Multi-institutional evaluation of a Pareto navigation guided automated radiotherapy planning solution for prostate cancer

Abstract

Background: Current automated planning solutions are calibrated using trial and error or machine learning on historical datasets. Neither method allows for the intuitive exploration of differing trade-off options during calibration, which may aid in ensuring automated solutions align with clinical preference. Pareto navigation provides this functionality and offers a potential calibration alternative. The purpose of this study was to validate an automated radiotherapy planning solution with a novel multi-dimensional Pareto navigation calibration interface across two external institutions for prostate cancer.

Methods: The implemented 'Pareto Guided Automated Planning' (PGAP) methodology was developed in RayStation using scripting and consisted of a Pareto navigation calibration interface built upon a 'Protocol Based Automatic Iterative Optimisation' planning framework. 30 previous patients were randomly selected by each institution (I_A and I_B), 10 for calibration and 20 for validation. Utilising the Pareto navigation interface automated protocols were calibrated to the institutions' clinical preferences. A single automated plan (VMAT_Auto) was generated for each validation patient with plan quality compared against the previously treated clinical plan (VMAT_Clinical) both quantitatively, using a range of DVH metrics, and qualitatively through blind review at the external institution.

Results: PGAP led to marked improvements across the majority of rectal dose metrics, with D_mean reduced by 3.7 Gy and 1.8 Gy for I_A and I_B respectively (p < 0.001). For bladder, results were mixed with low and intermediate dose metrics reduced for I_B but increased for I_A. Differences, whilst statistically significant (p < 0.05) were small and not considered clinically relevant. The reduction in rectum dose was not at the expense of PTV coverage (D_98% was generally improved with VMAT_Auto), but was somewhat detrimental to PTV conformality. The prioritisation of rectum over conformality was however aligned with preferences expressed during calibration and was a key driver in both institutions demonstrating a clear preference towards VMAT_Auto, with 31/40 considered superior to VMAT_Clinical upon blind review.

Conclusions: PGAP enabled intuitive adaptation of automated protocols to an institution's planning aims and yielded plans more congruent with the institution's clinical preference than the locally produced manual clinical plans.

Keywords: AI; Automation; IMRT; MCO; Multi-institutional; Pareto; Prostate cancer; Radiotherapy; Treatment planning; VMAT.

Fig. 1

Pareto navigation calibration interface. Navigation is performed using the slider bars (top left), with the dose distribution (top centre) and DVH (top right– solid line) updated in real time within RayStation’s evaluation module. During navigation the operator can set the navigated distribution as a reference distribution (bottom centre) and DVH (top right– dotted line) to aid in the decision making. In this example the navigated position represents a solution where the rectum is spared at the expense of homogeneity and conformality (Cal₁) with the reference distribution representative of the final calibration for I_A (Cal₂). The corresponding Cal₂ slider positions are provided for reference (bottom left) and isodose legends have been enhanced for clarity. ROIs: rectum (brown), bladder (yellow), external (blue), PTV60 (pink), PTV57.5 (red) and PTV48 (orange)

Fig. 2

Pareto front representations of the three navigated trade-offs (rectum D_mean, HI_PTV60 and CI_PTV48) demonstrating the dosimetric impact of two differently balanced calibrations (Cal₁ & Cal₂) on novel patients in the I_A calibration dataset. Data from the navigation patient (Patient 1) is presented for reference, with Cal₁ and Cal₂ data points encompassed by the red and blue boxes respectively

Fig. 3

1–1 plots comparing VMAT_Auto and VMAT_Clinical across a range of OAR and PTV dose metrics for both institutions. Unity line is presented for reference and represents equivalence between the two techniques