A Feasibility Study of Dose Band Prediction in Radiotherapy: Predicting a Dose Spectrum

Abstract

Current deep learning-based dose prediction methods can only predict a specific dose distribution. If the predicted dose is inaccurate, no more options can be selected. We proposed a novel dose prediction method named dose band prediction, which outcomes a spectrum of predicted dose distribution for planning and quality assurance (QA). Upper-Band and Lower-Band losses were involved in 3D convolution neural networks to establish the Upper-Band Network (UBN) and Lower-Band Network (LBN). Each voxel's ideal dose spectrum (dose band) was defined by the maximum/minimum rational dose predicted by UBN/LBN. 130 NPC cases with Tomotherapy (dataset 1), 49 cervix cases with IMRT (dataset 2) and 43 cervix cases with VMAT (dataset 3) were enrolled to establish and evaluate our dose band prediction method. The dose band prediction method can successfully predict a spectrum of doses. Upper-Band/Lower-Band presents maximum/minimum rational dose; Middle-Line presents the average of Upper-Band and Lower-Band. The clinical implement dose was used as the reference dose. We evaluated the maximum interval between the reference and Upper-Band/Middle-Line/Lower-Band doses, and the percentage dose difference was used as the evaluation method. The differences in PTV for Upper-Band, Middle-Line and Lower-Band in dataset 1 were within 2.47%, 0.54%, and 2.8%; in dataset 2, they were within 0.37%, 1.15%, and 2.69%; in dataset 3, they were within 0.96%, 0.35%, and 1.66%. The mean difference of OARs for the Upper-Band, Middle-Line and Lower-Band in dataset 1 were within 8.13%, 4.97%, and 8.19%; in dataset 2, they were within 8.8%, 4.48%, and 5.52%; in dataset 3, they were within 4.01%, 3.13%, and 5.79% (shown in Table 1). Dose Band prediction achieved high-accuracy dose prediction by the Middle-Line. More importantly, the Upper-Band/Lower-Band provided a spectrum of possible rational doses. Our Dose Band prediction method is based on a specific loss function, so it can easily be applied in various network and patient cases. Dose Band prediction towards a more robust plan QA and planning assistance. Table 1. The maximum interval of doses (percentage dose difference, %).