Dual Energy Imaging
Sabee Molloi, Ph.D.
University of California
Department of Radiological Sciences
Irvine, California
DISCLOSURES
• Toshiba
• Philips
Outline
•Introduction
•Dual energy mammography
•Spectral mammography
•Dual energy breast CT
•Spectral breast CT
•Conclusion
Dual Energy Imaging
(cm -1 )
Dual Energy Mammography
0.8
Glandular
0.7
Adipose
Linear attenuation coefficient
0.6
0.5
0.4
0.3
0.2
20
30
40
50
60
70
Energy (keV)
Dual Energy Decomposition
l = l(tg,ta)
tg = tg (l,h)
h = h(tg,ta)
ta = ta (l,h)
Ducote J L , Molloi S, Quantification of breast density with dual energy mammography:
An experimental feasibility study, Med. Phys. 37: 793, 2010.
Outline
•Introduction
•Dual energy mammography
•Spectral mammography
•Dual energy breast CT
•Spectral breast CT
•Conclusion
Dual energy Mammography
• Hologic Selenia Digital
Mammography
• Tungsten anode x-ray
tube.
• 28 kVp, 60 mAs, 50 µm
rhodium filter.
• 49 kVp, 30 mAs, 300 µm
copper filter.
• Scatter correction.
Dual kVp Mammography
Intensity (a. u.)
1.0 28 kVp w/ Rh
0.8
0.6
0.4
49 kVp w/ Cu
0.2
0.0
10
20
30
40
Tube Voltage (kVp)
50
Breast density
Mammographically dense
breast has been shown
to be strongly associated
with breast cancer risk1
1. Boyd, et al. J National Cancer Inst, 87. p670-675, 1995.
Breast density
Breast Density 
tg
tg ta
A
G
Breast Tissue Study
• 20 postmortem breast pairs
• BI-RADS ranking by 3
radiologists
• Standard grey level thresholding
• Dual energy mammography
• Chemical analysis
x100
Chemical Analysis
Tissue
chemical analysis
Water
Lipid
Protein
1. Evaporate water in
vacuum oven
2. Dissolve lipid in
petroleum ether
3. Remove protein
using vacuum
filtration
Fibroglandular Volume Fraction
%FGVx100 
VW  VP
VW  VL  VP
Right-left Breast Correlation
from Chemical Analysis
% FGV of right breast (%)
80
70
60
Y = 0.99 X - 1.0%
2
( R ~ 0.964)
50
40
30
20
10
10
20
30
40
50
60
% FGV of left breast (%)
70
80
Visual estimation
Breast Imaging Reporting and
Data System (BI-RADS)
BI-RADS 1-4 with increasing
level of glandularity.
BI-RADS Rankings by Radiologists
5
Y= 0.76 X + 0.7
(r ~ 0.84)
4
BI-RADS Ranking
BI-RADS Ranking_Right
5
3
2
3
2
1
1
0
4
0
1
2
3
BI-RADS Ranking_Left
4
5
0
0
20
40
60
80
FGV from Chemical analysis (%)
Breast Density measurement
Gray level thresholding
100
100
100
Y= 0.63 X + 12.8
(r ~ 0.75)
80
80
Breast Density (%)
Breast density - Right (%)
Gray Level Thresholding
60
40
60
40
20
0
20
0
20
40
60
80
0
0
100
Breast density - Left (%)
20
40
60
80
100
FGV from Chemical analysis (%)
(cm -1 )
Dual Energy Mammography
0.8
Glandular
0.7
Adipose
Linear attenuation coefficient
0.6
0.5
0.4
0.3
0.2
20
30
40
50
60
70
Energy (keV)
120
120
100
Y= 0.97 X + 0.4
(r ~ 0.99)
80
100
80
60
Breast density (%)
Breast density - Right (%)
Dual energy material
decomposition
40
20
0
-20
-20
0
20
40
60
80
Breast density - Left (%)
100
120
60
40
20
0
-20
0
20
40
60
80
100
FGV from Chemical analysis (%)
Breast Density Variability
BiThresholding
RADS
Dual
Energy
Right - Left
2.0
2.0
1.0
Chemical
Analysis
2.1
1.8
1.0
Outline
•Introduction
•Dual energy mammography
•Spectral mammography
•Dual energy breast CT
•Spectral breast CT
•Conclusion
Spectral Mammography
• Philips MicroDose SI
Digital Mammography
• Tungsten anode x-ray
tube.
• Equivalent filtration 0.75
mm of Al.
