Literature DB >> 25700615

We Built This House; It's Time to Move in: Leveraging Existing DICOM Structure to More Completely Utilize Readily Available Detailed Contrast Administration Information.

Jeffrey D Hirsch1, Eliot L Siegel, Sridhar Balasubramanian, Kenneth C Wang.   

Abstract

The Digital Imaging and Communications in Medicine (DICOM) standard is the universal format for interoperability in medical imaging. In addition to imaging data, DICOM has evolved to support a wide range of imaging metadata including contrast administration data that is readily available from many modern contrast injectors. Contrast agent, route of administration, start and stop time, volume, flow rate, and duration can be recorded using DICOM attributes [1]. While this information is sparsely and inconsistently recorded in routine clinical practice, it could potentially be of significant diagnostic value. This work will describe parameters recorded by automatic contrast injectors, summarize the DICOM mechanisms available for tracking contrast injection data, and discuss the role of such data in clinical radiology.

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Year:  2015        PMID: 25700615      PMCID: PMC4501949          DOI: 10.1007/s10278-015-9771-y

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  9 in total

1.  Suspected pulmonary embolism: enhancement of pulmonary arteries at deep-inspiration CT angiography--influence of patent foramen ovale and atrial-septal defect.

Authors:  Christine B Henk; Stephan Grampp; Kenneth F Linnau; Majda M Thurnher; Christian Czerny; Christian J Herold; Gerhard H Mostbeck
Journal:  Radiology       Date:  2003-01-15       Impact factor: 11.105

2.  Contrast dynamics during CT pulmonary angiogram: analysis of an inspiration associated artifact.

Authors:  Marc V Gosselin; Ulrich A Rassner; Sheldon L Thieszen; Jinnah Phillips; Allison Oki
Journal:  J Thorac Imaging       Date:  2004-01       Impact factor: 3.000

3.  RADIANCE: An automated, enterprise-wide solution for archiving and reporting CT radiation dose estimates.

Authors:  Tessa S Cook; Stefan L Zimmerman; Scott R Steingall; Andrew D A Maidment; Woojin Kim; William W Boonn
Journal:  Radiographics       Date:  2011-10-03       Impact factor: 5.333

Review 4.  Intravenous contrast medium administration and scan timing at CT: considerations and approaches.

Authors:  Kyongtae T Bae
Journal:  Radiology       Date:  2010-07       Impact factor: 11.105

5.  Comparison of enhancement, image quality, cost, and adverse reactions using 2 different contrast medium concentrations for routine chest CT on 16-slice MDCT.

Authors:  Bindu N Setty; Dushyant V Sahani; Kathy Ouellette-Piazzo; Peter F Hahn; Jo-Anne O Shepard
Journal:  J Comput Assist Tomogr       Date:  2006 Sep-Oct       Impact factor: 1.826

6.  Patient-tailored scan delay for multiphase liver CT: improved scan quality and lesion conspicuity with a novel timing bolus method.

Authors:  J Gabriel Schneider; Zhen J Wang; Wilbur Wang; Judy Yee; Yanjun Fu; Benjamin M Yeh
Journal:  AJR Am J Roentgenol       Date:  2014-02       Impact factor: 3.959

7.  Prospective study of access site complications of automated contrast injection with peripheral venous access in MDCT.

Authors:  Susanne Wienbeck; Roman Fischbach; Stephan P Kloska; Peter Seidensticker; Noriaki Osada; Walter Heindel; Kai U Juergens
Journal:  AJR Am J Roentgenol       Date:  2010-10       Impact factor: 3.959

Review 8.  Iodinated contrast injection data from a new technology.

Authors:  Frank J Rybicki; Kathleen Piazzo; Richard Prior; Nicole Wake; Karin E Dill
Journal:  Radiol Technol       Date:  2012 Nov-Dec

9.  Comparison of dual-syringe and syringeless power injectors in outpatient MDCT practice: impact on the operator's performance, CT workflow, and operation cost.

Authors:  Xiaozhou Ma; Anand Singh; Joseph Fay; Giles Boland; Dushyant V Sahani
Journal:  J Am Coll Radiol       Date:  2012-08       Impact factor: 5.532

  9 in total
  2 in total

1.  DeepDicomSort: An Automatic Sorting Algorithm for Brain Magnetic Resonance Imaging Data.

Authors:  Sebastian R van der Voort; Marion Smits; Stefan Klein
Journal:  Neuroinformatics       Date:  2021-01

2.  Automated detection of the contrast phase in MDCT by an artificial neural network improves the accuracy of opportunistic bone mineral density measurements.

Authors:  Sebastian Rühling; Fernando Navarro; Anjany Sekuboyina; Malek El Husseini; Thomas Baum; Bjoern Menze; Rickmer Braren; Claus Zimmer; Jan S Kirschke
Journal:  Eur Radiol       Date:  2021-10-23       Impact factor: 5.315

  2 in total

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