Transcript Laura C Bell - Department of Radiology, University of Wisconsin

Simultaneous Single Breath-hold MR
Imaging of Lung Perfusion and Structure
using 3D Radial UTE
Laura C Bell1, Kevin M Johnson2,
Sean B Fain1, Randi Drees3, Scott K Nagle1,2,4
Departments of 1Medical Physics , 2Radiology, 3Veterinary Medicine, and 4Pediatrics
University of Wisconsin – Madison, WI, U.S.A
Outline
 Introduction
 Background
- Challenges in Lung Imaging
- Current Structure and Perfusion Techniques
 Methods
- Dog Experiments
- MR Protocol and Post-Processing
 Results/Discussion
 Future Work
Introduction
 Many lung diseases cause structural changes in the lungs and also impair
lung function such as pulmonary perfusion or ventilation. For example,
Lung Disease
Structural Changes
Pulmonary Emboli Lumen of the pulmonary artery
Chronic Obstructive Pulmonary
Mucus plugging of the airways
Disease (COPD)
Fibrosis Architectural distortions
Perfusion Changes
Regional decrease in perfusion
Loss of ventilation results in
compensatory decrease in
perfusion
Regional decrease in perfusion
 Often, structural imaging is desired to rule-out alternative diagnoses that
may not manifest perfusion abnormalities
 Recently, ultra short echo times (UTE) sequences have allowed for high
resolution structural visualization of the lung
Background: Lung Imaging Challenges
MR imaging of the lungs is difficult due to:
1) Cardiac and
Respiratory
Motion
3) Lung alveoli create local
field inhomogenities and
susceptibility gradients 
very short T2* (~1ms)
†Fawcett/Gehr/Science Photo Library
2) Low Proton Density
(0.15 g/ml)
Rapid
dephasing of
inherently
low signal.
Background: Current Imaging Methods
 Structural lung imaging has recently benefited
from the development of 3D Radial UTE
sequences 1-3
 Highly accelerated contrast-enhanced perfusion
MR imaging has allowed for sufficiently high
temporal resolution (~1 sec) with good spatial
resolution (3 – 4 mm3) typically acquired with
spoiled gradient echo sequences
 Therefore, evaluation of both perfusion and
vascular structure require separate scans which:
– Increases scan time and number of breathholds in patients who are often short of breath
– Can make it difficult to correlate the perfusion
and structural abnormalities due to
misregistration
Cystic Fibrosis patient
[1] Togao O et al, MRM (2010), v64, 1491 – 1498
[2] Kuethe DO et al, MRM (2007), v57, 1058 - 1064
[3] Johnson KM et al, MRM (2012), Optimized 3D ultrashort echo time pulmonary MRI
[4] Wang K et al, J Magn Reson Imaging (2013), Pulmonary Perfusion MRI using IVD sampling and HYCR
Purpose
To develop and demonstrate a high resolution
breath-held 3D radial UTE acquisition to
simultaneously visualize lung perfusion and
structure.
Methods
 Nine healthy dogs were imaged twice (separated by 2 – 4 days) resulting in
18* datasets
– 8 males & 1 female
– Weight 10.7 7± 1.2 kg
– Mean age 13 months
 Dogs were ventilated and placed in the scanner in the supine position
 3T clinical scanner
 20 elements of a commercial 32-channel phased array chest coil
* The first two datasets had different scan parameters, and therefore were eliminated for analysis in this study.
