Abstract
Purpose: Using in vivo measurements from optically stimulated luminescence dosimeters (OSLDs) to develop and validate a prediction model for estimating the skin dose received by patients undergoing breast intraoperative radiation therapy (IORT). Methods and Materials: IORT was performed using INTRABEAM-600 with spherical applicators placed in the lumpectomy cavity. Ultrasound skin bridge measurements were used to determine the applicator-to-skin distance, with OSLDs placed to measure the skin surface dose at the corresponding points. The OSLD response was calibrated for the 50 kVp INTRABEAM-600 output. Models were fit to describe the dose fall-off with increasing applicator-to-skin distance and the best fitting model was chosen for estimating skin dose. Results: Twenty four patients with 25 lumpectomy cavities were included, and the average skin dose recorded was 1.18 Gy ± 0.88 Gy, ranging from 0.17 Gy to 4.77 Gy, with an average applicator-to-skin distance of 19.9 mm ± 5.1 mm. An exponential-plateau model was found to best describe the dose fall-off with a root-mean-square error of 0.73. This model was then validated prospectively using skin dose measurements from five consecutive patients. Validation measurements were well within the 95% prediction limits of the model, with a root-mean-square error of 0.52, showing that the prediction model accurately estimates skin dose using ultrasound skin bridge measurements. Conclusions: This prediction model constitutes a useful tool for estimating the skin dose received during breast lumpectomy IORT. The model and accompanying 95% confidence intervals can be used to establish a minimum allowable skin bridge distance, effectively limiting the maximum allowable skin dose.
Original language | English (US) |
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Pages (from-to) | 720-726 |
Number of pages | 7 |
Journal | Brachytherapy |
Volume | 18 |
Issue number | 5 |
DOIs | |
State | Published - Sep 1 2019 |
Keywords
- Breast cancer
- Intraoperative radiation
- Prediction models
- Skin dose
ASJC Scopus subject areas
- Oncology
- Radiology Nuclear Medicine and imaging