Validation of Photon Collimation Techniques for Monolithic PET Detector Calibration

Abstract

Monolithic-based positron emission tomography (PET) detectors have become an attractive alternative to traditional pixelated scintillator modules. One of the main limiting factors to further expand the use of the monolithic approach in commercial PET scanners is the requirement of more complex calibration setups than for their pixelated counterparts. These calibration procedures are usually based on hardware-collimation methods in which a physically collimated beam source is moved across the front face of the scintillator. These procedures require the use of manifold hardware setups and are time consuming, especially when dealing with systems composed of many detector modules. To reduce the mechanical complexity and long acquisition times required to obtain calibration datasets when using monolithic-based detectors, we have validated in this work the recently proposed method of using software-collimated calibration data for monolithic PET detectors. software-collimated methods require less hardware, are easier to implement, and have the potential to be used in an assembled PET scanner. We are evaluating a defined bias estimator and the overall detector spatial resolution using data obtained with the two different collimation techniques. Results showed bias behavior and spatial resolution discrepancies as small as 4.9% between the two datasets for a monolithic crystal with dimensions of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$50 \times 50 \times 8$ </tex-math></inline-formula> mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> . These results demonstrate that software-collimated data in combination with accurate positioning algorithms promises to be competitive against traditional hardware-collimation procedures. Finally, we have explored and confirmed the use of software-collimated data for the calibration step using two procedures, the PC3 method (calibrated data is shown) and Voronoi diagrams.