ESTRO 2024 - Abstract Book

S2980

Interdiscplinary - Other

ESTRO 2024

not for Dmin (Δ-0,34 Gy). yDERO was 10 time faster than visual estimation with a mediane time about 6,5min (range, 6.0-9.0) vs 60 min (range, 45,0-94,0), p=0,0047.

Conclusion:

yDERO provide a dose estimates more accurate than visual estimates, consistent to calculated dose in expert contours, and is 10 times faster than the current daily practice. Dental radiation maps are a useful documentation and communication tool between radiation oncologists and dentists in routine practice.

Keywords: dental dosimetric mapping, dental care, children

References: Oeffinger KC, Mertens AC, Sklar CA, Kawashima T, Hudson MM, Meadows AT, et al. Chronic Health Conditions in Adult Survivors of Childhood Cancer. N Engl J Med. 12 oct 2006;355(15):1572-82. Kaste SC, Goodman P, Leisenring W, Stovall M, Hayashi R, Yeazel M, et al. Impact of Radiation and Chemotherapy on Risk of Dental Abnormalities: A Report from the Childhood Cancer Survivor Study. Cancer. 15 déc 2009;115(24):5817-27. Delpon G, Renouf M, Langé M, Blery P, Dupas C, Longis J, et al. Systematic dosimetric evaluation of risk of osteoradionecrosis (DERO): First results of dose reporting for preventing teeth osteoradionecrosis after head and neck irradiation. Cancer Radiother J Soc Francaise Radiother Oncol. avr 2023;27(2):103-8.

2969

Digital Poster

Assessing auto-contours: inter- and intra-rater reliability with a novel qualitative scoring system

Katherine Mackay 1,2 , David Bernstein 3,2 , Sooha Kim 2 , Harshani Green 1,2 , Binnaz Yasar 1,2 , Ragu Ratnakumaran 1,2 , Hoda Abdel-Aty 2 , Charleen Chan Wah Hak 2 , Vincent Khoo 1,2 , Alexandra Taylor 1,2 1 The Royal Marsden Hospital NHS Foundation Trust, Department of Radiotherapy, London, United Kingdom. 2 The Institute of Cancer Research, Radiotherapy and Imaging, London, United Kingdom. 3 The Royal Marsden Hospital NHS Foundation Trust, Department of Physics, London, United Kingdom

Purpose/Objective:

Despite the rapid increase in availability of artificial intelligence-based auto-contouring systems, there is limited guidance on implementation and ongoing quality assurance. Whereas quantitative statistics may be useful for model development, other metrics including dosimetric impact and qualitative assessment are more relevant for use in daily clinical practice. It is essential to have clinical review of any auto-contours prior to clinical use. However, there is no agreement on how clinicians should perform this, with multiple Likert scales being used between 2-11 points in published studies [1]. This makes it difficult to compare studies and introduce standardised assessment methods. Standardised, structured assessments are needed, to reduce the risk of automation bias when checking auto-contours and remind clinicians to prioritise critical areas. The most effective proposed method is to develop a tumour specific tool, capturing both time-saving and dosimetric impact.