ESTRO 2023 - Abstract Book

S1355

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ESTRO 2023

259 consecutive patients with newly diagnosed GBM between 2012-2019 at a single center, each with a planning-MRI, and a clinical GTV following the ESTRO guideline, were included. For each patient, the clinical GTV was edited by a single independent radiation oncologist. The cases were randomly split into train and test set (80:20), with stratification for extent of surgery (biopsy/limited/complete excision). We used nnU-net to train a model on clinical GTVs and similarly on edited GTVs, with contrast enchanced T1w-MRI as input. Both models were trained using 5-fold cross-validation, followed by ensemble predictions (mean probability maps of the 5-folds) on the test set. For evaluation surface Dice with a 2mm tolerance (sDSC) and Hausdorff Distance 95% (HD95) were reported in a cross comparison using both models and delineation-sets (Fig. 1). A. We first compared sDSC between models. B. We compared sDSC of the clinical model evaluated on the clinical vs. the edited test set, to assess the impact of editing on model evaluation.

C. Similarly, we compared sDSC of the edited model evaluated on the clinical vs. the edited test set.

D. We then compared models again, while evaluating both models on the same edited test set.

For statistical comparison a paired Wilcoxon signed-rank test was used.

Results

HD95 median (range)

Model:Evaluation sDSC

median (range)

Clin:Clin Edit:Edit Clin:Edit Edit:Clin

0.91 (0.35-0.996) 3.0 (1.12-19.34) 0.98 (0.79-0.9999) 1.66 (1.0-44.11) 0.94 (0.66-0.993) 2.26 (1.26-37.55)

0.90 (0.37-0.995) 3.18 (1.12-43.66) The Edit model evaluated on the Edit test set (Edit:Edit), outperformed all other model test combinations (Fig. 1ACD & 2, table). We only present p-values for sDSC comparisons, as the conclusions for HD95 are identical. Interestingly, the sDSC results significantly improved when the clinical model was evaluated on the edited test set instead of the clinical (Clin:Clin vs. Clin:Edit) (Fig. 1B). Altogether showing that both the clinical and edited model predictions better resembled the edited GTVs in the test set. Moreover, when evaluating with the clinical test set, there was no significant difference between the models (Fig 2, Clin:Clin vs. Edit:Clin p=.36).