A Novel Hybrid Microdosimeter for Radiation Field Characterization Based on the Tissue Equivalent Proportional Counter Detector and Low Gain Avalanche Detectors Tracker: A Feasibility Study

Abstract

In microdosimetry, lineal energies y are calculated from energy depositions ϵ inside the microdosimeter divided by the mean chord length, whose value is based on geometrical assumptions on both the detector and the radiation field. This work presents an innovative two-stages hybrid detector (HDM: hybrid detector for microdosimetry) composed by a tissue equivalent proportional counter and a silicon tracker made of 4 low gain avalanche diode. This design provides a direct measurement of energy deposition in tissue as well as particles tracking with a submillimeter lateral spatial resolution. The data collected by the detector allow to obtain the real track length traversed by each particle in the tissue equivalent proportional counter and thus estimates microdosimetry spectra without the mean chord length approximation. Using Geant4 toolkit, we investigated HDM performances in terms of detection and tracking efficiencies when placed in water and exposed to protons and carbon ions in the therapeutic energy range. The results indicate that the mean chord length approximation underestimate particles with short track, which often are characterized by a high energy deposition and thus can be biologically relevant. Tracking efficiency depends on the low gain avalanche diode configurations: 34 strips sensors have a higher detection efficiency but lower spatial resolution than 71 strips sensors. Further studies will be performed both with Geant4 and experimentally to optimize the detector design on the bases of the radiation field of interest.The main purpose of HDM is to improve the assessment of the radiation biological effectiveness via microdosimetric measurements, exploiting a new definition of the lineal energy (yT), defined as the energy deposition ϵ inside the microdosimeter divided by the real track length of the particle.

MINAS TIRITH: a new tool for simulating radiation-induced DNA damage at the cell population level

“…In other studies, the quantity y , T obtained by calculating the ratio between the imparted energy i e and track length of each particle, has been identified as a good predictor of biological effectiveness (Vassiliev et al 2020). Moreover, it can be experimentally measured (Missiaggia, et al 2021(Missiaggia, et al , 2022. However, the y T definition does not correspond to the use for which the spectra are obtained because the track length cannot be reconstructed geometrically.…”

ICRU Report 98, Stochastic Nature of Radiation Interactions: Microdosimetry

“…Machine-learning techniques have been used to refine the design of a complex detector system (Missiaggia et al, 2021;2022) and to produce microdosimetric values for targeted alpha therapy (Wagstaff et al, 2022).…”

“…Once the ML model is trained and tested, it can be used as a predictive tool. The ML acceleration relies on the previous time-consuming generation of data by means of Monte Carlo simulations, which results in a trade-off between gain in speed by the ML model and time needed to produce the ML model. Machine-learning techniques have been used to refine the design of a complex detector system (Missiaggia et al , 2021; 2022) and to produce microdosimetric values for targeted alpha therapy (Wagstaff et al , 2022). From the physics perspective, one main challenge presented by ML-driven acceleration is the change of paradigm in the calculation of physics results.…”

Design and development of Low Gain Avalanche Detectors using Teledyne e2v process

“…Owing to their timing characteristics, LGADs have been proposed as the technology choice for the timing sensors of the High-Granularity Timing Detector of the Inner Tracker (ITK) [3] of the ATLAS experiment for the HL-LHC at CERN [4]. Additional potential applications are being investigated in the field of radiation dosimetry and X-ray detection [5,6].…”