Vienna, Austria

ESTRO 2023

Session Item

Poster (Digital)
KB plan optimization models’ transferability: multi-institutional international consortia validation
Lorenzo Placidi, Italy


KB plan optimization models’ transferability: multi-institutional international consortia validation

Lorenzo Placidi1, Roberta Castriconi2, Giovanna Benecchi3, Mark Burns4, Elisabetta Cagni5, Peter Griffin6, Cathy Markham7, Karen McGoldrick8, Valeria Landoni9, Eugenia Moretti10, Caterina Oliviero11, Vanessa Panettieri12, Giulia Rambaldi Guidasci13, Tiziana Rancati14, Alan Turner15, Alessandro Scaggion16, Alessia Tudda17, Claudio Fiorino17

1Fondazione Policlinico Universitario A. Gemelli IRCCS, UOSD Medical Physics and Radioprotection, Roma, Italy; 2IRCCS San Raffaele Scientific Institute, Medical Physics Department , Milano, Italy; 3University Hospital of Parma AOUP, Medical Physics Department, Parma, Italy; 4Peter MacCallum Cancer Centre, Box Hill Campus, Melbourne, Australia; 5Azienda USL-IRCCS, Department of Advanced Technology, Reggio Emilia, Italy; 6The Alfred Hospital, Alfred Health Radiation Oncology, Melbourne, Italy; 7Peter MacCallum Cancer Centre, Parkville Campus, Australia, Australia; 8Peter MacCallum Cancer Centre, Parkville Campus, Melbourne, Australia; 9IRCSS Regina Elena National Cancer Institute, Department of Medical Physics, Rome, Italy; 10Udine University Hospital, Department of Medical Physics, Udine, Italy; 11University Hospital, ‘‘Federico II”, Medical Physics, Napoli, Italy; 12The Alfred Hospital, Alfred Health Medical Physics, Melbourne, Australia; 13Fatebenefratelli Isola Tiberina – Gemelli Isola, UOC di Radioterapia Oncologica, Roma, Italy; 14Fondazione IRCCS Istituto Nazionale dei Tumori, Prosate Cancer Program, Milano, Italy; 15Peter MacCallum Cancer Centre, Bendigo Campus, Bendigo, Australia; 16Veneto Institute of Oncology IOV–IRCCS, Medical Physics Department, Padova, Italy; 17IRCCS San Raffaele Scientific Institute, Medical Physics Department, Milano, Italy

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Purpose or Objective

The Knowledge-based (KB) approach may efficiently translate planning experiences into models able to classify patients according to their individual anatomical features and possibly to automatically drive optimization on new patients. The reliability of model predictions between institutes may be due to poor overlap between the geometrical/anatomical features of Institutional training cohorts. The aim of current investigation was to assess models’ transferability between two multi-institutional international consortia (one in Europe and one outside Europe) in the case of tangential field (TF) irradiation of right whole breast (RWB).

Material and Methods

In the context of a national multi-institutional project (consortium A), ten institutes set their KB models using RapidPlan (Varian Inc.) for RWB irradiation using TF. Intra-consortium transferability was evaluated by the overlap of the geometric Principal Component (PC1) when applied to the test patients (two from each institution) of the other 9 institutes. This parameter was assessed as representative of the association between anatomy/geometry and DVH prediction of OARs, quantifying if a model can be reasonably applied to a patient owning to another Institute. With the same methodology, twenty patients belonging to another national multi-institutional consortium (consortium B) were used to perform cross inter-consortium validation tests. Each model of consortium A was evaluated on 20 patients provided by consortium B. The degree of transferability of all models was quantified by the number of cases in which the ipsilateral lung PC1 was within the 90th percentile of the training set.


Figure 1 shows transferability values in terms of the percentage of patients with the ipsilateral lung PC1 within the 90th percentile of the training set for both consortia. For consortium A, test results already demonstrated a high inter-institute transferability, with a PC1 value inside the 90th in 9 out of 10 models for more than 90% of the patients.

When models from consortium A were applied to patients from consortium B, PC1 was inside the 90th percentile in 6 out of 10 models in 90% of the patients, highlighting a favourable transferability agreement. In 2 out of 10 models, all patients have a PC1 inside the 90th percentile against 7/10 of consortium A. PC1 for model 6 showed poorest transferability for both consortia.  


Geometrical/anatomical quantitative parameter as PC1 confirms a reasonably good inter-consortium model’s transferability. Variation in models’ transferability will be better investigated looking at national contouring guideline differences, geometrical features, models’ dose prediction and the SD of several DVHs and dose/statistic parameters.

This study is supported by an AIRC grant (IG23150).