Micro-PET and PET preclinical systems are subject to very high costs per unit, which severely impact their potential adoption by smaller labs, as we saw in this post. The need to have access to MRI data on top of PET is making the situation even more challenging, and is reflected in the growth in demand for multimodal PET-MRI systems. There are some aspects of cost reduction initiatives that Nutaq can’t get involved in, but our expertise definitely allows us to explore solutions as far as FPGA data acquisition (front-end electronics) is concerned.

 

The Cost Breakdown Of A PET System

 

A PET system is made of three major components: the sensor (or detector) unit, the coincidence processing unit, and the image reconstruction unit. As pointed out by Dr. Arion Chatziioannou, Director of the Imaging Sciences Lab at the UCLA Crump Institute for Molecular Imaging, these components can be further divided as follows:

  • front-end electronics
  • optical quality crystals made from rare earth materials that are precisely cut, polished and assembled to high density arrays
  • multichannel photo detectors covering large surface areas
  • anesthesia system
  • embedded computer
  • high end host PC
  • system gantry with mechanics
  • multifunctional animal support system and many other smaller electronic components

Each of these system components represents a certain percentage of the overall system costs. As technologies evolve within these sub-systems, a reduction in price generally follows, and new system components become the bottleneck in terms of cost. A rule of thumb for optimizing the system cost is to take a close look at any system component that represents close to 20% of the overall cost, work with the manufacturer to reduce its impact, and keep looking for other possible technologies if the cost objective isn’t reached. As soon as the situation is resolved, you move to the next most costly item on the list (cost reduction is a never ending cycle).

 

Reducing System Costs With FPGA

 

In the light of this, I would like to provide insight on what this means where an FPGA data acquisition provider, such as Nutaq, is concerned. Although in the section above we’re only the first item in a long list of sub-components to be closely monitored by the preclinical system manufacturer, front-end electronics often come up as one of the top three cost elements in a system. This means we’re constantly under scrutiny and are forced to continually find new ways to reduce the cost per channel.

In the last few years, three game-changing developments appeared in the front-end electronics market, supporting a new wave of innovation:

  • high-performance ADCs integrating several channels within the same module, such as the LTM®9012 from Linear Technology®, which resulted in lower cost per channel, smaller PCB size, and easier integration
  • exponential increase in processing power of Xilinx® FPGAs, again not impacting at all the PCB size, and allowing a single FPGA device to be able to cope with the additional channels now offered by ADC devices
  • standards for FPGA mezzanine cards (FMC), which enabled vendors like Nutaq to gain economies of scale by fitting their module on any carrier featuring an FMC connector, no matter its manufacturer

Nutaq has taken the lead in driving costs down by combining the three advantages above, while adding the ability to stack modules on top of each other.

 

FPGA Multichannel DAQ Product Evolution Cycle

 

As an FPGA data acquisition system manufacturer, what is extremely motivating about our industry is that it’s constantly changing. There are probably new products being developed as I write this that will to add to the list above in the coming months. Again, this will drive us toward reaching a new level of compactness and cost reduction, helping to resolve the problems that you face, as a multi-channel systems user.

Another aspect that will definitely benefit the entire community of FPGA data acquisition users is how broad the field of applications is nowadays. We have discussed preclinical imaging (in vivo) systems, but a strong demand for FPGA DAQ systems is also coming from many other applications such as linear accelerators, radio astronomy, geolocation, cargo security inspection, MIMO radar, and others. It is astonishing to realise how similar the needs are for such a diverse array of applications.

 

Innovation Drives Cost Reduction

 

The front-end electronics portion of a PET system is very often a key cost component. As we discussed, as technologies improve, FPGA data acquisition manufacturers are presented with new opportunities to innovate and drive costs down. Many markets, not just preclinical imaging, will benefit from this cost reduction.