported in Table 3. The ADC values at b=600 s/mm2 (mean ADC, 1.95±0.24×10−3 mm2/s) were significantly higher than those at b=1000 s/mm2 (mean ADC, 1.78±0.28×10−3 mm2/s, Pb.001), and the mean difference was 0.18±0.09 s/mm2. The mean FA values at b=600 and b=1000 s/mm2 were not significantly different (P=.42). These results are illustrated in Fig. 4. One subject underwent scanning at additional b values in order to assess effects on DTI measures in more detail. Breast ADC decreased with increasing b value over the full range of
Table 3 Mean DTI measures for each subject by b value Volunteer Mean ADC (×10−3 mm2/s) Fig. 3. Diffusion tensor imaging parameters compared by location in the breast (anterior, central and posterior). Data points represent mean of the right and left measures in each subject. Apparent diffusion coefficient measures were significantly lower for posterior vs. central breast regions, P=.042, Wilcoxon signed-rank test (A). Anterior ADC measures also tended to be lower than central measures, but the difference was not significant (P=.054). Breast FA values also differed between breast locations (B). Fractional anisotropy measures for the anterior and central breast were significantly lower than posterior measures, P=.005 and P=.019, respectively. Other comparisons between regions were not significant (PN.05).
3.1. Comparison of DTI measures between breast regions The DTI values were compared between breast regions, and measurements are given for b=600 s/mm2 in Table 2. Small but significant regional differences were observed in
2
1 2 3 4 5 6 7 8 9 10 11 12 Mean S.D.
Mean FA 2
b=600 s/mm
b=1000 s/mm
b=600 s/mm2 b=1000 s/mm2
2.00 2.34 1.90 1.72 2.34 2.07 1.98 1.89 1.86 2.06 1.72 1.53 1.95 0.24
1.82 2.21 1.71 1.46 2.19 1.89 1.92 1.85 1.62 1.77 1.62 1.18 1.77 0.29
0.32 0.28 0.29 0.36 0.20 0.26 0.26 0.28 0.27 0.36 0.29 0.36 0.29 0.05
0.31 0.29 0.33 0.38 0.18 0.32 0.24 0.27 0.28 0.34 0.33 0.33 0.30 0.05
Data are average of right and left breast measures (mean of all six ROI locations).
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diffusion weightings from b=0 to 1000 s/mm2 (Fig. 5A). Breast FA decreased with b value over the range of b=0 to 300 s/mm2 and showed little change for b values above 300 s/mm2 (Fig. 5B). 3.3. Variability of breast FA and ADC measures Nine subjects were removed from the scanner and repositioned during the examination, and the b=0 and 600 s/mm2 scans were repeated to assess variability of the DTI
Fig. 5. Influence of diffusion weighting (b value) on breast DTI measures. Data acquired in a single subject over a range of b values. Data points represent the mean of bilateral anterior, central and posterior measures at each b value; error bars indicate the S.D. across the six ROIs. Asterisks indicate significant difference (Pb.05) from the b=1000 s/mm2 measures by paired t test. Apparent diffusion coefficient values generally increased with decreasing b value, although for this subject, the difference from b=1000 s/mm2 was not significant until bb400 s/mm2 (A). Fractional anisotropy values were relatively stable over the range of b≥300 s/mm2 but increased with decreasing b value at lower diffusion weightings (bb300 s/mm2).
Fig. 4. Diffusion tensor imaging parameters compared for b=600 s/mm2 and b=1000 s/mm2. Data points represent mean of all the right and left measures in each subject. Significantly lower breast ADC values were measured for b=1000 s/mm2 vs. b=600 s/mm2, Pb.001, Wilcoxon signed-rank test (A). Breast FA values did not vary significantly between the two b values, P=.42 (B).
measures. Average DTI measures for each breast were repeated and compared for each subject. Results are given in Table 4. The data complied with statistical assumptions for the reproducibility analysis: no associations were observed between measurement error and mean value for either ADC or FA (PN.05, Kendall's τ), and there were no significant differences in distributions of ADC and FA between the two scans (PN.05, Wilcoxon signed-rank test). The mean difference in breast ADC was 0.028±0.12×10−3 mm2/s; the mean difference in FA was 0.004±0.050. For ADC, the repeatability was 0.23×10−3 mm2/s, and the within-subject coefficient of variation was 4.5%. For FA, the repeatability was 0.095, and the within-subject coefficient of variation was 11.4%.
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Table 4 Repeatability of breast DTI measures in nine subjects who underwent repeated b=0 and 600 s/mm2 scans Parameter Global mean Kendall's τ Wilcoxon signed-rank test Mean difference (±S.D.) Within-subject S.D. Repeatability (α=0.05) Within-subject coefficient of variation (%)
ADC
FA −3
2
1.85×10 mm /s -0.066, P=.70 P=.32 0.028 (±0.12)×10−3 mm2/s 0.084×10−3 mm2/s 0.23×10−3 mm2/s 4.5%
0.30 0.24, P=.16 P=.77 0.004 (±0.050) 0.034 0.095 11.4%
Statistics were calculated from mean ADC and FA values for each breast in each subject, resulting in 18 repeated measures for each parameter.
