Dear Editor-in-Chief,

We read with great interest the recent article by El Atifi et al. evaluating whether early cone-beam computed tomography (CBCT)-derived translational set-up instability could serve as a triage tool for adaptive replanning in patients with head-and-neck squamous cell carcinoma (HNSCC) treated with volumetric modulated arc therapy (VMAT).^{Reference El Atifi, Mkimel and El Rhazouani1} The authors should be commended for addressing an increasingly important challenge in contemporary radiotherapy: identifying patients who are most likely to benefit from adaptive radiotherapy (ART) while minimizing unnecessary replanning and resource utilization. We would, however, like to highlight a conceptual aspect that may further refine the interpretation of the study findings.

In our opinion, early translational set-up instability should be regarded primarily as an imaging-derived monitoring indicator that identifies patients requiring closer evaluation rather than immediate adaptive intervention. In other words, it may represent an effective triage tool for enhanced surveillance, but not necessarily an independent decision criterion for adaptive replanning. This distinction is important because the purpose of triage is to prioritize patients for further assessment, whereas the decision to initiate ART requires integration of multiple sources of clinical evidence.^{Reference Dona Lemus, Cao and Cai2}

Indeed, ART has progressively evolved from parameter-based adaptation towards evidence-based adaptive decision-making, in which imaging findings support – but do not independently determine – clinical intervention.^{Reference Dona Lemus, Cao and Cai2} In current head-and-neck practice, adaptive replanning is typically prompted by the combined assessment of anatomical evolution, including weight loss, tumor regression, parotid shrinkage and soft-tissue deformation, together with accumulated dosimetric changes, target coverage, organ-at-risk doses, treatment feasibility and the anticipated clinical benefit.^{Reference Dona Lemus, Cao and Cai2–Reference Weppler, Quon and Schinkel6} Consequently, translational set-up instability should be interpreted as one component of an integrated adaptive decision framework rather than as a surrogate for the adaptive decision itself.

Interestingly, the findings reported by El Atifi et al. appear to reinforce this perspective.^{Reference El Atifi, Mkimel and El Rhazouani1} The receiver operating characteristic analysis demonstrated only modest discriminatory performance (Area Under the Curve (AUC) ≈ 0.5), indicating that early translational set-up deviations alone have limited discriminatory performance for identifying patients with simulated dosimetric deterioration. Furthermore, no patient in the investigated cohort underwent adaptive replanning during treatment; therefore, the proposed predictive approach was evaluated against a simulated dosimetric endpoint rather than actual clinical adaptive decisions.^{Reference El Atifi, Mkimel and El Rhazouani1} Rather than diminishing the clinical relevance of the study, these findings suggest that rigid translational set-up uncertainty, although clinically relevant, should not be interpreted in isolation when selecting candidates for ART.

Beyond evaluating the performance of a single predictive parameter, this study raises an important conceptual question regarding how imaging findings should be translated into adaptive radiotherapy decisions. Future studies may therefore benefit from developing integrated adaptive decision frameworks that combine set-up uncertainty with longitudinal anatomical evolution, deformable accumulated dose, volumetric–dosimetric monitoring, patient-reported outcomes and other patient-specific anatomical, dosimetric and clinical information.^{Reference Zhong, Pursley and Rong3–Reference Chen, Larocque and Wang7} Such multidimensional approaches are increasingly recognized as the future direction of ART and are likely to improve both predictive performance and efficient allocation of adaptive resources.

We congratulate the authors for their valuable contribution to the growing field of ART. Their work provides important evidence supporting a broader discussion on how imaging-derived monitoring parameters should be incorporated into adaptive decision-making. Ultimately, the challenge may not be to identify a single predictor of adaptive replanning, but rather to determine how complementary sources of evidence can be integrated to support individualized adaptive radiotherapy decisions.