This thesis introduces an innovative approach for enhancing the characterization of radiation field quality through microdosimetry. Over the past 30 years, clinical results have shown that ion therapy may be a superior treatment option for several types of cancer, including recurrent cancers, compared to conventional radiation. Despite these promising results, there are still several treatment uncertainties related to biological and physical processes that prevent the full exploitation of particle therapy. Among the physical characterizations, it is paramount to measure the quality of the irradiating field in order to link the biological effect to its physical description. In this way, uncertainties in treatment can be reduced and outcomes optimized. One tool for studying the radiation field that has become increasingly important in the last decade is microdosimetry . Over the last years, microdosimetry has proved to be a superior tool for describing radiation quality, especially when compared to standard reference quantities used nowadays in the clinic. In microdosimetry, the fundamental quantity is the lineal energy y, defined as the energy deposition in the detector divided by the Mean Chord Length (MCL): an approximation used to estimate the track length traveled by radiation in the detector, valid in an isotropic, uniform radiation field. As a consequence, microdosimeters has evolved in obtaining the best possible energy release estimation, without improving the accuracy of the MCL approximation. Measuring the Real Track Length (RTL) traveled by the particle inside the detector could provide a better description of the radiation quality. In fact, from a biological perspective, it is critical if a large amount of energy is released over a long particle track, or if it is extremely dense over a small particle track. If the energy released is more dense, the biological damage induced is likely to be more complex and therefore more significant. For these reasons, a novel approach to microdosimetry is presented that considers the RTL in the radiation quality description. The first chapter of the thesis presents standard microdosimetry and its main quantities. A special emphasis is given to the microdosimeter used in this work, i.e. the TEPC or Tissue Equivalent Proportional Counter, a gas microdosimeter that is equivalent in terms of energy deposition to 2 um of tissue. A comprehensive characterization of the TEPC response to different ions and energies can be found in the literature. A topic missing in the literature is the investigation of the TEPC response to clinical protons of different particles rates. A section is dedicated to the TEPC detector response to pileup. Pileup occurs where two or more energy deposition events are processed together, disrupting the normal signal processing. By exposing the TEPC to particles rates ranging from few particles per seconds to 106 particles per second, it was possible to estimate the distortion of the acquired spectra due to pileup. On the other hand, by using Monte Carlo simulations, it was possible to reproduce the effect of pileup on microdosimetric spectra. Using a quantitative approach, the experimental spectra measured at different particles rate and the spectra simulated at a different pileup probability are matched based on a similarity criteria. In this way, it was possible to build a particle rate-pileup curve for the TEPC, used to quantify the pileup probability contribution. More in general, this approach could be extended and used to other microdosimeters. The acquisition of the data in pileup condition is sometimes inevitable, and some microdosimeters are more likely to suffer from high particle rates. With this part of the thesis, I aim to provide a tool to acquire microdosimetric spectra even in pileup condition. A description of the TEPC acquisition chain is provided in the next section. This is an important topic as any further integration or improvement will require the modification of at least one element of the acquisition. Then, the typical data analysis carried out on the microdosimetric spectra is presented, together with the calibration procedure of the TEPC detector based on Monte Carlo simulation using Geant4. Finally, I provide an overview of the software Mandarina, which is the implemented Graphical User Interface (GUI), written in C# language, and developed specifically to analyze the experimental microdosimetric data. By using this software, users can build a microdosimetric spectra starting from raw acquired data. In addition, the software provides the ability to modify key acquisition parameters and provides real-time feedback on how the microdosimetric spectra change under these modifications. Then, I introduce the concept of Hybrid Detector of Microdosimetry (HDM). HDM is composed of a commercial TEPC, and 4 layers of Low Gain Avalanche Detectors (LGADs). LGADs are silicon detectors featuring an internal gain by exploring the avalanche effect. This makes them suitable to detect particles with a broad range of energy release in the silicon. A detailed description of how the LGADs detect ionizing radiation is provided in this work. LGADs are used in the HDM as a tracking component, capable of reconstructing the particle trajectories inside the TEPC. In this way, instead of relying on the MCL approximation to calculate the value of y, it is possible to define a new quantity: yr. yr differs from the standard y because it uses the real track length instead of the mean chord length approximation. Next, a preliminary Geant4-based study for optimizing the detector geometry is discussed. Tracking capability and simulated microdosimetric spectra with the estimated track length were assessed and are presented in this thesis. To experimentally realize HDM, the acquisition chain of the TEPC must be upgraded since the original acquisition system cannot directly integrate the tracking information from the LGADs strips. A chapter of this work is dedicated to the implementation of the new acquisition system, which allows for the digitalization of the time series signal produced by the detector. The system is based on an Eclypse-Z7 FPGA development board which can host up to 4 Analog to Digital Converters (ADC). Following a bottom-up approach, this chapter describes first the main characteristics of the signal to be digitized. An overview of the Eclypse-Z7 development