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Magn Reson Imaging. 2012 Nov;30(9):1357-66. doi: 10.1016/j.mri.2012.04.018. Epub 2012 Jul 12.

Quantitative metrics in clinical radiology reporting: a snapshot perspective from a single mixed academic-community practice.

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Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA.


Quantitative imaging has emerged as a leading priority on the imaging research agenda, yet clinical radiology has traditionally maintained a skeptical attitude toward numerical measurement in diagnostic interpretation. To gauge the extent to which quantitative reporting has been incorporated into routine clinical radiology practice, and to offer preliminary baseline data against which the evolution of quantitative imaging can be measured, we obtained all clinical computed tomography (CT) and magnetic resonance imaging (MRI) reports from two randomly selected weekdays in 2011 at a single mixed academic-community practice and evaluated those reports for the presence of quantitative descriptors. We found that 44% of all reports contained at least one "quantitative metric" (QM), defined as any numerical descriptor of a physical property other than quantity, but only 2% of reports contained an "advanced quantitative metric" (AQM), defined as a numerical parameter reporting on lesion function or composition, excluding simple size and distance measurements. Possible reasons for the slow translation of AQMs into routine clinical radiology reporting include perceptions that the primary clinical question may be qualitative in nature or that a qualitative answer may be sufficient; concern that quantitative approaches may obscure important qualitative information, may not be adequately validated, or may not allow sufficient expression of uncertainty; the feeling that "gestalt" interpretation may be superior to quantitative paradigms; and practical workflow limitations. We suggest that quantitative imaging techniques will evolve primarily as dedicated instruments for answering specific clinical questions requiring precise and standardized interpretation. Validation in real-world settings, ease of use, and reimbursement economics will all play a role in determining the rate of translation of AQMs into broad practice.

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