ArticleCancers2023
Optimized Conformal Total Body Irradiation with VMAT Using a Linear-Accelerator-Based Radiosurgery Treatment System in Comparison to the Golden Standard Helical TomoTherapy.
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 7 citations in OpenAlex.
- VMAT-based total body irradiation on a conventional LINAC: workflow, procedure and preliminary results.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Paired dosimetric comparison of VMAT-based total body and total marrow irradiation in adult leukemia patients: enhanced organ sparing with consistent plan complexity.Frontiers in oncology · 2026Article
- Comparative dosimetric analysis of base dose and gradient-based optimization in overlapping regions of extended target volumes using an anthropomorphic phantom.Radiological physics and technology · 2025Article
- Feasibility of segmental total body irradiation (SegTBI) using a 1.5T MR-linac.Journal of applied clinical medical physics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modern irradiation techniques for optimized conformal TBI can be realized by Helical Tomotherapy (HT) or Volumetric Modulated Arc Therapy (VMAT), depending on the availability of suitable specialized equipment. In this dosimetric planning study, we compared both modalities and addressed the question of whether VMAT with small field sizes is also suitable as a backup in case of HT equipment malfunctions. For this purpose, we retrospectively used planning computed tomography (CT) data from 10 patients treated with HT with a total dose of 8 Gy (n = 5) or 12 Gy (n = 5) for treatment planning for VMAT with a small field size (36 × 22 cm). The target volume coverage, dose homogeneity at target volume, and dose reduction in organs at risk (OAR) (lungs, kidneys, lenses) were analyzed and compared. One patient was irradiated with both modalities due to a device failure of the HT equipment during the study, which facilitated a comparison in a real clinical setting. The findings indicate that in addition to a higher mean dose to the lenses in the 12 Gy group for VMAT and a better dose homogeneity in the target volume for HT, comparably good and adequate target dose coverage and dose reduction in the other OAR could be achieved for both modalities, with significantly longer treatment times for VMAT. In conclusion, after appropriate optimization of the treatment times, VMAT using linear accelerator radiosurgery technology can be used both as a backup in addition to HT and in clinical routines to perform optimized conformal TBI.
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.