Evidence map›Paper›PMID 33369002›Full record

ArticleJournal of applied clinical medical physics2021

Lower limit of iron quantification using dual-energy CT - a phantom study.

Xia Jiang, David E Hintenlang, Richard D White

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Harnessing dual-energy CT for glycogen quantification: a phantom analysis.Quantitative imaging in medicine and surgery · 2023
    Article
  4. Spectral CT: Current Liver Applications.Diagnostics (Basel, Switzerland) · 2023
    Review
  5. Review
  6. Quantitative dual-energy CT techniques in the abdomen.Abdominal radiology (New York) · 2022
    Review
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.

Xia JiangDepartment of Radiology, Ohio State University College of Medicine, Columbus, OH, USA.
David E HintenlangDepartment of Radiology, Ohio State University College of Medicine, Columbus, OH, USA.
Richard D WhiteDepartment of Radiology, Ohio State University College of Medicine, Columbus, OH, USA.

Funding

Siemens Medical Solutions USA, inc. #00051796
6 · The paper itself

Abstract

purposeDual-energy computed tomography (DECT) has been proposed for quantification of hepatic iron concentration (IC). However, the lower limit of quantification (LLOQ) has not been established, limiting the clinical adoption of this technology. In this study, we aim to (a) establish the LLOQ using phantoms and (b) investigate the effects of patient size, dose level, energy combination, and reconstruction method.

methodsThree phantom sizes and eight vials of ferric nitrate solution with IC ranging from 0 to 10 mg/ml were used. DECT scans were performed at 80/140 and 100/140Sn kVp, and using five different levels of CT dose index (CTDI). An image-domain three-material-decomposition algorithm was used to calculate the IC. The LLOQ was determined based on the coefficient of variation from repeated measurements.

resultsThe measured IC correlated strongly with the true IC in the small and medium phantoms (R

conclusionIron quantification at clinically important levels was achieved in a small- and a medium-sized phantom using DECT, but proved challenging in a large phantom. Wide spectral separation and accurate calibration were found to be critical to the success of the technology.

Indexed as

IodineIronAlgorithmsHumansPhantoms, ImagingTomography, X-Ray ComputedIodineIrondual-energy CTiron overloadlower limit of quantificationthree-material-decomposition

Identifiers

PMID33369002
PMCPMC7856509

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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.