4. Discussion To our knowledge, this is the first study using DTI to measure diffusion anisotropy of breast fibroglandular tissue in a group of normal women and to assess the influence of breast location and diffusion weighting on DTI parameters. We found normal fibroglandular tissue to exhibit low to moderate anisotropy, with a mean FA of 0.29±0.05. Normative breast FA values were considerably higher than FA measures in an isotropic water phantom and breast cyst (mean FA, 0.06 and 0.09, respectively). Normative breast ADC values in our study (mean ADC, 1.9 ±0.24×10−3 mm2/s) compared well to prior DWI studies of the breast [1,3,23]. The mean displacement (L) of unrestricted water molecules in the body during a DTI acquisition is estimated to be on the order of 25 μm (based on the Einstein equation [24]: L2=6Dt, where D is the diffusion constant of water at 37 °C ≈ ADC=3.0×10−3 mm2/s, t is the diffusion time ≈ TE/2=35 ms). With normal breast ducts averaging 90 μm in diameter [25], DTI sensitivity to diffusion anisotropy of water within the ducts may be low. However, ducts in the nonlactating breast are often collapsed, which could increase the feasibility of detecting restricted diffusion within a duct. It is plausible that DTI at longer diffusion times and higher spatial resolution may enable mapping and assessment of the ductal network using fiber tracking techniques, as has been previously proposed [26]. Alternatively, breast anisotropy measures may relate to the architecture of fibrous breast stroma, which surrounds the ducts and comprises at least 80% of the nonadipose breast volume [27]. Information on stromal alterations could be useful for detecting disease on DWI and assessing local invasion. Further study with higher spatial resolution DTI and detailed comparisons to histology is necessary for better understanding the primary source of anisotropy measures in breast tissue. Both ADC and FA measures were significantly affected by location in the breast. Regional differences in breast DTI measures have not been previously reported. Apparent diffusion coefficient was generally higher in the central region, which may be in part due to larger areas of fibroglandular tissue in this region, resulting in less partial
volume averaging with adipose tissue. Fractional anisotropy was generally higher in the outer posterior region. This may reflect microstructural differences in the fibroglandular tissue. A higher concentration of smaller tapering ducts and terminal ductolobular units in the peripheral breast [28,29] could influence diffusion directionality and increase posterior FA measures in this region. The importance of regional and physiologic differences in breast tissue is illustrated by the facts that approximately 90% of all breast cancers arise from epithelial cells lining the ducts and the majority originate in the upper outer quadrant of the breast, which is attributed to a greater proportion of epithelial tissue in that region [30]. However, it is important to note that the definitions for anterior, central and posterior regions were subjective, and the regional differences we observed in DTI parameters were relatively small, particularly for ADC, and require further validation in larger studies. Breast ADC was significantly dependent on b value (higher ADC at b=600 compared to b=1000 s/mm2), which has been described previously and likely reflects differences in the water compartments probed by the different diffusion sensitizations [31–33]. On the other hand, there was no difference in FA between b=600 and b=1000 s/mm2. Our results agree well with Melhem et al. [15] who also observed negative correlation between b value and ADC measures, but no differences in FA for b values ranging between 320 and 800 s/mm2 in DTI of the brain. Increased breast FA measures were observed in our study at very low b values (less than 300 s/mm2), which is most likely due to contributions from perfusion [34] as well as overestimation of λ1 at low b [35]. It has been shown that the optimum b value that provides the highest signal-to-noise (SNR) for a spin-echo diffusionweighting sequence is 1.1/ADC [36]. For breast imaging, with typical reported ADC values of 1.6 to 2.0×10−3 mm2/s for normal tissue, this corresponds to an optimal diffusion weighting of approximately b=600 s/mm2. Alternatively, DTI at higher b values may be more sensitive to slower diffusing water compartments, such as intracellular water, and may better reflect reduced water diffusion associated with breast tumors [31,37]. However, the dependence of DTI parameters, particularly ADC, on b value should be considered when interpreting breast ADC measurements. We found good repeatability of breast DTI measures after repositioning and rescanning, with less measurement error for ADC than FA: the within-subject coefficient of variation was 4.5% for ADC and 11.4% for FA. This is not surprising as calculation of the ADC maps incorporates averaging of the data from the six diffusion directions, resulting in less heterogeneity and noise within the ADC maps compared to the FA maps. Prior studies have demonstrated ADC to be a sensitive biomarker for treatment response [38]. Our results suggest that FA may be less sensitive for monitoring treatment effects in individuals due to the higher variability of the measures. There are limitations to our study. Imaging was performed at 1.5 T with relatively thick slices (4–5 mm)
