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Dynamic Myocardial Perfusion in a
Porcine Balloon-induced Ischemia Model
using Spectral Detector CT
Rachid Fahmi 1, Ph.D.,
Brendan Eck1, Jacob Levi1, Anas Fares2, Mani Vembar3, Amar Dhanantwari3,
Hiram Bezerra2, and David Wilson1,4
1 Biomedical Imaging Laboratory, Case Western Reserve University
2 Harrington Heart and Vascular Institute, University Hospitals, Case Medical Center
3 Philips Healthcare
4 Radiology, Case Western Reserve University
rxf143@case.edu
Investigate the performance of dual energy CT (DECT) with a prototype
spectral detector CT (SDCT) scanner (Philips Healthcare) to perform
dynamic myocardial CT perfusion (CTP) on a percutaneous porcine
model with adjustable coronary occlusion guided by fractional flow
reserve (FFR) measurements.
Objective
Adding robust cardiac CTP to coronary CTA will make CT a one stop
shop imaging modality for cardiac imaging.
Clinical Relevance
Clinical use of CTP remains limited to date due in part to x-ray dose, BH
artifacts, and partial scan artifacts.
Current Challenges
Context and motivation
How can we address some CTP challenges?
• DECT has the potential of producing images free of beam hardening artifacts
by synthesizing mono-energetic (monoE) images.
• Dynamic CTP requires faster scanners to avoid partial scan artifacts.
• Coronary CTA is the only non-invasive imaging method capable of detecting
coronary stenoses.
• Significant discordance between angiographic stenosis (anatomy) and
myocardial ischemia (function).
• Over 60% of invasive coronary angiographies (ICA) are negative, subjecting
patients to unnecessary discomfort/risk, and driving up costs.
• No existing non-invasive test to assess both anatomic and functional
ischemia in a single setting.
• Current guidelines recommend documenting ischemia with a non-invasive
functional test (s.a., SPECT, MR).
• CT may be the perfect gatekeeper exam giving both anatomy (CTA) and
function (CTP), a one-stop-shop for value-based reimbursement.
DECT Technologies
“Dual Source”
Two x-ray spectra (e.g.,
80kV and 140kV)
“Single source with dual
kV” in single rotation (e.g.,
80kV and 140kV)
“Spectral Detector System”
One x-ray source and two
energy-resolving detectors
… Single source and kV switching between sequential gantry rotations.
… Or photon counting detector
• Simultaneous detection of low and high x-ray photon energies:
 Low and high projection data are perfectly registered, spatially
and temporally, with each other.
 Ideal for imaging moving objects such as a beating heart.
• Allows for projection space reconstruction and processes
 Accurate material decomposition and BH correction.
• Fast gantry rotation (0.27s)
 Allows full 360degree acquisitions
 No shading artifacts in dynamic acquisitions.
• Full field of view (FOV) acquisitions (50cm).
• No cross scatter .
Some advantages of the SDCT system
Generation of monoE images
( ) ( ) ( )1 2
1 2
, ( ) ( )r E r E r E
µ µ
µ ρ ρ
ρ ρ
   
= +   
   
Two basis material
sinograms
Two basis material
density maps
70keV50keV 120keV
Synthesized
monoE images
Cylindrical acrylic phantom:
diameter: 26 cm
thickness: 6cm
8 inserts
Measured iodine
concentrations (IC) from
iodine equivalent-density
image versus real IC used in
the phantom.
Phantom Experiment
y = 1.0586x + 0.1298
R² = 0.9999
0
2
4
6
8
10
12
0 2 4 6 8 10 12
Measured[mgI/mL]
Real [mgI/mL]
Accuracy of material decomposition
Linearity of mean HU vs. iodine concentration for monoE scans
-40
-20
0
20
40
60 70 80 90 100 110 120 120kVp
BHA(HU)
keV
conventional monoE
Optimal keV?
70keV is chosen as
the optimal keV to
quantify blood flow
at high iodine CNR
and low noise level.
