Technical Note: Performance evaluation of a small-animal PET/CT system based on NEMA NU 4-2008 standards

Technical opportunities and challenges in developing total-body PET scanners for mice and rats

Positron emission tomography (PET) is the most sensitive in vivo molecular imaging technique available. Small animal PET has been widely used in studying pharmaceutical biodistribution and disease progression over time by imaging a wide range of biological processes. However, it remains true that almost all small animal PET studies using mouse or rat as preclinical models are either limited by the spatial resolution or the sensitivity (especially for dynamic studies), or both, reducing the quantitative accuracy and quantitative precision of the results. Total-body small animal PET scanners, which have axial lengths longer than the nose-to-anus length of the mouse/rat and can provide high sensitivity across the entire body of mouse/rat, can realize new opportunities for small animal PET. This article aims to discuss the technical opportunities and challenges in developing total-body small animal PET scanners for mice and rats.

Performance Evaluation of a PET of 7T Bruker Micro-PET/MR Based on NEMA NU 4-2008 Standards

Purpose: This study aimed to measure the performance evaluation of the Bruker sequential micro-positron emission tomography/magnetic resonance imaging (PET/MRI) scanner by following National Electrical Manufacturers Association (NEMA) NU 4-2008 standards’ protocol. The system consists of a high-performance silicon photomultiplier (SiPM) advanced technology detector and a continuous lutetium-yttrium oxyorthosilicate (LYSO) crystal. Methods: A 22Na (sodium-22) point source was utilized to assess the spatial resolution and system sensitivity, and the Micro-PET scatter phantom measurements were conducted to measure count rate measurements and scatter fractions (SF). A mouse-like Micro-PET image quality (IQ) phantom was utilized as a model to analyze the uniformity, recovery coefficient (RC), and spillover ratio (SOR). A small animal PET/MRI imaging study was performed in a rat. Results: We calculated the spatial resolutions of filtered back-projection (FBP), and used 3D-MLEM to reconstruct PET images at the axial center and ¼ of the axial field of view (FOV) in axial, radial, and tangential directions. The best observed spatial resolutions in both reconstructed images were obtained in the tangential direction, and the values were 0.80 mm in 3D-MLEM and 0.94 mm in FBP. The peak noise equivalent count rate (NECR) in the 358–664 keV energy window was 477.30 kcps at 95.83 MBq and 774.45 kcps at 103.6 MBq for rat and mouse-sized scatter phantoms, respectively. The rat and mouse-sized phantoms scatter fractions (SF) were 14.2% and 6.9%, respectively. Conclusions: According to our results, the performance characteristics of the scanner are high sensitivity, good spatial resolution, low scatter fraction, and good IQ, indicating that it is suitable for preclinical imaging studies.

Reconstruction of Preclinical PET Images via Chebyshev Polynomial Approximation of the Sinogram

Over the last decades, there has been an increasing interest in dedicated preclinical imaging modalities for research in biomedicine. Especially in the case of positron emission tomography (PET), reconstructed images provide useful information of the morphology and function of an internal organ. PET data, stored as sinograms, involve the Radon transform of the image under investigation. The analytical approach to PET image reconstruction incorporates the derivative of the Hilbert transform of the sinogram. In this direction, in the present work we present a novel numerical algorithm for the inversion of the Radon transform based on Chebyshev polynomials of the first kind. By employing these polynomials, the computation of the derivative of the Hilbert transform of the sinogram is significantly simplified. Extending the mathematical setting of previous research based on Chebyshev polynomials, we are able to efficiently apply our new Chebyshev inversion scheme for the case of analytic preclinical PET image reconstruction. We evaluated our reconstruction algorithm on projection data from a small-animal image quality (IQ) simulated phantom study, in accordance with the NEMA NU 4-2008 standards protocol. In particular, we quantified our reconstructions via the image quality metrics of percentage standard deviation, recovery coefficient, and spill-over ratio. The projection data employed were acquired for three different Poisson noise levels: 100% (NL1), 50% (NL2), and 20% (NL3) of the total counts, respectively. In the uniform region of the IQ phantom, Chebyshev reconstructions were consistently improved over filtered backprojection (FBP), in terms of percentage standard deviation (up to 29% lower, depending on the noise level). For all rods, we measured the contrast-to-noise-ratio, indicating an improvement of up to 68% depending on the noise level. In order to compare our reconstruction method with FBP, at equal noise levels, plots of recovery coefficient and spill-over ratio as functions of the percentage standard deviation were generated, after smoothing the NL3 reconstructions with three different Gaussian filters. When post-smoothing was applied, Chebyshev demonstrated recovery coefficient values up to 14% and 42% higher, for rods 1–3 mm and 4–5 mm, respectively, compared to FBP, depending on the smoothing sigma values. Our results indicate that our Chebyshev-based analytic reconstruction method may provide PET reconstructions that are comparable to FBP, thus yielding a good alternative to standard analytic preclinical PET reconstruction methods.

Physical and Imaging Performance of SIAT aPET under Different Energy Windows and Timing Windows

PURPOSE

The performance of small animal PET scanners depends on the energy window (EW) and timing window (TW). In 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 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 center of field of view 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 center of field of view 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. This article is protected by copyright. All rights reserved.