ESTRO 2024 - Abstract Book

S553

Clinical - Breast

ESTRO 2024

MHD ≥5 Gy was significantly associated with an increased rate of ACVE and a decreased LVEF from the baseline. Preemptive assessment for myocardial dysfunction may be necessary for patients who received trastuzumab and underwent RT with a high MHD.

Keywords: cardiovascular event, ejection fraction

1490

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SGRT for inter-fractional positioning and intra-fractional monitoring for breast cancer patients

Wellington F.P. Neves-Junior, Beatriz C. Nascimento, Vitor C. Gomes, Anselmo Mancini, Samir A. Hanna, Gustavo N. Marta

Hospital Sírio-Libanês, Department of Radiation Oncology, Sao Paulo, Brazil

Purpose/Objective:

Breast radiotherapy presents unique challenges and outcomes can be limited due to uncertainties, such as inter- and intra-fraction motion. Surface-Guided Radiotherapy (SGRT) technology allows positioning and real-time quantitative monitoring of breast position during treatment, enabling better control of uncertainties. This work aims to: (i) evaluate the performance of SGRT for breast positioning compared to laser/skin marks using Cone Beam Computed Tomography (CBCT) as reference, and (ii) assess results of intra-fractional breast motion detected through SGRT.

Material/Methods:

Data has been retrospectively collected from breast cancer patients treated with radiotherapy from October/2018 to December/2020. To evaluate SGRT’s inter -fractional performance, we collected errors detected by CBCT after laser or SGRT positioning, with the difference between these errors evaluated through the calculation of the planning target volume margin (PTV) and an unpaired t-test. To evaluate intra-fraction motion, the continuous real time translational displacements (vertical, lateral, and longitudinal coordinates) were used to calculate vectors and their respective means (M) and standard deviations (SD). The M was considered a measure of intra-fraction systematic error, while the SD a measure of intra-fraction variability. Additionally, the percentage of time with vector deviations in the following millimetre intervals were calculated from 0 to 1, from 1 to 2, from 2 to 3, from 3 to 4, from 4 to 5 and greater than 5. The data was processed to exclude outliers and monitoring sessions with implausible characteristics (uninterrupted monitoring at the end of the session, camera blockages, etc). A linear regression model (alpha=5%) was used to analyse the potential impact of age, breast volume, the presence of silicone implants (yes or no), and breast pendulous characteristics (yes or no) on the detected deviations.

Results:

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