Evaluation of a cycle-generative adversarial network-based cone-beam CT to synthetic CT conversion algorithm for adaptive radiation therapy
| Autor: | Volker Steil, Miriam Eckl, Jens Fleckenstein, Judit Boda-Heggemann, Gustavo R. Sarria, Anna Simeonova-Chergou, Lea Hoppen, Frank A. Giordano |
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| Rok vydání: | 2020 |
| Předmět: |
Male
Image quality medicine.medical_treatment Biophysics General Physics and Astronomy 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Hounsfield scale Image Processing Computer-Assisted medicine Humans Radiology Nuclear Medicine and imaging Segmentation Radiometry Cone beam ct business.industry Radiotherapy Planning Computer-Assisted Radiotherapy Dosage General Medicine Image segmentation Cone-Beam Computed Tomography Radiation therapy 030220 oncology & carcinogenesis Body region business Algorithm Algorithms Adaptive radiation therapy |
| Zdroj: | Physica Medica. 80:308-316 |
| ISSN: | 1120-1797 |
| DOI: | 10.1016/j.ejmp.2020.11.007 |
| Popis: | Purpose Image-guided radiation therapy could benefit from implementing adaptive radiation therapy (ART) techniques. A cycle-generative adversarial network (cycle-GAN)-based cone-beam computed tomography (CBCT)-to-synthetic CT (sCT) conversion algorithm was evaluated regarding image quality, image segmentation and dosimetric accuracy for head and neck (H&N), thoracic and pelvic body regions. Methods Using a cycle-GAN, three body site-specific models were priorly trained with independent paired CT and CBCT datasets of a kV imaging system (XVI, Elekta). sCT were generated based on first-fraction CBCT for 15 patients of each body region. Mean errors (ME) and mean absolute errors (MAE) were analyzed for the sCT. On the sCT, manually delineated structures were compared to deformed structures from the planning CT (pCT) and evaluated with standard segmentation metrics. Treatment plans were recalculated on sCT. A comparison of clinically relevant dose-volume parameters (D98, D50 and D2 of the target volume) and 3D-gamma (3%/3mm) analysis were performed. Results The mean ME and MAE were 1.4, 29.6, 5.4 Hounsfield units (HU) and 77.2, 94.2, 41.8 HU for H&N, thoracic and pelvic region, respectively. Dice similarity coefficients varied between 66.7 ± 8.3% (seminal vesicles) and 94.9 ± 2.0% (lungs). Maximum mean surface distances were 6.3 mm (heart), followed by 3.5 mm (brainstem). The mean dosimetric differences of the target volumes did not exceed 1.7%. Mean 3D gamma pass rates greater than 97.8% were achieved in all cases. Conclusions The presented method generates sCT images with a quality close to pCT and yielded clinically acceptable dosimetric deviations. Thus, an important prerequisite towards clinical implementation of CBCT-based ART is fulfilled. |
| Databáze: | OpenAIRE |
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