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• W4386624666 abstract "In radiography, much valuable associated data (metadata) is generated during image acquisition. The current setup of picture archive and communication systems (PACS) can make extraction of this metadata difficult, especially as it is typically stored with the image. The aim of this work is to examine the current challenges in extracting image metadata and to discuss the potential benefits of using this rich information. This work focuses on breast screening, though the conclusions are applicable to other modalities.The data stored in PACS contain information, currently underutilised, and is of great benefit for auditing and improving imaging and radiographic practice. From the literature, we present examples of the potential clinical benefit such as audits of dose, and radiographic practice, as well as more advanced research highlighting the effects of radiographic practice, e.g. cancer detection rates affected by imaging technology.This review considers the challenges in extracting data, namely,• The search tools for data on most PACS are inadequate being both time-consuming and limited in elements that can be searched.• Security and information governance considerations• Anonymisation of data if required• Data curationThe review describes some solutions that have been successfully implemented.• Retrospective extraction: direct query on PACS• Extracting data prospectively• Use of structured reports• Use of trusted research environmentsUltimately, the data access process will be made easier by inclusion during PACS procurement. Auditing data from PACS can be used to improve quality of imaging and workflow, all of which will be a clinical benefit to patients." @default.
• W4386624666 created "2023-09-13" @default.
• W4386624666 creator A5008383476 @default.
• W4386624666 creator A5013056764 @default.
• W4386624666 creator A5080910385 @default.
• W4386624666 date "2023-09-12" @default.
• W4386624666 modified "2023-10-18" @default.
• W4386624666 title "Successes and challenges in extracting information from DICOM image databases for audit and research" @default.
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• W4386624666 doi "https://doi.org/10.1259/bjr.20230104" @default.
• W4386624666 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37698251" @default.
• W4386624666 hasPublicationYear "2023" @default.
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