Direct mapping from PET coincidence data to proton-dose and positron activity using a deep learning approach.

Objective. Obtaining the intrinsic dose distributions in particle therapy is a challenging problem that needs to be addressed by imaging algorithms to take advantage of secondary particle detectors. In this work, we investigate the utility of deep learning methods for achieving direct mapping from detector data to the intrinsic dose distribution.Approach. We performed Monte Carlo simulations using GATE/Geant4 10.4 simulation toolkits to generate a dataset using human CT phantom irradiated with high-energy protons and imaged with compact in-beam PET for realistic beam delivery in a single-fraction (∼2 Gy). We developed a neural network model based on conditional generative adversarial networks to generate dose maps conditioned on coincidence distributions in the detector. The model performance is evaluated by the mean relative error, absolute dose fraction difference, and shift in Bragg peak position.Main results. The relative deviation in the dose and range of the distributions predicted by the model from the true values for mono-energetic irradiation between 50 and 122 MeV lie within 1% and 2%, respectively. This was achieved using 105coincidences acquired five minutes after irradiation. The relative deviation in the dose and range for spread-out Bragg peak distributions were within 1% and 2.6% uncertainties, respectively.Significance. An important aspect of this study is the demonstration of a method for direct mapping from detector counts to dose domain using the low count data of compact detectors suited for practical implementation in particle therapy. Including additional prior information in the future can further expand the scope of our model and also extend its application to other areas of medical imaging.

Sub-100 ps coincidence time resolution for positron emission tomography with LSO:Ce codoped with Ca.

The coincidence time resolution (CTR) becomes a key parameter of 511 keV gamma detection in time of flight positron emission tomography (TOF-PET). This is because additional information obtained through timing leads to a better noise suppression and therefore a better signal to noise ratio in the reconstructed image. In this paper we present the results of CTR measurements on two different SiPM technologies from FBK coupled to LSO:Ce codoped 0.4%Ca crystals. We compare the measurements performed at two separate test setups, i.e. at CERN and at FBK, showing that the obtained results agree within a few percent. We achieve a best CTR value of 85 ± 4 ps FWHM for 2 × 2 × 3 mm(3) LSO:Ce codoped 0.4%Ca crystals, thus breaking the 100 ps barrier with scintillators similar to LSO:Ce or LYSO:Ce. We also demonstrate that a CTR of 140 ± 5 ps can be achieved for longer 2 × 2 × 20 mm(3) crystals, which can readily be implemented in the current generation PET systems to achieve the desired increase in the signal to noise ratio.