Cardiac CTP Experiments: porcine model
Animal preparation in surgical suite:
placement of FFR wire, balloon, and
microsphere injections
Acquisition of CTP scans for different
hemodynamic conditions guided by FFR
Fluorescent image of microsphere
deposition in myocardium used for
ground truth flow quantification
FFR readings to achieve
a targeted ischemia level
Preparation of heart for
freezing and Cryo-imaging
• First myocardial CT perfusion using the SDCT scanner.
Imaging Protocol
11
• Prospective ECG-triggered scans at end systole (45% R-R).
• Tube Voltage: 120kVp; Tube Current: 100mAs.
• Full 360 degree scan coverage.
• Omnipaque 350 followed by saline flush (20 mL @ 5 mL/sec).
• Initiate scan 3-4sec post injection, and acquire every heart beat a total of
30-35 volumetric scans (< 25sec) with respirator off.
• Scan under different hemodynamic conditions, with >15min between
consecutive scans.
• Conventional and monoE reconstructions of 2mm thick slices with no overlap.
• Motion correction using a cubic B-spline deformable registration model.
• Average CT map generation from registered scans.
• Semi-automatic segmentation of LV myocardium using averaged CT volume.
• Propagate segmentation results to entire 4D sequence.
• Model-independent deconvolution method based on bSVD with Tikhonov
regularization to quantify myocardial blood flow (MBF).
Recons and Preprocessing
tissue artC (t) F.C (t) R(t)= ⊗
• Arterial input function and tissue time-attenuation curve are related by
Quantification of Myocardial Blood Flow
• Ill-posed problem due to noise  Regularize using Tikhonov method
2 22
2 2x
x argmin( x x )A b Lλ= − +
2
2 2
1
.b
x ( ). .
Tn
i i
i
i i i
u
vλ
σ
σ λ σ=
=
+
∑
• Solve for flow-scaled IRF, x=F.R(t), using bSVD decomposition of
1
1
.
x ( . . ). ( ).
Tn
T i
i
i i
b
V U b
σ
−
=
=Σ =∑
u
v
2
2x
x argmin( x )lsq A b= −
. .VT
A U= Σ
• Discretize and transform into an algebraic form
.xA b= 1. (t ) 0 ,
0 .
a i j
ij
t C for j i
a
for j i
− −∆ ≤ <
= 
≥
( ),i tissue ib C t=with and
log xA b−
optλ
Less filtering
More filtering
log Lx
How to pick ?λ
• L-curve criterion (LCC): log-log plot of for a range of values( Lx , x )A bλ λ − λ
• Fit a smooth spline to obtained data points.
• Optimal corresponds to location on fitted spline with max curvature.λ
• If too small: noisy solution.
• If too large: poor approximation to real solution.
λ
λ
• Due to high iodine concentration in aorta and heart chambers and to the polychromatic
x-ray beam, some BH artifacts appear as hypo-enhanced areas on myocardium.
• These artifacts may be construed as perfusion defects. If uncorrected they lead to
inaccurate perfusion quantification.
• BH artifacts are significantly reduced on the projection-based 70keV images.
Beam hardening (BH) artifacts
Successive slices corresponding to a baseline scan (FFR=1).
W/L:150/60
Conventional
120kV
monoE
70keV
Baseline scan: no inflation
• Baseline scan with balloon deflated.
• Deconvolution of distorted arterial and
myocardial TACs leads to inaccurate MBF
measurments.
Effects of BH on TACs
and quantified MBF
120kV 70keV
120kV 70keV
• 15% flow reduction in BH-affected
myocardial regions in 120kV data vs. 70keV.
• BH effects distort tissue TACs in 120kV
images.
• BH effects on myocardial TACs are
significantly reduced for 70keV.
0
20
40
60
80
100
120
Antero-septal Inferior Lateral Anterior
MBF(ml/min/100g)
Myocardial wall
120 kVp
0
20
40
60
80
100
120
Antero-septal Inferior Lateral Anterior
MBF(ml/min/100g)
Myocardial wall
70 keV
• Baseline scan with balloon completely deflated.
• Reduced BH artifacts in 70keV lead to more
uniform MBF throughout the non-ischemic
myocardium compared to 120kV-based MBF.
BH effects MBF (Cont’d)
• Detection of ischemia in correct LAD territory (FFR~0.35).
