Evidence map›Paper›PMID 26001521›Full record

ArticleJournal of digital imaging2015

DICOM for Clinical Research: PACS-Integrated Electronic Data Capture in Multi-Center Trials.

Daniel Haak, Charles-E Page, Sebastian Reinartz, Thilo Krüger, Thomas M Deserno

Abstract read
In one paragraph

Article in Journal of digital imaging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. 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

5 authors.

Daniel HaakDepartment of Medical Informatics, Uniklinik RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Germany. dhaak@mi.rwth-aachen.de.
Charles-E PageDepartment of Medical Informatics, Uniklinik RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Germany.
Sebastian ReinartzDepartment of Diagnostic and Interventional Radiology, Uniklinik RWTH Aachen, Pauwelsstr. 30, Aachen, 52074, Germany.
Thilo KrügerDepartment of Cardiology, Uniklinik RWTH Aachen, Pauwelsstr. 30, Aachen, 52074, Germany.
Thomas M DesernoDepartment of Medical Informatics, Uniklinik RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Providing surrogate endpoints in clinical trials, medical imaging has become increasingly important in human-centered research. Nowadays, electronic data capture systems (EDCS) are used but binary image data is integrated insufficiently. There exists no structured way, neither to manage digital imaging and communications in medicine (DICOM) data in EDCS nor to interconnect EDCS with picture archiving and communication systems (PACS). Manual detours in the trial workflow yield errors, delays, and costs. In this paper, requirements for a DICOM-based system interconnection of EDCS and research PACS are analysed. Several workflow architectures are compared. Optimized for multi-center trials, we propose an entirely web-based solution integrating EDCS, PACS, and DICOM viewer, which has been implemented using the open source projects OpenClinica, DCM4CHEE, and Weasis, respectively. The EDCS forms the primary access point. EDCS to PACS interchange is integrated seamlessly on the data and the context levels. DICOM data is viewed directly from the electronic case report form (eCRF), while PACS-based management is hidden from the user. Data privacy is ensured by automatic de-identification and re-labelling with study identifiers. Our concept is evaluated on a variety of 13 DICOM modalities and transfer syntaxes. We have implemented the system in an ongoing investigator-initiated trial (IIT), where five centers have recruited 24 patients so far, performing decentralized computed tomography (CT) screening. Using our system, the chief radiologist is reading DICOM data directly from the eCRF. Errors and workflow processing time are reduced. Furthermore, an imaging database is built that may support future research.

Indexed as

Multicenter Studies as TopicRadiology Information SystemsSystems IntegrationTomography, X-Ray ComputedHumansWorkflowClinical trialDigital Imaging and Communications in Medicine (DICOM)Open sourcePACSSystems integrationWorkflow

Identifiers

PMID26001521
PMCPMC4570903

What OpenQuestion holds

Textmetadata
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.