| Ma Chenying,Xu Xiaoting,Zhou Juying.Development status of multimodal-fusion image-guided brachytherapy for cervical cancer[J].Chinese Journal of Radiological Medicine and Protection,2022,42(12):1004-1009 |
| Development status of multimodal-fusion image-guided brachytherapy for cervical cancer |
| Received:September 22, 2022 |
| DOI：10.3760/cma.j.cn112271-20220922-00384 |
| KeyWords:Cervical cancer|IGBT|Multimodal-fusion|Artificial intelligence|Deep learning |
| FundProject:国家自然科学基金(81602792);江苏省妇幼保健科研项目(F202210);放射医学与辐射防护国家重点实验室资助项目(GZK1202101);苏州市科技发展计划(KJXW2020008);苏州大学附属第一医院自然科学基金博习培育计划项目(BXQN202107) |
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| Abstract:: |
| Cisplatin-based systemic chemotherapy combined with external beam radiation followed by intracavitary brachytherapy (ICBT) has become the standard treatment modality for locally advanced cervical cancer. Benefiting from the improvement in the imaging accuracy of medical imaging equipment and the development of image fusion technology, ICBT has developed into image-guided brachytherapy (IGBT) rather than the mode relying only on single image guidance. Factors such as the selection of a suitable image acquisition technology and the optimization of the multimodal imaging fusion strategy to reduce the dose deviation of IGBT are the key to the success of cervical cancer treatment. Radiotherapy practice is also plagued by these factors. Deep learning-based artificial intelligence technology has emerged in constructing intelligent radiotherapy platforms and solutions and has become an important means of solving the key problems in the multi-modal fusion IGBT for cervical cancer. Moreover, this technology is also a new way to improve the overall diagnosis and treatment level of cervical cancer, reduce the workload of physicians, and popularize the radiotherapy experience in grassroots organizations. |
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