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for SNR purposes. Partial volume averaging within imaging slices may have contributed to the low FA measures. Scanning at higher field strength can enable DWI with thinner slices, as has been demonstrated for the breast at 3 T [39], and may provide better sensitivity to tissue anisotropy. Our study assessed only intrasubject repeatability of the DTI measures by repositioning each subject and repeating the scan within a short period, with the measurements repeated by the same operator. We did not evaluate interoperator reproducibility [4] or physiologic variability of the breast DTI measures [40], which have been previously investigated. Consideration of these additional sources of measurement variability will be important for clinical interpretation and standardization of breast DTI techniques. In summary, we found low to moderate diffusion anisotropy in normal fibroglandular tissue, which may reflect organization of the breast parenchyma. Both ADC and FA differed between breast regions, and ADC was additionally influenced by b value. Attention to these influences on DTI measurements may be important for clinical interpretation and standardization of techniques. To our knowledge, this is the first study to characterize normative anisotropy measures in the breast and assess the dependence on breast location and b value. Future work will assess the clinical utility of DTI for breast imaging by comparing diffusion anisotropy in breast tumors and normal tissue. Diffusion tensor imaging may reflect disruptions in normal anisotropy of water diffusion in the breast due to cancer growth and may lead to new indices for discriminating breast cancer. References [1] Yoshikawa MI, Ohsumi S, Sugata S, Kataoka M, Takashima S, Kikuchi K, et al. Comparison of breast cancer detection by diffusionweighted magnetic resonance imaging and mammography. Radiat Med 2007;25:218–23. [2] Yabuuchi H, Matsuo Y, Okafuji T, Kamitani T, Soeda H, Setoguchi 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. [3] Woodhams R, Matsunaga K, Kan S, Hata H, Ozaki M, Iwabuchi K, et al. ADC mapping of benign and malignant breast tumors. Magn Reson Med Sci 2005;4:35–42. [4] 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. [5] Kuroki-Suzuki S, Kuroki Y, Nasu K, Nawano S, Moriyama N, Okazaki M. Detecting breast cancer with non-contrast MR imaging: combining diffusion-weighted and STIR imaging. Magn Reson Med Sci 2007;6:21–7. [6] Pierpaoli C, Jezzard P, Basser PJ, Barnett A, Di Chiro G. Diffusion tensor MR imaging of the human brain. Radiology 1996;201: 637–48. [7] Partridge SC, Mukherjee P, Henry RG, Miller SP, Berman JI, Jin H, et al. Diffusion tensor imaging: serial quantitation of white matter tract maturity in premature newborns. Neuroimage 2004;22:1302–14. [8] Beppu T, Inoue T, Shibata Y, Yamada N, Kurose A, Ogasawara K, et al. Fractional anisotropy value by diffusion tensor magnetic
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Diffusion tensor magnetic resonance imaging of the normal breast☆ Savannah C. Partridge a,⁎, Revathi S. Murthy b , Ali Ziadloo b , Steven W. White c , Kimberly H. Allison d , Constance D. Lehman a a Department of Radiology, University of Washington, Seattle, WA 98195, USA Department of Bioengineering, University of Washington, Seattle, WA 98195, USA c Department of Computer Science, University of Washington, Seattle, WA 98195, USA d Department of Pathology, University of Washington, Seattle, WA 98195, USA Received 28 May 2009; revised 15 October 2009; accepted 27 October 2009 b
Abstract Purpose: The objective of this study was to evaluate diffusion anisotropy of the breast parenchyma and assess the range and repeatability of diffusion tensor imaging (DTI) parameters in normal breast tissue. Materials and Methods: The study was approved by our institutional review board and included 12 healthy females (median age, 36 years). Diffusion tensor imaging was performed at 1.5 T using a diffusion-weighted echo planar imaging sequence. Diffusion tensor imaging parameters including tensor eigenvalues (λ1, λ2, λ3), fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were measured for anterior, central and posterior breast regions. Results: Mean normal breast DTI measures were λ1=2.51×10−3 mm2/s, λ2=1.89×10−3 mm2/s, λ3=1.39×10−3 mm2/s, ADC=1.95±0.24×10−3 mm2/s and FA=0.29±0.05 for b=600 s/mm2. Significant regional differences were observed for both FA and ADC (Pb.05), with higher ADC in the central breast and higher FA in the posterior breast. Comparison of DTI values calculated using b=0, 600 s/mm2 vs. b=0, 1000 s/mm2, showed significant differences in ADC (Pb.001), but not FA. Repeatability assessment produced within-subject coefficient of variations of 4.5% for ADC and 11.4% for FA measures. Conclusion: This study demonstrates anisotropy of water diffusion in normal breast tissue and establishes a normative range of breast FA values. Attention to the influence of breast region and b value on breast DTI measurements may be important for clinical interpretation and standardization of techniques. © 2010 Elsevier Inc. All rights reserved. Keywords: Diffusion tensor imaging (DTI); Normal breast; Fractional anisotropy (FA); Apparent diffusion coefficient (ADC); Repeatability
1. Introduction Diffusion-weighted imaging (DWI) is an MRI technique that characterizes the three-dimensional (3D) mobility of water in vivo and probes tissue organization at the microscopic level. Recent studies have demonstrated the potential of DWI as a noncontrast technique for detecting breast cancer and characterizing breast lesions [1–5]. Standard DWI, based on diffusion encoding in three ☆ Supported by Susan G. Komen for the Cure grant BCTR0600618 and the Avon Breast Cancer Crusade Opportunity Fund. ⁎ Corresponding author. University of Washington School of Medicine, Seattle Cancer Care Alliance, Seattle, WA 98109-1023. Tel.: +1 206 288 1306; fax: +1 206 288 6473. E-mail address: [email protected] (S.C. Partridge).