• Noise floor 8.7 keV.
• No scatter correction.
Spectral mammography system
Spectral Mammography
Intensity (a. u.)
1.0
32 kVp w/ Al
0.8
0.6
0.4
0.2
0.0
5
10
15
20
25
30
35
Tube Voltage (kVp)
Human Study
• 93 mammography patients
• BI-RADS ranking by 10 radiologists
(5 US, 5 UK)
• Standard grey level thresholding
(Cumulus)
Examples of Spectral Mammography images
Unprocessed
total
Processed
Unprocessed
High energy
Glandular
Adipose
BI-RADS Rankings by Radiologists
BI-RADS ranking - Right
5
Y= 0.90 X + 0.38
(r ~ 0.93)
4
3
2
1
0
0
1
2
3
4
5
BI-RADS ranking - Left
Breast density - Right (%)
Grey Level Thresholding
100
Y= 0.87 X + 5.03%
(r ~ 0.80)
80
60
40
20
0
0
20
40
60
80
100
Breast density - Left (%)
Spectral material decomposition
Breast density - Right (%)
35
30
25
Y= 0.90 X + 1.1%
(r ~ 0.96)
20
15
10
5
0
0
5
10
15
20
25
30
35
Breast density - Left (%)
Breast Density Variability
BiThresholding Spectral
RADS
Right - Left
2.0
2.9
1.0
Outline
•Introduction
•Dual energy mammography
•Spectral mammography
•Dual energy breast CT
•Spectral breast CT
•Conclusion
Dual energy breast CT
• 20 pairs of
postmortem breasts
• Varian 4030CB on
optical bench
• Scatter-glare and
beam hardening
Corrections
-1
Linear attenuation coefficient (cm )
Dual Energy Decomposition
1
0.9
0.8
0.7
Water
Lipid (glycerol trioleate)
0.6
Protein
0.5
Polyoxymethylene
0.4
0.3
0.2
20
40
60
80
100
120
140
Photon Energy (keV)
Normalized intensity (a. u.)
Dual energy CT
1.0
50 kVp
120 kVp
0.8
0.6
0.4
0.2
0.0
20
40
60
80
100
Photon Energy (keV)
120
160
Calibration phantom
Water
Oil
Delrin plastic
(Polyoxymethylene)
50 kVp
Water
Lipid
Protein
Water
Lipid
Protein
Accuracy of Volumetric Water Fraction
Water fraction from Dual kVp CT
0.7
2
Y= 1.08X - 0.025 (R ~ 0.926)
0.6
0.5
0.4
0.3
0.2
RMS error: 4.7%
0.1
0.1
0.2
0.3
0.4
0.5
0.6
Water fraction from chemical analysis
0.7
Accuracy of Volumetric Lipid Fraction
Lipid fraction from Dual kVp CT
1.0
0.9
2
Y= 1.09 X - 0.06 (R ~ 0.962)
0.8
0.7
0.6
0.5
0.4
0.3
RMS error: 4.2%
0.2
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Lipid fraction from chemical analysis
Accuracy of Volumetric Protein Fraction
0.25
Protein fraction from Dual kVp CT
2
Y= 1.06 X - 0.003 (R ~ 0.542)
0.20
0.15
0.10
0.05
RMS error: 2.6%
0.00
0.00
0.05
0.10
0.15
0.20
0.25
Protein fraction from chemical analysis
Outline
•Introduction
•Dual energy mammography
•Spectral mammography
•Dual energy breast CT
•Spectral breast CT
•Conclusion
Spectral breast CT
• 20 pairs of
postmortem breasts
• eV 2500 CZT on
optical bench
• Spectral distortion
corrections
Low
Rotation and translation stage
Aft
collimator
Phantom
Fore
collimator
CZT
detector
X-ray
Source
Spectral breast CT
15
2
Count Rate (kcps/mm )
noise floor
(22keV)
10
splitting energy
(42keV)
5
0
20
40
60
80
Photon Energy (keV)
100
120
Low
Water
Lipid
Protein
Accuracy of Volumetric Water Fraction
Water fraction from spectral CT (%)
100
90
Y = 0.99 X - 0.24%
(r ~ 0.97)
80
70
60
50
40
30
20
10
0
0
10 20 30 40 50 60 70 80 90 100
Water fraction from chemical analysis (%)
Accuracy of Volumetric Lipid Fraction
Lipid fraction from spectral CT (%)
100
90
80
70
Y = 0.97 X + 2.89%
(r ~ 0.98)
60
50
40
30
20
10
0
0
10 20 30 40 50 60 70 80 90 100
Lipid fraction from chemical analysis (%)
Accuracy of Volumetric Protein Fraction
Protein fraction from spectral CT (%)
20
15
Y = 0.88 X + 0.43%
( r ~ 0.78)
10
5
0
0
5
10
15
20
Protein fraction from chemical analysis (%)
Outline
•Introduction
•Dual energy mammography
•Spectral mammography
•Dual energy breast CT
•Spectral breast CT
•Conclusion
Conclusions
• Dual energy imaging can be used to
accurately quantify breast density or
water, lipid, and protein contents in
breast tissue.
