guest ::
| Home > Publications database > A mechanistic model of brain necrosis progression based on vascular heterogeneity. |
| Home > Publications database > A mechanistic model of brain necrosis progression based on vascular heterogeneity. |
| Journal Article | DKFZ-2025-02105 |
; ; ; ; ; ; ; ; ;
2025
Elsevier Science
Amsterdam [u.a.]
This record in other databases: 
Please use a persistent id in citations: doi:10.1016/j.ijrobp.2025.09.059
Abstract: Brain radionecrosis (RN) is a significant late toxicity of radiation therapy, yet its progression remains challenging to predict due to patient-specific factors. This study develops a mechanistic model to simulate RN expansion focusing on vascular heterogeneity.A three-dimensional cellular automaton (CA) model was developed to simulate RN progression, based on the assumption that vascular heterogeneity drives its spatial dynamics. Patient-specific vasculature maps were generated by registering a synthetic brain phantom to MRI-derived segmentations. Microvessel length density (Ld) was estimated to account for regional vascular heterogeneity. The model parameters-RN progression rate (k) and necrotic neighborhood threshold (ρt)-were inferred using sequential Monte Carlo approximate Bayesian computation. Probability risk maps were validated against follow-up (FU) imaging from three independent cases, with voxel-wise agreement assessed using receiver operating characteristic analysis.The model successfully predicted RN expansion patterns, achieving area under the curve values of 0.87-0.95 in validation cases. Simulated necrotic regions exhibited anisotropic expansion influenced by local vascular density, supporting the vascular hypothesis. Patient-specific posterior distributions for progression rate reflected wide interpatient variability, while the necrotic neighboring effect had a narrower range. The model consistently identified high-risk voxels, with predicted necrotic regions overlapping observed RN in FU imaging.This study presents a mechanistic model that integrates vascular heterogeneity to predict RN progression, providing interpretable, patient-specific risk maps. It extends RN evolution modeling beyond dose-based metrics, potentially aiding in refining treatment planning and adaptive FU strategies to minimize radiation-induced toxicity.
Keyword(s): Radiation therapy ; brain necrosis ; mechanistic modeling ; predictive modeling ; proton therapy ; radiation necrosis ; radiation toxicity
; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; Nationallizenz
; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
|
The record appears in these collections: |