S2859
RTT - RTT education, training, and advanced practice
ESTRO 2026
public sector, where most departments rated staffing and operational efficiency as inadequate. Equipment procurement presented a challenge with 65% of centers (majority in the public sector), expressing that the tendering delays severely or critically affected their ability to provide care. These findings demonstrate marked sector-based inequities in RT capacity and access.
Digital Poster 2055 Unlocking Radiotherapy Access: The Critical Role of Structural Quality and Radiation Therapists in Saudi Arabia Zaheeda Mulla 1 , Wsam Ghandourh 2 , Hussain Almerdhemah 1 , Norah Al Bishi 3 , Ahmed Kattan 4 , Amal Al Qahtani 5 , Zainab Mansoor Alsaihaty 6 , Ghada Aldosary 7 1 Oncology, King Faisal Specialist Hospital and Research Centre, Jeddah, Saudi Arabia. 2 Department of Health Care Management, Umm Al-Qura University, Makkah, Saudi Arabia. 3 Oncology, Prince Sultan Military Medical City, Riyadh, Saudi Arabia. 4 Oncology, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia. 5 Oncology, John Hopkins Aramco Healthcare, Dhahran, Saudi Arabia. 6 Oncology, King Fahad Specialist Hospital, Dammam, Saudi Arabia. 7 Radiation Oncology, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia Purpose/Objective: Radiation therapy is vital for cancer treatment, significantly improving survival and quality of life yet access remains a challenge even in high-income countries like Saudi Arabia. Key structural indicators include staffing and equipment availability, measured by staff-to-patient ratios and operational radiotherapy units. This study aims to examine how staffing and equipment availability, distribution, and capacity affect access to care and quality of radiotherapy services in Saudi Arabia. Material/Methods: A mixed-methods design using a descriptive cross- sectional approach was employed. A survey adapted from Ramashia et al. (2025), developed to collect both quantitative and qualitative data from public, private, mixed (public–private), and military radiotherapy (RT) centers, was distributed electronically to the supervisors/managers of 20 RT units in Saudi Arabia between 24 September and 23 October 2025. The qualitative phase explored the perspectives of radiation therapists and medical physicists, while the quantitative phase examined variables such as staff numbers and distribution, patient volumes, equipment availability, treatment waiting times, and overall facility capacity for the period January to December 2024. Results: Seventeen out of the 20 RT centers (85% response rate) were assessed. Public facilities treated the highest caseloads but had fewer linear accelerators per patient, higher clinician workloads, and longer waiting times, with radical treatment often exceeding 14 days (Figure 1). Mixed centers had the greatest machine capacity and advanced technologies (Table 1). Training opportunities were limited, particularly in the
Conclusion: These findings will support the development of a strategic framework to strengthen RT capacity and reduce sector-based disparities. Ultimately, this evidence can guide policy and resource planning toward more equitable cancer care delivery in the country. Keywords: Radiotherapy access, quality indicators References: Ramashia et al. Improving Access to Radiotherapy: Exploring Structural Quality Indicators for Radiotherapy in Gauteng Province, South Africa. Int J Environ Res Public Health. 2025 Apr 8;22(4):585. doi: 10.3390/ijerph22040585. Digital Poster 2072 Assessment of IRIS reconstruction image quality in pelvic CBCT for online adaptive contouring Annelies J Zoetelief, Michael J Rijssel, Kim Verhoef, Gonda G Sikkes, Claudia M.C.W. Galama-Meester, Margriet Vriens, Martijn P.W. Intven, Gert J Meijer Radiotherapy, UMC Utrecht, Utrecht, Netherlands Purpose/Objective: Cone-beam CT (CBCT) image quality remains a limiting factor for accurate adaptation in online adaptive workflows for pelvic sites. This study aimed to evaluate different options to introduce AI-enhanced IRIS reconstruction (Elekta) to improve CBCT image quality for online adaptive workflows [1]. Subsequently, the image quality of CBCT scans with
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