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Comprehensive Treatment Uncertainty Analysis and PTV Margin Estimation for Fiducial Tracking in Robotic Liver Stereotactic Body Radiation Therapy.
Liang, Zhi-Wen; Zhai, Meng-Lan; Tu, Biao; Nie, Xin; Zhu, Xiao-Hui; Cheng, Jun-Ping; Li, Guo-Quan; Yu, Dan-Dan; Zhang, Tao; Zhang, Sheng.
Affiliation
  • Liang ZW; Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Zhai ML; Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Tu B; Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Nie X; Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Zhu XH; Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Cheng JP; Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Li GQ; Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Yu DD; Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Zhang T; Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China. taozhangxh@hust.edu.cn.
  • Zhang S; Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China. tonydppx@hotmail.com.
Curr Med Sci ; 43(3): 572-578, 2023 Jun.
Article in En | MEDLINE | ID: mdl-37142817
ABSTRACT

OBJECTIVE:

This study aims to quantify the uncertainties of CyberKnife Synchrony fiducial tracking for liver stereotactic body radiation therapy (SBRT) cases, and evaluate the required planning target volume (PTV) margins.

METHODS:

A total of 11 liver tumor patients with a total of 57 fractions, who underwent SBRT with synchronous fiducial tracking, were enrolled for the present study. The correlation/prediction model error, geometric error, and beam targeting error were quantified to determine the patient-level and fraction-level individual composite treatment uncertainties. The composite uncertainties and multiple margin recipes were compared for scenarios with and without rotation correction during treatment.

RESULTS:

The correlation model error-related uncertainty was 4.3±1.8, 1.4±0.5 and 1.8±0.7 mm in the superior-inferior (SI), left-right, and anterior-posterior directions, respectively. These were the primary contributors among all uncertainty sources. The geometric error significantly increased for treatments without rotation correction. The fraction-level composite uncertainties had a long tail distribution. Furthermore, the generally used 5-mm isotropic margin covered all uncertainties in the left-right and anterior-posterior directions, and only 75% of uncertainties in the SI direction. In order to cover 90% of uncertainties in the SI direction, an 8-mm margin would be needed. For scenarios without rotation correction, additional safety margins should be added, especially in the superior-inferior and anterior-posterior directions.

CONCLUSION:

The present study revealed that the correlation model error contributes to most of the uncertainties in the results. Most patients/fractions can be covered by a 5-mm margin. Patients with large treatment uncertainties might need a patient-specific margin.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiosurgery / Carcinoma, Hepatocellular / Robotic Surgical Procedures / Liver Neoplasms Type of study: Prognostic_studies Language: En Journal: Curr Med Sci Year: 2023 Type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiosurgery / Carcinoma, Hepatocellular / Robotic Surgical Procedures / Liver Neoplasms Type of study: Prognostic_studies Language: En Journal: Curr Med Sci Year: 2023 Type: Article Affiliation country: China