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Automated fluence optimization in breast cancer radiotherapy: balancing dosimetric quality, organ-at-risk sparing, and workflow efficiency.

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Radiation oncology (London, England) 2026 Vol.21(1)
Retraction 확인
출처

PICO 자동 추출 (휴리스틱, conf 3/4)

유사 논문
P · Population 대상 환자/모집단
35 patients who received whole-breast irradiation for left-sided breast cancer.
I · Intervention 중재 / 시술
whole-breast irradiation for left-sided breast cancer
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
These findings support the integration of EZF into routine clinical practice to optimize radiotherapy delivery. [SUPPLEMENTARY INFORMATION] The online version contains supplementary material available at 10.1186/s13014-026-02815-y.

Choi YE, Shin HB, Sung K

📝 환자 설명용 한 줄

[BACKGROUND] In this study, we evaluated the effectiveness of EZFluence (EZF), an automated fluence optimization tool, in planning breast cancer radiotherapy by comparing its dosimetric performance wi

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BibTeX ↓ RIS ↓
APA Choi YE, Shin HB, Sung K (2026). Automated fluence optimization in breast cancer radiotherapy: balancing dosimetric quality, organ-at-risk sparing, and workflow efficiency.. Radiation oncology (London, England), 21(1). https://doi.org/10.1186/s13014-026-02815-y
MLA Choi YE, et al.. "Automated fluence optimization in breast cancer radiotherapy: balancing dosimetric quality, organ-at-risk sparing, and workflow efficiency.." Radiation oncology (London, England), vol. 21, no. 1, 2026.
PMID 41781988

Abstract

[BACKGROUND] In this study, we evaluated the effectiveness of EZFluence (EZF), an automated fluence optimization tool, in planning breast cancer radiotherapy by comparing its dosimetric performance with that of three-dimensional conformal radiotherapy (3D-CRT), intensity-modulated radiation therapy (IMRT), and volumetric-modulated arc therapy (VMAT). Specifically, we aimed to determine whether EZF can enhance target coverage, minimize dose to organs at risk, and improve planning efficiency.

[METHODS] This retrospective analysis included 35 patients who received whole-breast irradiation for left-sided breast cancer. Treatment plans were generated using 3D-CRT, IMRT, VMAT, and EZF-based forward-planned field-in-field techniques. Dosimetric parameters, including planning target volume coverage, cardiac exposure, left anterior descending artery dose, lung dose, and contralateral tissue dose, were analyzed. Planning efficiency was assessed by comparing the monitor units and planning time.

[RESULTS] EZF demonstrated significantly superior dose homogeneity and a lower delivered maximum dose compared with 3D-CRT and IMRT. Although VMAT provided the highest planning target volume V, EZF maintained comparable target coverage with significantly reduced high-dose regions. Additionally, EZF achieved a lower mean heart dose compared with 3D-CRT and IMRT. While VMAT offered superior high-dose cardiac sparing, EZF minimized low-dose cardiac spread and significantly reduced the mean lung dose and low-dose volumes of the left lung compared with IMRT and VMAT. The mean doses to the contralateral breast with 3D-CRT and EZF were less than 1 Gy, whereas those when using IMRT and VMAT exceeded 1 Gy. Regarding efficiency, EZF required fewer monitor units than did IMRT and VMAT, and its automated planning process reduced inter-planner variability.

[CONCLUSION] EZF demonstrated significant potential as an innovative approach in breast cancer radiotherapy, providing comparable target coverage with enhanced sparing of organs at risk and without unnecessary contralateral dose. Its automated fluence optimization enhanced planning efficiency by simplifying planning and reducing variability. These findings support the integration of EZF into routine clinical practice to optimize radiotherapy delivery.

[SUPPLEMENTARY INFORMATION] The online version contains supplementary material available at 10.1186/s13014-026-02815-y.