Neural networks

This paper reports the use of a magnetic resonance imaging (MRI) system to propel a ferromagnetic core. The concept was studied for future development of microdevices designed to perform minimally invasive interventions in remote sites accessible through the human cardiovascular system. A mathematical model is described taking into account various parameters such as the size of blood vessels, the velocities and viscous properties of blood, the magnetic properties of the materials, the characteristics of MRI gradient coils, as well as the ratio between the diameter of a spherical core and the diameter of the blood vessels. The concept of magnetic propulsion by MRI is validated experimentally by measuring the flow velocities that magnetized spheres (carbon steel 1010/1020) can withstand inside cylindrical tubes under the different magnetic forces created with a Siemens Magnetom Vision 1.5 T MRI system. The differences between the velocities predicted by the theoretical model and the experiments are approximately 10%. The results indicate that with the technology available today for gradient coils used in clinical MRI systems, it is possible to generate sufficient gradients to propel a ferromagnetic sphere in the larger sections of the arterial system. In other words, the results show that in the larger blood vessels where the diameter of the microdevices could be as large as a couple a millimeters, the few tens of mT/m of gradients required for displacement against the relatively high blood flow rate is well within the limits of clinical MRI systems. On the other hand, although propulsion of a ferromagnetic core with diameter of /spl sim/600 /spl mu/m may be possible with existing clinical MRI systems, gradient amplitudes of several T/m would be required to propel a much smaller ferromagnetic core in small vessels such as capillaries and additional gradient coils would be required to upgrade existing MRI systems for operations at such a scale.

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Method of propulsion of a ferromagnetic core in the cardiovascular system through magnetic gradients generated by an MRI system

There are two major issues in the delay chain based FPGA TDC due to uneven internal delay in the carry chain. (1) The bin widths are uneven and depend on temperature and power supply voltage, which must be calibrated as frequently as possible. The auto-calibration functional block developed in this work provides semi-continuous calibration that converts the TDC measurements from bins to picoseconds. (2) In many applications, the TDC resolution is limited by the “ultra-wide bins”, corresponding to the carry chain crossing at the boundaries of the logic array blocks. The apparent widths of these ultra-wide bins can be several times bigger than the average bin width. The “wave union launchers” described in this paper are designed to make multiple measurements with a single delay chain structure, effectively to sub-divide the ultra-wide bins in each raw measurement. Several TDC schemes with resolutions in 20 to10 picoseconds range implemented in today’s low cost FPGA have been tested.

/pdf/the-10-ps-wave-union-tdc-improving-fpga-tdc-resolution-1pes3aod5f.pdf

The 10-ps wave union TDC: Improving FPGA TDC resolution beyond its cell delay

The National Electrical Manufacturers Association (NEMA) standard NU 4-2008 for performance measurements of small-animal tomographs was recently published. Before this standard, there were no standard testing procedures for preclinical PET systems, and manufacturers could not provide clear specifications similar to those available for clinical systems under NEMA NU 2-1994 and 2-2001. Consequently, performance evaluation papers used methods that were modified ad hoc from the clinical PET NEMA standard, thus making comparisons between systems difficult. Methods: We acquired NEMA NU 4-2008 performance data for a collection of commercial animal PET systems manufactured since 2000: microPET P4, microPET R4, microPET Focus 120, microPET Focus 220, Inveon, ClearPET, Mosaic HP, Argus (formerly eXplore Vista), VrPET, LabPET 8, and LabPET 12. The data included spatial resolution, counting-rate performance, scatter fraction, sensitivity, and image quality and were acquired using settings for routine PET. Results: The data showed a steady improvement in system performance for newer systems as compared with first-generation systems, with notable improvements in spatial resolution and sensitivity. Conclusion: Variation in system design makes direct comparisons between systems from different vendors difficult. When considering the results from NEMA testing, one must also consider the suitability of the PET system for the specific imaging task at hand.

https://jnm.snmjournals.org/content/jnumed/53/8/1300.full.pdf

NEMA NU 4-2008 Comparison of Preclinical PET Imaging Systems

The LabPETtrade is a fully digital avalanche photodiode (APD) based PET scanner designed for state-of-the-art molecular and genomic imaging of small animals. Two versions of the scanner were evaluated, having 3.75 (LabPET4) and 7.5 cm axial FOV (LabPET8). The detectors are made of 2times2times12/14 mm3 LYSO and LGSO crystals assembled in phoswich pairs read out by an APD. After digital crystal identification, the average energy resolution is 24plusmn6% for LYSO and 25plusmn6% for LGSO. The scanner's overall timing resolution is 6.6 ns for LYSO/LYSO and 10.7 ns for LGSO/LGSO coincidences after coarse timing alignment. The FBP reconstructed tangential/radial resolution is 1.3/1.4 mm FWHM (2.5/2.4 mm FWTM) at the FOV center and remains below 2.1 mm FWHM (3.6 mm FWTM) within the central 4-cm diameter FOV. MLEM reconstruction of a micro resolution phantom provided clear separation of the 1.0 mm spots. With an energy window of 250-650 keV, the sensitivity is 1.1% for LabPET4 and 2.1% for LabPET8. The imaging capabilities of the scanner are demonstrated with in vivo images of rats and mice.

