Evidence map›Paper›PMID 28840168›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2017

Size-based quality-informed framework for quantitative optimization of pediatric CT.

Ehsan Samei, Xiang Li, Donald P Frush

Abstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Ehsan SameiDuke University Medical Center, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Carl E. Ravin Advanced Imaging Laboratories, Medical Physics Graduate Program, Durham, North Carolina, United States.
Xiang LiCleveland Clinic, Imaging Institute, Section of Medical Physics, Cleveland, Ohio, United States.
Donald P FrushDuke University Medical Center, Division of Pediatric Radiology, Department of Radiology, Medical Physics Graduate Program, Durham, North Carolina, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study was to formulate a systematic, evidence-based method to relate quantitative diagnostic performance to radiation dose, enabling a multidimensional system to optimize computed tomography imaging across pediatric populations. Based on two prior foundational studies, radiation dose was assessed in terms of organ doses, effective dose ([Formula: see text]), and risk index for 30 patients within nine color-coded pediatric age-size groups as a function of imaging parameters. The cases, supplemented with added noise and simulated lesions, were assessed in terms of nodule detection accuracy in an observer receiving operating characteristic study. The resulting continuous accuracy-dose relationships were used to optimize individual scan parameters. Before optimization, the nine protocols had a similar [Formula: see text] of [Formula: see text] with accuracy decreasing from 0.89 for the youngest patients to 0.67 for the oldest. After optimization, a consistent target accuracy of 0.83 was established for all patient categories with [Formula: see text] ranging from 1 to 10 mSv. Alternatively, isogradient operating points targeted a consistent ratio of accuracy-per-unit-dose across the patient categories. The developed model can be used to optimize individual scan parameters and provide for consistent diagnostic performance across the broad range of body sizes in children.

Indexed as

childrencomputed tomographydiagnostic accuracyimage qualitylung nodulepediatricradiation dosesize-specific protocols

Identifiers

PMID28840168
PMCPMC5565677

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.