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Brzezinski, K., Oliver, J. F., Gillam, J., & Rafecas, M. (2014). Study of a high-resolution PET system using a Silicon detector probe. Phys. Med. Biol., 59(20), 6117–6140.
Abstract: A high-resolution silicon detector probe, in coincidence with a conventional PET scanner, is expected to provide images of higher quality than those achievable using the scanner alone. Spatial resolution should improve due to the finer pixelization of the probe detector, while increased sensitivity in the probe vicinity is expected to decrease noise. A PET-probe prototype is being developed utilizing this principle. The system includes a probe consisting of ten layers of silicon detectors, each a 80 x 52 array of 1 x 1 x 1 mm(3) pixels, to be operated in coincidence with a modern clinical PET scanner. Detailed simulation studies of this system have been performed to assess the effect of the additional probe information on the quality of the reconstructed images. A grid of point sources was simulated to study the contribution of the probe to the system resolution at different locations over the field of view (FOV). A resolution phantom was used to demonstrate the effect on image resolution for two probe positions. A homogeneous source distribution with hot and cold regions was used to demonstrate that the localized improvement in resolution does not come at the expense of the overall quality of the image. Since the improvement is constrained to an area close to the probe, breast imaging is proposed as a potential application for the novel geometry. In this sense, a simplified breast phantom, adjacent to heart and torso compartments, was simulated and the effect of the probe on lesion detectability, through measurements of the local contrast recovery coefficient-to-noise ratio (CNR), was observed. The list-mode ML-EM algorithm was used for image reconstruction in all cases. As expected, the point spread function of the PET-probe system was found to be non-isotropic and vary with position, offering improvement in specific regions. Increase in resolution, of factors of up to 2, was observed in the region close to the probe. Images of the resolution phantom showed visible improvement in resolution when including the probe in the simulations. The image quality study demonstrated that contrast and spill-over ratio in other areas of the FOV were not sacrificed for this enhancement. The CNR study performed on the breast phantom indicates increased lesion detectability provided by the probe.
Keywords: PET; high-resolution imaging; Si detectors; PET insert
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Borys, D. et al, & Brzezinski, K. (2022). ProTheRaMon-a GATE simulation framework for proton therapy range monitoring using PET imaging. Phys. Med. Biol., 67(22), 224002–15pp.
Abstract: Objective. This paper reports on the implementation and shows examples of the use of the ProTheRaMon framework for simulating the delivery of proton therapy treatment plans and range monitoring using positron emission tomography (PET). ProTheRaMon offers complete processing of proton therapy treatment plans, patient CT geometries, and intra-treatment PET imaging, taking into account therapy and imaging coordinate systems and activity decay during the PET imaging protocol specific to a given proton therapy facility. We present the ProTheRaMon framework and illustrate its potential use case and data processing steps for a patient treated at the Cyclotron Centre Bronowice (CCB) proton therapy center in Krakow, Poland. Approach. The ProTheRaMon framework is based on GATE Monte Carlo software, the CASToR reconstruction package and in-house developed Python and bash scripts. The framework consists of five separated simulation and data processing steps, that can be further optimized according to the user's needs and specific settings of a given proton therapy facility and PET scanner design. Main results. ProTheRaMon is presented using example data from a patient treated at CCB and the J-PET scanner to demonstrate the application of the framework for proton therapy range monitoring. The output of each simulation and data processing stage is described and visualized. Significance. We demonstrate that the ProTheRaMon simulation platform is a high-performance tool, capable of running on a computational cluster and suitable for multi-parameter studies, with databases consisting of large number of patients, as well as different PET scanner geometries and settings for range monitoring in a clinical environment. Due to its modular structure, the ProTheRaMon framework can be adjusted for different proton therapy centers and/or different PET detector geometries. It is available to the community via github (Borys et al 2022).
Keywords: proton therapy; GATE; Monte Carlo simulations; J-PET; medical imaging
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Brzezinski, K. et al. (2023). Detection of range shifts in proton beam therapy using the J-PET scanner: a patient simulation study. Phys. Med. Biol., 68(14), 145016–17pp.
Abstract: Objective. The Jagiellonian positron emission tomography (J-PET) technology, based on plastic scintillators, has been proposed as a cost effective tool for detecting range deviations during proton therapy. This study investigates the feasibility of using J-PET for range monitoring by means of a detailed Monte Carlo simulation study of 95 patients who underwent proton therapy at the Cyclotron Centre Bronowice (CCB) in Krakow, Poland. Approach. Discrepancies between prescribed and delivered treatments were artificially introduced in the simulations by means of shifts in patient positioning and in the Hounsfield unit to the relative proton stopping power calibration curve. A dual-layer, cylindrical J-PET geometry was simulated in an in-room monitoring scenario and a triple-layer, dual-head geometry in an in-beam protocol. The distribution of range shifts in reconstructed PET activity was visualized in the beam's eye view. Linear prediction models were constructed from all patients in the cohort, using the mean shift in reconstructed PET activity as a predictor of the mean proton range deviation. Main results. Maps of deviations in the range of reconstructed PET distributions showed agreement with those of deviations in dose range in most patients. The linear prediction model showed a good fit, with coefficient of determination r (2) = 0.84 (in-room) and 0.75 (in-beam). Residual standard error was below 1 mm: 0.33 mm (in-room) and 0.23 mm (in-beam). Significance. The precision of the proposed prediction models shows the sensitivity of the proposed J-PET scanners to shifts in proton range for a wide range of clinical treatment plans. Furthermore, it motivates the use of such models as a tool for predicting proton range deviations and opens up new prospects for investigations into the use of intra-treatment PET images for predicting clinical metrics that aid in the assessment of the quality of delivered treatment.
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