0730–725X/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.mri.2009.10.003
orthogonal directions, is limited to quantifying only the apparent diffusion coefficient (ADC). Diffusion tensor imaging (DTI) extends standard DWI, with diffusion encoding in at least six directions, to measure the full diffusion tensor and characterize the motion of water in more detail. In addition to ADC, DTI enables calculation of the degree of diffusion anisotropy (or directionality) and the associated primary diffusion direction in each voxel. Diffusion tensor imaging can provide valuable information on tissue microstructure and pathophysiology that cannot be obtained by other imaging techniques. In the brain, diffusion anisotropy measures have been useful for elucidating white matter organization and development and identifying abnormalities [6–9].With recent advancements in MRI technology, DTI has also enabled unique microstructural characterization of normal and abnormal tissues in
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other areas of the body such as muscle [10], prostate [11–13] and kidney [14]. The general assumption in prior studies has been that water diffusion in breast tissue is isotropic, with equal mobility in all directions. However, in organized tissue such as breast parenchyma, which has a network of branching ducts and associated periductal fibrous stroma extending radially and posteriorly from the nipple, it is possible that water molecules may tend to follow a less restricted path and diffuse preferentially along or parallel to the ducts. The result may be anisotropic diffusion in normal breast tissue that can be detected by DTI. To our knowledge, no published studies have applied DTI to assess the levels of diffusion anisotropy in the breast or the diagnostic value provided by this information. Additionally, a challenge to a more widespread application of quantitative DTI for breast tumor assessment is the lack of standardization. A better understanding of the normative range of values and factors that may influence them would facilitate interpretation of breast DTI parameters in a clinical setting. The diffusion weighting, or b value, is known to directly affect ADC measures [15,16] and may also influence other breast DTI parameters. Furthermore, organization of the breast parenchyma (including the ductal network, terminal lobular units, stromal architecture and supporting ligaments) may cause anatomical variations in DTI measures. The purpose of this study was to (1) evaluate diffusion anisotropy of the breast parenchyma using DTI and (2) assess the range and repeatability of DTI parameters in normal breast tissue.
2. Materials and methods 2.1. Subjects This prospective study was institutional review board approved and Health Insurance Portability and Accountability Act compliant, and subjects provided informed consent. The study included 12 healthy female volunteers with no known or prior breast abnormalities. Subject ages spanned 25 to 72 years, with a median of 36 years. Each subject underwent multiple DTI acquisitions during a single examination, with acquisitions at different b values and after repositioning (in nine subjects) to assess measurement variability. 2.2. Magnetic resonance imaging acquisition All MRI was performed on a GE 1.5-T Signa HD scanner using a dedicated 8-channel bilateral breast coil (General Electric Medical Systems, Milwaukee, WI, USA). Each MR examination included a T1-weighted sequence for anatomical reference and a DTI sequence with matching slice prescription; both sequences contained 24 slices in the axial orientation, with field of view of 36 cm and slice thickness of 4 to 5 mm. The T1-weighted sequence was acquired with a 3D fast spoiled gradient-recalled echo sequence with parallel
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imaging (Volume Imaging for Breast Assessment, VIBRANT); repetition time (TR)=6.2 ms, echo time (TE)=3 ms; flip angle=10°; 350×350 matrix, and 90-s scan time. Diffusion tensor imaging was performed using a diffusionweighted echo planar imaging sequence with Array Spatial Sensitivity Encoding Technique (ASSET) parallel imaging (reduction factor=2); TR/TE=7 s/71.5 ms, three averages, 192×192 matrix, zero gap between slices and 160-s scan time. Diffusion gradients were applied in six directions with b=0, 600 and 1000 s/mm2 in all cases. One subject was additionally scanned with b=50, 100, 200, 300, 400 and 500, 600 and 1000 s/mm2 in order to investigate the influence of b value on DTI measures in more detail. To assess the repeatability of DTI measures, we removed each subject from the MRI scanner and repositioned them during the examination, and the b=0 and 600 s/mm2 scans were repeated. A water phantom was scanned for reference. 2.3. Image analysis Diffusion tensor imaging images were retrospectively analyzed offline using in-house software written in MATLAB (The Mathworks, Natick, MA) and Java programming language for use with ImageJ (National Institutes of Health, public domain). Prior to processing, the DTI images were spatially registered to the b=0 s/mm2 reference images to minimize artifacts due to motion and eddy current-induced image distortion using a nonlinear-based two-dimensional registration algorithm (CADstream; Confirma, Seattle, WA). The algorithm employs an adaptive approach in which images are aligned from course to fine resolutions [17]. Transformations steps are rigid, affine and a local deformation, which allows for nonlinear spatial correction. The sum of squared differences (SSD) is minimized at each step using a Gauss–Newton optimization for five iterations. To reduce influence from signal intensity on the SSD metric, the algorithm filters the images with a Laplacian kernel. While the distortion artifacts in this study of normal volunteers were observed to be minor, we have previously found the registration algorithm to improve data quality for DWI scans in patients and apply it as a preliminary step in all cases. Parametric maps were generated for the five rotationally invariant DTI parameters: the directionally averaged diffusion coefficient (ADC), fractional anisotropy (FA) and the maximum, intermediate and minimum eigenvalues (λ1, λ2, and λ3, respectively) and their associated eigenvectors, based on the methods proposed by Basser and Pierpaoli [18]. The eigenvalues describe the magnitude or rate of diffusion along each of the three principal axes of the diffusion tensor ellipsoid (in mm2/s). Apparent diffusion coefficient (also known as the mean diffusivity, Dav) describes the degree of mobility or restriction of water molecules and is given by
ADC =
k1 + k2 + k3 3
ð1Þ
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Fig. 1. Methodology for ROI measurement illustrated in a 34-year-old female volunteer. The T1-weighted image was used for anatomical reference and to distinguish fibroglandular from adipose tissue (A). Bilateral ROIs defined in the anterior, central and posterior regions of the breast (outlined in white) were defined on the T2-weighted b=0 s/mm2 image (B). ROIs were typically 6×6 pixels, placed within areas of fibroglandular tissue in each region with care taken to exclude regions of adipose tissue as identified on the T1-weighted image (A). Measurements were then taken from the same ROI locations on the DTI maps, as shown on the ADC map (C) and FA map (D).
