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CT-Based Quantification

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Computed Tomography

Abstract

Image quantification is the extraction of quantitative measures from patient images and the relation of the quantitative measures to patient outcomes. For an image quantification to be most effective, it should meet four requirements of (1) relevance, (2) objectivity, (3) robustness, and (4) implementability. A relevant quantification assigns a number to an observable biological or clinical phenomenon. An objective quantification measures the phenomenon accurately. A robust quantification measures the phenomenon precisely. An implementable quantification is one which can be implemented in a timely fashion in a clinical environment and workflow. Relevance can be assessed by studying how the quantification metrics correlate with clinical patient outcomes. Objectivity and robustness can be assessed using phantoms and biological models to test how different feature extraction workflows lead to different biases and variabilities in the feature measurements. The implementation of quantification in a clinical environment should be such that it is automated, intuitive, and efficient. CT-based quantification has the potential to improve consistency and quality of patient care if it is applied using these principles.

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Author information

Authors and Affiliations

  1. Department of Radiology, Duke University, Durham, NC, USA

    Ehsan Samei

  2. Carl E. Ravin Advanced Imaging Laboratories (RAI Labs) and Medical Physics Graduate Program, Department of Radiology, Duke University, Durham, NC, USA

    Jocelyn Hoye

Authors
  1. Ehsan Samei
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  2. Jocelyn Hoye
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Corresponding author

Correspondence to Ehsan Samei .

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Editors and Affiliations

  1. Department of Radiology, Duke University, Durham, NC, USA

    Ehsan Samei

  2. Department of Bioengineering and Radiology, Stanford University, Stanford, CA, USA

    Norbert J. Pelc

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Samei, E., Hoye, J. (2020). CT-Based Quantification. In: Samei, E., Pelc, N. (eds) Computed Tomography . Springer, Cham. https://doi.org/10.1007/978-3-030-26957-9_15

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  • DOI: https://doi.org/10.1007/978-3-030-26957-9_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26956-2

  • Online ISBN: 978-3-030-26957-9

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