ESTRO 2023 - Abstract Book

S424

Sunday 14 May 2023

ESTRO 2023

diseases and for patients of the Copernic cohort referred for adverse events after RT (Le Reun et al. 2022). However, because clonogenic assays are too time-consuming, predictive functional assays simpler than SF2 are needed for routine practice. They should reflect the continuous spectrum of responses and the dose dependence over the relevant clinical dose range, establish a quantitative relationship between clinical radiosensitivity (from CTCAE grade 0 to grade 5 whatever the early or late nature of tissue reaction) and cellular radiosensitivity and identify patients with moderate radiosensitivity (CTCAE 2 to 5) and without a known radiosensitive genetic disease. Among the numerous functional assays tested for demonstrating individual intrinsic radiosensitivity: 1- cell death assays (mitotic death, micronuclei, cellular senescence, apoptosis); apoptosis is the most documented with significant cell type dependence, e.g., lymphocytes / fibroblasts, no general correlation between apoptosis and radiosensitivity, and one inverse correlation (with no mechanistic rationale) for late complications reported in CD8 T-lymphocytes at 8 Gy; 2- chromosome assays (Staining assay of chromosome breaks and aberrations, Premature chromosome condensation, Fluorescence in situ hybridization, Comparative genomic hybridization) are also time consuming and with no correlation with CTCAE grades; 3- DNA damage assays (PFGE, Halo, Comet, Cell free, H2AX foci, other immunofluorescent biomarkers) are not sufficient to predict moderate radio-sensitivity; 4- Genomic approaches (Micro-array techniques, Single nucleotide polymorphisms, Genome wide association studies) do not allow so far an individual assessment of radiosensitivity; CDKN1A (p21) decrease relative gene expression is a marker of severe early radiation toxicity; 5- RIANS assay (radiation induced ATM nucleo shuttling) investigates the shuttling of the ATM protein from cytoplasm to nucleus induced by IR (2Gy) and demonstrated by immunofluorescence. The delay is mechanistically explained by the cytoplasmic interaction of ATM with (abnormal) proteins in excess in the cytoplasm. Quantification is made with the maximal number of pATM foci in the nucleus of skin fibroblasts from 10 to 60 min. RIANS demonstrates significant quantitative correlation between: i. the maximal number of pATM foci and radiosensitivity evaluated by CTCAE grade (Granzotto 2016, Le Reun 2022), ii. the maximal number of pATM foci and SF2. ROC curves used for intercomparison show the superiority of RIANS over apoptosis and genomic approaches. In conclusion, clinical radiosensitivity after radiation therapy exists in a significant number of patients (up to 20%), is a continuous phenomenon between normal and highly abnormal and has an intrinsic individual component. Radio-oncologists require a predictive functional assay applicable in routine. SF2 provides the best correlation with CTCAE grades but is not clinically applicable. RIANS is the only other functional test, based on a significant mechanism that provides a correlation of maximum pATM with CTCAE grades and explains the linear-quadratic model.

SP-0522 Individual risk of radiogenic non-cancer effects TBC

SP-0523 How much can radiotherapy benefit from biomarkers of normal tissue response to radiation N. Somaiah

Abstract not available

Symposium: Do radiotherapy techniques impact the concept and size of planning target volumes margins?

SP-0524 Do we need PTV margins in daily adaptive MR-Linac treatment? M. Alber

Abstract not available

SP-0525 Do we need PTV margins in proton therapy? E. Korevaar 1 1 University of Groningen, University Medical Center Groningen, Radiation Oncology, Groningen, The Netherlands Abstract Text Proton therapy has made a large impact on the concept of planning target volume (PTV) margins. The concept to expand the clinical target volume (CTV) with a margin to achieve CTV coverage in case of patient setup errors has some clear limitations. The assumption that errors can be described as a shift of the CTV relative to a static dose cloud is not always accurate. An example is in photon treatments where patient setup errors result in dose distribution changes in build-up regions at low to high density interfaces. In proton therapy, the inaccuracy of the static dose cloud assumption results from the dependence of proton range on material in the beam path, e.g. caused by patient shifts. Furthermore, range errors arise from the inaccuracy of conversion of planning CT Hounsfield units to proton stopping powers. In intensity modulated proton treatments, steep inter-beam dose gradients can exist centrally in the CTV, and dose variations that originate from range errors cannot be handled with a CTV to PTV margin. A solution is robust planning, i.e., explicitly taking into account uncertainties during robust optimization and robustness evaluation of treatment plans, in so called treatment scenarios. Robust planning avoids the static dose cloud assumption by performing a dose calculation in each treatment scenario and assessment of dose to the CTV in these scenarios. As most proton centers clinically introduced robust planning in recent years, it is clear that PTVs are not needed in proton therapy. Although conceptually straightforward, robust planning introduces difficulties, e.g. in the scenario selection, evaluation method of the scenario dose distributions and plan acceptance criteria. The purpose of this talk is to give background information and provide practical choices in the transition from PTV based planning to robust treatment planning. In line with van Herks margin recipe based on normal distributions of systematic and day-to-day patient setup errors, worst case scenarios can be determined at a 90% confidence level. So, even after abandoning PTV margins as such, the PTV margin size is still being used in treatment scenarios in robust planning. A difficulty in robust planning is that the treatment scenarios result in numerous dose distributions per treatment plan that need to be assessed. A solution for the determination of the (near) minimum CTV dose under uncertainties is to review the voxel-wise minimum CTV dose. The voxel-wise minimum dose shows for each voxel the minimum dose over all scenarios. It can be shown that in radiotherapy treatments where the static dose cloud assumption is valid, a voxel-wise minimum dose evaluation is equivalent to a PTV minimum dose evaluation. This is an important observation for the consistency between proton treatments and (historical) photon treatments planned on a PTV. Plan acceptance criteria determined for the PTV minimum dose were found to require only minor adjustments (e.g. 1%) for application to voxel-wise minimum dose