Knowledge-based automatic plan optimization for left-sided whole breast tomotherapy. (July 2022)
- Record Type:
- Journal Article
- Title:
- Knowledge-based automatic plan optimization for left-sided whole breast tomotherapy. (July 2022)
- Main Title:
- Knowledge-based automatic plan optimization for left-sided whole breast tomotherapy
- Authors:
- Esposito, Pier Giorgio
Castriconi, Roberta
Mangili, Paola
Broggi, Sara
Fodor, Andrei
Pasetti, Marcella
Tudda, Alessia
Di Muzio, Nadia Gisella
del Vecchio, Antonella
Fiorino, Claudio - Abstract:
- Abstract: Background/Purpose: Tomotherapy may deliver high-quality whole breast irradiation at static angles. The aim of this study was to implement Knowledge-Based (KB) automatic planning for left-sided whole breast using this modality. Materials/Methods: Virtual volumetric plans were associated to the dose distributions of 69 Tomotherapy (TT) clinical plans of previously treated patients, aiming to train a KB-model using a commercial tool completely implemented in our treatment planning system. An individually optimized template based on the resulting KB-model was generated for automatic plan optimization. Thirty patients of the training set and ten new patients were considered for internal/external validation. Fully-automatic plans (KB-TT) were generated and compared using the same geometry/number of fields of the corresponding clinical plans. Results: KB-TT plans were successfully generated in 26/30 and 10/10 patients of the internal/external validation sets; for 4 patients whose original plans used only two fields, the manual insertion of one/two fields before running the automatic template was sufficient to obtain acceptable plans. Concerning internal validation, planning target volume V95% /D1% /dose distribution standard deviation improved by 0.9%/0.4Gy/0.2Gy (p < 0.05) against clinical plans; Organs at risk mean doses were also slightly improved (p < 0.05) by 0.07/0.4/0.2/0.01 Gy for left lung/heart/right breast/right lung respectively. Similarly satisfactoryAbstract: Background/Purpose: Tomotherapy may deliver high-quality whole breast irradiation at static angles. The aim of this study was to implement Knowledge-Based (KB) automatic planning for left-sided whole breast using this modality. Materials/Methods: Virtual volumetric plans were associated to the dose distributions of 69 Tomotherapy (TT) clinical plans of previously treated patients, aiming to train a KB-model using a commercial tool completely implemented in our treatment planning system. An individually optimized template based on the resulting KB-model was generated for automatic plan optimization. Thirty patients of the training set and ten new patients were considered for internal/external validation. Fully-automatic plans (KB-TT) were generated and compared using the same geometry/number of fields of the corresponding clinical plans. Results: KB-TT plans were successfully generated in 26/30 and 10/10 patients of the internal/external validation sets; for 4 patients whose original plans used only two fields, the manual insertion of one/two fields before running the automatic template was sufficient to obtain acceptable plans. Concerning internal validation, planning target volume V95% /D1% /dose distribution standard deviation improved by 0.9%/0.4Gy/0.2Gy (p < 0.05) against clinical plans; Organs at risk mean doses were also slightly improved (p < 0.05) by 0.07/0.4/0.2/0.01 Gy for left lung/heart/right breast/right lung respectively. Similarly satisfactory results were replicated in the external validation set. The resulting treatment duration was 8 ± 1 min, consistent with our clinical experience. The active planner time per patient was 5–10 minutes. Conclusion: Automatic TT left-sided breast KB-plans are comparable to or slightly better than clinical plans and can be obtained with limited planner time. The approach is currently under clinical implementation. … (more)
- Is Part Of:
- Physics and imaging in radiation oncology. Volume 23(2022)
- Journal:
- Physics and imaging in radiation oncology
- Issue:
- Volume 23(2022)
- Issue Display:
- Volume 23, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 23
- Issue:
- 2022
- Issue Sort Value:
- 2022-0023-2022-0000
- Page Start:
- 54
- Page End:
- 59
- Publication Date:
- 2022-07
- Subjects:
- Radiotherapy planning optimization -- Tomotherapy -- Breast cancer -- Knowledge-based models -- AI in Radiation Oncology
Radiotherapy -- Periodicals
Radiation dosimetry -- Periodicals
Cancer -- Imaging -- Periodicals
Oncology -- Periodicals
615.842 - Journal URLs:
- http://www.sciencedirect.com/ ↗
https://www.journals.elsevier.com/physics-and-imaging-in-radiation-oncology/ ↗ - DOI:
- 10.1016/j.phro.2022.06.009 ↗
- Languages:
- English
- ISSNs:
- 2405-6316
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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