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Advances in computational anthropomorphic phantoms and Monte Carlo-based dosimetry: A review.

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Τίτλος: Advances in computational anthropomorphic phantoms and Monte Carlo-based dosimetry: A review.
Συγγραφείς: Valeriano CCS; Programa de Pós-graduação em Engenharia Biomédica Faculdade de Engenharia Elétrica Universidade Federal de Uberlândia, Brazil. Electronic address: caio144fisicamedica@gmail.com., Cavalcanti IMGA; Universidade Federal de Sergipe, Brazil., Perini AP; Programa de Pós-graduação em Engenharia Biomédica Faculdade de Engenharia Elétrica Universidade Federal de Uberlândia, Brazil; Instituto de Física, Universidade Federal de Uberlândia, Brazil., Santos WS; Universidade Federal de Sergipe, Brazil.
Πηγή: Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine [Appl Radiat Isot] 2026 Oct; Vol. 236, pp. 112746. Date of Electronic Publication: 2026 Jun 30.
Τύπος έκδοσης: Journal Article; Review
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Pergamon Press Country of Publication: England NLM ID: 9306253 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-9800 (Electronic) Linking ISSN: 09698043 NLM ISO Abbreviation: Appl Radiat Isot Subsets: MEDLINE
Imprint Name(s): Original Publication: Oxford ; New York : Pergamon Press, c1993-
Ιατρικοί όροι (MeSH): Radiometry*/methods , Monte Carlo Method* , Phantoms, Imaging*, Humans ; Computer Simulation
Περίληψη: The application of computational anthropomorphic phantoms has become imperative in the field of radiation dosimetry because they facilitate anatomically faithful simulations of energy deposition within the human body. Their development reflects significant advances in computational modeling, with a transition from early stylized geometries to voxel-based, mesh-based, and Non-Uniform Rational B-Splines (NURBS) representations. The recent introduction of ICRP mesh-type reference computational phantoms (MRCPs), including advanced maternal and fetal models, has significantly improved the representation of anatomical heterogeneity. When coupled with Monte Carlo simulation codes (e.g., EGSnrc, MCNP, Geant4, PENELOPE, GATE, and TOPAS), these phantoms offer robust frameworks for calculating radiation transport. Additionally, a transition is underway in the dosimetric paradigm, marked by a shift from macroscopic organ assessments that utilize Condensed History algorithms to subcellular microdosimetry that relies on event-by-event Track Structure codes. Consequently, recent advances have extended their applications in a range of disciplines, including radiotherapy, nuclear medicine, and diagnostic imaging. These advances have also been used in vivo monitoring calibration and modeling of complex radiobiological effects at the DNA level via platforms like TOPAS-nBio. Artificial intelligence and digital-twin approaches are increasingly being explored as tools to support individualized dosimetry and adaptive treatment planning. This review delineates historical developments, methodological breakthroughs, and emerging trends in this field, highlighting the emergence of a new research frontier at the intersection of physics, biology, and computer science for personalized radiation dosimetry.
(Copyright © 2026. Published by Elsevier Ltd.)
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributed Indexing: Keywords: Artificial intelligence and digital twins; Computational anthropomorphic phantoms; Monte Carlo methods; Personalized radiotherapy; Radiation dosimetry
Entry Date(s): Date Created: 20260708 Date Completed: 20260716 Latest Revision: 20260716
Update Code: 20260717
DOI: 10.1016/j.apradiso.2026.112746
PMID: 42418862
Βάση Δεδομένων: MEDLINE
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  Data: The application of computational anthropomorphic phantoms has become imperative in the field of radiation dosimetry because they facilitate anatomically faithful simulations of energy deposition within the human body. Their development reflects significant advances in computational modeling, with a transition from early stylized geometries to voxel-based, mesh-based, and Non-Uniform Rational B-Splines (NURBS) representations. The recent introduction of ICRP mesh-type reference computational phantoms (MRCPs), including advanced maternal and fetal models, has significantly improved the representation of anatomical heterogeneity. When coupled with Monte Carlo simulation codes (e.g., EGSnrc, MCNP, Geant4, PENELOPE, GATE, and TOPAS), these phantoms offer robust frameworks for calculating radiation transport. Additionally, a transition is underway in the dosimetric paradigm, marked by a shift from macroscopic organ assessments that utilize Condensed History algorithms to subcellular microdosimetry that relies on event-by-event Track Structure codes. Consequently, recent advances have extended their applications in a range of disciplines, including radiotherapy, nuclear medicine, and diagnostic imaging. These advances have also been used in vivo monitoring calibration and modeling of complex radiobiological effects at the DNA level via platforms like TOPAS-nBio. Artificial intelligence and digital-twin approaches are increasingly being explored as tools to support individualized dosimetry and adaptive treatment planning. This review delineates historical developments, methodological breakthroughs, and emerging trends in this field, highlighting the emergence of a new research frontier at the intersection of physics, biology, and computer science for personalized radiation dosimetry.<br /> (Copyright © 2026. Published by Elsevier Ltd.)
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