Effectiveness of Automated Treatment Planning for Left-sided Breast in Flattening Filter-free Photon Beams.

Prasit Tansangworn, Nichakan Chatchumnan, Kitwadee Saksornchai, Sakda Kingkaew, Mananchaya Vimolnoch, Puntiwa Oonsiri, Sornjarod Oonsiri
Author Information
  1. Prasit Tansangworn: Department of Radiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
  2. Nichakan Chatchumnan: Department of Radiology, Division of Radiation Oncology, King Chulalongkorn Memorial Hospital, Bangkok, Thailand.
  3. Kitwadee Saksornchai: Department of Radiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
  4. Sakda Kingkaew: Department of Radiology, Division of Radiation Oncology, King Chulalongkorn Memorial Hospital, Bangkok, Thailand.
  5. Mananchaya Vimolnoch: Department of Radiology, Division of Radiation Oncology, King Chulalongkorn Memorial Hospital, Bangkok, Thailand.
  6. Puntiwa Oonsiri: Department of Radiology, Division of Radiation Oncology, King Chulalongkorn Memorial Hospital, Bangkok, Thailand.
  7. Sornjarod Oonsiri: Department of Radiology, Division of Radiation Oncology, King Chulalongkorn Memorial Hospital, Bangkok, Thailand.

Abstract

Purpose: Electronic compensator is a time-consuming technique for breast cancer radiation treatment planning, consequently, this presents challenges for the development of automated treatment planning for the treatment plan. Thus, this study aimed to investigate the use of automated treatment planning software for the left breast.
Subjects and Methods: Thirty-eight patients with left-sided breast cancer without locoregional nodes were treated with a prescribed dose of 42.4 Gy in 16 fractions. Treatment planning was performed using electronic compensators. In addition, automated treatment planning techniques were utilized, which involved automated plan generation. This facilitated the comparison of dosimetric parameters: target volume (D, homogeneity index [HI], and conformity index [CI]), organs at risk, plan parameters, and quality assurance.
Results: The automated treatment planning exerted lower D of PTV_Eval compared to electronic compensator techniques, that is, 43.4 �� 1.1 Gy and 43.9 �� 1.1 Gy, respectively ( < 0.05). Similarly, the HI of automated treatment planning was lower than other techniques, 0.10 �� 0.04 and 0.08 �� 0.03, respectively ( < 0.05). However, there were no significant differences in the CI or organs at risk between the two techniques ( = 0.11). In plan parameters, automated treatment planning required lower monitor units compared to the electronic compensator techniques, i.e., 534.3 �� 47.4 and 724.5 �� 117.9, respectively ( < 0.05). Furthermore, the automated treatment planning significantly reduced treatment time compared to electronic compensator techniques, that is, 2.3 �� 0.5 and 41.8 �� 15.1 min, respectively ( < 0.05).
Conclusions: Automated treatment planning improved the treatment plan homogeneity, reduced hotspots, enhanced treatment planning efficiency, and reduced treatment planning time and doses comparable to those of normal organs.

Keywords

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Word Cloud

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