Evidence map›Paper›PMID 28856413›Full record

ArticleEuropean radiology2018

Could new reconstruction CT techniques challenge MRI for the detection of brain metastases in the context of initial lung cancer staging?

Domitille Millon, David Byl, Philippe Collard, Samantha E Cambier, Aline G Van Maanen, Alain Vlassenbroek, Emmanuel E Coche

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In one paragraph

Article in European radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 20% of its field
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

3 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Article
  3. Multidisciplinary consensus statement on the clinical management of patients with stage III non-small cell lung cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2020
    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

7 authors at 3 institutions in 2 countries.

Domitille MillonDepartment of Radiology and Medical Imaging, Cliniques Universitaires Saint Luc, Université Catholique de Louvain, Avenue Hippocrate 10, 1200, Brussels, Belgium. domillon@gmail.com.ORCID http://orcid.org/0000-0002-2020-2633
David BylDepartment of Radiology and Medical Imaging, Cliniques Universitaires Saint Luc, Université Catholique de Louvain, Avenue Hippocrate 10, 1200, Brussels, Belgium.
Philippe CollardDepartment of Pneumology, Cliniques Universitaires Saint Luc, Université Catholique de Louvain, Avenue Hippocrate 10, 1200, Brussels, Belgium.
Samantha E CambierStatistic Unit, King Albert II Cancer Institute, Université Catholique de Louvain, Avenue Hippocrate 10, 1200, Brussels, Belgium.
Aline G Van MaanenStatistic Unit, King Albert II Cancer Institute, Université Catholique de Louvain, Avenue Hippocrate 10, 1200, Brussels, Belgium.
Alain VlassenbroekPhilips Healthcare, Rue des deux gares 80, 1070, Brussels, Belgium.
Emmanuel E CocheDepartment of Radiology and Medical Imaging, Cliniques Universitaires Saint Luc, Université Catholique de Louvain, Avenue Hippocrate 10, 1200, Brussels, Belgium.
Cliniques Universitaires Saint-Luc · BEde Duve Institute · BEPhilips (Belgium) · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo evaluate the diagnostic performance of brain CT images reconstructed with a model-based iterative algorithm performed at usual and reduced dose.

methods115 patients with histologically proven lung cancer were prospectively included over 15 months. Patients underwent two CT acquisitions at the initial staging, performed on a 256-slice MDCT, at standard (CTDIvol: 41.4 mGy) and half dose (CTDIvol: 20.7 mGy). Both image datasets were reconstructed with filtered back projection (FBP) and iterative model-based reconstruction (IMR) algorithms. Brain MRI was considered as the reference. Two blinded independent readers analysed the images.

resultsNinety-three patients underwent all examinations. At the standard dose, eight patients presented 17 and 15 lesions on IMR and FBP CT images, respectively. At half-dose, seven patients presented 15 and 13 lesions on IMR and FBP CT images, respectively. The test could not highlight any significant difference between the standard dose IMR and the half-dose FBP techniques (p-value = 0.12). MRI showed 46 metastases on 11 patients. Specificity, negative and positive predictive values were calculated (98.9-100 %, 93.6-94.6 %, 75-100 %, respectively, for all CT techniques).

conclusionNo significant difference could be demonstrated between the two CT reconstruction techniques. KEY POINTS: • No significant difference between IMR100 and FBP50 was shown. • Compared to FBP, IMR increased the image quality without diagnostic impairment. • A 50 % dose reduction combined with IMR reconstructions could be achieved. • Brain MRI remains the best tool in lung cancer staging.

Indexed as

Magnetic Resonance ImagingRadiographic Image Interpretation, Computer-AssistedTomography, X-Ray ComputedAdultAgedAged, 80 and overAlgorithmsBrain NeoplasmsFemaleHumansLung NeoplasmsMaleMiddle AgedNeoplasm StagingProspective StudiesSensitivity and SpecificityBrain CT with dose reductionBrain metastasesDiagnostic performanceLung cancer stagingModel-Based Iterative Reconstruction

Identifiers

PMID28856413
OpenAlexW2751011931

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Registered trials

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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.