Evidence map›Paper›PMID 24531191›Full record

ArticlePediatric radiology2014

Computed tomography depiction of small pediatric vessels with model-based iterative reconstruction.

Gonca Koc, Jesse L Courtier, Andrew Phelps, Peter A Marcovici, John D MacKenzie

Abstract readEvaluation Study
PubMed Publisher
In one paragraph

Article in Pediatric radiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Gonca KocDepartment of Radiology and Biomedical Imaging, UCSF Benioff Children's Hospital, 505 Parnassus Ave., San Francisco, CA, 94143-0628, USA.
Jesse L Courtier
Andrew Phelps
Peter A Marcovici
John D MacKenzie

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComputed tomography (CT) is extremely important in characterizing blood vessel anatomy and vascular lesions in children. Recent advances in CT reconstruction technology hold promise for improved image quality and also reductions in radiation dose. This report evaluates potential improvements in image quality for the depiction of small pediatric vessels with model-based iterative reconstruction (Veo™), a technique developed to improve image quality and reduce noise.

objectiveTo evaluate Veo™ as an improved method when compared to adaptive statistical iterative reconstruction (ASIR™) for the depiction of small vessels on pediatric CT. MATERIALS AND

methodsSeventeen patients (mean age: 3.4 years, range: 2 days to 10.0 years; 6 girls, 11 boys) underwent contrast-enhanced CT examinations of the chest and abdomen in this HIPAA compliant and institutional review board approved study. Raw data were reconstructed into separate image datasets using Veo™ and ASIR™ algorithms (GE Medical Systems, Milwaukee, WI). Four blinded radiologists subjectively evaluated image quality. The pulmonary, hepatic, splenic and renal arteries were evaluated for the length and number of branches depicted. Datasets were compared with parametric and non-parametric statistical tests.

resultsReaders stated a preference for Veo™ over ASIR™ images when subjectively evaluating image quality criteria for vessel definition, image noise and resolution of small anatomical structures. The mean image noise in the aorta and fat was significantly less for Veo™ vs. ASIR™ reconstructed images. Quantitative measurements of mean vessel lengths and number of branches vessels delineated were significantly different for Veo™ and ASIR™ images. Veo™ consistently showed more of the vessel anatomy: longer vessel length and more branching vessels.

conclusionWhen compared to the more established adaptive statistical iterative reconstruction algorithm, model-based iterative reconstruction appears to produce superior images for depiction of small pediatric vessels on computed tomography.

Indexed as

AlgorithmsAngiographyChild, PreschoolContrast MediaFemaleHumansMaleRadiographic Image EnhancementRadiographic Image Interpretation, Computer-AssistedTomography, X-Ray ComputedContrast Media

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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.