Performance evaluation of the mouse version of the LabPET II PET scanner.

The LabPET II is a new positron emission tomography technology platform designed to achieve submillimetric spatial resolution imaging using fully pixelated avalanche photodiodes-based detectors and highly integrated parallel front-end processing electronics. The detector was designed as a generic building block to develop devices for preclinical imaging of small to mid-sized animals and for clinical imaging of the human brain. The aim of this work is to assess the physical characteristics and imaging performance of the mouse version of LabPET II scanner following the NEMA NU4-2008 standard and using high resolution phantoms and in vivo imaging applications. A reconstructed spatial resolution of 0.78 mm (0.5 µ l) is measured close to the center of the radial field of view. With an energy window of 350 650 keV, the system absolute sensitivity is 1.2% and its maximum noise equivalent count rate reaches 61.1 kcps at 117 MBq. Submillimetric spatial resolution is achieved in a hot spot phantom and tiny bone structures were resolved with unprecedented contrast in the mouse. These results provide convincing evidence of the capabilities of the LabPET II technology for biomolecular imaging in preclinical research.

Dual-Threshold Time-over-Threshold Nonlinearity Correction for PET Detectors.

The Time-over-Threshold (ToT) analog-to-digital signal processing approach provides a power-efficient and cost-effective technique to extract all relevant information from detectors in high-energy physics and Positron Emission Tomography (PET) imaging. In this work, three calibration methods were investigated to correct the inherent nonlinear response of the ToT data using 1) γ-ray sources of various energies, 2) internal electronic gain variation in the LabPET II ASIC in combination with a single energy γ-ray source, and 3) internal gain variation along with an embedded pulse charge generator in replacement of a γ-ray source. The electronic gain calibration technique was shown to achieve equivalent correction accuracy as the γ-ray sources calibration. Furthermore, this method has the advantage of allowing a faster calibration requiring only one single γ-ray source (e.g., 511 keV) and a quick automated routine to sweep the internal gain. The last technique would be the most convenient method, provided that the signal pulse shape would be similar to the detector signal responding to a typical γ-ray event. Whereas the concept was demonstrated with a step pulse, extensive processing would be required to recover the nonlinearity correction factors for the detector pulse shape. After calibration, the 511-keV energy resolution of typical LabPET II detectors was only slightly degraded, by less than 12% and 8% for methods 1) and 2), respectively, relative to a conventional ADC-based data acquisition system. The feasibility of fast and accurate calibration for the nonlinearity correction of ToT data in PET imaging was demonstrated, making a daily quality control within reach.

Performance Simulation of an Ultra-High Resolution Brain PET Scanner Using 1.2-mm Pixel Detectors.

The concept of a new ultra-high resolution positron emission tomography (PET) brain scanner featuring truly pixelated detectors based on the LabPET II technology is presented. The aim of this study is to predict the performance of the scanner using GATE simulations. The NEMA procedures for human and small animal PET scanners were used, whenever appropriate, to simulate spatial resolution, scatter fraction, count rate performance and the sensitivity of the proposed system compared to state-of-the-art PET scanners that would currently be the preferred choices for brain imaging, namely the HRRT dedicated brain PET scanner and the Biograph Vision wholebody clinical PET scanner. The imaging performance was also assessed using the NEMA-NU4 image quality phantom, a mini hot spot phantom and a 3-D voxelized brain phantom. A reconstructed nearly isotropic spatial resolution of 1.3 mm FWHM is obtained at 10 mm from the center of the field of view. With an energy window of 250-650 keV, the system absolute sensitivity is estimated at 3.4% and its maximum NECR reaches 16.4 kcps at 12 kBq/cc. The simulation results provide evidence of the promising capabilities of the proposed scanner for ultra-high resolution brain imaging.

Accuracy of 177Lu activity quantification in SPECT imaging: a phantom study.

BACKGROUND: The aim of the study is to assess accuracy of activity quantification of 177Lu studies performed according to recommendations provided by the committee on Medical Internal Radiation Dose (MIRD) pamphlets 23 and 26. The performances of two scatter correction and three segmentation methods were compared. Additionally, the accuracy of tomographic and planar methods for determination of the camera normalization factor (CNF) was evaluated. Eight phantoms containing inserts of different sizes and shapes placed in air, water, and radioactive background were scanned using a Siemens SymbiaT SPECT/CT camera. Planar and tomographic scans with 177Lu sources were used to measure CNF. Images were reconstructed with our SPEQToR software using resolution recovery, attenuation, and two scatter correction methods (analytical photon distribution interpolated (APDI) and triple energy window (TEW)). Segmentation was performed using a fixed threshold method for both air and cold water scans. For hot water experiments three segmentation methods were compared as folows: a 40% fixed threshold, segmentation based on CT images, and our iterative adaptive dual thresholding (IADT). Quantification error, defined as the percent difference between experimental and true activities, was evaluated. RESULTS: Quantification error for scans in air was better for TEW scatter correction (<6%) than for APDI (<11%). This trend was reversed for scans in water (<10% for APDI and <14% for TEW). For hot water, the best results (<18% for small objects and <5% for objects >100 ml) were obtained when APDI and IADT were used for scatter correction and segmentation, respectively. Additionally, we showed that planar acquisitions with scatter correction and tomographic scans provide similar CNF values. This is an important finding because planar acquisitions are easier to perform than tomographic scans. TEW and APDI resulted in similar quantification errors with APDI showing a small advantage for objects placed in medium with non-uniform density. CONCLUSIONS: Following the MIRD recommendations for data acquisition and reconstruction resulted in accurate activity quantification (errors <5% for large objects). However, techniques for better organ/tumor segmentation must still be developed.