Fractional anisotropy is a unitless measure of the degree of directionality of intravoxel diffusivity, calculated by qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðk1 − k2 Þ2 + ðk2 − k3 Þ2 + ðk3 − k1 Þ2 ffi FA = ð2Þ pffiffiffiqffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 k12 + k22 + k32 For isotropic diffusion (λ1=λ2=λ3), FA is zero, and in the case of high anisotropy where there is a strongly preferred direction of diffusion (λ1≫λ2≥λ3), FA approaches one. Diffusion tensor imaging parameters were measured for six bilateral regions of interest (ROIs) in each subject. The T1-weighted image was used as an anatomical reference in each case, and the ROIs were drawn to include only fibroglandular tissue and exclude regions of adipose tissue
or cyst. The breasts were visually divided into three regions, representing the anterior, central and posterior thirds of the breast, and the ROIs were positioned on the b=0 s/mm 2 image at the level of the nipple, as illustrated in Fig. 1. ROIs were placed bilaterally in anterior (near the nipple), central (midway between anterior/posterior and lateral/medial) and lateral posterior regions. If there was not sufficient breast tissue visible in a region of the breast, that region was omitted from the analysis. Each ROI was 6×6 pixels square, except in areas of sparse tissue, where it was drawn freehand. The median value of the voxels in each ROI was calculated from both the FA and ADC maps. Fig. 1 illustrates the typical ROI size and placement. In general, the same ROIs were used for the b=600 and 1000 s/mm 2 acquisitions prior to subject repositioning, and the ROIs
Table 1 Mean breast DTI parameters measured at b=600 s/mm2 Volunteer
Age
λ1 (×10−3 mm2/s)
λ2 (×10−3 mm2/s)
λ3 (×10−3 mm2/s)
ADC (×10−3 mm2/s)
FA
1 2 3 4 5 6 7 8 9 10 11 12 Mean S.D.
25 29 30 34 34 35 37 38 45 45 51 72 40 12
2.61 3.04 2.48 2.41 2.77 2.58 2.44 2.46 2.30 2.83 2.27 1.99 2.51 0.28
1.91 2.29 1.86 1.60 2.28 1.98 1.99 1.84 1.80 1.96 1.67 1.45 1.89 0.25
1.33 1.70 1.37 1.14 1.90 1.55 1.49 1.37 1.35 1.29 1.27 0.90 1.39 0.26
2.00 2.34 1.90 1.72 2.34 2.07 1.98 1.89 1.86 2.06 1.72 1.53 1.95 0.24
0.32 0.28 0.29 0.36 0.20 0.26 0.26 0.28 0.27 0.36 0.29 0.36 0.29 0.05
Data for each subject are average of right and left breast measures (mean of all six ROI locations). λ1=primary eigenvalue, λ2=second eigenvalue, λ3=third eigenvalue.
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were then redefined for the repeated b=0 and 600 s/mm2 image acquisitions.
Table 2 Diffusion tensor imaging parameters by location in the breast for b=600 s/mm2
2.4. Statistical analysis
Volunteer
Normative values were calculated for each DTI parameter as the mean and S.D. of all subjects. Additionally, DTI measures were compared by breast region and by b value. Mean ADC and FA values for the anterior, central and posterior regions of the breast were compared within each b value by Wilcoxon signed-rank test for paired data. In addition, overall ADC and FA values (average of all locations) for each subject were compared between b values by Wilcoxon signedrank test. Descriptive and reproducibility statistics were calculated for repeated DTI measures in nine subjects based on previously described methods [19–21]: withinsubject S.D., repeatability and within-subject coefficient of variation. Data were first assessed to verify there was no relationship between the measurement error and magnitude of the parameter values (by Kendall's τ), and there were no statistically significant differences between the repeated examinations (by Wilcoxon signed-rank test). Analyses were conducted using R version 2.7.1 (R Foundation for Statistical Computing, Vienna, Austria) and JMP 7.0 (SAS, Cary, NC). 3. Results Diffusion tensor imaging parameters including ADC and FA were measured bilaterally in the breasts of 12 healthy volunteers. One subject only had sufficient breast tissue for measurement in the anterior region of the breast. A water phantom was scanned for reference using the same DTI technique. The mean ADC for the water phantom at room temperature was 2.22×10−3 mm2/s at both b=600 and
1 2 3 4 5 6 7 8 9 10 11 12 Mean S.D.