• Consistency of MBF quantification across several consecutive slices.
• BH artifacts lead to inaccurate perfusion measurements for conventional 120kV data:
 BH lead to underestimation of mean MBF in anterior and inferior walls (yellow arrows).
 BH and higher noise lead to overestimation of mean flow in mid-septal and infero-lateral walls(red arrows).
MonoE 70keV
Conventional 120kV
Slice2 Slice8Slice6Slice4 ml/min/100g
Ischemic case
Slice2 Slice8Slice6Slice4
ischemic
ratio
normal
mbf
F
mbf
=
Validation of MBF quantification
• Use relative flow as ratio of mean ischemic to mean normal flow and compare against
wire FFR for different hemodynamic conditions:
*
**
***
p=0.001 from 70keV
p=0.002 from 70keV
p=0.08 from 70keV*
***
**
• Compute and average over 15 adjacent slices and compare results to pressure
FFR target for normal and two ischemic conditions.
ratioF
Summary
• We reported the first dynamic CT perfusion findings using a novel
percutaneous porcine model and Philips’s SDCT scanner.
• Simultaneous acquisitions of LE & HE data permits synthesis of projection-
based monoE images relatively free of BH artifacts.
• A phantom experiment designed to analyze sensitivity of iodine detection for
monoE images vs. conventional single energy CT.
• 70keV chosen as the optimal energy for myocardial CTP assessment.
• Designed a comprehensive processing tools for quantitative myocardial CTP.
• Compared to conventional SECT, 70keV-based flow less affected by BH and
corresponding relative flow correlates better with pressure FFR values.
• Ongoing work:
• Additional animal studies.
• CTP validation against microspheres-based measurements.
Acknowledgments
Biomedical Imaging Lab
Hao Wu
Radiology
Scott Esposito
Philips Healthcare
Tsvi Katchalski, PhD (Haifa, Israel)
Steve Utrup (Cleveland, OH)
Funding
Ohio Third Frontier research grant from the state of Ohio
to CWRU, Univ. Hospitals and Philips Healthcare, OH.
Surgery
Steve Schomisch, PhD
Cassandra Cipriano
Cardiovascular CORE Lab
Xiaorong Zhou, MD
Kashif Shaikh, MD
THANK YOU
QUESTIONS

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SPIE_2015_Fahmi

  • 1. Dynamic Myocardial Perfusion in a Porcine Balloon-induced Ischemia Model using Spectral Detector CT Rachid Fahmi 1, Ph.D., Brendan Eck1, Jacob Levi1, Anas Fares2, Mani Vembar3, Amar Dhanantwari3, Hiram Bezerra2, and David Wilson1,4 1 Biomedical Imaging Laboratory, Case Western Reserve University 2 Harrington Heart and Vascular Institute, University Hospitals, Case Medical Center 3 Philips Healthcare 4 Radiology, Case Western Reserve University rxf143@case.edu
  • 2. Investigate the performance of dual energy CT (DECT) with a prototype spectral detector CT (SDCT) scanner (Philips Healthcare) to perform dynamic myocardial CT perfusion (CTP) on a percutaneous porcine model with adjustable coronary occlusion guided by fractional flow reserve (FFR) measurements. Objective Adding robust cardiac CTP to coronary CTA will make CT a one stop shop imaging modality for cardiac imaging. Clinical Relevance Clinical use of CTP remains limited to date due in part to x-ray dose, BH artifacts, and partial scan artifacts. Current Challenges
  • 3. Context and motivation How can we address some CTP challenges? • DECT has the potential of producing images free of beam hardening artifacts by synthesizing mono-energetic (monoE) images. • Dynamic CTP requires faster scanners to avoid partial scan artifacts. • Coronary CTA is the only non-invasive imaging method capable of detecting coronary stenoses. • Significant discordance between angiographic stenosis (anatomy) and myocardial ischemia (function). • Over 60% of invasive coronary angiographies (ICA) are negative, subjecting patients to unnecessary discomfort/risk, and driving up costs. • No existing non-invasive test to assess both anatomic and functional ischemia in a single setting. • Current guidelines recommend documenting ischemia with a non-invasive functional test (s.a., SPECT, MR). • CT may be the perfect gatekeeper exam giving both anatomy (CTA) and function (CTP), a one-stop-shop for value-based reimbursement.
