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. 2022 Apr 11:12:838039.
doi: 10.3389/fonc.2022.838039. eCollection 2022.

Dosimetric Impact of Inter-Fraction Variability in the Treatment of Breast Cancer: Towards New Criteria to Evaluate the Appropriateness of Online Adaptive Radiotherapy

Martina Iezzi  1 , Davide Cusumano  2   3 , Danila Piccari  2   3 , Sebastiano Menna  2   3 , Francesco Catucci  3 , Andrea D'Aviero  3 , Alessia Re  3 , Carmela Di Dio  3 , Flaviovincenzo Quaranta  3 , Althea Boschetti  3 , Marco Marras  3 , Domenico Piro  3 , Flavia Tomei  3 , Claudio Votta  2   3 , Vincenzo Valentini  2 , Gian Carlo Mattiucci  2   3
Affiliations

Dosimetric Impact of Inter-Fraction Variability in the Treatment of Breast Cancer: Towards New Criteria to Evaluate the Appropriateness of Online Adaptive Radiotherapy

Martina Iezzi et al. Front Oncol. .

Abstract

Purpose: As a discipline in its infancy, online adaptive RT (ART) needs new ontologies and ad hoc criteria to evaluate the appropriateness of its use in clinical practice. In this experience, we propose a predictive model able to quantify the dosimetric impact due to daily inter-fraction variability in a standard RT breast treatment, to identify in advance the treatment fractions where patients might benefit from an online ART approach.

Methods: The study was focused on right breast cancer patients treated using standard adjuvant RT on an artificial intelligence (AI)-based linear accelerator. Patients were treated with daily CBCT images and without online adaptation, prescribing 40.05 Gy in 15 fractions, with four IMRT tangential beams. ESTRO guidelines were followed for the delineation on planning CT (pCT) of organs at risk and targets. For each patient, all the CBCT images were rigidly aligned to pCT: CTV and PTV were manually re-contoured and the original treatment plan was recalculated. Various radiological parameters were measured on CBCT images, to quantify inter-fraction variability present in each RT fraction after the couch shifts compensation. The variation of these parameters was correlated with the variation of V95% of PTV (ΔV95%) using the Wilcoxon Mann-Whitney test. Fractions where ΔV95% > 2% were considered as adverse events. A logistic regression model was calculated considering the most significant parameter, and its performance was quantified with a receiver operating characteristic (ROC) curve.

Results: A total of 75 fractions on 5 patients were analyzed. The body variation between daily CBCT and pCT along the beam axis with the highest MU was identified as the best predictor (p = 0.002). The predictive model showed an area under ROC curve of 0.86 (95% CI, 0.82-0.99) with a sensitivity of 85.7% and a specificity of 83.8% at the best threshold, which was equal to 3 mm.

Conclusion: A novel strategy to identify treatment fractions that may benefit online ART was proposed. After image alignment, the measure of body difference between daily CBCT and pCT can be considered as an indirect estimator of V95% PTV variation: a difference larger than 3 mm will result in a V95% decrease larger than 2%. A larger number of observations is needed to confirm the results of this hypothesis-generating study.

Keywords: AI radiotherapy; CBCT radiotherapy; inter-fraction dose variation; online adaptation; predictive modeling.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Visual example of the body variation measurement: the difference between the body in CBCT and the corresponding one in simulation CT along the beam axis with higher MUs is highlighted in red.
Figure 2
Figure 2
Visual representation of the treatment fractions analyzed for each patient. The optimal fractions are in green, the non-optimal but acceptable fractions are in yellow, and the fractions requiring online adaptation are in red.
Figure 3
Figure 3
ROC curve of the predictive model focused on identifying treatment fractions where a variation higher than −2% was observed in V95% of PTV.
Figure 4
Figure 4
Probability of obtaining a fraction requiring adaptation as a function of body variation measured along the beam axis with the highest MU.
See this image and copyright information in PMC

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