A multi-threshold sampling method for TOF-PET signal processing

✍ Scribed by H. Kim; C.M. Kao; Q. Xie; C.T. Chen; L. Zhou; F. Tang; H. Frisch; W.W. Moses; W.S. Choong

• Publisher: Elsevier Science
• Year: 2009
• Tongue: English
• Weight: 442 KB
• Volume: 602
• Category: Article
• ISSN: 0168-9002
• DOI: 10.1016/j.nima.2009.01.100

✦ Synopsis

As an approach to realizing all-digital data acquisition for positron emission tomography (PET), we have previously proposed and studied a multi-threshold sampling method to generate samples of a PET event waveform with respect to a few user-defined amplitudes. In this sampling scheme, one can extract both the energy and timing information for an event. In this paper, we report our prototype implementation of this sampling method and the performance results obtained with this prototype. The prototype consists of two multi-threshold discriminator boards and a time-to-digital converter (TDC) board. Each of the multi-threshold discriminator boards takes one input and provides up to 8 threshold levels, which can be defined by users, for sampling the input signal. The TDC board employs the CERN HPTDC chip that determines the digitized times of the leading and falling edges of the discriminator output pulses. We connect our prototype electronics to the outputs of two Hamamatsu R9800 photomultiplier tubes (PMTs) that are individually coupled to a 6.25×6.25×25mm(3) LSO crystal. By analyzing waveform samples generated by using four thresholds, we obtain a coincidence timing resolution of about 340 ps and an ∼18% energy resolution at 511 keV. We are also able to estimate the decay-time constant from the resulting samples and obtain a mean value of 44ns with an ∼9 ns FWHM. In comparison, using digitized waveforms obtained at a 20 GSps sampling rate for the same LSO/PMT modules we obtain ∼300 ps coincidence timing resolution, ∼14% energy resolution at 511 keV, and ∼5 ns FWHM for the estimated decay-time constant. Details of the results on the timing and energy resolutions by using the multi-threshold method indicate that it is a promising approach for implementing digital PET data acquisition.