Marta Missiaggia

University of Miami Miller School of Medicine | UM · Department of Radiation Oncology

The present work develops ANAKIN: an Artificial iNtelligence bAsed model for (radiation induced) cell KIlliNg prediction. ANAKIN is trained and tested over 513 cell survival experiments with different types of radiation contained in the publicly available PIDE database. We show how ANAKIN accurately predicts several relevant biological endpoints ov...

The present work develops ANAKIN: an Artificial iNtelligence bAsed model for (radiation induced) cell KIlliNg prediction. ANAKIN is trained and tested over 513 cell survival experiments with different types of radiation contained in the publicly available PIDE database. We show how ANAKIN accurately predicts several relevant biological endpoints ov...

Purpose: In the present paper we investigate how some stochastic effects are included in a class of radiobiological models with particular emphasis on how such randomnesses reflect into the predicted cell survival curve. Materials and methods: We consider four different models, namely the Generalized Stochastic Microdosimetric Model GSM2, in its...

Purpose: Using microdosimetry, we investigated the relative biological effectiveness (RBE) and quality factor (Q¯) variations in- and out-of-field as a function of radiation quality for clinical protons. Methods and Materials: we irradiated a water phantom with a Spread-Out-Bragg-Peak (SOBP) and acquired microdosimetric spectra at several distal an...

A new miniaturized Tissue Equivalent Proportional Counter (mini‒TEPC) with cylindrical sensitive volume of 1.0 mm in diameter and height, and with external diameter of 1.53 cm, has been developed to work without gas flow. With this mini counter we have measured the radiation quality of the 148 MeV energy-modulated proton beam at the radiobiological...

In this work we present an advanced Random Forest-based Machine Learning (ML) model, trained and tested on Geant4 simulations. The developed ML model is designed to improve the performance of the Hybrid Detector for Microdosimetry (HDM), a novel hybrid detector recently introduced to augment the microdosimetric information with the track length of...

Microdosimetry

Space agencies have recognized the risks of astronauts’ exposure to space radiation and are developing complex model-based risk mitigation strategies. In the foundation of these models, there are still significant gaps of knowledge concerning nuclear fragmentation reactions which need to be addressed by ground-based experiments. There is a lack of...

The current article presents the first application of the Generalized Stochastic Microdosimetric Model (GSM2) for computing explicitly a cell survival curve. GSM2 is a general probabilistic model that predicts the kinetic evolution of DNA damages taking full advantage of a microdosimetric description of a radiation energy deposition. We show that,...

Different qualities of radiation are known to cause different biological effects at the same absorbed dose. Enhancements of the biological effectiveness are a direct consequence of the energy deposition clustering at the scales of DNA molecule and cell nucleus whilst absorbed dose is a macroscopic averaged quantity which does not take into account...

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 ti...

The present work introduces a rigorous stochastic model, called the generalized stochastic microdosimetric model (GSM2), to describe biological damage induced by ionizing radiation. Starting from the microdosimetric spectra of energy deposition in tissue, we derive a master equation describing the time evolution of the probability density function...

The present work introduces a rigorous stochastic model, named Generalized Stochastic Microdosimetric Model (GSM2), to describe biological damage induced by ionizing radiation. Starting from microdosimetric spectra of energy deposition in tissue, we derive a master equation describing the time evolution of the probability density function of lethal...

Different qualities of radiation are known to cause different biological effects at the same absorbed dose. Enhancements of the biological effectiveness are a direct consequence of the energy deposition clustering at the scales of DNA molecule and cell nucleus whilst absorbed dose is a macroscopic averaged quantity which does not take into account...

In microdosimetry, lineal energies y are calculated from energy depositions $\epsilon$ 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) compose...

Relative Biological Effectiveness (RBE) variations are thought to be one of the primary causes of unexpected normal tissue toxicities during tumor treatments with charged particles. Unlike carbon therapy, where the treatment planning is optimized on the basis of the RBE-weighted dose, a constant RBE value of 1.1 is currently used in proton therapy....