Evidence map›Paper›PMID 35455668›Full record

ArticleJournal of personalized medicine2022

CT Reconstruction Kernels and the Effect of Pre- and Post-Processing on the Reproducibility of Handcrafted Radiomic Features.

Turkey Refaee, Zohaib Salahuddin, Yousif Widaatalla, Sergey Primakov, Henry C Woodruff, Roland Hustinx, Felix M Mottaghy, Abdalla Ibrahim, Philippe Lambin

Abstract read
In one paragraph

Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. 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

9 authors.

Turkey RefaeeThe D-Lab, Department of Precision Medicine, GROW-School for Oncology, Maastricht University, 6200 Maastricht, The Netherlands.ORCID 0000-0001-6605-1845
Zohaib SalahuddinThe D-Lab, Department of Precision Medicine, GROW-School for Oncology, Maastricht University, 6200 Maastricht, The Netherlands.
Yousif WidaatallaThe D-Lab, Department of Precision Medicine, GROW-School for Oncology, Maastricht University, 6200 Maastricht, The Netherlands.
Sergey PrimakovThe D-Lab, Department of Precision Medicine, GROW-School for Oncology, Maastricht University, 6200 Maastricht, The Netherlands.
Henry C WoodruffThe D-Lab, Department of Precision Medicine, GROW-School for Oncology, Maastricht University, 6200 Maastricht, The Netherlands.ORCID 0000-0001-7911-5123
Roland HustinxDivision of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, University Hospital of Liege and GIGA CRC-In Vivo Imaging, University of Liege, 4000 Liege, Belgium.
Felix M MottaghyDepartment of Radiology and Nuclear Medicine, Maastricht University Medical Center, 6200 Maastricht, The Netherlands.
Abdalla IbrahimThe D-Lab, Department of Precision Medicine, GROW-School for Oncology, Maastricht University, 6200 Maastricht, The Netherlands.ORCID 0000-0003-4138-5755
Philippe LambinThe D-Lab, Department of Precision Medicine, GROW-School for Oncology, Maastricht University, 6200 Maastricht, The Netherlands.ORCID 0000-0001-7961-0191

Funding

Dutch Cancer Society 12085/2018-2European Research Council 101034347European Research Council ERC-ADG-2015 694812H2020 European Research Council 733008H2020 European Research Council 766276H2020 European Research Council 952013H2020 European Research Council 952172TRANSCAN Joint Transnational Call 2016 UM 2017-8295
6 · The paper itself

Abstract

Handcrafted radiomics features (HRFs) are quantitative features extracted from medical images to decode biological information to improve clinical decision making. Despite the potential of the field, limitations have been identified. The most important identified limitation, currently, is the sensitivity of HRF to variations in image acquisition and reconstruction parameters. In this study, we investigated the use of Reconstruction Kernel Normalization (RKN) and ComBat harmonization to improve the reproducibility of HRFs across scans acquired with different reconstruction kernels. A set of phantom scans (

Indexed as

ComBat harmonizationimage harmonizationradiomics reproducibilityreconstruction kernel

Identifiers

PMID35455668
PMCPMC9030848

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.