ArticleStrahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]2023
Clinical application of breathing-adapted 4D CT: image quality comparison to conventional 4D CT.
Article in Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al], 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 19 citations in OpenAlex.
- Lymphedema imaging and AI: A review of diagnostic modalities, biomarkers, and clinical integration.Biomedical journal · 2026Review
- Deep learning-enhanced data-driven gating improves FDG PET/CT clinical image quality.EJNMMI physics · 2026Article
- Automated quality assurance of imaging dose and protocol adherence in computed tomography radiotherapy planning using TotalSegmentator-based segmentation.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Article
- Surface-guided breathing signal integration in breathing-adapted intelligent 4D computed tomography: prototype implementation and comparison with an infrared marker-based system.Physics and imaging in radiation oncology · 2025Article
- A novel respiratory surrogate system with table motion correction and visual feedback for computed tomography.Physics and imaging in radiation oncology · 2025Article
- Investigating the effects of table movement and sag on optical surrogate-driven respiratory-guided computed tomography.Journal of applied clinical medical physics · 2025Article
- 4DCT image artifact detection using deep learning.Medical physics · 2025Article
- Development of a novel 3D-printed dynamic anthropomorphic thorax phantom for evaluation of four-dimensional computed tomography.Physics and imaging in radiation oncology · 2024Article
- First implementation of an innovative infra-red camera system integrated into a mobile CBCT scanner for applicator tracking in brachytherapy-Initial performance characterization.Journal of applied clinical medical physics · 2024Article
- Optimized raw data selection for artifact reduction of breathing controlled four-dimensional sequence scanning.Physics and imaging in radiation oncology · 2024Article
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose4D CT imaging is an integral part of 4D radiotherapy workflows. However, 4D CT data often contain motion artifacts that mitigate treatment planning. Recently, breathing-adapted 4D CT (i4DCT) was introduced into clinical practice, promising artifact reduction in in-silico and phantom studies. Here, we present an image quality comparison study, pooling clinical patient data from two centers: a new i4DCT and a conventional spiral 4D CT patient cohort.
methodsThe i4DCT cohort comprises 129 and the conventional spiral 4D CT cohort 417 4D CT data sets of lung and liver tumor patients. All data were acquired for treatment planning. The study consists of three parts: illustration of image quality in selected patients of the two cohorts with similar breathing patterns; an image quality expert rater study; and automated analysis of the artifact frequency.
resultsImage data of the patients with similar breathing patterns underline artifact reduction by i4DCT compared to conventional spiral 4D CT. Based on a subgroup of 50 patients with irregular breathing patterns, the rater study reveals a fraction of almost artifact-free scans of 89% for i4DCT and only 25% for conventional 4D CT; the quantitative analysis indicated a reduction of artifact frequency by 31% for i4DCT.
conclusionThe results demonstrate 4D CT image quality improvement for patients with irregular breathing patterns by breathing-adapted 4D CT in this first corresponding clinical data image quality comparison study.
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