ArticleZeitschrift fur medizinische Physik2025
Intra-fractional lung tumor motion monitoring using arbitrary gantry angles during radiotherapy treatment.
Article in Zeitschrift fur medizinische Physik, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Assessing the technical capability of a room- and a gantry-mounted kV imaging device for intra-fractional fluoroscopy during stereotactic lung radiotherapy at a C-arm linear accelerator.Physics and imaging in radiation oncology · 2026Article
- Initial Experience with Correlation Object-Based DRR Targeting Using Stereoscopic X-Ray Imaging in Lung SBRT.Cancers · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Intensity-based 2D/3D registration using kilo-voltage (kV) and mega-voltage (MV) on-board imaging is a promising approach for real-time tumor motion tracking. So far, the performance of the kV images as well as kV-MV image pairs for 2D/3D registration using only one gantry angle (in anterior-posterior (AP) direction) has been investigated on patient data. In stereotactic body radiation therapy (SBRT), however, various gantry angles are typically used. This study attempts to answer the question of whether automatic 2D/3D registration is possible using kV images as well as kV-MV image pairs for gantry angles other than the AP direction. We also investigated the effect of additional portal MV images paired with kV images to improve 2D/3D registration in extracting cranio-caudal (CC) and AP displacement at arbitrary gantry angles and different fractions. The kV and MV image sequences as well as 3D volume data from five patients suffering from non-small cell lung cancer undergoing SBRT were used. Diaphragm motion served as the reference signal. The CC and AP displacements resulting from the registration results were compared with the corresponding reference motion signal. Pearson correlation coefficients (R value) was used to calculate the similarity measure between reference signal and the extracted displacements resulting from the registration. Signals we found that using 2D/3D registration tumor motion in 5 degrees of freedom (DOF) with kV images and in 6 degrees of freedom with kV-MV image pairs can be extracted for most gantry angles in all patients. Furthermore, our results have shown that the use of kV-MV image pairs increases the overall chance of tumor visibility and therefore leads to more successful extraction of CC as well as AP displacements for almost all gantry angles in all patients. We observed an improvement in registration of at least 0.29% more gantry angle for all patients when we used kV-MV images compared to kV images alone. In addition, an improvement in the R-value was observed in up to 16 fractions in various patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.