Yang Yu-Xian, Yang Xin, Jiang Xiao-Bo, Lin Li, Wang Guang-Yu, Sun Wen-Zhao, Zhang Kang, Li Bing-Huan, Li Hua, Jia Le-Cheng, Wei Zi-Quan, Liu Yan-Fei, Fu Dan-Ning, Tang Jun-Xiang, Zhang Wei, Zhou Jing-Jie, Diao Wen-Chao, Wang Ya-Juan, Chen Xue-Mei, Xu Chen-Di, Lin Liu-Wen, Wu Jia-Ying, Wu Jia-Wei, Peng Li-Xia, Pan Jin-Fa, Liu Bing-Zhong, Feng Chi, Huang Xiao-Yan, Zhou Guan-Qun, Sun Ying
Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China.
Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China.
Int J Radiat Oncol Biol Phys. 2025 Jul 15;122(4):902-913. doi: 10.1016/j.ijrobp.2024.11.096. Epub 2024 Dec 19.
To establish an artificial intelligence (AI)-empowered multistep integrated (MSI) radiation therapy (RT) workflow for patients with nasopharyngeal carcinoma (NPC) and evaluate its feasibility and clinical performance.
Patients with NPC scheduled for MSI RT workflow were prospectively enrolled. This workflow integrates RT procedures from computed tomography (CT) scan to beam delivery, all performed with the patient on the treatment couch. Workflow performance, tumor response, patient-reported acute toxicities, and quality of life were evaluated.
From March 2022 to October 2023, 120 newly diagnosed, nonmetastatic patients with NPC were enrolled. Of these, 117 completed the workflow with a median duration of 23.2 minutes (range, 16.3-45.8). Median translation errors were 0.2 mm (from CT scan to planning approval) and 0.1 mm (during beam delivery). AI-generated contours required minimal revision for the high-risk clinical target volume and organs at risk, minor revision for the involved cervical lymph nodes and low-risk clinical target volume (median Dice similarity coefficients (DSC), 0.98 and 0.94), and more revision for the gross tumor at the primary site and the involved retropharyngeal lymph nodes (median DSC, 0.84). Of 117 AI-generated plans, 108 (92.3%) passed after the first optimization, with ≥97.8% of target volumes receiving ≥100% of the prescribed dose. Dosimetric constraints were met for most organs at risk, except the thyroid and submandibular glands. One hundred and fifteen patients achieved a complete response at week 12 post-RT, while 14 patients reported any acute toxicity as "very severe" from the start of RT to week 12 post-RT.
AI-empowered MSI RT workflow for patients with NPC is clinically feasible in a single institutional setting compared with standard, human-based RT workflow.
建立一种由人工智能(AI)赋能的多步骤集成(MSI)放射治疗(RT)工作流程,用于鼻咽癌(NPC)患者,并评估其可行性和临床性能。
前瞻性纳入计划进行MSI RT工作流程的NPC患者。该工作流程整合了从计算机断层扫描(CT)扫描到射束投送的RT程序,所有操作均在治疗床上对患者进行。评估了工作流程性能、肿瘤反应、患者报告的急性毒性和生活质量。
2022年3月至2023年10月,纳入120例新诊断的非转移性NPC患者。其中,117例完成了工作流程,中位持续时间为23.2分钟(范围16.3 - 45.8分钟)。中位平移误差为0.2毫米(从CT扫描到计划批准)和0.1毫米(射束投送期间)。AI生成的轮廓对于高危临床靶区和危及器官需要最小程度的修正,对于受累颈部淋巴结和低危临床靶区需要较小程度的修正(中位骰子相似系数(DSC)分别为0.98和0.94),而对于原发部位的大体肿瘤和受累咽后淋巴结需要更多修正(中位DSC为0.84)。在117个AI生成的计划中,108个(92.3%)在首次优化后通过,≥97.8%的靶区接受了≥100%的处方剂量。除甲状腺和下颌下腺外,大多数危及器官的剂量学约束均得到满足。115例患者在放疗后第12周达到完全缓解,而14例患者报告从放疗开始到放疗后第12周任何急性毒性为“非常严重”。
与基于人工的标准RT工作流程相比,由AI赋能的NPC患者MSI RT工作流程在单一机构环境中临床可行。