ArticleFrontiers in bioengineering and biotechnology2025
Experimental determination of effective X-ray attenuation coefficients of 3D-printed materials under clinical mammography spectra.
Article in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Impact of dopants on X‑ray attenuation of 3D‑printed polymers for mammography and tomosynthesis spectra.Journal of applied clinical medical physics · 2026Article
- Design and measurement of 3D-printed variable-morphology and variable-density breast phantoms for mammography and breast CT dose assessment.3D printing in medicine · 2026Article
- Mimicking Tissues in 3D-Printed Radiology Phantoms: Brand, Product, and Color of Printing Filaments Matter!Polymers · 2026Article
- X-Ray Attenuation Properties of Additive Manufacturing and 3D Printing Materials for Mimicking Tissues in Radiographic Phantoms Measured by CT from 70 to 140 kV: 2025 Update.Biomimetics (Basel, Switzerland) · 2026Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: 3D printing enables the fabrication of customized breast phantoms for image quality assessment in digital mammography (DM) and digital breast tomosynthesis (DBT). A major challenge is the absence of standardized, accessible methods to characterize the attenuation properties of 3D-printed materials under clinical DM/DBT spectra. Methods: An experimental framework was implemented to determine the effective X-ray attenuation coefficient ( Results: Beam hardening and scatter reduced Conclusion: This framework demonstrates that routine clinical mammography systems can be used directly, without specialized instrumentation, to characterize 3D-printed materials as tissue surrogates. Several low-cost, widely available polymers were shown to reproduce breast tissue attenuation, supporting the local fabrication of anthropomorphic breast phantoms for realistic and clinically relevant image quality evaluation.
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