| Title: |
Systematic analysis of biological endpoint variability and implications for quantitative modeling of the FLASH sparing effect |
| Authors: |
Colizzi, Isabella; Toschini, Mathilde; Lomax, Antony J.; Psoroulas, Serena |
| Source: |
Physics and Imaging in Radiation Oncology, 37 |
| Publisher Information: |
Elsevier |
| Publication Year: |
2026 |
| Collection: |
ETH Zürich Research Collection |
| Subject Terms: |
FLASH; FLASH effect; UHDR; Meta-analysis; Preclinical studies; Endpoints; Guidelines; Modelling |
| Description: |
Background and purpose Ultra-high dose rate (UHDR) radiotherapy shows promise in sparing normal tissue while maintaining tumor control. However, heterogeneity across preclinical experiments limits cross-study comparability and the development of predictive models. By employing both qualitative and quantitative analyses, we aim to identify variability in endpoints, clarify inconsistencies, and highlight knowledge gaps critical for future quantitative modeling. Material and methods We reviewed in-vivo proton and electron FLASH murine experiments (1966–2024) and extracted commonly reported endpoints. A subset of comparable endpoints—crypt cell ratio and survival (abdominal), maximum moist desquamation (skin), and Novel-Object-Recognition tests (brain)—was analyzed using qualitative comparison and logistic regression to assess parameters potentially driving the FLASH effect. Results Fifty papers were reviewed, revealing substantial differences in endpoint selection, timing, and methodology. Most endpoints were not directly comparable across studies, with only four endpoints amenable to cross-study analysis. Logistic regression was constrained by high collinearity among parameters, reflecting both experimental heterogeneity and limited harmonization. Conclusion Our review highlights the urgent need for standardization in biological endpoints and methodologies in FLASH research. By quantifying variability in preclinical FLASH data and identifying comparable endpoints, our work provides essential guidance for future modeling efforts, bridging biological evidence and quantitative approaches for treatment planning applications. ; ISSN:2405-6316 |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/application/pdf |
| Language: |
English |
| Relation: |
info:eu-repo/semantics/altIdentifier/wos/001684365300001; https://hdl.handle.net/20.500.11850/795806 |
| DOI: |
10.3929/ethz-c-000795806 |
| Availability: |
https://hdl.handle.net/20.500.11850/795806; https://doi.org/10.3929/ethz-c-000795806 |
| Rights: |
info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by/4.0/ ; Creative Commons Attribution 4.0 International |
| Accession Number: |
edsbas.5B908106 |
| Database: |
BASE |