Evidence map›Paper›PMID 33468186›Full record

ArticleTrials2021

In silico imaging clinical trials: cheaper, faster, better, safer, and more scalable.

Aldo Badano

Abstract readLetter
In one paragraph

Article in Trials, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Survey of Deep Learning and Physics-Based Approaches in Computational Wave Imaging.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2025
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Toward Uncertainty-Aware Hemolysis Modeling: A Universal Approach to Address Experimental Variance.International journal for numerical methods in biomedical engineering · 2025
    Article
  10. Review
  11. Article
  12. Journal of medical imaging (Bellingham, Wash.) · 2025
    Article
  13. The emerging challenge ofClinical microbiology reviews · 2024
    Review
  14. Review
  15. Article
  16. Monte Carlo methods for medical imaging research.Biomedical engineering letters · 2024
    Review
  17. Article
  18. Review
  19. Toward trustworthy medical deviceFrontiers in medicine · 2024
    Article
  20. 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

1 author.

Aldo BadanoDivision of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA. aldo.badano@fda.hhs.gov.ORCID http://orcid.org/0000-0003-3712-6670

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Imaging clinical trials can be burdensome and often delay patient access to novel, high-quality medical devices. Tools for in silico imaging trials have significantly improved in sophistication and availability. Here, I describe some of the principal advantages of in silico imaging trials and enumerate five lessons learned during the design and execution of the first all-in silico virtual imaging clinical trial for regulatory evaluation (the VICTRE study).

Indexed as

Diagnostic ImagingComputer SimulationHumansComputational modelingIn silico trialsRegulatory evaluation

Identifiers

PMID33468186
PMCPMC7814719

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.