Computed tomography volume measurements of the liver using a liver segmentation and analysis package: an intra- and inter-rater reliability study

Childs, Jessie T., Thoirs, Kerry A., and Esterman, Adrian J. (2015) Computed tomography volume measurements of the liver using a liver segmentation and analysis package: an intra- and inter-rater reliability study. Journal of Biomedical Graphics and Computing, 5 (2). pp. 17-22.

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Abstract

Introduction: Recent advances in technology have seen the introduction of software assisted image post-processing (SAIP)tools to calculate the volume of the liver from Computed Tomography (CT) images. One such SAIP tool is the semi-automate dPhilips liver segmentation and analysis package (Endhoven, The Netherlands). The intra- and inter-rater reliability of the liver volumes of 16 participants calculated using this tool was assessed.

Methods: Two CT Technologists accessed Abdominal CT data sets and calculated the volume of the liver using the Philips liver segmentation and analysis package. One technologist repeated their calculation.

Results: Results demonstrated high intra-rater reliability (ICC 0.9997) and high inter-rater reliability (ICC 0.99994). Analysis with Bland Altman plots showed the mean bias for both intra- and inter-rater reliability to be close to zero with acceptable limits of agreement.

Conclusions: This study has shown that liver volume measurements using the Philips SAIP (Endhoven, The Netherlands) can betaken reliably by CT technologists, with confidence that the same results would be obtained between different CT technologists.

Item ID: 46234
Item Type: Article (Research - C1)
ISSN: 1925-4008
Keywords: computed tomography, liver, reliability, software assisted image post-processing, volume
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© Sciedu Press. This work is licensed under a Creative Commons Attribution 3.0 License.

Date Deposited: 21 Dec 2016 03:36
FoR Codes: 11 MEDICAL AND HEALTH SCIENCES > 1103 Clinical Sciences > 110307 Gastroenterology and Hepatology @ 100%
SEO Codes: 92 HEALTH > 9202 Health and Support Services > 920203 Diagnostic Methods @ 100%
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