ADC (×10−3 mm2/s)
FA
Anterior
Central
Posterior
Anterior
Central
Posterior
1.91 2.12 1.78 1.59 2.34 2.07 1.76 1.78 2.46 1.83 1.38 1.41 1.87 0.33
2.06 2.72 1.98 1.78 2.41 n/a 2.29 2.07 1.61 2.27 1.76 1.62 2.07 0.34
2.02 2.18 1.95 1.80 2.26 n/a 1.90 1.84 1.50 2.07 2.03 1.56 1.92 0.23
0.22 0.27 0.33 0.31 0.18 0.26 0.27 0.28 0.21 0.33 0.28 0.24 0.27 0.05
0.32 0.23 0.23 0.33 0.21 n/a 0.20 0.21 0.32 0.39 0.28 0.38 0.28 0.07
0.42 0.33 0.32 0.44 0.21 n/a 0.28 0.36 0.28 0.34 0.33 0.44 0.34 0.07
Data for each subject are average of right and left breast measures.
1000 s/mm2, which compared well to established measures [22]. The isotropic water phantom exhibited very low mean FA at both b values (0.06 at b=600 s/mm2 and 0.04 at b=1000 s/mm2). Breast DTI parameters for each subject measured at b=600 s/mm2 are given in Table 1. The mean eigenvalues measured for normal fibroglandular tissue were λ1=2.51±0.28×10−3 mm2/s, λ2=1.89±0.25×10−3 mm2/s and λ3=1.39±0.26×10−3 mm2/s. The mean breast ADC for the normal subjects was 1.95±0.24×10−3 mm2/s, and the mean FA was 0.29±0.05. The FA in breast fibroglandular tissue was substantially higher than that of the isotropic water phantom. A cyst identified in one subject exhibited very low anisotropy compared to surrounding fibroglandular tissue (Fig. 2).
Fig. 2. Example DTI images for a 34-year-old study subject. A cyst (arrow) was identified on the T2-weighted b=0 s/mm2 image (A). Compared to surrounding fibroglandular tissue, the cyst is hyperintense on the b=600 s/mm2 diffusion-weighted image (B), isointense on the ADC map (C) and hypointense on the FA map (D). Diffusion tensor imaging measures in this subject were mean ADC 1.72×10−3 mm2/s and mean FA of 0.36 in fibroglandular tissue, compared with ADC of 2.09×10−3 mm2/s and FA of 0.09 in the cyst.
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breast ADC (Fig. 3A). Apparent diffusion coefficient measures in the central breast (mean ADC, 2.07±0.34×10−3 mm2/s) were significantly higher than the posterior breast (mean ADC, 1.92±0.23×10−3 mm2/s, P=.042) in the same subjects, with a mean ADC difference of 0.13±0.21×10−3 mm2/s. Apparent diffusion coefficient in the central breast also tended to be higher than the anterior breast (mean ADC, 1.87±0.33×10−3 mm2/s), although the difference was not significant (P=.054). There was no significant difference in ADC between the anterior and posterior breast regions (P=.10). There were also regional differences in FA (Fig. 3B). Fractional anisotropy values in the posterior breast (mean FA, 0.34±0.07) were significantly higher than the anterior (mean FA, 0.27±0.05, P=.005) and central breast (mean FA, 0.28±0.07, P=.019). The mean difference between posterior and anterior breast FA was 0.08±0.07, and the mean difference between posterior and central breast was 0.06± 0.06. There was no significant difference in FA between the anterior and central breast regions (P=.52). 3.2. Comparison of DTI measures between b values The DTI measures calculated from the bilateral central, anterior and posterior ROIs were averaged to form one overall ADC and FA value for each subject. The overall ADC and FA values by b value are reported in Table 3. The ADC values at b=600 s/mm2 (mean ADC, 1.95±0.24×10−3 mm2/s) were significantly higher than those at b=1000 s/mm2 (mean ADC, 1.78±0.28×10−3 mm2/s, Pb.001), and the mean difference was 0.18±0.09 s/mm2. The mean FA values at b=600 and b=1000 s/mm2 were not significantly different (P=.42). These results are illustrated in Fig. 4. One subject underwent scanning at additional b values in order to assess effects on DTI measures in more detail. Breast ADC decreased with increasing b value over the full range of
Table 3 Mean DTI measures for each subject by b value Volunteer Mean ADC (×10−3 mm2/s) Fig. 3. Diffusion tensor imaging parameters compared by location in the breast (anterior, central and posterior). Data points represent mean of the right and left measures in each subject. Apparent diffusion coefficient measures were significantly lower for posterior vs. central breast regions, P=.042, Wilcoxon signed-rank test (A). Anterior ADC measures also tended to be lower than central measures, but the difference was not significant (P=.054). Breast FA values also differed between breast locations (B). Fractional anisotropy measures for the anterior and central breast were significantly lower than posterior measures, P=.005 and P=.019, respectively. Other comparisons between regions were not significant (PN.05).
3.1. Comparison of DTI measures between breast regions The DTI values were compared between breast regions, and measurements are given for b=600 s/mm2 in Table 2. Small but significant regional differences were observed in
2
1 2 3 4 5 6 7 8 9 10 11 12 Mean S.D.
Mean FA 2
b=600 s/mm
b=1000 s/mm
b=600 s/mm2 b=1000 s/mm2
2.00 2.34 1.90 1.72 2.34 2.07 1.98 1.89 1.86 2.06 1.72 1.53 1.95 0.24
1.82 2.21 1.71 1.46 2.19 1.89 1.92 1.85 1.62 1.77 1.62 1.18 1.77 0.29
0.32 0.28 0.29 0.36 0.20 0.26 0.26 0.28 0.27 0.36 0.29 0.36 0.29 0.05
0.31 0.29 0.33 0.38 0.18 0.32 0.24 0.27 0.28 0.34 0.33 0.33 0.30 0.05
Data are average of right and left breast measures (mean of all six ROI locations).
