Positron Emission Particle Tracking of Granular Flows

A topological approach to positron emission particle tracking for finding multiple particles in high noise environments

Positron emission particle tracking (PEPT) is an advanced imaging technique that accurately tracks the three-dimensional spatial coordinates of a radioactively-labelled particle with sub-millimetre and sub-millisecond precision. By detecting back-to-back 511 keV gamma rays from positron-electron annihilation coincidence events, PEPT can locate particles within highly dense, opaque systems such as fluidised beds, rotating drums, and mills. Despite the progress made in enhancing the precision and accuracy of PEPT, simultaneous multiple particle tracking remains a significant challenge, particularly in high-noise environments. This paper introduces T-PEPT, a novel algorithm that leverages topological data analysis-a relatively new field of applied mathematics that explores the underlying 'shape' of data through techniques like persistence homology. By creating simplicial complexes and applying persistence homology to PEPT point data, T-PEPT demonstrates highly effective performance in multiple-particle tracking, especially in scenarios with high noise. When benchmarked against existing PEPT algorithms using a widely recognised standard framework, T-PEPT consistently maintains sub-millimetre spatial and sub-millisecond temporal precision in nearly all cases, demonstrating its robustness and accuracy. For Data availability for T-PEPT, please use the GitHub repository: https://github.com/uob-positron-imaging-centre/pept .

Ultrasensitive and multiplexed tracking of single cells using whole-body PET/CT

In vivo molecular imaging tools are crucially important for elucidating how cells move through complex biological systems; however, achieving single-cell sensitivity over the entire body remains challenging. Here, we report a highly sensitive and multiplexed approach for tracking upward of 20 single cells simultaneously in the same subject using positron emission tomography (PET). The method relies on a statistical tracking algorithm (PEPT-EM) to achieve a sensitivity of 4 becquerel per cell and a streamlined workflow to reliably label single cells with over 50 becquerel per cell of 18F-fluorodeoxyglucose (FDG). To demonstrate the potential of the method, we tracked the fate of more than 70 melanoma cells after intracardiac injection and found they primarily arrested in the small capillaries of the pulmonary, musculoskeletal, and digestive organ systems. This study bolsters the evolving potential of PET in offering unmatched insights into the earliest phases of cell trafficking in physiological and pathological processes and in cell-based therapies.

Enhanced Tracer Particle Detection in Dynamic Bulk Systems Based on Polarimetric Radar Signature Correlation

This contribution focuses on the detection of tracer particles within non-homogeneous bulk media, aiming to enhance insights into particulate systems. Polarimetric radar measurements are employed, utilizing cross-polarizing channels in order to mitigate interference from bulk media reflections. To distinguish the tracer particle in the measurements, a resonant cross-polarizing structure is constructed, facilitating the isolation of frequency signatures from the surrounding bulk clutter. In addition to characterizing the bulk and tracer components, this study provides a detailed presentation and discussion of the measurement setup, along with the employed signal processing methods. The effectiveness of the proposed methods is demonstrated through comprehensive measurements, where a tracer particle is systematically positioned at various locations. The results affirm the feasibility and efficacy of the approach, highlighting its applicability for enhanced dynamic monitoring in particulate systems within industrial processes.

Application of Positron Emission Particle Tracking (PEPT) for the evaluation of powder behaviour in an incline linear blender for Continuous Direct Compression (CDC)

Positron Emission Particle Tracking (PEPT) is a non-invasive measurement technique which offers the ability to track the motion of individual particles with high temporal and spatial resolution, and thus build up an understanding of the bulk behaviour of a system from its microscopic (particle level) dynamics. Using this measurement technique, we have developed a series of novel metrics to better understand the behaviours of powders during the steady-state operation of a continuous blender system. Results are presented concerning the response of particle motion to processing parameters (mixing blade configuration and RPM), quantifying the motion in terms of predicted mixing performance. It was found that both increasing rpm and increasing hold-up mass (by selecting fewer transport blades and more mixing blades) provided improved mixing conditions. Interestingly, under specific conditions, there is evidence of convection-like mixing occurring at the interface of the transport and mixing region. This suggests the existence of a potential 'folding region' whereby powder is transported up the barrel (and away from the powder bulk bed) before being reconstituted back into the bulk mass. The results also provide valuable experimental data for the development, calibration and validation of future Discrete Element Method (DEM) simulations.

Efficient and multiplexed tracking of single cells using whole-body PET/CT

In vivo molecular imaging tools are crucially important for elucidating how cells move through complex biological systems, however, achieving single-cell sensitivity over the entire body remains challenging. Here, we report a highly sensitive and multiplexed approach for tracking upwards of 20 single cells simultaneously in the same subject using positron emission tomography (PET). The method relies on a new tracking algorithm (PEPT-EM) to push the cellular detection threshold to below 4 Bq/cell, and a streamlined workflow to reliably label single cells with over 50 Bq/cell of 18F-fluorodeoxyglucose (FDG). To demonstrate the potential of method, we tracked the fate of over 70 melanoma cells after intracardiac injection and found they primarily arrested in the small capillaries of the pulmonary, musculoskeletal, and digestive organ systems. This study bolsters the evolving potential of PET in offering unmatched insights into the earliest phases of cell trafficking in physiological and pathological processes and in cell-based therapies.

