A hybrid automated treatment planning solution for esophageal cancer
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RESEARCH
Open Access
A hybrid automated treatment planning solution for esophageal cancer Chifang Ling1,2†, Xu Han1,2†, Peng Zhai1,2, Hao Xu1,2, Jiayan Chen1,2, Jiazhou Wang1,2* and Weigang Hu1,2*
Abstract Objective: This study aims to investigate a hybrid automated treatment planning (HAP) solution that combines knowledge-based planning (KBP) and script-based planning for esophageal cancer. Methods: In order to fully investigate the advantages of HAP, three planning strategies were implemented in the present study: HAP, KBP, and full manual planning. Each method was applied to 20 patients. For HAP and KBP, the objective functions for plan optimization were generated from a dose–volume histogram (DVH) estimation model, which was based on 70 esophageal patients. Script-based automated planning was used for HAP, while the regular IMRT inverse planning method was used for KBP. For full manual planning, clinical standards were applied to create the plans. Paired t-tests were performed to compare the differences in dose-volume indices among the three planning methods. Results: Among the three planning strategies, HAP exhibited the best performance in all dose-volume indices, except for PTV dose homogeneity and lung V5. PTV conformity and spinal cord sparing were significantly improved in HAP (P < 0.001). Compared to KBP, HAP improved all indices, except for lung V5. Furthermore, the OAR sparing and target coverage between HAP and full manual planning were similar. Moreover, HAP had the shortest average planning time (57 min), when compared to KBP (63 min) and full manual planning (118 min). Conclusion: HAP is an effective planning strategy for obtaining a high quality treatment plan for esophageal cancer. Keywords: Automated planning, Knowledge-based planning, Esophageal carcinoma
Introduction Esophageal cancer is one of the most common thoracic malignancies, but more than 60% of patients are at a relatively late stage when diagnosed, resulting in non-eligibility for surgical resection. Radiotherapy is one of the standard options for advanced/late stage cancer [1]. Since 1985, an increasing number of patients have undergone preoperative radiotherapy to downstage tumor, and achieved higher cure rates [2]. Beginning in 2001, the prevalence of intensity modulated radiation therapy (IMRT) has led to better organs at risk (OAR) protection without compromising tumor coverage, when compared to three-dimensional conformal radiation therapy (3DCRT) [2].
* Correspondence: [email protected]; [email protected] † Chifang Ling and Xu Han contributed equally to this work. 1 Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai 200032, China Full list of author information is available at the end of the article
At present, pursuing optimal plans remains a timeconsuming and demanding task, especially for less experienced physicists/dosimetrists. Typically, plan optimization requires planners to adjust plan parameters according to the difference between current dose distribution and clinical goals. C
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