  • 4. DECT Technologies “Dual Source” Two x-ray spectra (e.g., 80kV and 140kV) “Single source with dual kV” in single rotation (e.g., 80kV and 140kV) “Spectral Detector System” One x-ray source and two energy-resolving detectors … Single source and kV switching between sequential gantry rotations. … Or photon counting detector
  • 5. • Simultaneous detection of low and high x-ray photon energies:  Low and high projection data are perfectly registered, spatially and temporally, with each other.  Ideal for imaging moving objects such as a beating heart. • Allows for projection space reconstruction and processes  Accurate material decomposition and BH correction. • Fast gantry rotation (0.27s)  Allows full 360degree acquisitions  No shading artifacts in dynamic acquisitions. • Full field of view (FOV) acquisitions (50cm). • No cross scatter . Some advantages of the SDCT system
  • 6. Generation of monoE images ( ) ( ) ( )1 2 1 2 , ( ) ( )r E r E r E µ µ µ ρ ρ ρ ρ     = +        Two basis material sinograms Two basis material density maps 70keV50keV 120keV Synthesized monoE images
  • 7. Cylindrical acrylic phantom: diameter: 26 cm thickness: 6cm 8 inserts Measured iodine concentrations (IC) from iodine equivalent-density image versus real IC used in the phantom. Phantom Experiment y = 1.0586x + 0.1298 R² = 0.9999 0 2 4 6 8 10 12 0 2 4 6 8 10 12 Measured[mgI/mL] Real [mgI/mL] Accuracy of material decomposition
  • 8. Linearity of mean HU vs. iodine concentration for monoE scans
  • 9. -40 -20 0 20 40 60 70 80 90 100 110 120 120kVp BHA(HU) keV conventional monoE Optimal keV? 70keV is chosen as the optimal keV to quantify blood flow at high iodine CNR and low noise level.
  • 10. Cardiac CTP Experiments: porcine model Animal preparation in surgical suite: placement of FFR wire, balloon, and microsphere injections Acquisition of CTP scans for different hemodynamic conditions guided by FFR Fluorescent image of microsphere deposition in myocardium used for ground truth flow quantification FFR readings to achieve a targeted ischemia level Preparation of heart for freezing and Cryo-imaging • First myocardial CT perfusion using the SDCT scanner.
  • 11. Imaging Protocol 11 • Prospective ECG-triggered scans at end systole (45% R-R). • Tube Voltage: 120kVp; Tube Current: 100mAs. • Full 360 degree scan coverage. • Omnipaque 350 followed by saline flush (20 mL @ 5 mL/sec). • Initiate scan 3-4sec post injection, and acquire every heart beat a total of 30-35 volumetric scans (< 25sec) with respirator off. • Scan under different hemodynamic conditions, with >15min between consecutive scans. • Conventional and monoE reconstructions of 2mm thick slices with no overlap. • Motion correction using a cubic B-spline deformable registration model. • Average CT map generation from registered scans. • Semi-automatic segmentation of LV myocardium using averaged CT volume. • Propagate segmentation results to entire 4D sequence. • Model-independent deconvolution method based on bSVD with Tikhonov regularization to quantify myocardial blood flow (MBF). Recons and Preprocessing
  • 12. tissue artC (t) F.C (t) R(t)= ⊗ • Arterial input function and tissue time-attenuation curve are related by Quantification of Myocardial Blood Flow • Ill-posed problem due to noise  Regularize using Tikhonov method 2 22 2 2x x argmin( x x )A b Lλ= − + 2 2 2 1 .b x ( ). . Tn i i i i i i u vλ σ σ λ σ= = + ∑ • Solve for flow-scaled IRF, x=F.R(t), using bSVD decomposition of 1 1 . x ( . . ). ( ). Tn T i i i i b V U b σ − = =Σ =∑ u v 2 2x x argmin( x )lsq A b= − . .VT A U= Σ • Discretize and transform into an algebraic form .xA b= 1. (t ) 0 , 0 . a i j ij t C for j i a for j i − −∆ ≤ < =  ≥ ( ),i tissue ib C t=with and
