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Beyond TG‑43: A PRISMA-based systematic review on model-based dose-calculation algorithms in brachytherapy.

Dat Tran1, Thanh-Tai Duong2, Shada Wadi-Ramahi3

  • 1Department of Physics, University of Houston, Houston, Texas, USA.

Journal of Applied Clinical Medical Physics
|May 20, 2026
PubMed
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This summary is machine-generated.

The American Association of Physicists in Medicine Task Group 43 (TG-43) formalism is outdated for brachytherapy dose calculation. Model-based dose-calculation algorithms (MBDCAs) and Monte Carlo (MC) simulations offer superior accuracy and are ready for clinical adoption.

Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Biology

Background:

  • The AAPM TG-43 formalism is the standard for brachytherapy dose calculation but assumes a homogeneous medium, neglecting tissue heterogeneities and scatter.
  • Model-based dose-calculation algorithms (MBDCAs), including Monte Carlo (MC) simulations, address these limitations by considering real tissue composition and scatter.

Purpose of the Study:

  • To systematically review and evaluate TG-43, MBDCAs, and MC methods for brachytherapy dose calculation.
  • Assess dosimetric accuracy, validation strategies, computational feasibility, and clinical implementation barriers.

Main Methods:

  • A PRISMA-guided literature search of the Scopus database identified 42 relevant studies.
  • Eligible studies compared TG-43, MBDCAs, and/or MCs in pelvic, breast, or head-and-neck brachytherapy.
Keywords:
AAPM TG‐43Acuros BVMonte Carlo simulationPRISMAadaptive radiotherapyartificial Intelligencebrachytherapyclinical implementationdose calculation accuracymodel‐based dose‐calculation algorithm

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  • Data extracted included dosimetric discrepancies, validation methods, computational performance, and workflow integration.
  • Main Results:

    • TG-43 showed variable bias depending on tissue composition and scatter; it often overestimated doses in homogeneous tissues but underestimated in low-density regions.
    • MBDCAs and MCs agreed within ~3% with experimental data, offering more reliable radiobiological metrics.
    • GPU acceleration and deep learning reduced computation times; standardization, commissioning, and QA remain challenges.

    Conclusions:

    • A transition to TG-186-compliant, heterogeneity-aware dose calculation frameworks is supported by evidence.
    • MBDCAs/MC algorithms offer superior accuracy and are compatible with adaptive and biologically guided planning.
    • Established QA standards and benchmarking datasets facilitate implementation, linking precision to patient outcomes.