Evidence map›Paper›PMID 33481143›Full record

ArticleJournal of digital imaging2021

The Importance of Body Part Labeling to Enable Enterprise Imaging: A HIMSS-SIIM Enterprise Imaging Community Collaborative White Paper.

Alexander J Towbin, Christopher J Roth, Cheryl A Petersilge, Kimberley Garriott, Kenneth A Buckwalter, David A Clunie

Open access · hybridAbstract readConsensus Statement
In one paragraph

Article in Journal of digital imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.5field-weighted citation impact, top 9% 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

17 citing papers in PubMed, 21 citations in OpenAlex.

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  4. Implementing a Photodocumentation Program.Journal of imaging informatics in medicine · 2025
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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

6 authors at 5 institutions in 1 country.

Alexander J TowbinDepartment of Radiology, Cincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, OH, USA. alexander.towbin@cchmc.org.
Christopher J RothDepartment of Radiology, Duke University Medical Center, Durham, NC, USA.
Cheryl A PetersilgeDepartment of Radiology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Kimberley GarriottNetApp Global Healthcare, CA, Sunnyvale, USA.
Kenneth A BuckwalterDepartment of Radiology, University of Michigan School of Medicine, Ann Arbor, MI, USA.
David A CluniePixelmed Publishing, LLC, Bangor, PA, USA.
Duke Medical Center · USNetApp (United States) · USUniversity of Cincinnati Medical Center · USUniversity of Michigan–Ann Arbor · USUniversity of Pittsburgh Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order for enterprise imaging to be successful across a multitude of specialties, systems, and sites, standards are essential to categorize and classify imaging data. The HIMSS-SIIM Enterprise Imaging Community believes that the Digital Imaging Communications in Medicine (DICOM) Anatomic Region Sequence, or its equivalent in other data standards, is a vital data element for this role, when populated with standard coded values. We believe that labeling images with standard Anatomic Region Sequence codes will enhance the user's ability to consume data, facilitate interoperability, and allow greater control of privacy. Image consumption-when a user views a patient's images, he or she often wants to see relevant comparison images of the same lesion or anatomic region for the same patient automatically presented. Relevant comparison images may have been acquired from a variety of modalities and specialties. The Anatomic Region Sequence data element provides a basis to allow for efficient comparison in both instances. Interoperability-as patients move between health care systems, it is important to minimize friction for data transfer. Health care providers and facilities need to be able to consume and review the increasingly large and complex volume of data efficiently. The use of Anatomic Region Sequence, or its equivalent, populated with standard values enables seamless interoperability of imaging data regardless of whether images are used within a site or across different sites and systems. Privacy-as more visible light photographs are integrated into electronic systems, it becomes apparent that some images may need to be sequestered. Although additional work is needed to protect sensitive images, standard coded values in Anatomic Region Sequence support the identification of potentially sensitive images, enable facilities to create access control policies, and can be used as an interim surrogate for more sophisticated rule-based or attribute-based access control mechanisms. To satisfy such use cases, the HIMSS-SIIM Enterprise Imaging Community encourages the use of a pre-existing body part ontology. Through this white paper, we will identify potential challenges in employing this standard and provide potential solutions for these challenges.

Indexed as

Electronic Health RecordsMedicineDiagnostic ImagingHuman BodyHumansDICOMEnterprise ImagingMedical PhotographyOntologyPhoto documentationStandards

Identifiers

PMID33481143
PMCPMC7887098
OpenAlexW3122115023

What Socratic 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 Socratic graph.