ESTRO 2022 - Abstract Book

S1403

Abstract book

ESTRO 2022

Purpose or Objective Several approaches of synthetic-CT (sCT) generation from MRI have been developed for radiotherapy dose calculation. Deep learning methods (DLMs) are making steady progress in improving the quality of sCT from different data inputs. The aim of this study was to evaluate the impact of the training cohort size on the sCT accuracy from pelvis MRI-linac data. Materials and Methods For this study, prostate CT and MR images were acquired in treatment position for 36 patients. MR acquisitions, using T2/T1-weighted TrueFISP sequences, were performed with a 0.35T MRI-linac device (MRIdian, Viewray sCT were obtained by a conditional GAN-based model (Pix2Pix) using the perceptual loss function and a ResNet 9 blocks generator. The hyperparameters used to train the model were, a learning rate of 0.001, a beta 1 of 0.7 and a batch size of 5. The evaluation was performed on a cross validation with five different sizes of training cohort (30 / 25 / 20 / 15 / 10 patients) in order to evaluate the impact of the cohort size on the sCT accuracy. Imaging endpoints were mean absolute error (MAE) in Hounsfield units (HU), and mean absolute percentage error (MAPE) in % (ideal values: MAE = 0 HU, MAPE = 0%), from comparisons between sCT and reference CT in the body and bones. The Wilcoxon test was used to compare the results obtained with the training of 30 patients to the other training sizes. Significant differences (*) were considered for p-value<0.05. Results Table 1 shows MAE and MAPE for each training cohort size for body and bones contours. Increasing the size of the cohort significantly reduces the MAE and MAPE results. No significant differences were found for a training of 30 patients compared to a training of 25 patients. Figure 1 shows absolute error maps in HUs of a representative patient for different number of patients in training. Body Bones

Training cohort size

MAE (HU)

MAPE (%) MAE (HU)

MAPE (%)

30

34.1 ± 8.6 1.2 ± 0.3 135.2 ± 21.7 0.5 ± 0.1

25

33.4 ± 7.7 1.2 ± 0.3 134.8 ± 19.4 0.5 ± 0.1

20

34.1 ± 8.2 1.3 ± 0.5 142.8 ± 23.7 0.5 ± 0.1

15

36.8 ± 9.6 1.4 ± 0.4 148.3 ± 26.9 0.5 ± 0.1

10

38.2 ± 9.2 1.5 ± 0.5 150.8 ± 29.9 0.5 ± 0.1 Table 1 : MAE and MAPE results in the prostate treatment area for the 36 patients according to the training cohort size variation. *: Significant differences compared to a training cohort size of 30 patients according to a Wilcoxon Test (p<0.05)

Conclusion The sCT uncertainties decrease with a higher number of patient in training. A minimum of 25 patients in the training cohort size seems to be required to obtain the lowest sCT uncertainties. A dosimetric evaluation will be performed to assess dose uncertainties.

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