PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
January 23, 2026Polymers0 citationsOpen Access

Modeling and Evaluation of Customizable Immobilization Masks for Precision Radiotherapy

View Full Paper
DADiana AdlienėAJAntonio JreijePGPaulius Griškevičius

Key Points

  • The aim is to design and evaluate customizable immobilization masks using ABS-based composites in radiotherapy.
  • Designed masks using ABS and ABS/Bi2O3 composites.
  • Conducted tensile testing to evaluate mechanical performance.
  • Modeled patient-specific masks and analyzed using finite element analysis (FEA).
  • Compared results against commercial thermoplastic masks.
  • ABS-based composites showed higher stiffness (1.7-2.5 GPa) and yield strength (20-25 MPa) compared to commercial masks.
  • FEA simulations indicated less displacement in ABS masks (1-5 mm at 2 mm thickness) vs. over 20 mm in commercial masks.
  • Reinforced hybrid configurations improved rigidity and optimized material usage.

Abstract

Accurate immobilization is critical in head and neck (H p < 0.001). FEA simulations revealed markedly reduced displacement in ABS masks (1–5 mm at 2 mm thickness; <1 mm at 4 mm thickness) relative to commercial masks, which exceeded 20 mm under lateral load. Hybrid configurations with reinforced edges further optimized rigidity while limiting material usage. Customized ABS-based immobilization masks outperform conventional thermoplastics in mechanical stability and displacement control, with the potential to reduce planning margins and improve patient comfort. In addition, ABS-based masks can be recycled, and Bi2O3-filled composites can be reused for printing new immobilization masks, thus contributing to a reduced amount of plastic waste. These findings support their promise as next-generation immobilization devices for precision radiotherapy, warranting further clinical validation, workflow integration and sustainable implementation within a circular economy.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Adlienė et al. (2026) studied this question.

synapsesocial.com/papers/69730f34c8125b09b0d1f0a8https://doi.org/10.3390/polym18020287
Ask AI
Helpful
Bookmark
Share
View Full Paper