board with its main capabilities is provided. Finally, the controller in charge of driving the ADC is described. Being a Zynq FPGA, both Programming Logic (PL) and Processing System (PS) need to be programmed. The PL is responsible for driving the ADC at a low level, controlling the triggering and the data flow to the PS. The PS hosts a custom Linux distribution with the task of supervising the acquisition by setting the main parameters, like the number of samples to acquire, the trigger condition and position with respect to the acquisition window. The PS is also responsible for storing the data safely into an SD card connected to the Eclypse-Z7. With a fully customizable system, it is then possible to integrate other systems by properly synchronizing the acquisition with other devices. In the specific case of HDM, a correspondence between the energy release and the LGAD-based tracking component needs to be implemented. Once the time series is properly acquired, the data analysis needs to be developed. A specific section of the thesis is dedicated to this important task, as the correct processing of the signals is a requirement to obtain robust microdosimetric spectra. The time series processing features a classification algorithm that allows to identify artifacts of the acquired signals, such as saturation, double hits and noisy signals. Once the time series are correctly processed and the relevant information is extracted, it is possible to calculate the microdosimetric spectra. In this acquisition chain the detector signal is processed with 3 different levels of gain, obtaining the same version of the signal but with different amplification. In this way it is possible to span a large dynamic range while maintaining the required resolution typical of microdosimetry. However, the three signals must be then joined together to span the required dynamic range. This process goes under the name of intercalibration and has a dedicated section in the chapter. Once the signals are intercalibrated, it is necessary to apply a calibration. The new calibration process developed within this work differs from the previously adopted calibration method based on Monte Carlo simulation, and is described in detail. Finally, the spectra obtained with the new acquisition are compared to those obtained with the original acquisition chain. The next chapter is dedicated to the LGAD readout. Again, following a bottom up approach, an introduction to the LGAD signal is provided. This readout acquisition chain is already partially available since it has been developed by the INFN-TO (Istituto Nazionale di Fisica Nucleare) of Turin. For the first stage of signal processing, two main components developed by the aforementioned INFN-TO are available: the ABACUS chip and the ESA_ABACUS printed circuit board (PCB) board. The ABACUS chip is an ASIC (application-specific integrated circuit) designed to process directly the small signal coming from the LGADs strips. At each activation of one LGAD strip, a digital signal is generated. Each ABACUS is capable of handling up to 24 LGADs strips and can adjust the threshold of each channel within a limited range. Threshold adjustment is required to separate the signal from the noise, as it is expected that all the channels do not share a common threshold due to their specific noise. The ABACUS PCB has been developed to physically host up to 6 ABACUS chips plus the LGAD sensor. It is equipped with an internal DAC (Digital to Analog Converted) used to set a common threshold for all 24 channels managed by one ABACUS chip. In this way, a common threshold can be selected using the ABACUS DAC, and then, to satisfy the specific needs of each channel, the ABACUS chip is used. In order to program the thresholds, the manufacturer required specific serial communication protocols. It is necessary to integrate this communication protocol into the acquisition system. To meet these requirements, I developed an FPGA-based readout system capable of processing the signal from the ABACUS chip and setting the threshold for each channel. I describe in detail the implementation of such a system in a dedicated chapter, again following a bottom-up approach starting from the PL, and moving to the PS. In a specific section, I show how the communication protocol has been implemented and tested and how the fast digital pulses, coming from the ABACUS chip, are processed in the PL. I also describe how the PS system was built. As in the case of the new TEPC acquisition, a Linux system was run on the PS. This made it easier for the end user to work with the acquired data and threshold controls. The movement of data from the PL to the PS is accomplished using DMA or Direct Memory Access. This is a critical component because it allows fast (within one clock cycle) data transfer from the PL to the user in the PS. The implementation of such architecture is quite complex and demands both knowledge in advanced electronics and Linux systems. In fact, the DMA requires the implementation of a Linux kernel driver to correctly move the data. This process is described in a dedicated section of this thesis. With this implementation design in the FPGA it was possible to acquire the signal from 24 LGADs strips and control the thresholds. An experimental campaign was conducted at the proton therapy center in Trento where the whole acquisition system was tested extensively. The results are reported in a dedicated section of this thesis. All the signals coming from the protons with energies ranging from 70 to 228 MeV were correctly discriminated, proving that the readout system can work with protons of clinical energies. Finally, thermal tests were conducted on the acquisition setups since during the experimental campaign some thermal drifts of the baseline were observed. The test results are shown in a dedicated section of this thesis. Finally, I included a chapter on discussion on the results achieved and on future perspective.
| Identifer | oai:union.ndltd.org:unitn.it/oai:iris.unitn.it:11572/398550 |
| Date | 05 December 2023 |
| Creators | Pierobon, Enrico |
| Contributors | Pierobon, Enrico, La Tessa, Chiara |
| Publisher | Università degli studi di Trento, place:TRENTO |
| Source Sets | Università di Trento |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | firstpage:1, lastpage:177, numberofpages:177 |
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