• It can potentially improve breast
cancer diagnosis.
ACKNOWLEDGMENTS
This research was supported in
part by Grant No. R01 CA136871
awarded by the NCI, DHHS.
X-ray Imaging Physics Laboratory
Huanjun Ding, Ph.D.
Hyo Min Cho, Ph.D.
Benjamin Ziemer, Ph.D.
Bahman Sadeghi, M.D.
Hanna Javan, M.D.
Graduate Students:
Logan Hubbard, M.D./Ph.D. student
Nikita Kumar
Collaborators:
Stephen Feig, M.D.
Carlos Iribarren, M.D., MPH, Ph.D.
Right-left Breast Correlations
80
70
60
Y = 0.99 X - 1.0%
2
( R ~ 0.964)
50
40
30
20
(a) Chemical analysis
10
10
20
30
40
50
60
% FGV of left breast (%)
70
80
% FGV from right breast (%)
% FGV of right breast (%)
80
70
60
(b) Dual kVp CT
Y= 1.03 X - 1.0%
2
(R ~ 0.922)
50
40
30
20
10
10
20
30
40
50
60
% FGV from left breast (%)
70
80
Overall Accuracy of Volumetric Fraction
9
Average RMS error: 3.58%
8
RMS error (%)
7
6
5
4
3
2
1
0
0
500
1000
1500
2000
2500
Sample mass (g)
Fractional composition
Protein Simulated with Delrin
1.4
Known Quantity
1.2
Theoretical Decompoisition
1.0
Pure Water
0.8
0.6
0.4
0.2
0.0
-0.2
Water
Lipid
Protein
DE decomposition using all photons with spectral corrections
Volumetric fraction_Dual Energy (%)
100
90
80
70
Y = 0.99 X - 0.24%
(r ~ 0.97)
60
50
40
30
20
(a) Water
10
0
0
10 20 30 40 50 60 70 80 90 100
Volumetric fraction_Dual Energy (%)
100
90
80
70
Y = 0.97 X + 2.89%
(r ~ 0.98)
60
50
40
30
20
10
0
0
(b) Lipid
10 20 30 40 50 60 70 80 90 100
Volumetric fraction_Chem ana (%)
Volumetric fraction_Dual Energy (%)
Volumetric fraction_Chem ana (%)
20
15
Y = 0.88 X + 0.43%
( r ~ 0.78)
10
5
(c) Protein
0
0
5
10
15
Volumetric fraction_Chem ana (%)
20
Fractional composition
Protein Simulated with Delrin
1.4
1.2
1.0
Known Quantity
Theoretical Decompoisition
Pure Lipid
0.8
0.6
0.4
0.2
0.0
-0.2
Water
Lipid
Protein
Fractional composition
Protein Simulated with Delrin
1.4
1.2
1.0
0.8
Known Quantity
Theoretical Decompoisition
Pure Protein
0.6
0.4
0.2
0.0
-0.2
Water
Lipid
Protein
Introduction
•
Breast tissue compositional
information may improve
breast cancer diagnosis.
•
Water content of tissue is
affected by pathology.
Goal
Validate dual energy CT
for decomposition of
breast tissue into water,
lipid and protein using
chemical analysis as the
gold standard.
Conclusions
• The high correlation of Breast
Density with respect to data from
chemical analysis validates the
use of dual energy mammography
as an accurate measurement of
breast tissue composition.
Conclusions
• Variability of breast density
measurement is reduced by a factor of
two as compared with BI-RADS
ranking.
• Spectral mammography is expected to
further enhance utility of breast density
as a risk factor for breast cancer.
