Prototype design of singles processing unit for the small animal PET

Deng, Peng; Liu, Zhao; Lu, Jiaming; Li, Bowen; Dong, Ruoshi; Liu, Shubin; An, Qi

doi:10.1088/1748-0221/13/05/t05007

Cited by 10 publications

(4 citation statements)

References 14 publications

(15 reference statements)

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“…In the resistor network readout circuit, first, signals of 8 SiPMs in a row were connected to a resistor chain, then both ends of the 8 resistor chains were connected to two column resistor chains, and finally 4 position encoding energy signals were generated. A singles processing unit can process 32 signals of four detector modules 35 . The electronics and data acquisition can be switched between raw data mode and image acquisition mode.…”

Section: Methodsmentioning

confidence: 99%

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Physical and imaging performance of SIAT aPET under different energy windows and timing windows

et al. 2022

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Purpose The performance of small animal PET scanners depends on the energy window (EW) and timing window (TW). In National Electrical Manufacturers Association (NEMA) Standards Publication NU 4–2008, detailed procedures of the performance measurements are defined, but the EW and TW are not specified. In this work, the effects of EW and TW on the physical and imaging performance of Shenzhen Institute of Advanced Technology small animal PET (SIAT aPET) will be evaluated. Methods First, the flood histogram, energy resolution, and timing resolution were measured for a detector of SIAT aPET. Second, the spatial resolutions were measured with different EWs. Third, the sensitivities, the scatter fractions (SFs), and noise equivalent count rates (NECRs) of a mouse‐sized phantom and a rat‐sized phantom, the recovery coefficients (RCs) of rods of different sizes, and the percentage standard deviation (%STD) of the NEMA image quality phantom were measured for different EWs and TWs. Last, images of a hot rod phantom, a mouse heart, and a rat brain were acquired from the scanner with different EWs. Results The SIAT aPET detectors provided good flood histograms such that all but the corner crystals can be resolved even with lower energies of 250–350 keV, an average energy resolution of 21.1 ± 1.9%, and an average timing resolution of 2.63 ± 0.69 ns. The average spatial resolutions obtained with EWs of 250–350 keV and 450–550 keV are 0.68 mm and 0.75 mm. For EWs of 250–750 keV, 350–750 keV, and 450–750 keV with a fixed TW of 12 ns, the sensitivities at the center of field of view (FOV) are 16.0%, 11.9%, and 8.2%, the peak NECRs of a mouse‐sized phantom are 355.6 kcps, 324.4 kcps, and 249.4 kcps, and the peak NECRs of a rat‐sized phantom are 148.5 kcps, 144.3 kcps, and 117.7 kcps, respectively. For the TWs of 4 ns, 8 ns,12 ns, and 20 ns with a fixed EW of 350–750 keV, the sensitivities at the center of FOV are 9.6%, 11.4%, 11.9%, and 12.2%, the peak NECRs of a mouse‐sized phantom are 260.1 kcps, 311.5 kcps, 324.4 kcps and 324.9 kcps, and the peak NECRs of a rat‐sized phantom are 110.5 kcps, 137.3 kcps, 144.3 kcps, and 142.6 kcps, respectively. Narrowing the EW and TW improves the RCs of rods of all sizes, and the %STD of images obtained with different EWs and TWs are similar. Rods with diameter down to 0.8 mm can be visually resolved from images of the hot rod phantom obtained with different EWs. Images of mouse heart with high spatial resolution and rat brain with detail brain structure were obtained with different EWs. Images of both phantom and in vivo animals obtained with different EWs only showed subtle difference. Conclusion The performance of SIAT aPET under different EWs and TWs was compared. The EW and TW affect the sensitivity, SF, and NECR but not the spatial resolution and animal images of SIAT aPET, which imply that careful optimization of the EW and TW is not required.

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Section: Methodsmentioning

confidence: 99%

“…A singles processing unit can process 32 signals of four detector modules. 35 The electronics and data acquisition can be switched between raw data mode and image acquisition mode. In the raw data mode, the flood histogram, DOI, energy, and timing of a detector can be measured.…”

Section: Siat Apet Scannermentioning

confidence: 99%

Physical and imaging performance of SIAT aPET under different energy windows and timing windows

et al. 2022

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“…Although TOT circuits are generally simpler than ADC circuits, TOT-based digitization has the disadvantages of poor nonlinearity and resolution. Therefore, in small animal PET electronics, ADC digitization is often used for high resolution charge measurement [7,17,18]. However, commercial ADCs suffer from high power consumption, high cost, and are difficult to integrate, so, it is necessary to research new charge measurement methods for small animal PET.…”

Section: Introductionmentioning

confidence: 99%

Prototype of a digitizer module based on multicycle-encoding FPGA ADC for a small animal PET

et al. 2023

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Current research in small animal positron emission tomography (PET) scanners focus on obtaining better spatial resolution and higher sensitivity. These enhancements of scanner performance result in a corresponding increase in the complexity of the electronics, which usually manifests through an increase in the number of electronics channels. Analog-to-digital converters (ADCs) implemented in field programmable gate arrays (FPGAs) are an effective way to simplify electronics complexity. In this paper, a resource-saving multicycle-encoding structure of an FPGA-based ADC with automated calibration is proposed, which achieves a sampling rate of 250 Msps. A digitizer module prototype containing 64 charge measurement channels based on the FPGA ADC is designed using a Kintex-7 FPGA. The effective number of bits (ENOB) achieved using the FPGA ADC is 4.26 bits under a 10.0555 MHz sine wave input. The charge measurement resolution of each channel is better than 5‰ full width half maximum under a 0.8 V signal input and 3% under inputs in the range 0.1 V to 1.2 V. The integral nonlinearity of each channel is within ± 1%.

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“…Using the mentioned method, a high-resolution charge measurement can be achieved (e.g., LHAASO WCDA electronics: 1% rms @4000 photoelectrons) [16]; however, this method is still limited by a noise of the analog circuit and analog-to-digital converter (ADC), and a peak detection error. An alternative method is to obtain the charge information through the summation of the sampling points from an ADC to calculate a "waveform area" instead of the peak detection [19][20][21][22][23].…”

mentioning

confidence: 99%

A Time-to-Digital Converter-Based Correction Method for Charge Measurement Through Area Integration

Zhang

Liu

Dong

et al. 2018

IEEE Trans. Nucl. Sci.

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A high-precision charge measurement can be achieved by the area integration of a digitized quasi-Gaussian signal after the signal passes through the shaper and analog-to-digital converter (ADC). The charge measurement contains an error due to the uncertainty of the first sampled point of a signal waveform. To reduce the error, we employ a time-to-digital converter (TDC) to measure the uncertainty precisely, and we design correction algorithms to improve the resolution of the charge measurement. This work includes analysis and simulations of the proposed algorithms and implementation of them in an FPGA device. Besides, the tests are also conducted to evaluate the performance of the correction method. Test results indicate that the resolution of the charge measurement is successfully improved from 2.31‰ to 1.26‰ by using a signal from the shaping circuit (with the amplitude of 2 V, and leading and trailing edges of about 80 ns and 280 ns, respectively) digitized at the sampling rate of 62.5 Msps.

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Prototype design of singles processing unit for the small animal PET

Cited by 10 publications

References 14 publications

Physical and imaging performance of SIAT aPET under different energy windows and timing windows

Physical and imaging performance of SIAT aPET under different energy windows and timing windows

Prototype of a digitizer module based on multicycle-encoding FPGA ADC for a small animal PET

A Time-to-Digital Converter-Based Correction Method for Charge Measurement Through Area Integration

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