Methods: Imaging Protocol
 Pseudo-random temporally interleaved 3D radial UTE imaging during
injection of 2.3 ml of gadobenate dimeglumine followed by a 17 ml saline
flush at 2 ml/sec in the cubital vein
 Dynamic 3D Radial UTE scan parameters:
Scan Parameter
Value
Total projections:
TR/TE:
8,000
3.3/0.08 ms
Flip Angle:
15°
Readout time:
1 ms
Field of View:
24 x 24 x 24 cm3
Spatial Resolution:
0.94 mm istropic
Acquired frame rate:
Total scan time:
1 frame/sec
33 sec breath-hold
 Optimization of the 3D Radial UTE sequence† required no hardware
modifications:
– Slab-selective RF excitation with limited FOV
– Variable read-out gradients
– Radially oversampled projections
†Johnson KM et al “Optimized 3D ultrashort echo time pulmonary MRI”
Methods: Data Reconstruction
Reconstruction of 3D Radial UTE data:
 IIterative sensitivity encoding algorithm (iSENSE) was used
 For structural images: composite reconstruction using all 8,000 projections
 For time-resolved perfusion images: temporal view-sharing method
– Filter has a width of 1 sec at the center of k-space and quadratically
increases to 7 sec at the edge of k-space
Composite
image of
structure
One
dataset of
8,000
projections
33 time
frames
each w/
242 projs
33
perfusion
images
Iterative Sensitivity
Encoding Algorithm
Adaptive k-space filter:
Width of 1 sec of center of
k-space and quadratically
increase to 7 sec at the
edge of k-space
33 time
frames
each w/
~2,000
projs
Iterative Sensitivity
Encoding Algorithm
Final Reconstructed Images
Raw Data
Methods: 3D Radial UTE Reconstruction Workflow
Methods: Data Analysis
,
 Relative Tissue Enhancement measurements
– (Max signal – Baseline signal) / Baseline signal
– Mean signal determined from circular ROI placed in the right lung
 Temporal Waveforms
– Circular ROIs centered on pulmonary artery and aorta
 Right Ventricle (RV) to Aorta Transit Times
– Mean signal determined from circular ROIs centered in the RV and the
descending aorta
– Transit time between max signal in RV and max signal in aorta
 Qualitative Relative Pulmonary Blood Flow (rPBF) maps
– Calculated by indicator dilution method on a pixel-by-pixel basis
†Meier P et al, J Appl Physiol (1954), 6:731-744
Results: Tissue Enhancement and Temporal Waveforms
 Relative lung
enhancement: 7.7 ± 1.5
compared to baseline
 RV to Aorta Transit
Times: 7.4 ± 2.0 sec
Coronal MIPS show first pass of contrast bolus at 1
frame/sec with 0.94 mm isotropic spatial resolution
Lung
Pulm Artery
Signal [A.U.]
Aorta
0
5
10
15
Time [sec]
20
25
30
Results: Tissue Enhancement and Temporal Waveforms
Coronal MIPS show first pass of contrast bolus at 1
frame/sec with 0.94 mm isotropic spatial resolution
Results: Qualitative rPBF maps co-registered to structure
Discussion:
 Same dataset =
Intrinsically coregistrated
 Structural images
show good depiction of
airway, vessels, and
lung tissue
 Perfusion images
show normal
physiologic gravitational
gradient in the A/P
direction
Top Row: rPBF maps co-registered to structure
Bottom Row: Corresponding structural images
 Minimal cardiac
motion due to ultrashort
TE and radial sampling
Future Work
 Co-registration of lung structure and perfusion in one
breath-hold in healthy dogs is feasible:
– Sufficient signal is available for structural visualization and perfusion
analysis
– High isotropic resolution (0.94 mm)
– Acquisition is robust to cardiac and respiratory motion
– To authors’ knowledge this is the first example of time-resolved 3D
UTE sequence in large animals
 Future work:
 Application of constrained reconstruction methods (e.g. compressed
sensing or HYPR)
 Pulse sequence development to allow for more quantitative
hemodynamic analysis
 Apply this method to different lung diseases
Acknowledgements
UW Madison
Christopher Francois
Sara Pladziewicz
Rebecca Johnson
Grzegorz Bauman
Funding
This project was supported by
Clinical and Translational Science Award (CTSA)
program, previously through the National Center
for Research Resources (NCRR) grant
1UL1RR025011, and now by the National Center
for Advancing Translational Sciences (NCATS),
grants 9U54TR000021.
The UW School of Medicine and Public Health
from the Wisconsin Partnership Program.
Check out our other UTE lung abstracts at ISMRM this year:
#2005 Johnson KM, “Lung Tissue Differentiation with Magnetization Transfer Prepared Multi-Echo UTE MRI”
#4538 Kruger SJ, “3D Radial Oxygen Enhanced Imaging in Normal and Asthmatic Human Subjects”