Goal
Develop a quantitative method
to measure breast tissue
composition in terms of water,
lipid and protein using
spectral CT
Outline
•Introduction
•Simulation studies
•Physical phantom studies
•Postmortem breast studies
Introduction
Mammographically dense
breast has been shown to be
strongly associated with
breast cancer risk1
1 Boyd, et al. J National Cancer Inst, 87. p670-675, 1995.
Introduction
Assessing breast
density using
pattern
classification
and visual
estimation
Introduction
Breast density is defined as the percentage
of glandular breast tissue
Breast Density 
G
GA
x100
A
G
Introduction
Two-tissue assumption and three compartment
model for breast.
Adipose
Water
Glandular
Lipid
Protein
Introduction
Three compartmental model
of breast
• Lesion characterization according to
their composition1
• Water content of tissue is affected
by pathology
1. A. D. Laidevant, S. Malkov, C. I. Flowers, K. Kerlikowske and J. A.
Shepherd, "Compositional breast imaging using a dual-energy
mammography protocol," Med Phys 37, 164-174 (2010).
Water
-1
Linear Attenuation (cm )
1.0
Lipid
0.8
Protein
0.6
0.4
0.2
0.0
0
20
40
60
80
100
120
140
Energy (keV)
Outline
•Introduction
•Simulation studies
•Physical phantom studies
•Postmortem breast studies
•Patient studies
Simulation Model
Analytical model to calculate optimal
figure of merit (FOM)
FOM=SNR/
• Details
Threshold Energy (keV)
140
1.0
0.90
0.80
0.70
0.60
0.50
0.40
< 0.30
120
100
80
60
40
40
60
80
100
120
Beam Energy (kVp)
140
1.2
1.0
Fractional composition
Fractional composition
Theoretical Analysis I
WLP -> WLP
(mean) energies of 50 kVp and 120 kVp
Chemcial Analysis
Theoretical Decomp
0.8
Lean
0.6
Tissue
0.4
0.2
0.0
-0.2
Water
Lipid
Protein
1.2
1.0
Chemcial Analysis
Theoretical Decomp
0.8
Adipose
0.6
Tissue
0.4
0.2
0.0
-0.2
Water
Lipid
Protein
1.2
1.0
Chemcial Analysis
Theoretical Decomp
0.8
Lean
Tissue
0.6
RMSE = 0.03
0.4
0.2
0.0
-0.2
Water
Lipid
Protein
Fractional composition
Fractional composition
Theoretical Analysis I
WLD -> WLP
1.2
1.0
0.8
0.6
Chemcial Analysis
Theoretical Decomp
RMSE=
Adipose
0.004
Tissue
0.4
0.2
0.0
-0.2
Water
Lipid
Protein
1.2
1.0
ICRU-44
Adipose Tissue
WLD Decomp
0.8 RMSE = 0.05
0.6
0.4
0.2
0.0
-0.2
Water
Lipid
Protein
Fractional composition
Fractional composition
Theoretical Analysis II
WLD Calibration -> …
1.2
1.0
ICRU-44
Glandular Tissue
WLD Decomp
0.8 RMSE = 0.04
0.6
0.4
0.2
0.0
-0.2
Water
Lipid
Protein
1.4
1.2
1.0
ICRU-44 (WLD)
Polyethylene
Flat Panel
RMSE = 0.11
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
Water
Lipid
Protein
Fractional composition
Fractional composition
Theoretical Analysis II
WLD Calibration -> …
1.4
1.0
0.4
0.2
0.0
-0.2
-0.4
Water
Lipid
Chemical Analysis
1.0
Fractional composition
Fractional composition
Adipose Tissue
Breast Composition (Hammerstein)
RMSD = 0.11
0.6
0.4
0.2
0.0
-0.2
PMMA
0.6
1.2
Chemical Analysis
0.8
Flat Panel
RMSE = 0.0001
0.8
1.2
1.0
ICRU-44 (WLD)
1.2
Protein
Lean Tissue
Breast Composition (Hammerstein)
0.8
RMSD = 0.13
0.6
0.4
0.2
0.0
-0.2
Water
Lipid
Protein
Water
Lipid
Outline
•Introduction
•Simulation studies
•Physical phantom studies
•Postmortem breast studies
•Patient studies
Protein
Photon counting and energy resolving detectors
• Photon counting
• Energy resolving
• Electronic noise
rejection
• Examples:
CdZnTe crystals
eV 2500 – eV Microelectronics
CdZnTe (CZT) crystals
4 crystals, 64 pixels
51.2 mm total length
0.8 mm pitch
5 energy bins
Small field-of-view prototype
Experiment
Beam energy: 100 kVp
Threshold energy: 40 keV (meat), 42 keV (post-mortem breast samples)
Current: 1.0 mA
Scan time: 61.5 s/rotation
