Présentation de la méthode de correction de mouvements TEP-IRM au colloque biennal "Recherche en Imagerie et Technologies pour la Santé (RITS)" 2017

1. General Overview
Anthonin Reilhac1, Rania Berrada1, Zacharie Irace1, Inés Mérida1, Clara Fonteneau1, Marie-Françoise Suaud-Chagny2, Nicolas Costes1
1CERMEP ‐ Imagerie du vivant, Lyon, France, 2Centre de Recherche en Neurosciences de Lyon, Equipe PSYR2, Lyon, France
Material
Assessment of the correction performance obtained with different configurations is done using
realistic Monte Carlo simulated data.
Show cases from selected actual studies are also presented.
Simulation - Simulated 600 secs list-mode FDG acquisition using PET-SORTEO [3], and for
which the motion was applied at t = 200 secs.
Actual Studies - Dynamic 110 min [11C]Raclopride acquisition.
Rigid body motions are estimated on an initial reconstruction with 66 short time frames (100s).
- Static 30 min [11C]PIB acquisition.
Rigid body motions are estimated on an initial reconstruction with19 short time frames (20s).
Eber: A List Mode Rebinner for Motion Correction
in PET-MRI Brain Imaging
www.cermep.fr
Introduction
Head motion occurring during brain PET acquisition leads to
• image blurring
• inaccurate localization of structures
• bias in measured local quantities
• errors in the parameter estimates derived from kinetic modeling
Motions can happen at anytime, and do not correspond to the arbitrary framing of the
reconstructed PET. Correction methods based on post-recontruction images correction can not
handle with intraframe motion.
With simultaneous recording of PET and MRI using hybrid MR-PET scanner, motion can be
estimated with higher frequency (2s in fMRI).
To use this motion information a specific rebinner of PET list-mode is needed.
Results
Conclusion
A list mode rebinner for the mMR scanner including rigid body motion correction capability has been developed and fully validated.
In these preliminary results, motions were estimated from an inital reconstruction using short frames,.
Alternatively, simultaneously acquired high temporal resolution MR-data such as with parallel fMRI sequences could be used for motion estimation.
References
[1] Costes, Nicolas, Alain Dagher, Kevin Larcher, Alan C. Evans, D. Louis Collins, and Anthonin Reilhac. 2009. "Motion correction of
multi-frame PET data in neuroreceptor mapping: Simulation based validation." Neuroimage 47 (4):1496-1505.
[2] Buhler et al., An Accurate Method for Correction of Head Movement in PET, in IEEE Trans. Med. Im., 2004..
[3] Reilhac, A, Sjoholm, T, Thomas, BA, Irace, Z, Merida, I, Villien, M, Redoute, J, and Costes, N. 2016. "Validation and application of
PET-SORTEO for the geometry of the Siemens mMR scanner." PSMR 2016, 5TH CONFERENCE ON PET/MR AND SPECT/MR,
Aim
Develop a novel implementation of a list-mode based motion correction
dedicated to the Siemens mMR (Siemens Healthcare GmbH, Erlangen,
Germany) PET-MRI scanner.
Methods
Motion estimation
• On PET series reconstructed without attenuation correction in short frame (100s or 20s) [1]
• Alternatively, on simultaneous bold fMRI series (not tested here)
With Minctracc (MincTool) with rigid body model and cross correlation
Eber: Rebinner of the PET list mode with motion correction
List mode is processed event by event
For each time interval of the motion parameter file, the following processes are applied:
1) Spatial transformation of a LOR
- Onto the nearest LOR of the scanner (Fig 1)
- Optional subsampling of LOR, and weighted distribution over the LORs intercepting the
transformed LOR (Fig. 2) to avoid discretization artifact [2]
2) Normalization
Before performing the spatial transformation, detected counts in each LOR are normalized by their
respective normalization factors.
Upon completion of a frame, the resulting sinogram is un-normalized.
3) Gaps and out-of-FOV correction
Event losses caused by the gaps are compensated by filling them with the neighbour counts prior
performing the correction.
For events leaving the FOV, the rebinner computes for each sinogram bin the sensitivity loss caused
by the motion, and corrects the counts accordingly.
Reconstruction of sinograms
Uncorrected and corrected sinograms are reconstructed in a desired framing, not necessary
corresponding to the motion framing, using OP-OSEM with all corrections applied.
Correction results obtained from actual PET studies show a net improvement of the image quality
(Fig. 4 and 5).
Motion correction avoids misinterpretation of the results (Fig 5)
Fig.3 shows the RMS error (%) as a function of the magnitude of the motion between the
reference image (no motion) and images obtained after different correction approaches:
• no correction,
• simple line approach (oversampling of 1 = OS1),
• OS1 including normalization (OS1+norm),
• OS1+norm with out-of-FOV correction (OS1+norm+exposure)
• and different level of crystal oversampling (2, 3 and 4). `
Out-of-FOV correction (see b), normalization (see c) as well as an oversampling factor of 3
(see a) are required for an accurate correction, reducing the RMS to the level of a test-retest
scenario without motion (origin of each graph).
Results obtained with translation along X and Y as well as with rotation around their axis lead
to the same conclusion (not shown). Note that an oversampling of 3 involves 13 line transforms
(9 direct and 4 tilted) for the spatial transformation of each LOR
Validation with simulated data Actual studies
Acknowledgments
This work was supported by a CIFRE studentship jointly funded by Siemens and the French national agency for research and Technology
(ANRT). Funding was also received from the french national ‘invest for the futur’ programs (LILI – Lyon Integrated Life Imaging: hybrid MR-
PET ANR-11-EQPX-0026) and the hospital University Institut CESAME (Brain and Mental Health ANR-10-IBHU-0003) .
Figure 4: [11C]Raclopride.
Top: uncorrected and corrected mean image. Bottom: time
activity curves extracted on the striatum region from the
uncorrected, or the corrected dynamic image.
Figure 1: Initial LOR is moved to a transformed LOR
according to the motion parameters found for the
corresponding time interval.
Figure 2: Initial LOR is ovever sampled (factor 2, 3 or 4), then moved
to a transformed position, and weighting-factors for event distribution
are computed to actual LORs of the scanner.
Figure 5: [11C]PIB. Static image resulting form a 30 min.
acquisition, with or without motion correction. Activity seen on the
cortical region in the uncorrected image, is clearly restricted to
the white matter region on this negative PIB scan.
Uncorrected Image
Corrected Image
Uncorrected Image
Corrected Image
[11C]Raclopride [11C]PIB
Figure 3: Root mean square error (%) a function of the magnitude of the motion for several configuration of Eber
PET List Mode
List of Mo on parameters
Mo on
es ma on
Eber:
LM rebinning with
mo on correc on
Mo on corrected sinogram
Mo on corrected PET image
Reconstruc on
without AC
in short frames
Series of short PET frames
PET image uncorrected for mo on
Reconstruc on
Standard
Rebinning
Uncorrected sinogram
Reconstruc on
fMRI series