Impact of Axial Compression for the mMR Simultaneous PET-MR ScannerMartin A Belzunce, Jim O’Doherty and Andrew J ReaderKing's College London, Division of Imaging Sciences, St Thomas’ Hospital, London, UK

PurposeTo evaluate the impact on the spatial resolution of reconstructing images without axial compression in comparison to the standard span-11 reconstruction in the Siemens Biograph mMR scanner. In addition, we aim to assess the spatial resolution for a number of span values and the effect of modeling the axial compression in the system matrix.

IntroductionIn 3D PET, an axial compression is used to reduce the data size and the computation times during the image reconstruction. This is achieved by averaging a set of sinograms with adjacent values of the oblique polar angle. This sampling scheme achieves good results in the centre of the FOV. However, there is a loss in the radial, tangential and axial resolutions at off-centre positions, which is increased in scanners with large FOVs.The Siemens Biograph mMR was the first simultaneous whole body PET-MR and it has one of the largest FOV commercially available. The system uses a

sinogram-based reconstruction with an axial compression of span-11 and a component-based normalization. Additionally, for each acquisition the scanner stores a span-1 sinogram for both the prompt and delayed events. This feature brings the possibility of implementing an image reconstruction algorithm without axial compression that would improve the spatial resolution in the outer regions of the FOV, which could benefit whole body studies.In this work, we study the impact of using an image reconstruction algorithm without axial compression and the use of higher span values modeled in the system matrix.

2) Estimate an axial profile for Incident events (not uniform: scatter, attenuation) using a normalized profile for each crystal position within a block. Correct the detected profile.3) Estimate the

detection efficiency Block Profile using the corrected profile from 2). The efficiency of each axial position within a block is:

spanN

saxialaxialzAX iiiN

121 )().()(

1) Total counts in the direct sinograms (detected profile) for a 5-hour 68Ge phantom scan.

4) The axial factor for each sinogram plane of the span-1 sinogram is computed using the Block Profile:

Materials and Methods

Span-1 Normalization Factors

ConclusionsA reconstruction algorithm without axial compression was im-plemented for the Biograph mMR and its general properties were verified using a NEMA IQ phantom acquisition and using STIR as a reference. Using a line source, we showed that a meaningful improvement in resolution in the x and z axes is achieved when there is not axial compression. Including the axial compression in the system matrix can compensate the spatial resolution degradation at the cost of a span-1 forward projection and an increase in the noise for higher span values.

References[1] B. Bendriem and D. W. Townsend, The Theory and Practice of 3D PET. Springer,1998.[2] G. Delso, S. Frst et al, ”Performance Measurements of the Siemens mMR Integrated Whole-Body PET/MR Scanner,” Journal of Nuclear Medicine, vol. 52, pp. 1914-1922, December 01, 2011.[3] R. D. Badawi and P. K. Marsden, ”Developments in component-based normal-ization for 3D PET,” Phys. Med. Biol., vol. 44, pp. 571-594, 1999.[4] K. Thielemans, C. Tsoumpas et al, STIR: Software for Tomographic Image Reconstruction Release 2,” Physics in Medicine and Biology, 57 (4), 2012 pp.867-883.

Span-1 Implementation

Modeling Axial Compression in the System Matrix

Impact on the Spatial Resolution

The Siemens mMR scanner uses a component-based normalization. The standard reconstruction uses span-11 sinograms and therefore the normalization factors also are designed for span-11. In order to generate span-1 normalization factors, the CBN components need to be adapted to that sinogram size. A 5-hours scan of the 68Ge uniform phantom was used to create new axial factors.

• The Siemens mMR scanner. It was the first simultaneous whole body PET-MR. It is composed of 8 rings of 56 detector blocks of 8x8 LSO crystal elements. The standard image reconstruction for this scanner uses 3D span-11 sinograms, with 837 sinogram planes of 344 [radial coordinate] x 252 [angle projection] bins. The system has a transaxial FOV of 59.4 cm and an axial FOV of 25.8 cm.

• The scanner also permits storage of span-1 sinograms. A span-1 image reconstruction algorithm was implemented (OP-OSEM). Normalization factors for this sinogram size were also generated.

• An assessment of the benefits of the span-1 implementation was performed using real and simulated data.

• The incorporation of the axial compression was included in the forward projection of the image reconstruction and compared to the span-1 reconstructions

• The implementation was validated evaluating the image properties of a NEMA Image Quality (IQ) phantom scan using a method capable of assessing image quality even if scatter correction is not applied to the data.

• 3D sinograms were simulated by projecting a NCAT and Defrise phantom and introducing them Poisson noise.

• The impact of the span-1 reconstruction on the spatial resolution was evaluated using a line source scan.

1

1

1)(blocksN

kNCik

blocksaxial C

Ni 5) The span-1 axial factors can

be converted into any span.

• A 3D OP-OSEM reconstruction algorithm was implemented in a C++/CUDA library for any span. A Siddon’s projector/backprojector was used.

srfXNACbNAX

ANXff kt

s

tst

kk

1

1

1

Xspan: X-ray transform for sinograms with span s.X1: X-ray transform for span-1 sinograms.C: axial compression to span s.

ML-EM with axial compression in the forward model:

Results for Defrise Phantom

Results for NCAT Phantom

We compute the SNR in the images using a spatially variant estimate of the mean value in the background of the phantom.

Evolution of STD vs CRC with iterations

Profiles in the z axis of the reconstructed images for Defrise phantoms with and without modeling the axial compression in the forward projection

Coronal Planes for Span-17

Modeled Axial CompressionStandard Reconstruction

Profile centered in the lesion of the NCAT phantom

with and without modeling the axial compression in the forward projection

Contrast Recovery in Lesion

Std Dev in Uniform Region

Span-51Span-11 modeledSpan-11 Span-51

modeledSpan-1

Simulated Defrise Phantom

Simulated NCAT Phantom

• In order to validate the algorithm, a scan of the NEMA phantom was reconstructed using 1 subset (ML-EM) and 60 iterations for the span 11 and span 1 sinograms, and with STIR.

• A line source scan was used to evaluate the spatial resolution for the span-1 reconstruction and for a number of other span values with and without modeling the axial compression in the forward model.

• The FWHM in each direction was computed for each transverse, coronal and sagital plane of the reconstructed images

FWHM in x in the

transverse slices Effect on the

FWHM of the span

modelling for a number of span values

Maximum intensity

projections in the coronal

plane