Coffee bean particle motion in a rotating drum measured using Positron Emission Particle Tracking (PEPT)

Physicochemical transformation of coffee during roasting depends on the applied time-temperature profile (i.e., rate of heat transfer), with heat transfer phenomena governed by particle dynamics. Positron Emission Particle Tracking (PEPT), a non-invasive imaging technique, was used here to characterise the granular flow of coffee in a real, pilot-scale rotating drum roaster. The experimental study established the impact of drum speed, batch size and bean density (i.e., roast degree) on the system's particle dynamics. Particle motion data revealed two distinct regions: (i) a disperse (low occupancy, high velocity) region of in-flight particles and (ii) a dense (high occupancy, low velocity) bean bed. Implications of these results for heat transfer suggest that controlling drum speed for different density coffees will provide roaster operators with a tool to modulate conductive heat transfer from the heated drum to the bean bed. These comprehensive data thus inform roasting best practices and support the development of physics-driven models coupling heat and mass transfer to particle dynamics.

Autonomous digitizer calibration of a Monte Carlo detector model through evolutionary simulation

Simulating the response of a radiation detector is a modelling challenge due to the stochastic nature of radiation, often complex geometries, and multi-stage signal processing. While sophisticated tools for Monte Carlo simulation have been developed for radiation transport, emulating signal processing and data loss must be accomplished using a simplified model of the electronics called the digitizer. Due to a large number of free parameters, calibrating a digitizer quickly becomes an optimisation problem. To address this, we propose a novel technique by which evolutionary algorithms calibrate a digitizer autonomously. We demonstrate this by calibrating six free parameters in a digitizer model for the ADAC Forte. The accuracy of solutions is quantified via a cost function measuring the absolute percent difference between simulated and experimental coincidence count rates across a robust characterisation data set, including three detector configurations and a range of source activities. Ultimately, this calibration produces a count rate response with 5.8% mean difference to the experiment, improving from 18.3% difference when manually calibrated. Using evolutionary algorithms for model calibration is a notable advancement because this method is novel, autonomous, fault-tolerant, and achieved through a direct comparison of simulation to reality. The software used in this work has been made freely available through a GitHub repository.

Performance Evaluation of the Current Birmingham PEPT Cameras

Positron emission particle tracking (PEPT), a powerful technique for studying fluid and granular flows, has been developed at Birmingham over the last 30 years. In PEPT, a “positron camera” is used to detect the pairs of back-to-back photons emitted from positron annihilation. Accurate high-speed tracking of small tracer particles requires a positron camera with high sensitivity and data rate. In this paper, we compare the sensitivity and data rates obtained from the three principal cameras currently used at Birmingham. The recently constructed SuperPEPT and MicroPEPT systems have much higher sensitivity than the longstanding ADAC Forte and can generate data at much higher rates, greatly extending the potential for PEPT studies.

Recent advances in positron emission particle tracking: a comparative review

Positron emission particle tracking (PEPT) is a technique which allows the high-resolution, three-dimensional imaging of particulate and multiphase systems, including systems which are large, dense, and/or optically opaque, and thus difficult to study using other methodologies. In this work, we bring together researchers from the world's foremost PEPT facilities not only to give a balanced and detailed overview and review of the technique but, for the first time, provide a rigorous, direct, quantitative assessment of the relative strengths and weaknesses of all contemporary PEPT methodologies. We provide detailed explanations of the methodologies explored, including also interactive code examples allowing the reader to actively explore, edit and apply the algorithms discussed. The suite of benchmarking tests performed and described within the document is made available in an open-source repository for future researchers.

Size segregation of irregular granular materials captured by time-resolved 3D imaging

When opening a box of mixed nuts, a common experience is to find the largest nuts at the top. This well-known effect is the result of size-segregation where differently sized ‘particles’ sort themselves into distinct layers when shaken, vibrated or sheared. Colloquially this is known as the ‘Brazil-nut effect’. While there have been many studies into the phenomena, difficulties observing granular materials mean that we still know relatively little about the process by which irregular larger particles (the Brazil nuts) reach the top. Here, for the first time, we capture the complex dynamics of Brazil nut motion within a sheared nut mixture through time-lapse X-ray Computed Tomography (CT). We have found that the Brazil nuts do not start to rise until they have first rotated sufficiently towards the vertical axis and then ultimately return to a flat orientation when they reach the surface. We also consider why certain Brazil nuts do not rise through the pack. This study highlights the important role of particle shape and orientation in segregation. Further, this ability to track the motion in 3D will pave the way for new experimental studies of segregating mixtures and will open the door to even more realistic simulations and powerful predictive models. Understanding the effect of size and shape on segregation has implications far beyond food products including various anti-mixing behaviors critical to many industries such as pharmaceuticals and mining.