• Probabilistic planning in radiotherapy emphasizes estimating normal tissue complication probability and tumor control probability from dose-volume data, guiding plan selection and constraint balancing via DVHs and volume-based risk factors [2], [7], [18], [4].

• Radiobiology-driven dose-fractionation frameworks unify linear-quadratic dose-effect modeling, protraction, and cellular kinetics (cell-cycle redistribution, repopulation) to optimize regimens; supporting both fractionation and protracted schemes [9], [12], [16], [8], [19], [20].

• Biology-first paradigm where inherent cellular radiosensitivity and tumour dose-response inform adaptive strategies; historical dose-response data underpin histology-informed fractionation and targets [6], [5], [1], [20].

• Mathematical optimization in planning, including constrained least-squares, decision-criteria models, and integrated optimization of brachytherapy/external beam dosimetry; formalized criteria for plan selection [17], [10], [11], [15], [18].

• Practical dosimetry standards and education shaping implementation: dosimetric precision, NSD/TDF simplification approaches, and early experiences with multi-daily sessions and radiotherapy textbooks [3], [1], [14], [13].