Within-patient four-dimensional computed tomography analysis reveals location-dependent motion of thoracic lymph nodes during respiration

Abstract Background Internal margins for thoracic lymph nodes in radiotherapy are commonly applied uniformly despite variability in nodal motion during respiration across patients and node stations. Four-dimensional CT (4DCT) has demonstrated movement of mediastinal and hilar lymph nodes and discordance with motion of the primary tumor, yet translation into practical margin strategies remains limited. We hypothesized that the amount of movement during respiration differs between upper and lower thoracic lymph nodes within the same patient and evaluated location-dependent motion to characterize regional and interpatient variability in respiratory motion. Methods This retrospective cohort study included patients undergoing 4DCT simulation for thoracic radiotherapy. Eligible patients had complete respiratory phase datasets and at least one upper and one lower thoracic lymph node identified on reference-phase CT. Nodes were classified relative to the carina. Lymph node centroids were tracked across respiratory phases to quantify directional displacement and three-dimensional vector magnitude relative to the reference phase. Differences in motion between upper (stations 1–6) and lower (stations 7–14) nodes were evaluated using linear mixed-effects models accounting for within-patient clustering. Results Forty-one patients with 229 lymph nodes were analyzed (130 upper, 99 lower). Motion was predominantly cranio–caudal. Mean cranio–caudal displacement was 3.3 ± 1.9 mm for upper nodes and 5.2 ± 3.0 mm for lower nodes. Within-patient analysis demonstrated greater motion for lower nodes (mean difference 1.9 mm; p < 0.001). Vector displacement was also greater for lower nodes (5.7 ± 2.9 mm vs. 4.1 ± 2.0 mm; p < 0.001). Motion exceeding 5 mm in three-dimensional vector magnitude occurred more frequently with lower nodes (51% vs. 37%). Exploratory patient-level 90th percentile analysis showed anisotropic motion. Conclusions Thoracic node motion during respiration is location-dependent, with greater displacement of lower nodes and substantial interpatient variability. These findings support individualized assessment of respiratory motion using 4DCT rather than reliance on uniform population-based internal margins.

Authors

Institutions

Publication Details

Journal
Radiation Oncology
Published
2026-10-26
DOI
https://doi.org/10.1186/s13014-026-02951-5
Primary Topic
Advanced Radiotherapy Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Within-patient four-dimensional computed tomography analysis reveals location-dependent motion of thoracic lymph nodes during respiration

Masaki Nakamura, Kouta Hirotaki, Sadamoto Zenda, 隆志 染谷 et al.
Radiation Oncology
Advanced Radiotherapy Techniques
article

Within-patient four-dimensional computed tomography analysis reveals location-dependent motion of thoracic lymph nodes during respiration

Masaki Nakamura, Kouta Hirotaki, Sadamoto Zenda, 隆志 染谷, Ryo Takahashi, Hidenobu Tachibana, Hajime Oyoshi, Tenyoh Suzuki, Shoki Nakamura, Yuki Mizunuma
article en

Abstract

Abstract Background Internal margins for thoracic lymph nodes in radiotherapy are commonly applied uniformly despite variability in nodal motion during respiration across patients and node stations. Four-dimensional CT (4DCT) has demonstrated movement of mediastinal and hilar lymph nodes and discordance with motion of the primary tumor, yet translation into practical margin strategies remains limited. We hypothesized that the amount of movement during respiration differs between upper and lower thoracic lymph nodes within the same patient and evaluated location-dependent motion to characterize regional and interpatient variability in respiratory motion. Methods This retrospective cohort study included patients undergoing 4DCT simulation for thoracic radiotherapy. Eligible patients had complete respiratory phase datasets and at least one upper and one lower thoracic lymph node identified on reference-phase CT. Nodes were classified relative to the carina. Lymph node centroids were tracked across respiratory phases to quantify directional displacement and three-dimensional vector magnitude relative to the reference phase. Differences in motion between upper (stations 1–6) and lower (stations 7–14) nodes were evaluated using linear mixed-effects models accounting for within-patient clustering. Results Forty-one patients with 229 lymph nodes were analyzed (130 upper, 99 lower). Motion was predominantly cranio–caudal. Mean cranio–caudal displacement was 3.3 ± 1.9 mm for upper nodes and 5.2 ± 3.0 mm for lower nodes. Within-patient analysis demonstrated greater motion for lower nodes (mean difference 1.9 mm; p < 0.001). Vector displacement was also greater for lower nodes (5.7 ± 2.9 mm vs. 4.1 ± 2.0 mm; p < 0.001). Motion exceeding 5 mm in three-dimensional vector magnitude occurred more frequently with lower nodes (51% vs. 37%). Exploratory patient-level 90th percentile analysis showed anisotropic motion. Conclusions Thoracic node motion during respiration is location-dependent, with greater displacement of lower nodes and substantial interpatient variability. These findings support individualized assessment of respiratory motion using 4DCT rather than reliance on uniform population-based internal margins.

Radiation Oncology
St. Marianna University School of Medicine (JP), National Cancer Center Hospital East (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 14%
Advanced Radiotherapy Techniques
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.

Laika access coming soon