Concept development of an on-chip PET system.

BACKGROUND: Organs-on-Chips (OOCs), microdevices mimicking in vivo organs, find growing applications in disease modeling and drug discovery. With the increasing number of uses comes a strong demand for imaging capabilities of OOCs as monitoring physiologic processes within OOCs is vital for the continuous improvement of this technology. Positron Emission Tomography (PET) would be ideal for OOC imaging, however, current PET systems are insufficient for this task due to their inadequate spatial resolution. In this work, we propose the concept of an On-Chip PET system capable of imaging OOCs and optimize its design using a Monte Carlo Simulation (MCS). MATERIAL AND METHODS: The proposed system consists of four detectors arranged around the OOC device. Each detector is made of two monolithic LYSO crystals and covered with Silicon photomultipliers (SiPMs) on multiple surfaces. We use a Convolutional Neural Network (CNN) trained with data from a MCS to predict the first gamma-ray interaction position inside the detector from the light patterns that are recorded by the SiPMs on the detector's surfaces. RESULTS: The CNN achieves a mean average prediction error of 0.80 mm in the best configuration. The proposed system achieves a sensitivity of 34.81% for 13 mm thick crystals and does not show a prediction degradation near the boundaries of the detector. We use the trained network to reconstruct an image of a grid of 21 point sources spread across the field-of-view and obtain a mean spatial resolution of 0.55 mm. We show that 25,000 Line of Responses (LORs) are needed to reconstruct a realistic OOC phantom with adequate image quality. CONCLUSIONS: We demonstrate that it is possible to achieve a spatial resolution of almost 0.5 mm in a PET system made of multiple monolithic LYSO crystals by directly predicting the scintillation position from light patterns created with SiPMs. We observe that a thinner crystal performs better than a thicker one, that increasing the SiPM size from 3 mm to 6 mm only slightly decreases the prediction performance, and that certain surfaces encode significantly more information for the scintillation-point prediction than others.

In silico study on radiobiological efficacy of Ac-225 and Lu-177 for PSMA-guided radiotherapy.

The good efficacy of radioligand therapy (RLT) targeting prostate specific-membrane antigen (PSMA) for the treatment of metastatic castration-resistant prostate cancer (mCRPC) has been recently demonstrated in several clinical studies. However, the treatment effect of 177Lu-PSMA-ligands is still suboptimal for a significant fraction of patients. In contrast to external beam radiotherapy, the radiation dose distribution itself is strongly influenced by the heterogeneous tumour microenvironment. Although microdosimetry is critical for RLT treatment outcome, it is difficult to clinically or experimentally establish the quantitative relation. We propose an in silico approach to quantitatively investigate the microdosimetry and its influence on treatment outcome for PSMA-directed RLT of two different radioisotopes 177Lu and 225 Ac. The ultimate goal is optimize the combined 177 Lu and 225 Ac-PSMA therapy and maximize the anti-tumour effect, while minimizing irradiation of off-target tissues.Clinical relevance- With the proposed hybrid model we show that 177Lu-PSMA-ligands treatment assures a more homogeneously distributed dose and a lower dependency of the treatment outcome on the domain vascularisation. On the other hand, the 225Ac-PSMA-ligands treatment shows a much stronger efficacy in killing tumor cells with an equivalent mean dose distribution even in an hypoxic environment.

Is Hypoxia a Factor Influencing PSMA-Directed Radioligand Therapy?-An In Silico Study on the Role of Chronic Hypoxia in Prostate Cancer.

Radioligand therapy (RLT) targeting prostate specific-membrane antigen (PSMA) is an emerging treatment for metastatic castration-resistant prostate cancer (mCRPC). It administrates 225Ac- or 177Lu-labeled ligands for the targeted killing of tumor cells. Differently from X- or γ-ray, for the emitted α or ß particles the ionization of the DNA molecule is less dependent on the tissue oxygenation status. Furthermore, the diffusion range of electrons in a tumor is much larger than the volume typically spanned by hypoxic regions. Therefore, hypoxia is less investigated as an influential factor for PSMA-directed RLT, in particular with ß emitters. This study proposes an in silico approach to theoretically investigate the influence of tumor hypoxia on the PSMA-directed RLT. Based on mice histology images, the distribution of the radiopharmaceuticals was simulated with an in silico PBPK-based convection-reaction-diffusion model. Three anti-CD31 immunohistochemistry slices were used to simulate the tumor microenvironment. Ten regions of interest with varying hypoxia severity were analyzed. A kernel-based method was developed for dose calculation. The cell survival probability was calculated according to the linear-quadratic model. The statistical analysis performed on all the regions of interest (ROIs) shows more heterogeneous dose distributions obtained with 225Ac compared to 177Lu. The higher homogeneity of 177Lu-PSMA-ligand treatment is due to the larger range covered by the emitted ß particles. The dose-to-tissue histogram (DTH) metric shows that in poorly vascularized ROIs only 10% of radiobiological hypoxic tissue receives the target dose using 177Lu-PSMA-ligand treatment. This percentage drops down to 5% using 225Ac. In highly vascularized ROIs, the percentage of hypoxic tissue receiving the target dose increases to more than 85% and 65% for the 177Lu and 225Ac-PSMA-ligands, respectively. The in silico study demonstrated that the reduced vascularization of the tumor strongly influences the dose delivered by PSMA-directed RLT, especially in hypoxic regions and consequently the treatment outcome.

Mapping the Damping Dynamics of Mega-Ampere Electron Pulses Inside a Solid.

We report the lifetime of intense-laser (2×10^{19} W/cm^{2}) generated relativistic electron pulses in solids by measuring the time evolution of their Cherenkov emission. Using a picosecond resolution optical Kerr gating technique, we demonstrate that the electrons remain relativistic as long as 50 picoseconds-more than 1000 times longer than the incident light pulse. Numerical simulations of the propagation of relativistic electrons and the emitted Cherenkov radiation with Monte Carlo geant4 package reproduce the striking experimental findings.

High performance modelling of the transport of energetic particles for photon radiotherapy.

This work consists of the validation of a new Grid Based Boltzmann Solver (GBBS) conceived for the description of the transport and energy deposition by energetic particles for radiotherapy purposes. The entropic closure and a compact mathematical formulation allow our code (M1) to calculate the delivered dose with an accuracy comparable to the Monte-Carlo (MC) codes with a computational time that is reduced to the order of few minutes without any special processing power requirement. A validation protocol with heterogeneity inserts has been defined for different photon sources. The comparison with the MC calculated depth-dose curves and transverse profiles of the beam at different depths shows an excellent accuracy of the M1 model.