1. PROPELLER Acquisition on the Philips Achieva

2. circular region of overlap at center of k-space
What is PROPELLER?
Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction – JG PIPE MRM 1999
k-space is sampled by multiple cartesian “blades”
Blades overlap in circular region at center of k-space
Overlap allows for
in-plane motion correction (rigid rotation/translation)
reject/underweight of inconsistent blades (through-plane or non-rigid motion)
circular region of overlap at center of k-space

3. PROPELLER does address other motions
From Pipe
MRM 1999

4. What’s the big deal about PROPELLER?
Allows dramatic motion correction of axial T2W brain images – heavily marketed by GE
Promising results as a multi-shot high resolution DWI/DTI technique (fewer B0-related artifacts than single-shot techniques)
Many recent papers and abstracts extending it uses
Term “PROPELLER” occurs 33 times in ISMRM 2005 program
Improved GraSE and EPI versions with parallel imaging

5. GE Healthcare web page on PROPELLER

6. PROPELLER at ISMRM 2005 T1W PROPELLER - #2236
Variable pitch PROPELLER for MRA - #2239
Mapping the anterior commissure - #12
High resolution DTI at 3T – #9
T2* mapping – #291
SPIO-enhanced DWI of Liver - #1881
Imaging of the female pelvis - #2698

7. Is PROPELLER more RADIAL or or more CARTESIAN?

8. Ans: RADIAL and CARTESIAN are special cases of PROPELLER!
LN=Mπ/2
L = # lines/blade
N = # blades
M = Readout matrix size
RADIAL
CARTESIAN
L=1
N= Mπ/2
N=1
L= M

9. PROPELLER implementation on the Philips Achieva
Strategy
Implementation
Treat PROPELLER as a “cartesian-like” scan
Allow prescription of very low resolution cartesian scan
Repeat the cartesian scan and rotate about the slice-select axis
Add new “propeller” option for “Acquisition Mode” that is treated internally as “cartesian”
New lower bound for “Scan Percentage”
Take advantage of the O_MATRIX object available in Philips pulse programming

10. PROPELLER patch interface

11. PROPELLER patch interface

12. PROPELLER : patch acquisition results
Matrix size = 256
Scan % = 9.38%
17 blades
TSE Factor = 24
18 slices
Scan time = 102 secs

13. PROPELLER: Image Reconstruction
Regridded using Kaiser-Bessel convolution
Iterative sampling density compensation

14. Motion Correction Validation
Acquire multiple phantom PROPELLER datasets
Each has different known Offsets and Angulations
1st scan undergoes FULL preparation phases subsequent scans skip prep. phases (SAMEPREP)
A set of blades randomly selected from datasets to create composite set containing “motion corruption”
PROPELLER algorithm reconstructs (and motion corrects) composite data set
Detected motions compared to known differences

15. Motion Correction Validation: in-plane rotation + in-plane translation
UNCORRECTED
CORRECTED

16. Motion Correction Validation: in-plane rotation + in-plane translation
UNCORRECTED
CORRECTED

17. PROPELLER Motion Correction: Low-Resolution “Disk Images”

18. PROPELLER PLUS – for lack of a better name
DC value based blade rejection
May allow recollection of problems blades
Should improve motion correction results by removing severely inconsistent blades from motion correction steps
Center of Mass translation correction (before rotation)
Allows use of complex k-space values for rotation correction step
Uses full resolution of long axis of each blade
Iterative rotational alignment
Each blade is rotationally aligned to the “average” blade which iterative updated until the rotational alignment converges
Should improve results in date with larger rotations
Combination with original published steps
Image based rotation and translation correction can still be performed – may refine/improve results

19. PROPELLER PLUS on the Philips Achieva
4/25/2017
PROPELLER PLUS on the Philips Achieva
Translation correction before rotation correction
k-space magnitude and phase used for rotational alignment
Iterative rotational alignment
Correction results of subject
executing in-plane motion
PROPELLER data is T2W TSE, 17 blades, TSE Factor=24, Matrix size=256
18 slices acquired in 1 minute 42 seconds, TE=80msec, TR=3000msec
Acquired using the T/R head coil (one channel of data for simplicity’s sake) on a 3.0T Achieva at Vanderbilt University
Reconstructed and corrected off-line using .list/.data files, algorithms implemented in Matlab
Overall reconstruction and motion correction is based on published propeller work by Jim Pipe with some notable “PLUS” features:
1. Translation correction is achieved using center of mass consistency properties of the spatial domain projections contained within each blade. It is performed before rotation correction, unlike the published algorithms
2. Because translation is performed first, both magnitude and phase information can be used in the rotational alignment of the blades. This allows detection of blade alignments over the full range of 0 to 360 degrees. Published propeller algorithms use magnitude information only and because of symmetry in k-space, such an approach can only correctly detect blade alignments over the range 0 to 180 degrees.
3. Rotational alignment is performed iteratively. Each blade is rotationally aligned with the “average blade” and the averaged blade is recalculated in each iteration from the current best estimate of the blade alignments.
The phantom-based motion detection validation results were gathered using the Philips resolution phantom and the T/R head coil. Multiple datasets with various known offcenters and angulations were collected. The preparation parameters (gains, F0, etc.) were forced to be consistent across all data sets. Artificial datasets were created by mixing blades from the various original datasets. Detected translations and rotations were compared to the known relative displacements.
Phantom-based Motion Detection Validation Results
Mean Absolute Error
0.14 mm and 0.11°

20. PROPELLER: ISMRM 2006 submission
** Accepted for presentation as electronic poster **

21. PROPELLER: ISMRM 2006 submission

22. PROPELLER: completed steps
Patch for acquisition of PROPELLER data 
Kaiser-Bessel convolution kernel regridding 
Implement motion correction steps: 
in-plane rotation 
in-plane translation 
inconsistent blade rejection -

23. PROPELLER: next steps GraSE and EPI reconstruction
Modifications for add’l prep. phase corrections
Modifications for T1W PROPELLER
Modifications for improved TSE PROPELLER DWI
On-host reconstruction using Gyrotools (Zurich) reconstruction paradigm
SENSE reconstructions
Real-time feedback to recollect inconsistent blades

24. What to call PROPELLER on the Philips system?
GE already uses PROPELLER
Rumors are that Siemens will call it BLADE
Why not WINDMILL? Philips is Dutch afterall!