Literature DB >> 21357413

Informatics in radiology: automated structured reporting of imaging findings using the AIM standard and XML.

Stefan L Zimmerman1, Woojin Kim, William W Boonn.   

Abstract

Quantitative and descriptive imaging data are a vital component of the radiology report and are frequently of paramount importance to the ordering physician. Unfortunately, current methods of recording these data in the report are both inefficient and error prone. In addition, the free-text, unstructured format of a radiology report makes aggregate analysis of data from multiple reports difficult or even impossible without manual intervention. A structured reporting work flow has been developed that allows quantitative data created at an advanced imaging workstation to be seamlessly integrated into the radiology report with minimal radiologist intervention. As an intermediary step between the workstation and the reporting software, quantitative and descriptive data are converted into an extensible markup language (XML) file in a standardized format specified by the Annotation and Image Markup (AIM) project of the National Institutes of Health Cancer Biomedical Informatics Grid. The AIM standard was created to allow image annotation data to be stored in a uniform machine-readable format. These XML files containing imaging data can also be stored on a local database for data mining and analysis. This structured work flow solution has the potential to improve radiologist efficiency, reduce errors, and facilitate storage of quantitative and descriptive imaging data for research.
Copyright © RSNA, 2011.

Mesh:

Year:  2011        PMID: 21357413     DOI: 10.1148/rg.313105195

Source DB:  PubMed          Journal:  Radiographics        ISSN: 0271-5333            Impact factor:   5.333


  16 in total

1.  Towards a repository for standardized medical image and signal case data annotated with ground truth.

Authors:  Thomas M Deserno; Petra Welter; Alexander Horsch
Journal:  J Digit Imaging       Date:  2012-04       Impact factor: 4.056

Review 2.  Imaging informatics: essential tools for the delivery of imaging services.

Authors:  David S Mendelson; Daniel L Rubin
Journal:  Acad Radiol       Date:  2013-10       Impact factor: 3.173

3.  Visual Interpretation with Three-Dimensional Annotations (VITA): three-dimensional image interpretation tool for radiological reporting.

Authors:  Sharmili Roy; Michael S Brown; George L Shih
Journal:  J Digit Imaging       Date:  2014-02       Impact factor: 4.056

4.  Strategies for radiology reporting and communication : part 2: using visual imagery for enhanced and standardized communication.

Authors:  Bruce I Reiner
Journal:  J Digit Imaging       Date:  2013-10       Impact factor: 4.056

5.  Ontology-based image navigation: exploring 3.0-T MR neurography of the brachial plexus using AIM and RadLex.

Authors:  Kenneth C Wang; Aditya R Salunkhe; James J Morrison; Pearlene P Lee; José L V Mejino; Landon T Detwiler; James F Brinkley; Eliot L Siegel; Daniel L Rubin; John A Carrino
Journal:  Radiographics       Date:  2015 Jan-Feb       Impact factor: 5.333

6.  Informatics in radiology: improving clinical work flow through an AIM database: a sample web-based lesion tracking application.

Authors:  Aaron C Abajian; Mia Levy; Daniel L Rubin
Journal:  Radiographics       Date:  2012-06-27       Impact factor: 5.333

7.  Electronic Medical Record Integration for Streamlined DXA Reporting.

Authors:  Jason Wachsmann; Kyle Blain; Mathew Thompson; Solomon Cherian; Orhan K Oz; Travis Browning
Journal:  J Digit Imaging       Date:  2018-04       Impact factor: 4.056

Review 8.  Multimedia-enhanced Radiology Reports: Concept, Components, and Challenges.

Authors:  Les R Folio; Laura B Machado; Andrew J Dwyer
Journal:  Radiographics       Date:  2018 Mar-Apr       Impact factor: 5.333

9.  ENABLE (Exportable Notation and Bookmark List Engine): an Interface to Manage Tumor Measurement Data from PACS to Cancer Databases.

Authors:  Nikhil Goyal; Andrea B Apolo; Eliana D Berman; Mohammad Hadi Bagheri; Jason E Levine; John W Glod; Rosandra N Kaplan; Laura B Machado; Les R Folio
Journal:  J Digit Imaging       Date:  2017-06       Impact factor: 4.056

10.  Automated tracking of quantitative assessments of tumor burden in clinical trials.

Authors:  Daniel L Rubin; Debra Willrett; Martin J O'Connor; Cleber Hage; Camille Kurtz; Dilvan A Moreira
Journal:  Transl Oncol       Date:  2014-02-01       Impact factor: 4.243

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