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diffusion weightings from b=0 to 1000 s/mm2 (Fig. 5A). Breast FA decreased with b value over the range of b=0 to 300 s/mm2 and showed little change for b values above 300 s/mm2 (Fig. 5B). 3.3. Variability of breast FA and ADC measures Nine subjects were removed from the scanner and repositioned during the examination, and the b=0 and 600 s/mm2 scans were repeated to assess variability of the DTI
Fig. 5. Influence of diffusion weighting (b value) on breast DTI measures. Data acquired in a single subject over a range of b values. Data points represent the mean of bilateral anterior, central and posterior measures at each b value; error bars indicate the S.D. across the six ROIs. Asterisks indicate significant difference (Pb.05) from the b=1000 s/mm2 measures by paired t test. Apparent diffusion coefficient values generally increased with decreasing b value, although for this subject, the difference from b=1000 s/mm2 was not significant until bb400 s/mm2 (A). Fractional anisotropy values were relatively stable over the range of b≥300 s/mm2 but increased with decreasing b value at lower diffusion weightings (bb300 s/mm2).
Fig. 4. Diffusion tensor imaging parameters compared for b=600 s/mm2 and b=1000 s/mm2. Data points represent mean of all the right and left measures in each subject. Significantly lower breast ADC values were measured for b=1000 s/mm2 vs. b=600 s/mm2, Pb.001, Wilcoxon signed-rank test (A). Breast FA values did not vary significantly between the two b values, P=.42 (B).
measures. Average DTI measures for each breast were repeated and compared for each subject. Results are given in Table 4. The data complied with statistical assumptions for the reproducibility analysis: no associations were observed between measurement error and mean value for either ADC or FA (PN.05, Kendall's τ), and there were no significant differences in distributions of ADC and FA between the two scans (PN.05, Wilcoxon signed-rank test). The mean difference in breast ADC was 0.028±0.12×10−3 mm2/s; the mean difference in FA was 0.004±0.050. For ADC, the repeatability was 0.23×10−3 mm2/s, and the within-subject coefficient of variation was 4.5%. For FA, the repeatability was 0.095, and the within-subject coefficient of variation was 11.4%.
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Table 4 Repeatability of breast DTI measures in nine subjects who underwent repeated b=0 and 600 s/mm2 scans Parameter Global mean Kendall's τ Wilcoxon signed-rank test Mean difference (±S.D.) Within-subject S.D. Repeatability (α=0.05) Within-subject coefficient of variation (%)
ADC
FA −3
2
1.85×10 mm /s -0.066, P=.70 P=.32 0.028 (±0.12)×10−3 mm2/s 0.084×10−3 mm2/s 0.23×10−3 mm2/s 4.5%
0.30 0.24, P=.16 P=.77 0.004 (±0.050) 0.034 0.095 11.4%
Statistics were calculated from mean ADC and FA values for each breast in each subject, resulting in 18 repeated measures for each parameter.
4. Discussion To our knowledge, this is the first study using DTI to measure diffusion anisotropy of breast fibroglandular tissue in a group of normal women and to assess the influence of breast location and diffusion weighting on DTI parameters. We found normal fibroglandular tissue to exhibit low to moderate anisotropy, with a mean FA of 0.29±0.05. Normative breast FA values were considerably higher than FA measures in an isotropic water phantom and breast cyst (mean FA, 0.06 and 0.09, respectively). Normative breast ADC values in our study (mean ADC, 1.9 ±0.24×10−3 mm2/s) compared well to prior DWI studies of the breast [1,3,23]. The mean displacement (L) of unrestricted water molecules in the body during a DTI acquisition is estimated to be on the order of 25 μm (based on the Einstein equation [24]: L2=6Dt, where D is the diffusion constant of water at 37 °C ≈ ADC=3.0×10−3 mm2/s, t is the diffusion time ≈ TE/2=35 ms). With normal breast ducts averaging 90 μm in diameter [25], DTI sensitivity to diffusion anisotropy of water within the ducts may be low. However, ducts in the nonlactating breast are often collapsed, which could increase the feasibility of detecting restricted diffusion within a duct. It is plausible that DTI at longer diffusion times and higher spatial resolution may enable mapping and assessment of the ductal network using fiber tracking techniques, as has been previously proposed [26]. Alternatively, breast anisotropy measures may relate to the architecture of fibrous breast stroma, which surrounds the ducts and comprises at least 80% of the nonadipose breast volume [27]. Information on stromal alterations could be useful for detecting disease on DWI and assessing local invasion. Further study with higher spatial resolution DTI and detailed comparisons to histology is necessary for better understanding the primary source of anisotropy measures in breast tissue. Both ADC and FA measures were significantly affected by location in the breast. Regional differences in breast DTI measures have not been previously reported. Apparent diffusion coefficient was generally higher in the central region, which may be in part due to larger areas of fibroglandular tissue in this region, resulting in less partial
