Evidence map›Paper›PMID 26894339›Full record

ArticleJournal of applied clinical medical physics2016

Radiation intensity (CTDIvol) and visibility of anatomical structures in head CT examinations.

Sameer Tipnis, Rajesh Thampy, Zoran Rumboldt, Maria Spampinato, Gisele Matheus, Walter Huda

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Sameer TipnisMedical University of South Carolina. tipnis@musc.edu.
Rajesh Thampy
Zoran Rumboldt
Maria Spampinato
Gisele Matheus
Walter Huda

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study was to quantify how changing the amount of radiation used to perform routine head CT examinations (CTDIvol) affects visibility of key anatomical structures. Eight routine noncontrast head CT exams were selected from six CT scanners, each of which had a different CTDIvol setting (60 to 75 mGy). All exams were normal and two slices were selected for evaluation, one at the level of basal ganglia and the other at the fourth ventricle. Three experienced neuroradiologists evaluated the visibility of selected structures, including the putamen, caudate nucleus, thalamus, internal capsule, grey/white differentiation, and brainstem. Images were scored on a five-point scoring scheme (1, unacceptable, 3, satisfactory, and 5, excellent). Reader scores, averaged over the cases obtained from each scanner, were plotted as a function of the corresponding CTDIvol. Average scores for the fourth ventricle were 3.06 ± 0.83 and for the basal ganglia were 3.20 ± 0.86. No image received a score of 1. Two readers showed no clear trend of an increasing score with increasing CTDIvol. One reader showed a slight trend of increasing score with increasing CTDIvol, but the increase in score from a 25% increase in CTDIvol was a fraction of the standard deviation associated average scores. Collectively, results indicated that there were no clear improvements in visualizing neuroanatomy when CTDIvol increased from 60 to 75 mGy in routine head CT examinations. Our study showed no apparent benefit of using more than 60 mGy when performing routine noncontrast head CT examinations.

Indexed as

Models, AnatomicPhantoms, ImagingAdultAgedAged, 80 and overBrain NeoplasmsFemaleHeadHumansMaleMiddle AgedRadiation DosageRetrospective StudiesTomography Scanners, X-Ray ComputedTomography, X-Ray ComputedYoung Adult

Identifiers

PMID26894339
PMCPMC5690219

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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.