Parallel modeling of the electric field distribution in the brain

The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.

Proton radiotherapy: a therapeutic opportunity for pediatric brain tumor patients

Proton radiation therapy is a form of external radiation that uses charged particles which have distinct physical advantages to deliver the majority of its dose in the target while minimizing the dose of radiation to normal tissues. In children who are particularly susceptible even at low and medium doses of radiation, the significant reduction of integral dose can potentially mitigate the incidence of side effects and improve quality of life. The aim of the first part of the thesis is to describe the physical and radiobiological properties of protons, the Proton Therapy Center of Trento (TCPT) active for clinical purpose since 2014, which use the most recent technique called active pencil beam scanning. The second part of the thesis describes the preliminary clinical results of 23 pediatric patients with central nervous system tumors as well as of two aggressive pediatric meningiomas treated with pencil beam scanning. All the patients were particularly well-suited candidates for proton therapy (PT) for possible benefits in terms of survival and incidence of acute and late side effects. We reported also a multicentric experience of 27 medulloblastoma patients (median age 6 years, M/F ratio 13/14) treated between 2015 and 2020 at TPTC coming from three Pediatric oncology centers: Bologna, Florence, and Ljubljana, with a focus on clinical results and toxicities related to radiotherapy (RT). Proton therapy was associated with mostly mild acute and late adverse effects and no cases of CNS necrosis or high grade of neuroradiological abnormailities. Comparable rates of survival and local control were obtained to those achievable with conventional RT. Finally, we performed a systematic review to specifically address the safety of PT for pediatric CNS patients, late side effects and clinical effectiveness after PT in this patient group.