ESTRO 2025 Congress Report I physics track

Since the International Commission on Radiation Units and Measurements (ICRU) Report 50, conventional radiotherapy has enshrined the principle that a therapeutic dose should be prescribed to an enlarged margin-based planning target volume (PTV) that encompasses both the traditional gross tumour volume (GTV) and clinical target volume (CTV), while trying to protect organs-at-risk (OARs) that contain vulnerable radiation-sensitive anatomy. However, within such apparently straightforward concepts, there is a myriad of uncertainties. These include identification of the location and characteristics of the GTV at a single point of assessment, and perturbations in position and shape during a course of fractionated radiotherapy. Leaving aside whether the imaging used has captured the GTV adequately, there may be uncertainty about the extent and distribution of microscopic disease that defines the CTV, as well as heterogeneity within the gross disease that is governed by numerous biological phenomena, which in turn could vary throughout the treatment course. Similar uncertainties apply to normal anatomy, although, in general, the main preoccupation has been the proximity to the high-dose target and important variations that may take place during treatment.

Overall, it is acknowledged that the GTV-CTV-PTV paradigm introduced by a series of ICRU reports has been exceptionally helpful and has enabled simple and consistent planning, as it employs standardised dose prescription and reporting that greatly facilitates the development of higher quality dose-volume relationship data across and between institutions. However, this traditional formalism has oversimplified with contours alone the heterogeneity and complexity that tumours exhibit and the alterations that might be needed regarding the protection of normal structures.

Procedures that explicitly consider the influence of possible variations during the planning of radiation therapy treatments can yield plans that are more robust to deviations while delivering lower doses to normal tissues than margin-based plans. Robust optimisation methods have emerged that may dispense with margins and instead account for patient anatomy change more optimally during and between fractions of radiotherapy. For example, it is conceivable that lower doses in some fractions could be compensated for by the employment of higher doses in others.

In order to allow for more rigorous probabilistic target definition and a probabilistic approach to treatment planning that could provide answers to these challenges, the session at the ESTRO 2025 meeting introduced the key concepts of the new ICRU report on probabilistic treatment planning, which aims to:

• enable the probabilistic description of the clinical target(s) and OARs, replacing current volume-based binary descriptions;
• support the migration to probabilistic uncertainties from the current construct of margin-based uncertainties;
• support the explicit definition of uncertainties, instead of the current implicit inclusion of uncertainties;
• facilitate the integration of individual-based uncertainties to supplement population-based uncertainties;
• enable a comprehensive combination of uncertainties, instead of the current ad-hoc combination of uncertainties; and
• provide optimal uncertainty management through robust optimisation approaches.

These requirements lead to the replacement of the binary GTV and CTV concept by a probabilistic cartographic principle to create spatial probability distribution functions of gross tumour maps (GTM) and clinical target maps (CTM). Similarly, the binary OAR concept is replaced with a probabilistic organs-at-risk map (ORM) probability distribution function. The probabilistic GTM/CTM and ORM definitions require careful preparation, based on patient-specific information that is extracted from various sources, including imaging. Finally, optimal treatment plans are obtained by explicit acknowledgement and integration of all uncertainties by means of robust optimisation approaches.

Robert Jeraj

University of Ljubljana, Slovenia and the University of Wisconsin, Madison, USA