  • 13. log xA b− optλ Less filtering More filtering log Lx How to pick ?λ • L-curve criterion (LCC): log-log plot of for a range of values( Lx , x )A bλ λ − λ • Fit a smooth spline to obtained data points. • Optimal corresponds to location on fitted spline with max curvature.λ • If too small: noisy solution. • If too large: poor approximation to real solution. λ λ
  • 14. • Due to high iodine concentration in aorta and heart chambers and to the polychromatic x-ray beam, some BH artifacts appear as hypo-enhanced areas on myocardium. • These artifacts may be construed as perfusion defects. If uncorrected they lead to inaccurate perfusion quantification. • BH artifacts are significantly reduced on the projection-based 70keV images. Beam hardening (BH) artifacts Successive slices corresponding to a baseline scan (FFR=1). W/L:150/60 Conventional 120kV monoE 70keV
  • 15. Baseline scan: no inflation • Baseline scan with balloon deflated. • Deconvolution of distorted arterial and myocardial TACs leads to inaccurate MBF measurments. Effects of BH on TACs and quantified MBF 120kV 70keV 120kV 70keV • 15% flow reduction in BH-affected myocardial regions in 120kV data vs. 70keV. • BH effects distort tissue TACs in 120kV images. • BH effects on myocardial TACs are significantly reduced for 70keV.
  • 16. 0 20 40 60 80 100 120 Antero-septal Inferior Lateral Anterior MBF(ml/min/100g) Myocardial wall 120 kVp 0 20 40 60 80 100 120 Antero-septal Inferior Lateral Anterior MBF(ml/min/100g) Myocardial wall 70 keV • Baseline scan with balloon completely deflated. • Reduced BH artifacts in 70keV lead to more uniform MBF throughout the non-ischemic myocardium compared to 120kV-based MBF. BH effects MBF (Cont’d)
  • 17. • Detection of ischemia in correct LAD territory (FFR~0.35). • Consistency of MBF quantification across several consecutive slices. • BH artifacts lead to inaccurate perfusion measurements for conventional 120kV data:  BH lead to underestimation of mean MBF in anterior and inferior walls (yellow arrows).  BH and higher noise lead to overestimation of mean flow in mid-septal and infero-lateral walls(red arrows). MonoE 70keV Conventional 120kV Slice2 Slice8Slice6Slice4 ml/min/100g Ischemic case Slice2 Slice8Slice6Slice4
  • 18. ischemic ratio normal mbf F mbf = Validation of MBF quantification • Use relative flow as ratio of mean ischemic to mean normal flow and compare against wire FFR for different hemodynamic conditions: * ** *** p=0.001 from 70keV p=0.002 from 70keV p=0.08 from 70keV* *** ** • Compute and average over 15 adjacent slices and compare results to pressure FFR target for normal and two ischemic conditions. ratioF
  • 19. Summary • We reported the first dynamic CT perfusion findings using a novel percutaneous porcine model and Philips’s SDCT scanner. • Simultaneous acquisitions of LE & HE data permits synthesis of projection- based monoE images relatively free of BH artifacts. • A phantom experiment designed to analyze sensitivity of iodine detection for monoE images vs. conventional single energy CT. • 70keV chosen as the optimal energy for myocardial CTP assessment. • Designed a comprehensive processing tools for quantitative myocardial CTP. • Compared to conventional SECT, 70keV-based flow less affected by BH and corresponding relative flow correlates better with pressure FFR values. • Ongoing work: • Additional animal studies. • CTP validation against microspheres-based measurements.
  • 20. Acknowledgments Biomedical Imaging Lab Hao Wu Radiology Scott Esposito Philips Healthcare Tsvi Katchalski, PhD (Haifa, Israel) Steve Utrup (Cleveland, OH) Funding Ohio Third Frontier research grant from the state of Ohio to CWRU, Univ. Hospitals and Philips Healthcare, OH. Surgery Steve Schomisch, PhD Cassandra Cipriano Cardiovascular CORE Lab Xiaorong Zhou, MD Kashif Shaikh, MD