14 research outputs found

    Impact of time-of-flight on quantitative accuracy and volume determination in non-uniform phantoms

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    Objectives: PET Contrast Recovery depends on lesion’s background. Identical lesions in different backgrounds can recover differently due to different convergence and spill in/out effects. In this work we investigate the effects of Time-of-flight PET for identical lesions in different backgrounds in terms of both CRC and threshold based volume definition. Methods: A phantom with lesions and organ inserts simulating an obese patient at high count rate was acquired on a TOF-PET scanner. Identical lesions were placed both in hot and cold background. We performed listmode TOF and non-TOF reconstruction for varying scan times (30 and 60 s with 10 realizations each). We compared the performances of the two methods in measuring lesions volume by applying a 42% threshold method. CRC was calculated for all lesions in PET and TOF for a range of clinically used iterations. Results: TOF CRC converges faster and to higher values for all cold and hot lesions except one (23 mm), which converges 10 % higher for non-TOF. For this lesion the difference between TOF and non-TOF CRCs is less than 5 % at 3 iterations, clinically the most used on site. Identical lesions in different backgrounds converge to different values, the difference being 20% smaller for TOF. Volume thresholding for lesions in a cold background gives up to a 30% better volume estimation when using TOF. Conclusions: TOF PET shows better characteristics for quantization tasks in different backgrounds and volume definition for cold background lesions. Count and contrast recovery is less depending on surrounding activity than with regular PET

    Determining timing resolution from TOF-PET emission data

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    TOF resolution is known to degrade with increasing count rate. During TOF-PET reconstruction the timing resolution of the data is used as an input for the reconstruction algorithm. The effect of the kernel width on the reconstruction was investigated in this paper. We looked at contrast recovery and background uniformity. Noise free simulation data were used together with high count measured TOF-PET data. The results clearly indicate that only the correct kernel should be used to reconstruct the data. Other kernels result in wrong contrast and less uniform background regions. Therefore it would be very useful to be able to estimate the TOF kernel from the data themselves. It is first shown that the likelihood reaches a maximum at the correct timing resolution. Then a method to estimate the kernel from both a non-TOF reconstruction and the measured TOF data is described. The determination of the timing resolution is performed with an iterative method using the non-TOF MLEM reconstruction and Richardson-Lucy deconvolution
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