Blood Flow Reduction in Breast Tissue due to Mammographic Compression

Rationale and objectives

This study measures hemodynamic properties such as blood flow and hemoglobin concentration and oxygenation in the healthy human breast under a wide range of compressive loads. Because many breast-imaging technologies derive contrast from the deformed breast, these load-dependent vascular responses affect contrast agent–enhanced and hemoglobin-based breast imaging.

Methods

Diffuse optical and diffuse correlation spectroscopies were used to measure the concentrations of oxygenated and deoxygenated hemoglobin, lipid, water, and microvascular blood flow during axial breast compression in the parallel-plate transmission geometry.

Results

Significant reductions ( P < .01) in total hemoglobin concentration (∼30%), blood oxygenation (∼20%), and blood flow (∼87%) were observed under applied pressures (forces) of up to 30 kPa (120 N) in 15 subjects. Lipid and water concentrations changed <10%.

Conclusions

Imaging protocols based on injected contrast agents should account for variation in tissue blood flow due to mammographic compression. Similarly, imaging techniques that depend on endogenous blood contrasts will be affected by breast compression during imaging.

Exogenous contrast agents are playing an increasingly important role in breast cancer screening and diagnosis, because they improve image signal-to-noise and offer novel targeting potential as tissue biomarkers. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) uses intravenous injection of gadolinium-diethylenetriamine pentaacetic acid (Gd-DTPA), for example, and is currently recommended as a screening tool for high-risk women . Similarly, contrast-enhanced digital x-ray tomosynthesis often uses injection of iodine-based agents into the compressed breast . Both of these techniques rely on adequate blood flow to control the delivery, uptake, and spatial distribution of the contrast agent. Deformation of breast tissue during compression, however, can lead to modifications of regional blood flow that alter tissue oxygenation and metabolism as well as contrast agent delivery. Furthermore, the mechanical properties of tumors are generally different from those of the surrounding tissues , and these differences can lead to uncontrolled and heterogeneous vascular responses of the breast to compression. Thus, compression can significantly reduce cancer contrast.

In addition to the standard clinical techniques mentioned previously, scientists continue to explore new technologies to enhance breast cancer specificity and sensitivity. Diffuse optical spectroscopy (DOS) and tomography (DOT), for example, are novel methodologies that utilize photons in the near-infrared (NIR, 650–950 nm) tissue transmission window to measure properties of normal and diseased breast tissues noninvasively and in vivo . In breast cancer, these physiological parameters typically include the concentration of oxygenated and deoxygenated hemoglobin (HbO 2 and Hb, respectively), from which total tissue hemoglobin concentration (Hb t = HbO 2 + Hb ∝ blood volume) and blood oxygen saturation (StO 2 = HbO 2 /Hb t ) are readily calculated. These hemodynamic parameters, including other tissue properties such as water and lipid concentration and reduced tissue scattering ( μ′s μ

′ ), all provide significant endogenous tumor contrast for the optical method. In practice, clinical DOS/DOT measurements typically involve placing breast tissue under some type of mild compression, however, and the effects of this compression on breast tissue vasculature are not generally considered in the analysis of DOT results, despite observations suggesting that compression effects are present .

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Methods

Recruitment

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Table 1

Demographic Information for Healthy Subjects Studied in the Compression Investigation

Parameters Subjects ( N = 15) Age, yr 35 ± 16 (19, 67) BMI, kg/m 2 26 ± 7.8 (19.6, 49.3) Menopausal status Premenopausal 12 (75%) Postmenopausal 3 (25%) Bra cup size B 1 (7%) C 8 (53%) D 5 (33%) E 1 (7%) Race/ethnicity Caucasian 11 (73%) African American 3 (20%) Asian 1 (7%) Hispanic 0 (0%)

Race/ethnicity and bra cup size are self-reported. Body mass index (BMI) and age are reported as mean ± standard deviation (minimum, maximum).

