Surface-guided radiation therapy combined with real-time position management-guided deep inspiratory breath-hold radiotherapy for left breast cancer

To evaluate the efficacy of surface-guided radiation therapy (SGRT) combined with real-time position management (RPM)-guided deep inspiratory breath-hold (DIBH) radiotherapy for left breast cancer. Twenty patients diagnosed with breast cancer, who underwent breast-conserving surgery and subsequent DIBH radiotherapy, were randomly assigned to two treatment groups: SGRT-guided (SGRT); and combined SGRT + RPM-guided (SGRT + RPM). Recorded setup and cone beam computed tomography (CBCT) validation execution Time (T1), Beam delivery time (T2). Residual vertical setup error (VRT Error), six-dimensional (6D) setup errors, and breath-hold error (BH Error) were obtained using breath hold CBCT. Correlations between BH Error and VRT Error were analyzed. Dose reconstruction was performed using velocity-generated adaptive CT to compute per-fraction and accumulated doses, with coefficient of variation (CV) analysis used to quantify interfractional dose variations in clinical target volume (CTV) and organs at risk (OARs). The mean (± SD) T1 and T2 times for the SGRT and SGRT + RPM groups were 452.53 ± 83.57 s vs. 299.58 ± 53.52 s (p < 0.05), and 147.85 ± 46.35 s vs. 135.3 ± 32.97 s (p > 0.05), respectively, with no statistical difference in 6D setup errors (p > 0.05). The SGRT group exhibited a mean BH Error that was 0.4 mm larger than that of the SGRT + RPM group, with a 0.7 mm reduction in stability. There was a correlation between BH Error and VRT Error in the SGRT group (r = 0.635, p < 0.05). Accumulated dose analysis revealed statistically significant decreases in CTV D98% and V95% in both groups (p < 0.05). However, maintained CTV coverage meeting clinical acceptability criteria (V95% ≥ 95%). The accumulated OARs doses demonstrated no significant differences compared with the planned doses (p > 0.05). There was no significant difference in CV values between the two groups (p > 0.05). The DIBH guided by SGRT + RPM simplify the radiotherapy workflow, improve the operation efficiency and breath-hold (BH) quality of patients. Simultaneously, it guaranteed alignment of the cumulative doses received by the CTV and OARs with the planned doses.

Authors

Institutions

Publication Details

Journal
BMC Cancer
Published
2026-03-14
DOI
https://doi.org/10.1186/s12885-026-15846-1
Primary Topic
Breast Cancer Treatment Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Surface-guided radiation therapy combined with real-time position management-guided deep inspiratory breath-hold radiotherapy for left breast cancer

Yipeng Song, Hailiang Guo, Ruilian Xie, Huaying Xie et al.
BMC Cancer
Breast Cancer Treatment Studies
article

Surface-guided radiation therapy combined with real-time position management-guided deep inspiratory breath-hold radiotherapy for left breast cancer

Yipeng Song, Hailiang Guo, Ruilian Xie, Huaying Xie, Chunling Jiang, Jing-hua ZHONG, Gang-feng Zhu, Huai-wen Zhang, Guo-Ping Liao, Can-feng Weng
article en

Abstract

To evaluate the efficacy of surface-guided radiation therapy (SGRT) combined with real-time position management (RPM)-guided deep inspiratory breath-hold (DIBH) radiotherapy for left breast cancer. Twenty patients diagnosed with breast cancer, who underwent breast-conserving surgery and subsequent DIBH radiotherapy, were randomly assigned to two treatment groups: SGRT-guided (SGRT); and combined SGRT + RPM-guided (SGRT + RPM). Recorded setup and cone beam computed tomography (CBCT) validation execution Time (T1), Beam delivery time (T2). Residual vertical setup error (VRT Error), six-dimensional (6D) setup errors, and breath-hold error (BH Error) were obtained using breath hold CBCT. Correlations between BH Error and VRT Error were analyzed. Dose reconstruction was performed using velocity-generated adaptive CT to compute per-fraction and accumulated doses, with coefficient of variation (CV) analysis used to quantify interfractional dose variations in clinical target volume (CTV) and organs at risk (OARs). The mean (± SD) T1 and T2 times for the SGRT and SGRT + RPM groups were 452.53 ± 83.57 s vs. 299.58 ± 53.52 s (p < 0.05), and 147.85 ± 46.35 s vs. 135.3 ± 32.97 s (p > 0.05), respectively, with no statistical difference in 6D setup errors (p > 0.05). The SGRT group exhibited a mean BH Error that was 0.4 mm larger than that of the SGRT + RPM group, with a 0.7 mm reduction in stability. There was a correlation between BH Error and VRT Error in the SGRT group (r = 0.635, p < 0.05). Accumulated dose analysis revealed statistically significant decreases in CTV D98% and V95% in both groups (p < 0.05). However, maintained CTV coverage meeting clinical acceptability criteria (V95% ≥ 95%). The accumulated OARs doses demonstrated no significant differences compared with the planned doses (p > 0.05). There was no significant difference in CV values between the two groups (p > 0.05). The DIBH guided by SGRT + RPM simplify the radiotherapy workflow, improve the operation efficiency and breath-hold (BH) quality of patients. Simultaneously, it guaranteed alignment of the cumulative doses received by the CTV and OARs with the planned doses.

BMC Cancer
Renji Hospital (CN), Ganzhou People's Hospital (CN), Jiangxi Provincial Cancer Hospital (CN), Shanghai Cancer Institute (CN), Gannan Medical University (CN), First Affiliated Hospital of Gannan Medical University (CN), Guangzhou Medical University Cancer Hospital (CN), Guangzhou Medical University (CN)
Good health and well-being
Openalex Percentile: Top 22%
Breast Cancer Treatment Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.