Improving radiotherapy through medical physics developments

The Italian young medical physicist scenario: Results from the young AIFM group survey

PURPOSE

The young working group of the Italian Association of Medical and Health Physics (AIFM) designed a survey to assess the current situation of the under 35 AIFM members.

METHODS

An online survey including 65 questions was designed to gather personal information, educational issues, working and research experience, and to evaluate the AIFM activities. The survey was distributed to the under 35 members between November 2022 and February 2023, through the young AIFM mailing list and social media.

RESULTS

160 answers from 230 affiliates (70%, 31 years median age) were obtained. The results highlighted that 87% of the respondents had a fixed term/permanent employment, mainly in public hospitals (58%). Regarding Medical Physicists (MPs) training, 54% of the students left their region of origin due to the training plan (40%) and the availability of scholarships (25%) in the chosen university. Most of the respondents have no Radiation Protection Expert title, while the remaining 20%, 6%, and 3% are qualified to the first, second, and third level, respectively. Several young MPs (62.2%) were involved in research activities; however, only 28% had teaching experience, mainly within their workplace (20%, safety courses), during AIFM courses (4%), or university lectures (3%).

CONCLUSIONS

This survey reported the current situation of the under 35 AIFM members, highlighting the "brain drain" phenomenon from the south to the north of Italy, mainly due to the lack of post-graduate schools, scholarships, and job opportunities. The obtained results will help the future working program of the AIFM.

Survey on the interest and commitment of AIFM members to scientific activities (SicAS) - The initiative of the FutuRuS working group

PURPOSE

The "FutuRuS" working group of the Italian Association of Medical Physics and Health Physics (AIFM) designed a survey (SicAS) to get feedback from its members regarding their interests and their experience in taking part in scientific activities and events, with the objective of focusing future efforts of the AIFM towards increasing the scientific activity of the medical physics expert (MPE).

METHODS

SicAS was sent out in March 2022 to all AIFM members by newsletter and official communication. SicAS was structured into three sections: personal information and institution of affiliation information, involvement in scientific activities, interest in and commitment to scientific activities. Responses were collected in a fully anonymised mode from the Google Forms platform and analysed with descriptive statistics.

RESULTS

Out of 1289 members (active at the end of 2021), 467 responded to the Survey (response rate of 36%). The Survey results highlighted that AIFM members ranked the involvement of the MPE in scientific activities as highly relevant to the profession. However, 34.7% indicated devoting less than 10% of their working time to scientific activities. 67.5% of the respondents were dissatisfied with the time spent on scientific activities. The primary barrier was the lack of time (77%), followed by a lack of mentoring (32%).

CONCLUSIONS

SicAS highlighted the need for AIFM initiatives to support members' scientific activities. National societies should help develop and support networks between members, create links among universities, hospitals, research institutions and industries, and provide guidelines and learning platforms for enhancing the MPEs' involvement in scientific activities.

Risk and Quality in Brachytherapy From a Technical Perspective

AIMS

To provide an overview of the history of incidents in brachytherapy and to describe the pillars in place to ensure that medical physicists deliver high-quality brachytherapy.

MATERIALS AND METHODS

A review of the literature was carried out to identify reported incidents in brachytherapy, together with an evaluation of the structures and processes in place to ensure that medical physicists deliver high-quality brachytherapy. In particular, the role of education and training, the use of process and technical quality assurance and the role of international guidelines are discussed.

RESULTS

There are many human factors in brachytherapy procedures that introduce additional risks into the process. Most of the reported incidents in the literature are related to human factors. Brachytherapy-related education and training initiatives are in place at the societal and departmental level for medical physicists. Additionally, medical physicists have developed process and technical quality assurance procedures, together with international guidelines and protocols. Education and training initiatives, together with quality assurance procedures and international guidelines may reduce the risk of human factors in brachytherapy.

CONCLUSION

Through application of the three pillars (education and training; process control and technical quality assurance; international guidelines), medical physicists will continue to minimise risk and deliver high-quality brachytherapy treatments.

Survey on deep learning for radiotherapy

More than 50% of cancer patients are treated with radiotherapy, either exclusively or in combination with other methods. The planning and delivery of radiotherapy treatment is a complex process, but can now be greatly facilitated by artificial intelligence technology. Deep learning is the fastest-growing field in artificial intelligence and has been successfully used in recent years in many domains, including medicine. In this article, we first explain the concept of deep learning, addressing it in the broader context of machine learning. The most common network architectures are presented, with a more specific focus on convolutional neural networks. We then present a review of the published works on deep learning methods that can be applied to radiotherapy, which are classified into seven categories related to the patient workflow, and can provide some insights of potential future applications. We have attempted to make this paper accessible to both radiotherapy and deep learning communities, and hope that it will inspire new collaborations between these two communities to develop dedicated radiotherapy applications.

Target position uncertainty during visually guided deep-inspiration breath-hold radiotherapy in locally advanced lung cancer

PURPOSE

The purpose of this study was to estimate the uncertainty in voluntary deep-inspiration breath-hold (DIBH) radiotherapy for locally advanced non-small cell lung cancer (NSCLC) patients.

METHODS

Perpendicular fluoroscopic movies were acquired in free breathing (FB) and DIBH during a course of visually guided DIBH radiotherapy of nine patients with NSCLC. Patients had liquid markers injected in mediastinal lymph nodes and primary tumours. Excursion, systematic- and random errors, and inter-breath-hold position uncertainty were investigated using an image based tracking algorithm.

RESULTS

A mean reduction of 2-6mm in marker excursion in DIBH versus FB was seen in the anterior-posterior (AP), left-right (LR) and cranio-caudal (CC) directions. Lymph node motion during DIBH originated from cardiac motion. The systematic- (standard deviation (SD) of all the mean marker positions) and random errors (root-mean-square of the intra-BH SD) during DIBH were 0.5 and 0.3mm (AP), 0.5 and 0.3mm (LR), 0.8 and 0.4mm (CC), respectively. The mean inter-breath-hold shifts were -0.3mm (AP), -0.2mm (LR), and -0.2mm (CC).

CONCLUSION

Intra- and inter-breath-hold uncertainty of tumours and lymph nodes were small in visually guided breath-hold radiotherapy of NSCLC. Target motion could be substantially reduced, but not eliminated, using visually guided DIBH.