MR-Guided Near Infrared Spectral
Tomography of the Breast
Why Image the Breast with Light?
Optical Molecular Interactions
Elastic Scatter
Absorption
More features
Keith D. Paulsen, PhD
Thayer School of Engineering, Dartmouth College
Department of Radiology, Dartmouth Medical School
Major absorbers (chromophores) in
breast tissue
Luminesce
Raman
better specificity
Higher probability of interaction
Near-Infrared imaging:
1. Non-invasive
2. Non-ionizing
3. Relatively inexpensive
Tissue Targeting:
Vascular leakage
Selective Uptake
Receptor Binding
Molecular level information:
Blood vessel density
Local Metabolism
Cellular size and density
Courtesy of Brian Pogue
How to Image when
Photon scatter affects resolution
X-Ray Fluence
NearNear-Infrared System - 2004
NIR Fluence
1.2cm
1.2cm
Bartrum & Crowe, AJR,
1984
values from: Castro et al. Xray
Spec. 2005
- 3 planes
- 6 wavelengths
Complex Diffusion equation
r
r
r iω r
r
−∇ D(r )∇Φ(r ,ω) + (µa (r ) + )Φ(r ,ω) = S0 (r ,ω)
c
Newton-Raphson method
∆µ = [J T J + λI ]−1 J T (ΦC −ΦM )
Light source
Transmitted light detection
Major absorbers (chromophores) in breast tissue
HbT = HbO2 + Hb
StO2 = HbO2/ HbT
ACR 1 Results Summary
NIR ACR 1 Results
NIR Results Stratified by Size
77 Women, 150 Exams
AUCs: CA-N = 0.88; CA-nCA = 0.82; CA-AB = 0.76
Poplack et. al Radiology 243:350-359,2007
Image-Guided Optical Molecular
Spectroscopy
X-ray CT
Ultrasound
MRI
Microscope
MR-guided Optical Imaging
MR
+
• Spatial maps
• Tissue types
• Suspect lesions
• Water content
• Blood oxygen (BOLD)
Optical
Spectroscopy
Elastic
Scatter
Absorption
More features
Luminesce
better specificity
Higher probability of interaction
Raman
Optics
• Hemodynamic
content
• Quantification
High resolution maps of:
HbT, StO2, H2O & Scatter
*Brooksby
et al. PNAS (2006).
Optically Coupled Philips 3T MR
Coil for Breast Imaging
Patient Interfaces – circular & compression
Carpenter et al, Optics Express (2008)
Data Collection
Transmit near infrared light through tissue
to determine light absorption
μa
Top view
Side view
Transmit near infrared light through tissue
to determine light absorption
μa
Transmit near infrared light through tissue
to determine light absorption
Data Collection
μa
Data Collection
Incorporating MR Spatial Images
Incorporating spatial data from MR with Mimics ©
BEM Method for IG-NIRS
Imaging Domain
3D
2D
FEM
BEM
Light Propagation in a
3-D Breast Model using BEM
Light Propagation in a
3-D Breast Model using BEM
Monitoring Chemotherapy Using
Multiple Imaging Sessions
Four Visits Imaged using IG-NIRS
Breast Clip
Blood Volume Index Decreases by
61% between sessions I and II;
96% between I and III
3D Overlay on MRI – Patient prior to
neoadjuvant chemo
Sagittal T1 MR
Gross mastectomy
specimen
Carpenter et al, Opt. Lett. (2007)
microMolar
Hemoglobin
Srinivasan et al, JMRI Submitted, 2009
Subject post 1 cycle
neoadjuvant chemotherapy
DCE MR subject with IDC, prior to chemotherapy. Slight enhancement of 1
main node with 3 satellite lesions, all showing increased hemoglobin.
3007 - 2 days after Cycle 2
Carpenter et al, Opt. Exp. (in press, 2008)
Lesion characterization: Case Study
•
Patient 1915 – IDCa
(coronal display)
Patient with a benign lesion that enhanced in DCE-MR
Sagittal T1 MR
Gross mastectomy
specimen
Carpenter et al, Opt. Lett. (2007)
Continuous Wave Experiment
Results in 5 Patients
Spectrometer-based system
•
Results suggest that this technique exhibits high tumor
to background contrast
•
Oxygen sat, water, scatter show no consistent trends
O2 Sat
Only the change of transmitted
light intensity is recorded with
CCD cameras.
