ESTRO 2023 - Abstract Book

S1873

Digital Posters

ESTRO 2023

A total of 91 patients were enrolled. Patients treated from April 2015 to February 2020 were considered as training set (58), while patients treated from March 2020 to December 2021 were considered for validation set (33). Overall, pCR (defined as absence of viable tumour cells in both primary tumour and nodal pathological specimens, i.e. pT0N0) was observed in 25 cases (27.4%).

A total of 990 quantitative image features were extracted and processed.

A total of 118 nested models were then calculated, combining each significant radiomic feature with ERITCP. The model showing the highest performance was obtained combining ERITCP with the 10th percentile of the grey-levels histogram, calculated on the GTV of the MR image acquired when a BED value of 40 Gy was reached. For the training set, the resulting area under curve (AUC) values of the ERITCP model and the combined model were 0.94 (95%CI: 0.88-0.99) and 0.98 (95%CI: 0.95-1) (p=0.04) respectively, while 0.89 and 0.92 were obtained on the validation set (Fig.1).

Conclusion The integration of radiomic features with ERITCP is able to improve pCR prediction in LARC patients. The combined model can be particularly useful in borderline situations where ERITCP is close to the cut-off threshold.

PO-2091 A method to explore dose and LET for normal tissue response studies in large proton therapy cohorts

R. Klitgaard 1,2 , P. Johnson 3 , N.P. Mendenhall 3 , M. Artz 3 , C. Bryant 3 , P. Lægdsmand 1,2 , L.F. Fjæra 4 , L.P. Muren 1,2

1 Aarhus University, Department of Clinical Medicine, Aarhus, Denmark; 2 Aarhus University Hospital, Danish Centre for Particle Therapy, Aarhus, Denmark; 3 University of Florida College of Medicine, Department of Radiation Oncology, Jacksonville, FL, USA; 4 University of Bergen, Department of Physics and Technology, Bergen, Norway Purpose or Objective Normal tissue complication probability (NTCP) calculations in proton therapy (PT) are usually performed using models derived from photon-based radiotherapy, with the assumption of a constant relative biological effectiveness (RBE) of 1.1. However, RBE has been shown to vary with dose weighted linear energy transfer (LETd), which is often not considered by NTCP models. LETd distributions can be obtained by use of Monte Carlo simulations (MC). However, there is currently no consensus on how to analyze LETd in larger cohorts, nor on how to include LETd in proton-specific NTCP models. In this work we seek to explore a method of analyzing dose and LETd distributions with respect to morbidity, based on multiple pairs of dose and LETd thresholds, in a large cohort of prostate cancer patients treated with passively scattered PT. Materials and Methods For the organ of interest we iteratively selected a dose threshold and from the sub-region of the organ with a dose higher than this threshold, we selected an LETd threshold. For each combination we then graphed the dose threshold vs. the LETd threshold for each patient, with color-coding for patients with vs. without