The study retrospectively included 100 patients who underwent radiotherapy after breast-conserving surgery. The patients were treated using a standard treatment planning process with CT images and at least one set of CBCT images acquired during treatment. The CT images were acquired using the Siemens Medical System scanner with a voxel size of 0.977 × 0.977 × 5 mm3 and a data size of 512 ×512 × 80. The CBCT was acquired using the Varian Edge (Varian Medical Systems, Palo Alto, CA) scanner with a voxel size of 0.977 × 0.977 × 5 mm3. Due to the difference in scanning range and voxel size between CT and CBCT, we first rigidly aligned the CT and resampled the voxel size to match CBCT.
In our study, a DL network generated sCT images from CBCT images. And then, pCT was aligned with CBCT and sCT images, respectively, using the DIR method. Next, the contours on pCT were propagated on CBCT (sCT) images. Physicians first manually outlined pCT and CBCT data contours (target area contours including tumor bed area clinical target volume (CTV) 1, CTV 2, Heart). The final contours propagated on the sCT images have a more similar anatomy to the original CBCT, especially in soft tissues with significant effects. The model was trained, validated, and tested using 52/7/41 patients, corresponding to 4160/560/3280 slices.
In our study, a DL network generated sCT images from CBCT images. And then, pCT was aligned with CBCT and sCT images, respectively, using the DIR method. Next, the contours on pCT were propagated on CBCT (sCT) images. Physicians first manually outlined pCT and CBCT data contours (target area contours including tumor bed area clinical target volume (CTV) 1, CTV 2, Heart). The final contours propagated on the sCT images have a more similar anatomy to the original CBCT, especially in soft tissues with significant effects. The model was trained, validated, and tested using 52/7/41 patients, corresponding to 4160/560/3280 slices.
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