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Purpose  The purpose of this study was to evaluate the accuracy of a lung stereotactic body radiotherapy (SBRT) treatment plan with the target of a newly predicted internal target volume (ITV predict ) and the feasibility of its clinical application. ITV predict  was automatically generated by our in-house deep learning model according to the cone-beam CT (CBCT) image database.    Method  A retrospective study of 45 patients who underwent SBRT was involved, and Mask R-CNN based algorithm model helped to predict the internal target volume (ITV) using the CBCT image database. The geometric accuracy of ITV predict  was verified by the Dice Similarity Coefficient (DSC), 3D Motion Range (R 3D ), Relative Volume Index (RVI), and Hausdorff Distance (HD). The PTV predict  was generated by ITV predict , which was registered and then projected on free-breath CT (FBCT) images. The PTV FBCT  was margined from the GTV on FBCT images gross tumor volume on free-breath CT (GTV FBCT ). Treatment plans with the target of Predict planning target volume on CBCT images (PTV predict ) and planning target volume on free-breath CT (PTV FBCT ) were respectively re-established, and the dosimetric parameters included the ratio of the volume of patients receiving at least the prescribed dose to the volume of PTV (R 100% ), the ratio of the volume of patients receiving at least 50% of the prescribed dose to the volume of PTV in the Radiation Therapy Oncology Group (RTOG) 0813 Trial (R 50% ), Gradient Index (GI), and the maximum dose 2 cm from the PTV (D 2cm ), which were evaluated  via  Plan 4DCT , plan which based on PTV predict  (Plan predict ), and plan which based on PTV FBCT  (Plan FBCT ).    Result  The geometric results showed that there existed a good correlation between ITV predict  and ITV on the 4-dimensional CT [ITV 4DCT ; DSC= 0.83 ±0.18]. However, the average volume of ITV predict  was 10% less than that of ITV 4DCT  ( p  = 0.333). No significant difference in dose coverage was found in V 100%  for the ITV with 99.98 ± 0.04% in the ITV 4DCT  vs. 97.56 ± 4.71% in the ITV predict  ( p  = 0.162). Dosimetry parameters of PTV, including R 100% , R 50% , GI and D 2cm  showed no statistically significant difference between each plan ( p  &amp;gt; 0.05).    Conclusion  Dosimetric parameters of Plan predict  are clinically comparable to those of the original Plan 4DCT.  This study confirmed that the treatment plan based on ITV predict  produced by our model could automatically meet clinical requirements. Thus, for patients undergoing lung SBRT, the model has great potential for using CBCT images for ITV contouring which can be used in treatment planning.

Dosimetric Study of Deep Learning-Guided ITV Prediction in Cone-beam CT for Lung Stereotactic Body Radiotherapy