Evidence map›Paper›PMID 29114620›Full record

ArticleAdvances in radiation oncology

Reducing radiation dose and enhancing imaging quality of 4DCT for radiation therapy using iterative reconstruction algorithms.

George Noid, An Tai, Guang-Pei Chen, Jared Robbins, X Allen Li

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Article in Advances in radiation oncology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

George NoidMedical College of Wisconsin, Department of Radiation Oncology, Milwaukee, Wisconsin.
An TaiMedical College of Wisconsin, Department of Radiation Oncology, Milwaukee, Wisconsin.
Guang-Pei ChenMedical College of Wisconsin, Department of Radiation Oncology, Milwaukee, Wisconsin.
Jared RobbinsMedical College of Wisconsin, Department of Radiation Oncology, Milwaukee, Wisconsin.
X Allen LiMedical College of Wisconsin, Department of Radiation Oncology, Milwaukee, Wisconsin.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeFour-dimensional computed tomography (CT) images are typically used to quantify the necessary internal target volumes for thoracic and abdominal tumors. However, 4-dimensional CT is typically associated with excessive imaging dose to patients and the situation is exacerbated when using repeat 4-dimensional CT imaging on a weekly or daily basis throughout fractionated therapy. The aim of this work is to evaluate an iterative reconstruction (IR) algorithm that helps reduce the imaging dose to the patient while maintaining imaging quality as quantified by point spread function and contrast-to-noise ratios (CNRs). METHODS AND MATERIALS: An IR algorithm, SAFIRE, was applied to CT data of a phantom and patients with varying CT doses and reconstruction kernels. Phantom data enable measurements of spatial resolution, contrast, and noise. The impact of SAFIRE on 4-dimensional CT was assessed with patient data acquired at 2 different dose levels during image guided radiation therapy with an in-room CT.

resultsPhantom data demonstrate that IR reduces noise approximately in proportion to the number of iterations indicated by the strength (SAFIRE 1 to SAFIRE 5). Spatial resolution and contrast are conserved independent of dose and reconstruction parameters. The CNR increases with an increase of imaging dose or an increase in the number of iterations. The use of IR on CT sets confirms the results that were derived from phantom scans. The IR significantly enhances single breathing phase CTs in 4-dimensional CT sets as assessed by CT number discrimination. Furthermore, the IR of the low dose 4-dimensional CT features a 45% increase in the CNR in comparison with the standard dose 4-dimensional CT.

conclusionsThe use of IR algorithms reduces noise while preserving spatial resolution and contrast, as evaluated from both phantom and patient CT data sets. For 4-dimensional CT, the IR can significantly improve image quality and reduce imaging dose without compromising image quality.

Identifiers

PMID29114620
PMCPMC5605285

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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.