Summary
DICOM conformance means an imaging file follows the rules of the DICOM (Digital Imaging and Communications in Medicine) standard, both in how it is structured and in which identification tags it carries. In veterinary imaging, the identification side is where it breaks down. A survey of 488 referral studies from 115 German veterinary institutions found 5.1% fully complied with the veterinary identification tags. Species, breed, and owner information are frequently absent or in the wrong field, which costs you at referral and at retrieval.
Key facts
- Brühschwein and colleagues analyzed 488 veterinary imaging studies from 115 institutions in Germany, collected between 2002 and 2015, and found 5.1% fully complied with the recommended veterinary identification tags (J Digit Imaging. 2018;31(1):13-18).
- The gap is in how the veterinary tags are populated, not in whether the file is valid DICOM. Commonly available imaging equipment is generally conformant at the structural level.
- Keystone PACS archives every study off-site for 7 years with automated integrity checks. NewLumen applies species-aware hanging protocols and a multi-tenant teleradiology worklist. Both are Asteris products, and both depend on those tags being populated at acquisition.
- Storage and verified storage are not the same thing.
What does DICOM conformance actually mean in veterinary imaging?
There are two layers, and they fail for different reasons.
The first is structural. Required data elements are present, the file is encoded correctly, and series are organized the way any conformant system expects. Most veterinary imaging equipment handles this adequately, because it inherits the implementation from human medicine.
The second is identification, and this is where veterinary imaging diverges. In 2006 the DICOM Standards Committee added veterinary identification tags to the DICOM standard for exactly this reason: a veterinary patient has a species, a breed, a responsible person, and often a name shared with a dozen other patients in the same practice.
The recommendations are specific. The patient name field was built for human names in five components, so the guidance is to combine the responsible person's family name with the animal's given name rather than the animal's name alone. The microchip number belongs in the other patient ID field. Species and breed have their own coded fields.
When those tags go unused, or hold whatever the modality defaults to, the file is still readable. It has just lost the context that makes it useful outside your building. Both layers matter. Only one has a number attached to it.
How common is the problem, and what does the evidence actually show?
The measurement comes from a 2018 study in the Journal of Digital Imaging. Brühschwein, Klever, Wilkinson and Meyer-Lindenberg ran a computer-aided readout of DICOM headers from 488 referral studies at 115 veterinary institutions in Germany. Of those, 25 studies, or 5.1%, fully complied with the veterinary identification tags. The authors concluded the committee's recommendations had found minimal acceptance in the sample.
Read the scope carefully, because it is often stated more broadly than it deserves. The study measured whether the veterinary identification tags were correctly used. It did not measure whether files opened, images rendered, or studies survived transfer, and "fully complied" was a strict bar.
So the evidence supports that veterinary identification metadata is poorly and inconsistently populated, which the authors link to weaker interoperability. It does not support the claim that most veterinary DICOM files are broken. Treating those as one problem leads practices to check the wrong thing.
Why does weak identification metadata cause problems at referral and retrieval?
Because the metadata is what lets a system outside yours know what it is looking at.
At referral, the receiving practice imports your study into their own veterinary PACS. If the patient name field holds a modality default, if species is absent, or if owner and patient are conflated, the specialist reads with less context than the case deserves. They may email back for basics, or note the gap in the report. Both cost time, and both are worth factoring into how you set up sharing veterinary images.
At retrieval, the gap compounds. Three years later a patient returns and the practice looks for the prior study. If the identifiers are inconsistent, the prior may be there and still not be findable, because nothing links it reliably to the patient in front of you.
There is a harder version, and it belongs to the structural layer. A study is acquired, the local machine is later replaced or fails, and the practice goes to recall the study. The file reference exists. The study never finished archiving. Nobody knew, because nothing had checked. That is why transfer and storage confirmation is worth understanding separately.
What should you check in your own archive?
You do not need to audit every file. Four checks will tell you most of what you need to know.
Review your PACS import logs. A cluster of failures traced to one modality, one export path, or one referral source points at a fixable problem at the origin rather than a general condition of your archive.
Look at the patient name field on your worklist. Check whether it carries the responsible person's family name alongside the animal's name, or the animal's name alone. If it is the latter, the rest of the veterinary tags are almost certainly empty too.
Ask your referral partners directly. Specialists and teleradiology services see incomplete metadata constantly and work around it silently, because the workaround takes less time than the conversation.
Ask your vendor whether the archive verifies what it stores. The question is whether the system runs automated integrity checks on archived studies, or only confirms a file was written.
If you are evaluating systems rather than auditing one you run, veterinary PACS vs generic medical PACS covers the wider question set.
How does Asteris handle this across Keystone PACS and NewLumen?
Two products, two different halves of the same problem.
Keystone PACS treats archival as a verified transaction rather than a file copy. The proprietary transfer protocol manages the move from local capture to off-site archival, so a study that does not transfer completely is not recorded as though it did. Every study is archived off-site for 7 years, and automated integrity checks confirm the full study arrived, not most of it.
NewLumen, Asteris's cloud-native veterinary imaging platform, meets the metadata question from the other direction. Its hanging protocols are species-aware and its teleradiology worklist is multi-tenant, so studies from many clinics arrive in one queue. A study without a species tag cannot have a species-aware protocol applied, and inconsistent identification is harder to sort in a shared worklist than a single-site one.
Neither product can invent a species tag that was never entered at the modality. Nothing downstream can. What they address is the half of the problem after acquisition, and that half matters more as workflow moves off a single site, not less.
To see how capture, review, sharing, and archival fit together across a working day, start with the Keystone PACS overview.
FAQ
What is DICOM conformance in veterinary imaging?
DICOM conformance means an imaging file follows the rules of the DICOM standard, both structurally and in the identification tags it carries. The veterinary tags cover species, breed, and responsible person, which the human patient model does not need. A file can be structurally valid DICOM and still lack the veterinary identification data a referral partner needs.
How common is poor DICOM conformance in veterinary practices?
A 2018 study in the Journal of Digital Imaging analyzed 488 referral studies from 115 German veterinary institutions and found 5.1% fully complied with the recommended veterinary identification tags. The sample covered studies collected between 2002 and 2015. The finding concerns identification metadata specifically, not whether files were structurally valid or could be opened.
Does poor conformance mean my DICOM files are broken?
Usually not. Most veterinary imaging equipment produces structurally valid DICOM, because that layer is inherited from human medicine. The common failure is that veterinary identification tags go unpopulated or hold modality defaults. The file opens, but reaches a referral partner without the species, breed, or owner context the specialist needs.
Does moving to a cloud platform fix DICOM metadata problems?
No. Identification tags are written at acquisition, so no downstream platform can supply a species tag that was never entered. What changes is the cost of the gap. Cloud and teleradiology workflows put studies from many sources into shared queues, where consistent patient identification does more work than inside a single practice.
What is an archival integrity check?
An archival integrity check is an automated verification that a stored study is complete and retrievable, not merely that a file exists at the storage location. Without it, an archive can hold references to studies that never finished transferring. Keystone PACS runs these checks on studies in its 7-year off-site archive.
Sources
Brühschwein A, Klever J, Wilkinson T Jr, Meyer-Lindenberg A. DICOM Standard Conformance in Veterinary Medicine in Germany: a Survey of Imaging Studies in Referral Cases. J Digit Imaging. 2018 Feb;31(1):13-18. doi:10.1007/s10278-017-9998-x. Free full text via PubMed.
DICOM Standards Committee. Veterinary identification tags (PS 3.3, 3.5, 3.6, 3.16). National Electrical Manufacturers Association, 2006. Change proposal CP-643.