Artificial intelligence in high-dose-rate brachytherapy treatment planning for cervical cancer: a review
Cervical cancer remains a significant global health concern, characterized by high morbidity and mortality rates. High-dose-rate brachytherapy (HDR-BT) is a critical component of cervical cancer treatment, requiring precise and efficient treatment planning. However, the process is labor-intensive, h...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2025.1507592/full |
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| author | Junyue Shi Junyue Shi Jun Chen Gaokui He Qinghe Peng |
| author_facet | Junyue Shi Junyue Shi Jun Chen Gaokui He Qinghe Peng |
| author_sort | Junyue Shi |
| collection | DOAJ |
| description | Cervical cancer remains a significant global health concern, characterized by high morbidity and mortality rates. High-dose-rate brachytherapy (HDR-BT) is a critical component of cervical cancer treatment, requiring precise and efficient treatment planning. However, the process is labor-intensive, heavily reliant on operator expertise, and prone to variability due to factors such as applicator shifts and organ filling changes. Recent advancements in artificial intelligence (AI), particularly in medical image processing, offer significant potential for automating and standardizing treatment planning in HDR-BT. This review examines the progress and challenge of AI applications in HDR-BT treatment planning, focusing on automatic segmentation, applicator reconstruction, dose calculation, and plan optimization. By addressing current limitations and exploring future directions, this paper aims to guide the integration of AI into clinical practice, ultimately improving treatment accuracy, reducing preparation time, and enhancing patient outcomes. |
| format | Article |
| id | doaj-art-9ca8c5185a364d309ad8b19e042223cd |
| institution | Kabale University |
| issn | 2234-943X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj-art-9ca8c5185a364d309ad8b19e042223cd2025-01-27T06:40:15ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-01-011510.3389/fonc.2025.15075921507592Artificial intelligence in high-dose-rate brachytherapy treatment planning for cervical cancer: a reviewJunyue Shi0Junyue Shi1Jun Chen2Gaokui He3Qinghe Peng4Department of Nuclear Technology Application, China Institute of Atomic Energy, Beijing, ChinaDepartment of Radiation Oncology, Foresea Life Insurance Guangzhou General Hospital, Guangzhou, ChinaDepartment of Radiation Oncology, Foresea Life Insurance Guangzhou General Hospital, Guangzhou, ChinaDepartment of Nuclear Technology Application, China Institute of Atomic Energy, Beijing, ChinaDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, ChinaCervical cancer remains a significant global health concern, characterized by high morbidity and mortality rates. High-dose-rate brachytherapy (HDR-BT) is a critical component of cervical cancer treatment, requiring precise and efficient treatment planning. However, the process is labor-intensive, heavily reliant on operator expertise, and prone to variability due to factors such as applicator shifts and organ filling changes. Recent advancements in artificial intelligence (AI), particularly in medical image processing, offer significant potential for automating and standardizing treatment planning in HDR-BT. This review examines the progress and challenge of AI applications in HDR-BT treatment planning, focusing on automatic segmentation, applicator reconstruction, dose calculation, and plan optimization. By addressing current limitations and exploring future directions, this paper aims to guide the integration of AI into clinical practice, ultimately improving treatment accuracy, reducing preparation time, and enhancing patient outcomes.https://www.frontiersin.org/articles/10.3389/fonc.2025.1507592/fullartificial intelligence (AI)cervical cancerhigh-dose-rate brachytherapy (HDR-BT)treatment planningdeep learning (DL) |
| spellingShingle | Junyue Shi Junyue Shi Jun Chen Gaokui He Qinghe Peng Artificial intelligence in high-dose-rate brachytherapy treatment planning for cervical cancer: a review Frontiers in Oncology artificial intelligence (AI) cervical cancer high-dose-rate brachytherapy (HDR-BT) treatment planning deep learning (DL) |
| title | Artificial intelligence in high-dose-rate brachytherapy treatment planning for cervical cancer: a review |
| title_full | Artificial intelligence in high-dose-rate brachytherapy treatment planning for cervical cancer: a review |
| title_fullStr | Artificial intelligence in high-dose-rate brachytherapy treatment planning for cervical cancer: a review |
| title_full_unstemmed | Artificial intelligence in high-dose-rate brachytherapy treatment planning for cervical cancer: a review |
| title_short | Artificial intelligence in high-dose-rate brachytherapy treatment planning for cervical cancer: a review |
| title_sort | artificial intelligence in high dose rate brachytherapy treatment planning for cervical cancer a review |
| topic | artificial intelligence (AI) cervical cancer high-dose-rate brachytherapy (HDR-BT) treatment planning deep learning (DL) |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2025.1507592/full |
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