Post on 29-Mar-2015
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 4PediatricsUniversity 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,
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
Lung Disease Structural Changes Perfusion Changes
Pulmonary Emboli Lumen of the pulmonary artery
Regional decrease in perfusion
Chronic Obstructive Pulmonary Disease (COPD)
Mucus plugging of the airways
Loss of ventilation results in compensatory decrease in perfusion
Fibrosis Architectural distortions Regional decrease in perfusion
Background: Lung Imaging Challenges
MR imaging of the lungs is difficult due to:
1) Cardiac and Respiratory Motion
2) Low Proton Density
(0.15 g/ml)
3) Lung alveoli create local field inhomogenities and susceptibility gradients very short T2* (~1ms)
†Fawcett/Gehr/Science Photo Library
Rapid dephasing of inherently low signal.
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
breath-holds in patients who are often short of breath
– Can make it difficult to correlate the perfusion and structural abnormalities due to misregistration
Background: Current Imaging Methods
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
To develop and demonstrate a high resolution breath-held 3D radial UTE acquisition to simultaneously visualize lung perfusion and structure.
Purpose
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:
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
Scan Parameter Value
Total projections: 8,000
TR/TE: 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: 1 frame/sec
Total scan time: 33 sec breath-hold
†Johnson KM et al “Optimized 3D ultrashort echo time pulmonary MRI”
Methods: Data ReconstructionReconstruction 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
One dataset of 8,000 projectio
ns
Iterative Sensitivity Encoding Algorithm
Composite image
of structure
33 time frames each w/
242 projs
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
33 perfusion images
Methods: 3D Radial UTE Reconstruction Workflow Fin
al R
eco
nstru
cted
Imag
es
Raw
Data
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
0 5 10 15 20 25 30
Lung
Pulm Artery
Aorta
Time [sec]
Sig
na
l [A
.U.]
Coronal MIPS show first pass of contrast bolus at 1 frame/sec with 0.94 mm isotropic spatial resolution
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 co-registrated
Structural images show good depiction of airway, vessels, and lung tissue
Perfusion images show normal physiologic gravitational gradient in the A/P direction
Minimal cardiac motion due to ultrashort TE and radial sampling
Top Row: rPBF maps co-registered to structureBottom Row: Corresponding structural images
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
Christopher FrancoisSara PladziewiczRebecca JohnsonGrzegorz Bauman
Funding
Acknowledgements
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”
UW MadisonThis 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.