Scan mode: 2D (meat), 3D Helical (post-mortem breast samples)
Filtration: 1 mm Al (meat), 2 mm Al (post-mortem breast samples)
Dose: 3.74 mGy (meat), 1.75 mGy (post-mortem breast samples)
Phantom study
Protein
oil
32 mm
10 mm
water
Bin1 (22 ~ 40 keV) Bin2 (40 ~ 100 keV)
Three material decomposition on phantom
ROI
Water
Oil
Protein
measured
expected
measured
expected
measured
expected
1
55.5%
50%
-3.9%
0%
48.3%
50%
2
3.3%
0%
48.7%
50%
47.9%
50%
3
9.1%
10%
13.7%
10%
77.3%
80%
Volume percentage (%)
80
60
ROI 3 (whole phantom)
measured
expected
40
20
0
Water
Lipid
Protein
Outline
•Introduction
•Simulation studies
•Physical phantom studies
•Postmortem breast studies
•Patient studies
Meat study
Bin1 (22 ~ 40 keV) Bin2 (40 ~ 100 keV)
~ 30 mm
90
Lean
70
chemical analysis
CZT spectral CT
60
50
40
30
20
10
0
90
80
Volume percentage (%)
Volume percentage (%)
80
chemical analysis
CZT spectral CT
Adipose
70
60
50
40
30
20
10
0
-10
-10
Water
Lipid
Protein
Water
Lipid
Protein
Post-mortem breast sample
Bin1 (22 ~ 42 keV) Bin2 (42 ~ 100 keV)
~ 100 mm
Three material decomposition of post-mortem breast sample
CZT
chem
Volume percentage (%)
60
RMS: 6.02%
40
20
0
Water
Lipid
Protein
System requirements for patient studies
• Minimal time interval (less than 1 sec)
between low and high energy images.
• Ability to switch kVp between low and
high energy images (i.e. 28 kVp to 49
kVp).
• Ability to switch beam filter between
low and high energy images (i.e. Rh
filter to Cu filter).
• Negligible lag and ghosting between
low and high energy images.
Conclusions
• Expected additional dose is low
• Proposed technique could be incorporated into
existing screening mammography.
• Preliminary studies to date indicate the
possibility of accurate breast density
measurement in phantoms (within 3% error)
ACKNOWLEDGMENTS
This research was supported in
part by Grant No. R01 CA136871
awarded by the NCI, DHHS.
Breast Density and Water Content
120
Breast Density (%)
105
90
75
60
45
30
15
0
BD = 2.15 W – 0.49 (R2 = 0.98)
-15
-30
10
20
30
40
50
60
70
80
Volumetric Percentage of Water (%)
Breast Density and Lipid Content
120
Breast Density (%)
105
90
75
60
45
30
15
0
-15
-30
10
BD = -1.90 L + 1.40 (R2 = 0.98)
20
30
40
50
60
70
80
Volumetric Percentage of Lipid (%)
90
Breast Density and Protein Content
120
Breast Density (%)
105
90
75
60
45
30
15
0
BD = 14.34 P – 0.45 (R2 = 0.84)
-15
-30
0
2
4
6
8
10
12
14
Volumetric Percentage of Protein (%)
BI-RADS Reader Study
IRB approval
93 patients
10 radiologists
CC and MLO
views
• Right and left
breasts viewed
in random order
•
•
•
•
Averaged BI-RADS ranking_right
BI-RADS Ranking
4.0
3.5
Y= 0.89 X + 0.41
(Pearson's r ~ 0.921)
3.0
2.5
2.0
1.5
1.0
1.0
1.5
2.0
2.5
3.0
3.5
Averaged BI-RADS ranking_left
4.0
BI-RADS Breast Density
Areal Breast Density_right (%)
100
Y= 0.89 X + 8.91
Pearson's r ~ 0.92
90
80
70
60
50
40
30
20
10
0
Converted BI-RADS
0
10
20
30
40
50
60
70
80
90 100
Areal Brest Density_left (%)
Observer Variability
100
Reader A
Reader B
Reader C
Reader D
Reader E
90
No. of images
80
70
60
50
40
30
20
10
0
1
2
3
4
BI-RADS ranking
Histogram Thresholding
• Cumulus 4
• Two thresholds
• CC and MLO views
in sequence
• Right and left
blinded
CC and MLO correlation from Cumulus
MLO view_Cumulus (%)
100
Y= 0.95 X + 1.04
2
(R ~ 0.952)
80
60
40
20
0
0
20
40
60
80
100
CC view_Cumulus (%)
Right-left correlation from Cumulus
100
Y= 0.87 X +4.98
(r ~ 0.799)
Right_avg (%)
80
60
40
20
0
0
10
20
30
40
50
60
70
80
90 100
Left_avg (%)
Fuzzy C-mean Clustering
• Automatic
segmentation
• Total of 6
clusters
• First three
clusters
glandular tissue
.