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Measurement Protocol

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μ′s(λ)=Aλ−b μ

′

(

)

−

for each optical wavelength λ (nm). Note that μ′s μ

′ and the quantity ( Aλ − b ) have units of cm −1 . The tissue absorption coefficient is a sum of terms containing both the i th chromophore concentration ( C__i , mol/L) and their respective extinction coefficients (ε i , cm −1 mol −1 L), that is,

μa(λ)=∑iCi⋅εi(λ)⋅ln(10) μ

(

)

∑

(

)

(

)

where the sum is over all tissue chromophores and μ__a has units of cm −1 . Additionally, two derived parameters, total hemoglobin concentration and blood oxygen saturation, were calculated at each time point.

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rHbt=Hbt(Hbt)0ΔStO2=StO2−(StO2)0rBF=BFBF0ΔLipid=Lipid−Lipid0ΔH2O=H2O−(H2O)0rμ′s=μ′s(μ′s)0ΔP=P−P0ΔF=F−F0 rHb

(

)

ΔStO

StO

−

(

StO

)

ΔLipid

Lipid

−

Lipid

ΔH

−

(

)

′

(

′

)

−

where the resulting normalized physiological parameters are measured in percentages (or as differences) relative to the baseline ( X__0 ) value.

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Statistical Methods

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Results

Example Data from Individual Subjects

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Population-averaged Mechanical Properties

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$Figure 5, Mechanical properties of breast tissue. Each point corresponds to the average parameter during a baseline or compressed period (e.g., as in Fig 2 a); error bars are the standard deviation of the parameter. Red dots denote postmenopausal, and blue dots, premenopausal subjects. (a) Change in surface pressure (Δ P = P − P 0 ) versus applied force (Δ F = F − F 0 ) from baseline. (b) Δ P (≃ stress) versus fractional change in plate separation (Δ d d 0 ≃ strain). Note that, we performed linear fits over two ranges of stress: 0%–20% ( green ) and 0%–50% ( black , all data). Although the latter range includes some data points, which may be outside of the linear stress–strain regimen, we use a simple linear model for the present analysis. Approximate systolic and diastolic blood pressures for healthy persons are shown for reference. For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.$

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Population-averaged Physiological Properties

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Discussion

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Conclusions

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Acknowledgments

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Appendix A

Optical data analysis

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χ2=∑λ,t(T(t,λ)−Tc(t,λ)T(t,λ)√∣∣∣t2t1) χ

∑

(

)

−

(

)

(

)

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Gdcsslab[τ]=14π∑∞m=−∞(r−11,me−kdcs(τ)r1,m−r−12,me−kdcs(τ)r2,m) G

slab

dcs

[

]

∑

−

∞

(

−

dcs

(

)

−

dcs

(

)

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r1,m=ρ2+z21,m−−−−−−−√ r

r2,m=ρ2+z22,m−−−−−−−√ r

z1,m=d(1−2m)−4mzb−z0 z

(

−

)

−

z2,m=d(1−2m)−(4m−2)zb+z0 z

(

−

)

−

(

−

)

z0=1μ′s+μa≃1μ′s z

′

≃

′

zb=2z031+Reff1−Reff z

eff

−

eff

kdcs(τ)=vD(μa+αμ′sκ20<Δr2(τ)>3)−−−−−−−−−−−−−−−−−−√ k

dcs

(

)

(

′

(

)

κ0=2πnλ κ

D=v3(μ′s+μa)≃v3μ′s D

(

′

)

≃

′

where d is the slab thickness, ρ the transverse source-detector separation, v is the speed of light, n is the index of refraction, R eff is the Fresnel reflection coefficient at the slab boundaries, and α is the fraction of moving scatterers. Note, this fit uses the optical properties ( μ__a and μ′s μ

′ ) at the DCS wavelength (785 nm) determined from TD-DOS measurements.

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k2dcs[τ]=vD(μa+2μ′sκ20αDBτ) k

dcs

[

]

(

′

)

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Blood Flow Reduction in Breast Tissue due to Mammographic Compression

Rationale and objectives

Methods

Results

Conclusions

Methods

Recruitment

Measurement Protocol

Statistical Methods

Results

Example Data from Individual Subjects

Population-averaged Mechanical Properties

Population-averaged Physiological Properties

Discussion

Conclusions

Acknowledgments

Appendix A

Optical data analysis

References

Further Reading

Adaptable Near-Infrared Spectroscopy Fiber Array for Improved Coupling to Different Breast Sizes During Clinical MRI

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