Daily dose evaluation based on corrected CBCTs for breast cancer patients: accuracy of dose and complication risk assessment.
Radiat Oncol
; 17(1): 205, 2022 Dec 12.
Article
em En
| MEDLINE
| ID: mdl-36510254
OBJECTIVES: The goal of this study is to validate different CBCT correction methods to select the superior method that can be used for dose evaluation in breast cancer patients with large anatomical changes treated with photon irradiation. MATERIALS AND METHOD: Seventy-six breast cancer patients treated with a partial VMAT photon technique (70% conformal, 30% VMAT) were included in this study. All patients showed at least a 5 mm variation (swelling or shrinkage) of the breast on the CBCT compared to the planning-CT (pCT) and had a repeat-CT (rCT) for dose evaluation acquired within 3 days of this CBCT. The original CBCT was corrected using four methods: (1) HU-override correction (CBCTHU), (2) analytical correction and conversion (CBCTCC), (3) deep learning (DL) correction (CTDL) and (4) virtual correction (CTV). Image quality evaluation consisted of calculating the mean absolute error (MAE) and mean error (ME) within the whole breast clinical target volume (CTV) and the field of view of the CBCT minus 2 cm (CBCT-ROI) with respect to the rCT. The dose was calculated on all image sets using the clinical treatment plan for dose and gamma passing rate analysis. RESULTS: The MAE of the CBCT-ROI was below 66 HU for all corrected CBCTs, except for the CBCTHU with a MAE of 142 HU. No significant dose differences were observed in the CTV regions in the CBCTCC, CTDL and CTv. Only the CBCTHU deviated significantly (p < 0.01) resulting in 1.7% (± 1.1%) average dose deviation. Gamma passing rates were > 95% for 2%/2 mm for all corrected CBCTs. CONCLUSION: The analytical correction and conversion, deep learning correction and virtual correction methods can be applied for an accurate CBCT correction that can be used for dose evaluation during the course of photon radiotherapy of breast cancer patients.
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Texto completo:
1
Temas:
ECOS
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Aspectos_gerais
Bases de dados:
MEDLINE
Assunto principal:
Planejamento da Radioterapia Assistida por Computador
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Neoplasias da Mama
Tipo de estudo:
Etiology_studies
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Risk_factors_studies
Limite:
Female
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Humans
Idioma:
En
Revista:
Radiat Oncol
Assunto da revista:
NEOPLASIAS
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RADIOTERAPIA
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Holanda