Systematic implementation of rapidplan for prostate cancer: toward a unified knowledge-based planning model
Abstract This study presents a comprehensive methodology for implementing a unified knowledge-based planning model for RapidPlan™ (RP) to manage all 11 prostate cancer prescriptions used at our institution. Several RP configurations were evaluated to address different clinical scenarios. The initial...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-08553-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849769291492098048 |
|---|---|
| author | Ahmed Hadj Henni Asma Hamouali Alexandre Marque Ilias Arhoun |
| author_facet | Ahmed Hadj Henni Asma Hamouali Alexandre Marque Ilias Arhoun |
| author_sort | Ahmed Hadj Henni |
| collection | DOAJ |
| description | Abstract This study presents a comprehensive methodology for implementing a unified knowledge-based planning model for RapidPlan™ (RP) to manage all 11 prostate cancer prescriptions used at our institution. Several RP configurations were evaluated to address different clinical scenarios. The initial models RP_46 and RP_30 involved the prostate, seminal vesicles, and lymph nodes treated with 46 Gy in 23 fractions and the prostate alone treated with 30 Gy in 15 fractions, respectively. These models were progressively expanded to incorporate all sequential boost treatment plans (RP_46 + 30), including those targeting the prostate bed (RP_Seq). Simultaneous integrated boost prescriptions were used to train the RP_SIB model, which was subsequently combined with the RP_Seq model to form the unified RP_UNI model. Each configuration was compared with the manual method using a cohort of 10–25 patients. All the models produced treatment plans that met the clinical requirements. An overall analysis revealed that the RP_UNI model significantly reduced the 45 Gy and 15 Gy volumes (cm3) in the peritoneal cavity by approximately 18%. The RP_UNI model was chosen for clinical implementation owing to its broader applicability compared with the other models, offering a 66% reduction in planning time with respect to the manual method. The unified model, derived from simpler RP configurations, successfully integrated all 11 prostate cancer prescriptions used at our institution. This model performed efficiently regardless of the complexity of the target volumes or whether the irradiation technique was a sequential or simultaneous integrated boost. |
| format | Article |
| id | doaj-art-9f06aecc5c204535abb447bec653e533 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-9f06aecc5c204535abb447bec653e5332025-08-20T03:03:28ZengNature PortfolioScientific Reports2045-23222025-07-0115111010.1038/s41598-025-08553-7Systematic implementation of rapidplan for prostate cancer: toward a unified knowledge-based planning modelAhmed Hadj Henni0Asma Hamouali1Alexandre Marque2Ilias Arhoun3Centre Frédéric JoliotCentre Frédéric JoliotCentre Frédéric JoliotCentre Frédéric JoliotAbstract This study presents a comprehensive methodology for implementing a unified knowledge-based planning model for RapidPlan™ (RP) to manage all 11 prostate cancer prescriptions used at our institution. Several RP configurations were evaluated to address different clinical scenarios. The initial models RP_46 and RP_30 involved the prostate, seminal vesicles, and lymph nodes treated with 46 Gy in 23 fractions and the prostate alone treated with 30 Gy in 15 fractions, respectively. These models were progressively expanded to incorporate all sequential boost treatment plans (RP_46 + 30), including those targeting the prostate bed (RP_Seq). Simultaneous integrated boost prescriptions were used to train the RP_SIB model, which was subsequently combined with the RP_Seq model to form the unified RP_UNI model. Each configuration was compared with the manual method using a cohort of 10–25 patients. All the models produced treatment plans that met the clinical requirements. An overall analysis revealed that the RP_UNI model significantly reduced the 45 Gy and 15 Gy volumes (cm3) in the peritoneal cavity by approximately 18%. The RP_UNI model was chosen for clinical implementation owing to its broader applicability compared with the other models, offering a 66% reduction in planning time with respect to the manual method. The unified model, derived from simpler RP configurations, successfully integrated all 11 prostate cancer prescriptions used at our institution. This model performed efficiently regardless of the complexity of the target volumes or whether the irradiation technique was a sequential or simultaneous integrated boost.https://doi.org/10.1038/s41598-025-08553-7RapidPlan™Knowledge-based planningProstate cancer treatmentDose–volume constraintsTreatment planning |
| spellingShingle | Ahmed Hadj Henni Asma Hamouali Alexandre Marque Ilias Arhoun Systematic implementation of rapidplan for prostate cancer: toward a unified knowledge-based planning model Scientific Reports RapidPlan™ Knowledge-based planning Prostate cancer treatment Dose–volume constraints Treatment planning |
| title | Systematic implementation of rapidplan for prostate cancer: toward a unified knowledge-based planning model |
| title_full | Systematic implementation of rapidplan for prostate cancer: toward a unified knowledge-based planning model |
| title_fullStr | Systematic implementation of rapidplan for prostate cancer: toward a unified knowledge-based planning model |
| title_full_unstemmed | Systematic implementation of rapidplan for prostate cancer: toward a unified knowledge-based planning model |
| title_short | Systematic implementation of rapidplan for prostate cancer: toward a unified knowledge-based planning model |
| title_sort | systematic implementation of rapidplan for prostate cancer toward a unified knowledge based planning model |
| topic | RapidPlan™ Knowledge-based planning Prostate cancer treatment Dose–volume constraints Treatment planning |
| url | https://doi.org/10.1038/s41598-025-08553-7 |
| work_keys_str_mv | AT ahmedhadjhenni systematicimplementationofrapidplanforprostatecancertowardaunifiedknowledgebasedplanningmodel AT asmahamouali systematicimplementationofrapidplanforprostatecancertowardaunifiedknowledgebasedplanningmodel AT alexandremarque systematicimplementationofrapidplanforprostatecancertowardaunifiedknowledgebasedplanningmodel AT iliasarhoun systematicimplementationofrapidplanforprostatecancertowardaunifiedknowledgebasedplanningmodel |