ESTRO 2023 - Abstract Book

S1408

Digital Posters

ESTRO 2023

to store accompanying data (such as radiomics features or dose volume histograms) alongside the NIfTI data. The tool tracks all converted data objects for each patient to streamline processing and analysis.

Results The tool has been successfully utilised in several research projects including the analysis of two clinical trial datasets as well as cardiac sub-structure toxicities in a local dataset. Most notably an in-house project where auto-segmentation models are trained on local data using the nnUNet has been streamlined by utilising the Pydicer pipeline. While some basic coding ability is required to use the tool, most logic has been abstracted into separate modules. This allows users who may have limited coding skills (such as medical physicists) to compose a suitable pipeline and process imaging data in bulk for their research. While difficult to quantify, this has shown a significant time saving over manual analysis using various commercial tools (e.g. MIM). The flexible nature of the tool enables the analysis of larger research datasets derived from our clinical data. Conclusion The Pydicer tool has demonstrated versatility across radiotherapy research projects that analyse imaging data. By being open source, the entire community can benefit from this tool and as features are added or bugs fixed these can be contributed to the tool for all to benefit.

PO-1697 Development of virtual CBCT simulator and deep-learning-based elemental material decomposition.

T. Shimomura 1 , D. Fujiwara 1 , Y. Inoue 1 , A. Takeya 1 , T. Ohta 2 , Y. Nozawa 2 , T. Imae 2 , K. Nawa 2 , K. Nakagawa 2 , A. Haga 1

1 Tokushima University, Medical Informatics, Tokushima, Japan; 2 The University of Tokyo Hospital, Radiology, Tokyo, Japan

Purpose or Objective Nowadays, Cone-Beam Computed Tomography (CBCT) system plays an important role in image-guided radiation therapy and adaptive radiation therapy (ART). However, the image quality degradation made by the scattered x-ray provides the difficulty in the quantitative dose evaluation. For the quantitative CBCT imaging, in this study, we newly propose the development of a virtual CBCT simulator including the scattered x-ray and show the usefulness in an elemental material decomposition (EMD) by developing a head-and-neck (HN) human phantom library. Materials and Methods A HN human phantom library including 36 phantoms composing of six elements (H, C, N, O, P, and Ca) was developed by extending the International Commission on Radiological Protection (ICRP) 110 adult female/male phantoms with the information of age, height, and weight in the human population. A CBCT database using this library was then created by a virtual CBCT simulator, which simulates the direct and scattered x-ray on a flat panel detector (FPD) from a raytracing model and a deep-learning (DL) model, respectively. The Gaussian distributed noise on FPD, of which magnitude was evaluated with a cylindrical water phantom of 25 cm diameter using a real CBCT system (Elekta X-ray Volumetric Imaging