Brain PET imaging optimization with time of flight and point spread function modelling

PURPOSE:
To assess the influence of reconstruction algorithms and parameters on the PET image quality of brain phantoms in order to optimize reconstruction for clinical PET brain studies in a new generation PET/CT.

METHODS:
The 3D Hoffman phantom that simulates (18)F-fluorodeoxyglucose (FDG) distribution was imaged in a Siemens Biograph mCT TrueV PET/CT with Time of Flight (TOF) and Point Spread Function (PSF) modelling.

Contrast-to-Noise Ratio (CNR), contrast and noise were studied for different reconstruction models: OSEM, OSEM + TOF, OSEM + PSF and OSEM + PSF + TOF. The 2D multi-compartment Hoffman phantom was filled to simulate 4 different tracers' spatial distribution: FDG, (11)C-flumazenil (FMZ), (11)C-Methionine (MET) and 6-(18)F-fluoro-l-dopa (FDOPA).

The best algorithm for each tracer was selected by visual inspection. The maximization of CNR determined the optimal parameters for each reconstruction.

RESULTS:
In the 3D Hoffman phantom, both noise and contrast increased with increasing number of iterations and decreased with increasing FWHM. OSEM + PSF + TOF reconstruction was generally superior to other reconstruction models.

Visual analysis of the 2D Hoffman brain phantom suggested that OSEM + PSF + TOF is the optimum algorithm for tracers with focal uptake, such as MET or FDOPA, and OSEM + TOF for tracers with diffuse cortical uptake (i.e. FDG and FMZ). Optimization of CNR demonstrated that OSEM + TOF reconstruction must be performed with 2 iterations and a filter FWHM of 3 mm, and OSEM + PSF + TOF reconstruction with 4 iterations and 1 mm FWHM filter.

CONCLUSIONS:
Optimization of reconstruction algorithm and parameters has been performed to take particular advantage of the last generation PET scanner, recommending specific settings for different brain PET radiotracers.

CITA DEL ARTÍCULO  Phys Med. 2015 Dec;31(8):948-55. doi: 10.1016/j.ejmp.2015.07.001. Epub 2015 Aug 4.