ArticleThe British journal of radiology2019
Establishing how patient size and degree of miscentring affect CTDI
Article in The British journal of radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Patient Centring in CT: An International Survey of Clinical Practice and Future Directions.Journal of medical radiation sciences · 2026Article
- Machine learning-based estimation of patient body weight from radiation dose metrics in computed tomography.Journal of applied clinical medical physics · 2024Article
- Patient cumulative radiation exposure-the potential for unintended consequences.European radiology · 2020Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe work aimed to investigate and model the relationship between CT dose index (CTDI
methodsCT scan parameters, patient dose metrics, patient positioning information and patient and water equivalent diameter information was extracted from abdomen, thorax-abdomen-pelvis and thorax imaging exams acquired on a 128-slice Siemens Somatom Definition AS + CT system using dose tracking software over a 1 year period. A miscentring factor, accounting for the magnification of the patient due to miscentring was derived. Significant predictors (
resultsThe model was capable of describing the CTDI
conclusionsWe demonstrate the use of clinical data, extracted from dose tracking software, to investigate and monitor AEC behaviour and CT output. ADVANCES IN KNOWLEDGE: The presented model allows for the remote investigation of AEC behaviour using patient data.
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Registered trials
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