volume averaging with adipose tissue. Fractional anisotropy was generally higher in the outer posterior region. This may reflect microstructural differences in the fibroglandular tissue. A higher concentration of smaller tapering ducts and terminal ductolobular units in the peripheral breast [28,29] could influence diffusion directionality and increase posterior FA measures in this region. The importance of regional and physiologic differences in breast tissue is illustrated by the facts that approximately 90% of all breast cancers arise from epithelial cells lining the ducts and the majority originate in the upper outer quadrant of the breast, which is attributed to a greater proportion of epithelial tissue in that region [30]. However, it is important to note that the definitions for anterior, central and posterior regions were subjective, and the regional differences we observed in DTI parameters were relatively small, particularly for ADC, and require further validation in larger studies. Breast ADC was significantly dependent on b value (higher ADC at b=600 compared to b=1000 s/mm2), which has been described previously and likely reflects differences in the water compartments probed by the different diffusion sensitizations [31–33]. On the other hand, there was no difference in FA between b=600 and b=1000 s/mm2. Our results agree well with Melhem et al. [15] who also observed negative correlation between b value and ADC measures, but no differences in FA for b values ranging between 320 and 800 s/mm2 in DTI of the brain. Increased breast FA measures were observed in our study at very low b values (less than 300 s/mm2), which is most likely due to contributions from perfusion [34] as well as overestimation of λ1 at low b [35]. It has been shown that the optimum b value that provides the highest signal-to-noise (SNR) for a spin-echo diffusionweighting sequence is 1.1/ADC [36]. For breast imaging, with typical reported ADC values of 1.6 to 2.0×10−3 mm2/s for normal tissue, this corresponds to an optimal diffusion weighting of approximately b=600 s/mm2. Alternatively, DTI at higher b values may be more sensitive to slower diffusing water compartments, such as intracellular water, and may better reflect reduced water diffusion associated with breast tumors [31,37]. However, the dependence of DTI parameters, particularly ADC, on b value should be considered when interpreting breast ADC measurements. We found good repeatability of breast DTI measures after repositioning and rescanning, with less measurement error for ADC than FA: the within-subject coefficient of variation was 4.5% for ADC and 11.4% for FA. This is not surprising as calculation of the ADC maps incorporates averaging of the data from the six diffusion directions, resulting in less heterogeneity and noise within the ADC maps compared to the FA maps. Prior studies have demonstrated ADC to be a sensitive biomarker for treatment response [38]. Our results suggest that FA may be less sensitive for monitoring treatment effects in individuals due to the higher variability of the measures. There are limitations to our study. Imaging was performed at 1.5 T with relatively thick slices (4–5 mm)
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for SNR purposes. Partial volume averaging within imaging slices may have contributed to the low FA measures. Scanning at higher field strength can enable DWI with thinner slices, as has been demonstrated for the breast at 3 T [39], and may provide better sensitivity to tissue anisotropy. Our study assessed only intrasubject repeatability of the DTI measures by repositioning each subject and repeating the scan within a short period, with the measurements repeated by the same operator. We did not evaluate interoperator reproducibility [4] or physiologic variability of the breast DTI measures [40], which have been previously investigated. Consideration of these additional sources of measurement variability will be important for clinical interpretation and standardization of breast DTI techniques. In summary, we found low to moderate diffusion anisotropy in normal fibroglandular tissue, which may reflect organization of the breast parenchyma. Both ADC and FA differed between breast regions, and ADC was additionally influenced by b value. Attention to these influences on DTI measurements may be important for clinical interpretation and standardization of techniques. To our knowledge, this is the first study to characterize normative anisotropy measures in the breast and assess the dependence on breast location and b value. Future work will assess the clinical utility of DTI for breast imaging by comparing diffusion anisotropy in breast tumors and normal tissue. Diffusion tensor imaging may reflect disruptions in normal anisotropy of water diffusion in the breast due to cancer growth and may lead to new indices for discriminating breast cancer. References [1] Yoshikawa MI, Ohsumi S, Sugata S, Kataoka M, Takashima S, Kikuchi K, et al. Comparison of breast cancer detection by diffusionweighted magnetic resonance imaging and mammography. Radiat Med 2007;25:218–23. [2] Yabuuchi H, Matsuo Y, Okafuji T, Kamitani T, Soeda H, Setoguchi 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. [3] Woodhams R, Matsunaga K, Kan S, Hata H, Ozaki M, Iwabuchi K, et al. ADC mapping of benign and malignant breast tumors. Magn Reson Med Sci 2005;4:35–42. [4] 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. [5] Kuroki-Suzuki S, Kuroki Y, Nasu K, Nawano S, Moriyama N, Okazaki M. Detecting breast cancer with non-contrast MR imaging: combining diffusion-weighted and STIR imaging. Magn Reson Med Sci 2007;6:21–7. [6] Pierpaoli C, Jezzard P, Basser PJ, Barnett A, Di Chiro G. Diffusion tensor MR imaging of the human brain. Radiology 1996;201: 637–48. [7] Partridge SC, Mukherjee P, Henry RG, Miller SP, Berman JI, Jin H, et al. Diffusion tensor imaging: serial quantitation of white matter tract maturity in premature newborns. Neuroimage 2004;22:1302–14. [8] Beppu T, Inoue T, Shibata Y, Yamada N, Kurose A, Ogasawara K, et al. Fractional anisotropy value by diffusion tensor magnetic
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