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Improving Clinical Decision-Making in Radiotherapy: A Comparative Analysis of Linear-Quadratic LQ and

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PubMed
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Radiotherapy dose modelling using linear-quadratic (LQ) and linear-quadratic-linear (LQL) models shows high variability in clinical application. Standardised guidelines and training are needed to improve consistency in biologically effective dose (BED) calculations and patient care.

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Biologically effective dosedose optimisationlinear quadratic modelpersonalised cancer treatmentradiotherapy

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Area of Science:

  • Radiation Oncology
  • Medical Physics
  • Cancer Treatment

Background:

  • Accurate radiotherapy dose planning is crucial for optimizing tumor control and sparing healthy tissues.
  • Advanced dose modelling, including linear-quadratic (LQ) and linear-quadratic-linear (LQL) models, aims to refine biologically effective dose (BED) calculations for personalized treatment.

Purpose of the Study:

  • To investigate advanced dose modelling approaches (LQ and LQL) for calculating BED and improving radiotherapy personalization.
  • To evaluate the practical application and clinical consensus on these models in real-world scenarios.

Main Methods:

  • A radiobiology workshop integrated LQ/LQL models and BED calculators with patient-specific data (fractionation, OAR constraints).
  • A unified interface was used to simulate treatment plans and predict normal tissue complication probabilities (NTCPs) under practical constraints.
  • Clinical case studies analyzed participant responses using the Jaccard similarity index.

Main Results:

  • Significant lack of consensus was observed in treatment planning decisions, with a mean agreement of 25.83% among participants.
  • This heterogeneity highlights ambiguity in model selection and application, potentially leading to divergent treatment recommendations.
  • Variability was noted across various scenarios, including treatment interruptions, palliative boosts, and re-irradiation.

Conclusions:

  • Interpretation and implementation of LQ and LQL models for personalized radiotherapy are highly variable.
  • Professional responsibility in dose equivalence calculations and accountability frameworks require clarification.
  • Standardized guidelines, enhanced training, and decision support systems are essential to reduce interobserver variability and improve clinical adoption.