Performance Evaluation of the LabPET APD-Based Digital PET Scanner

The RatCAP has been designed and constructed to image the awake rat brain. In order to maximize system performance, offline digital coincidence data processing algorithms including offset delay correction and prompt and delayed coincidence detection have been developed and validated. With offset delay correction using a singular value decomposition (SVD) technique, overall time resolution was improved from 32.6 ns to 17.6 ns FWHM. The experimental results confirm that the ratio of prompts (or trues) to randoms was improved because a smaller timing window could be used. 18F-fluoride rat bone scan data was reconstructed with our fully 3-D MLEM with a highly accurate detector response model using Monte Carlo simulation.

Digital Coincidence Processing for the RatCAP Conscious Rat Brain PET Scanner

The highly multiplexed, integrated analog processing front-end of current PET scanners yields high accuracy for timing and crystal identification, but also adds significant dead time and offers little flexibility for improvement. A new fully digital APD-based scanner architecture is proposed wherein nuclear pulses are sampled directly at the output of the charge sensitive preamplifier with one free-running ADC per channel. This approach offers the opportunity to explore new digital signal processing algorithms borrowed to command and control theory, as well as advanced heuristics such as neural networks. The analog front-end consists of a dedicated 0.18-mum, 16-channel CMOS charge sensitive preamplifier. Digitization is performed with off-the-shelf dual 8-bit 45-MHz analog-to-digital converters. Digital processing is concentrated in a dual processor FPGA and a digital signal processor (DSP), which can process the data from up to 64 parallel channels with no dead time. The FPGA deals with the initial signal analysis for energy measurement and time stamping, while crystal identification is deferred to the DSP running computation-intensive auto-regressive algorithms. The entire system is controlled serially through a Firewire link by a graphic user interface. The initial LabPETtrade implementation of the system is a dedicated small animal scanner holding up to 3072 APD channels at an averaged count rate of up to 10 000 events/s each

The architecture of LabPET/spl trade/, a small animal APD-based digital PET scanner

Digital processing for positron emission tomography (PET) scanners commonly relies on low frequency sampling (MHz) to reduce power consumption. Timestamps must then be interpolated between samples to achieve adequate time resolution for coincidence detection of annihilation radiation. A low-pass filter based interpolation algorithm adding up to 31 samples between original samples was designed to improve timing resolution of the LabPET scanner. A 2-bit refinement in the determination of the pulse maximum amplitude leads to a better estimation of the triggering threshold, which in turn enables a more accurate timestamp generation. Timestamp accuracy was investigated as a function of trigger level (15%-50% of maximum value). With the trigger threshold set at 20%, coincidence time resolution of ns for LYSO-LYSO and ns for LGSO-LGSO are obtained. A real time implementation of the algorithm was achieved in a Xilinx FPGA.

Timing Improvement by Low-Pass Filtering and Linear Interpolation for the LabPET Scanner

Most positron emission tomography (PET) scanners still partly rely on analog processing to sort out events from the PET detector front-end. Recent all-digital architectures enable the use of more complex algorithms to solve common problems in PET scanners, such as crystal identification and parallax error. Auto-regressive moving-average (ARMAX) algorithms are among the most powerful methods for parallax mitigation in phoswich detectors. Although ARMAX achieves excellent discrimination accuracy even with noisy data, such methods are computationally expensive and can hardly be implemented in a real-time digital PET system. A crystal identification method based on adaptive filter theory using an auto-regressive (AR) model is proposed to enable real-time crystal identification in a noisy environment. Preliminary results based on MatLab simulation demonstrate a high discrimination accuracy (~95%) for phoswich LSO-LYSO crystals (with 40 and 51 ns decay time constants) and nearly 99% for BGO-LSO, including Compton photons

Crystal Identification Based on Recursive-Least-Squares and Least-Mean-Squares Auto-Regressive Models for Small Animal Pet

A centralized, fully digital, FPGA-based coincidence detection system has been developed for the LabPET APD-based scanner. The digital flexibility allows excellent timing resolution using digital signal processing and high precision crystal identification. In this digital architecture, fast AND-gate coincidence detection is no longer possible due to signal analysis delay. Timestamp based coincidences must be carried out by a central digital process that handles huge amounts of data. A 45 MHz system clock is used by free running ADCs and reference time counters. Event timestamp is refined to ~0.7 ns resolution with digital analysis. A real-time digital coincidence detection system capable of processing 32 million single events per second is proposed to support a fully digital APD-based architecture. The coincidence engine retains a technology independent structure, making it easily reusable in subsequent generation architectures. The system detects prompt coincidences and evaluates random coincidences using both a delayed-window coincidence and the singles count rate. Finally, it supports dynamic adaptive coincidence windowing for multi-crystal PET scanners, ranging from 0 to 100 ns in 0.7 ns increments

R. Fontaine

Papers

Digital Coincidence Processing for the RatCAP Conscious Rat Brain PET Scanner

The architecture of LabPET/spl trade/, a small animal APD-based digital PET scanner

Timing Improvement by Low-Pass Filtering and Linear Interpolation for the LabPET Scanner

Crystal Identification Based on Recursive-Least-Squares and Least-Mean-Squares Auto-Regressive Models for Small Animal Pet

Real time coincidence detection system for digital high resolution APD-based animal PET scanner