Water
Malignant
S. C. Davis, H. Dehghani, J. Wang, S. Jiang, B. W. Pogue and K. D. Paulsen, Opt. Express 15(7), 4066-4082 (2007).
Sc-Amp
Sc-Power
Combined Frequency-domain
& CW Spectrometer System
MR-coupled spectroscopy system
Amplitude
modulated
laser diodes
(8)
Frequency
Domain:
PMT-based
detection
system
PMT
detectors
Philips 3T MRI
Spectroscopy
detection:
16 Acton
Research
spectrometers
with cooled
CCD cameras
5.5
Attenuation (OD)
5.0
4.5
4.0
3.5
700
800
900
Wavelength (nm)
• CW measurement from 700nm to 900nm with 12 wavelengths.
Combine Frequency domain and Continuous wave data sets for spectral reconstruction
solution inclusion
2% blood 1% Intralipid
Contrast in HbT
Contrast in water
(~100% in solution)
Frequency domain
Absorption
Scattering
700 – 840nm
700 – 900nm
,
gelatin inclusion
,
2% blood
Continuous wave
Contrast in HbT
Homogeneous water image
.
Gelatin Background
( 1% blood )
700 – 840nm
700 – 900nm
Mixed Jacobian Matrix
δC =
δ C1
δ C2
M
δ CN
J λFD
(C1 )
1
J λFD
(C2 ) L
1
J λFD
(C N )
1
J λFD
(C1 )
2
J λFD
(C2 ) L
2
J λFD
(C N )
2
M
FD
J = J λ f (C1 )
J λCW
(C1 )
1
M
J λc (C1 )
∂ ln I
∂D
∂ ln I
∂µa
∂θ
∂D
∂θ
∂µa
Amplitude
I λFD
1
M
J λFD
(C N )
f
FD
Φ = Iλ f
I λCW
1
J λFD
(C2 ) L
f
M
CW
O
Phase
I λFD
2
M
J λCW
(C2 ) L J λCW
(CN )
1
1
M
CW
O
J FD =
M
M
CW
CW
J λc (C2 ) L J λc (CN )
J CW =
∂ ln I
∂D
∂ ln I
∂µa
I λc
Intensity
Patient 2. Infiltrating ductal carcinoma
Patient 1. Ductal carcinoma in situ and invasive ductal carcinoma
Dynamic Contrast MRI image
with GE Signa Excite1.5-T
Dynamic Contrast MRI image
Frequency domain
Frequency domain
Frequency domain
+
Continuous wave
Frequency domain
+
Continuous wave
Breast-sized phantoms with ICG:
Shallow object
Contrast
No spatial
priors
Soft spatial
priors
Hard spatial
priors
1.5:1
3.3:1
6.6:1
Breast-sized phantoms with ICG:
Deep object
Contrast
No spatial
priors
Soft spatial
priors
Hard spatial
priors
1.5:1
3.3:1
6.6:1
Acknowledgements:
Layered Phantoms
10:1 tumor to outer layer
3.3:1 tumor to Layer 2
Venkat
Shudong
Krishnaswamy Jiang
Wendy
Wells
Jack
Hoopes
Subha
Srinivasan
Steve
Poplack
Kim
Samkoe
Peter
Kaufman
Brian Wilson
U. Toronto
Scott
Davis
Tayyaba Hasan
Harvard Med.
Brian
Pogue
Engineering &
Med School Colleagues
Graduate Students
No spatial priors
Soft spatial priors
Hard spatial priors
Josiah
Gruber
Zhiqiu Li
Colin
Carpenter
Dax
Kepshire
Jia Wang
Ashley
Laughney
Imran
Rizvi
Alumni
Heng
Xu
Ben
Brooksby
Chao
Sheng
Troy
McBride
Hamid
Daqing
Phani
Xin
Summer
Yalavarthy Gibbs-Strauss
Wang Dehghani Piao
Bin
Chen
FUNDING:
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