ArticleEuropean radiology2014
Image noise-based dose adaptation in dynamic volume CT of the heart: dose and image quality optimisation in comparison with BMI-based dose adaptation.
Article in European radiology, 2014. 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
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
3 citing papers in PubMed, 9 citations in OpenAlex.
- Image quality in coronary CT angiography: challenges and technical solutions.The British journal of radiology · 2017Review
- Third-generation dual-source CT of the neck using automated tube voltage adaptation in combination with advanced modeled iterative reconstruction: evaluation of image quality and radiation dose.European radiology · 2016Article
- A practical approach for a patient-tailored dose protocol in coronary CT angiography using prospective ECG triggering.The international journal of cardiovascular imaging · 2016Article
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 at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo compare the image quality and radiation dose using image-noise (IN)-based determination of X-ray tube settings compared with a body mass index (BMI)-based protocol during CT coronary angiography (CTCA).
methodsTwo hundred consecutive patients referred for CTCA to our institution were divided into two groups: BMI-based, 100 patients had CTCA with the X-ray tube current adjusted to the patient's BMI while maintaining a fixed tube potential of 120 kV; IN-based, 100 patients underwent imaging with the X-ray tube current and voltage adjusted to the IN measured within the mid-left ventricle on a pre-acquisition trans-axial image. Two independent cardiac radiologists performed blinded image quality assessment with quantification of the IN and signal-to-noise ratio (SNR) from the mid-LV and qualitative assessment using a three-point score. Radiation dose (CTDI and DLP) was recorded from the console.
resultsResults showed: IN (HU): BMI-based, 30.1 ± 9.9; IN-based, 33.1 ± 6.7; 32 % variation reduction (P = 0.001); SNR: BMI-based, 18.6 ± 7.1; IN-based, 15.4 ± 3.7; 48 % variation reduction (P < 0.0001). Visual scores: BMI-based, 2.3 ± 0.6; IN-based, 2.2 ± 0.5 (P = 0.54). Radiation dose: CTDI (mGy), BMI-based, 22.68 ± 8.9; IN-based, 17.16 ± 7.6; 24.3 % reduction (P < 0.001); DLP (mGy.cm), BMI-based, 309.3 ± 127.5; IN-based, 230.6 ± 105.5; 25.4 % reduction (P < 0.001).
conclusionsImage-noise-based stratification of X-ray tube parameters for CTCA results in 32 % improvement in image quality and 25 % reduction in radiation dose compared with a BMI-based protocol. KEY POINTS: • Image quality and radiation dose are closely related in CT coronary angiography. • So too are the image quality, radiation dose and body mass index (BMI). • An image-noise-based CTCA protocol reduces the radiation dose by 25 %. • It improves inter-patient image homogeneity by 32 %.
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.