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Detection of drifts on Proton Therapy machines through the analysis of irradiation logs / Harold Snyers d'Attenhoven 

Public ISBD Titre : Detection of drifts on Proton Therapy machines through the analysis of irradiation logs Type de document : Travail de fin d'études Auteurs : Harold Snyers d'Attenhoven, Auteur ; Felix Maldague, ; Nicolas Marchand, Editeur : ECAM Année de publication : 2021 Note générale : IBA PROTON THERAPY SOLUTIONS Langues : Anglais (eng) Index. décimale : TFE - Informatique (ECAM) Résumé : Over the past decade, Proton Therapy (PT) has gained much traction thanks to its unique aptitudes to treat cancer in a safe environment. This year, IBA celebrated an important milestone with over 100.000 patients treated in their 36 centres worldwide. IBA aims at providing treatment for everyone and in the first steps to achieve this, reducing the downtime of their Proton Therapy System (PTS) is one of their main priorities. For every unscheduled maintenance, the downtime period can last more than a day which consequently removes the ability to treat patients. In 2016, a first theoretical study was done to find time invariants in feedbacks of irradiations in order to detect drifts in time in the PTS. Being able to detect these drifts or early degradations of the system will enable IBA to apply preventive maintenance on their systems and consequently reducing the downtime of the PTS. The goal of this thesis is to provide a study in the development of an algorithm or model able to do preventive maintenance. This study will be divided into three main steps; i) group the irradiation that can be compared together in time using Splunk, only irradiations from the same patient can be compared together as they have the same treatment plan (a patient istreated over an average of 20 days to reduce the damage on healthy tissues). ii) Analyse different methods of normalization of data and find time invariants iii) Develop algorithm to detect drifts in PTS. Detection of drifts on Proton Therapy machines through the analysis of irradiation logs [Travail de fin d'études] / Harold Snyers d'Attenhoven, Auteur ; Felix Maldague, ; Nicolas Marchand,  . - ECAM, 2021. IBA PROTON THERAPY SOLUTIONS Langues : Anglais (eng) Index. décimale : TFE - Informatique (ECAM) Résumé : Over the past decade, Proton Therapy (PT) has gained much traction thanks to its unique aptitudes to treat cancer in a safe environment. This year, IBA celebrated an important milestone with over 100.000 patients treated in their 36 centres worldwide. IBA aims at providing treatment for everyone and in the first steps to achieve this, reducing the downtime of their Proton Therapy System (PTS) is one of their main priorities. For every unscheduled maintenance, the downtime period can last more than a day which consequently removes the ability to treat patients. In 2016, a first theoretical study was done to find time invariants in feedbacks of irradiations in order to detect drifts in time in the PTS. Being able to detect these drifts or early degradations of the system will enable IBA to apply preventive maintenance on their systems and consequently reducing the downtime of the PTS. The goal of this thesis is to provide a study in the development of an algorithm or model able to do preventive maintenance. This study will be divided into three main steps; i) group the irradiation that can be compared together in time using Splunk, only irradiations from the same patient can be compared together as they have the same treatment plan (a patient istreated over an average of 20 days to reduce the damage on healthy tissues). ii) Analyse different methods of normalization of data and find time invariants iii) Develop algorithm to detect drifts in PTS.

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