Automatic Segmentation using Fuzzy C-mean
Dual Energy Decomposition
Low energy
Glandular
High energy
Adipose
Right breast density (%)
120
100
Y= 0.97 X + 0.4
(r ~ 0.99)
80
60
40
20
0
-20
-20
0
20
40
60
80
100
120
Left breast density (%)
Fig 6: BD from DE right breast vs. left breast. BD from DE vs. %FGV
from chemical analysis.
CC and MLO from dual energy
Breast density_MLO (%)
30
Y = 0.79 X +3.4%
(Pearson's r ~ 0.86)
25
20
15
10
5
0
0
5
10
15
20
25
30
35
Breast density_CC (%)
Breast Volume from Dual Energy
3
Breast volume_right (x 10 cm )
1000
Y = 0.97 X + 7.6
(Pearson's r ~ 0.96)
3
800
600
400
200
0
0
100 200 300 400 500 600 700 800 900 1000
3
3
Breast volume_left (x 10 cm )
Volumetric Breast Density_right (%)
Breast Density from Dual Energy
35
30
25
Y= 0.91 X + 1.1%
(Pearson's r ~ 0.94)
20
15
10
5
0
0
5
10
15
20
25
30
35
Volumetric Breast Density_left (%)
Conclusions
• Spectral mammography offers
quantification of volumetric breast
density with excellent precision.
• It largely eliminates the inter- and
intra-observer variability in breast
density estimation.
ACKNOWLEDGMENTS
This research was supported in
part by Grant No. R01 CA136871
awarded by the NCI, DHHS.
Right-left Breast Correlations
80
70
60
Y = 0.99 X - 1.0%
2
( R ~ 0.964)
50
40
30
20
(a) Chemical analysis
10
% FGV from right breast (%)
% FGV of right breast (%)
80
70
60
(b) Dual kVp CT
Y= 1.03 X - 1.0%
2
(R ~ 0.922)
50
40
30
20
10
10
10
20
30
40
50
60
70
80
20
30
40
50
60
70
80
% FGV from left breast (%)
% FGV of left breast (%)
Breast Tissue Composition
Ducote J, Klopfer M and Molloi S, Volumetric lean percentage measurement using dual
energy mammography, Med Phys, 2011 Aug;38(8):4498-504.
VLP Comparison II
Spectral Mammography
• Philips MicroDose Digital
Mammography System
• Tungsten anode x-ray tube.
• Appropriate energy bin
selection.
• No Scatter correction necessary.
Dual Energy Decomposition
Ducote J L , Molloi S, Quantification of breast density with dual energy mammography:
An experimental feasibility study, Med. Phys. 37: 793, 2010.
VLP Comparison
Breast Tissue Composition
Ducote J, Klopfer M and Molloi S, Volumetric lean percentage measurement using dual
energy mammography, Med Phys, 2011 Aug;38(8):4498-504.
Breast Tissue Composition
Breast Tissue Composition
Apparent Density
Conclusion: don’t necessarily expect 1:1 correspondence
140
Hammerstein
120
Woodard and White
100
Johns and Yaffe
80
60
40
20
0
-20
-40
-20
0
20
40
60
80
100 120
Known Density
Volumetric lean percentage measurement using dual energy mammography
J Ducote, M Klopfer and S Molloi Med. Phys. (2011) AT-PRESS
Fig. 4 R&L
100
90
(a)
Lipid_Right breast (%)
Water_Right breast (%)
100
80
70
60
50
40
30
20
10
0
0
10
20
30
40
50
60
70
80
90
70
60
50
40
30
20
10
0
90 100
(b)
80
0
10
Water_Left breast (%)
(c)
Lipid_Right breast (%)
Water_Right breast (%)
30
40
50
60
70
80
90 100
80
90 100
100
90
80
70
60
50
40
30
20
10
0
20
Lipid_Left breast (%)
100
0
10
20
30
40
50
60
70
Water_Left breast (%)
80
90 100
90
(d)
80
70
60
50
40
30
20
10
0
0
10
20
30
40
50
60
70
Lipid_Left breast (%)