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Determination of iodine detectability in different types of multiple-energy images for a photon-counting detector computed tomography system

Determination of iodine detectability in different types of multiple-energy images for a... Abstract.In addition to low-energy-threshold images (TLIs), photon-counting detector (PCD) computed tomography (CT) can generate virtual monoenergetic images (VMIs) and iodine maps. Our study sought to determine the image type that maximizes iodine detectability. Adult abdominal phantoms with iodine inserts of various concentrations and lesion sizes were scanned on a PCD-CT system. TLIs, VMIs at 50 keV, and iodine maps were generated, and iodine contrast-to-noise ratio (CNR) was measured. A channelized Hotelling observer was used to determine the area under the receiver-operating-characteristic curve (AUC) for iodine detectability. Iodine map CNR (0.57  ±  0.42) was significantly higher (P  <  0.05) than for TLIs (0.46  ±  0.26) and lower (P  <  0.001) than for VMIs at 50 keV (0.74  ±  0.33) for 0.5 mgI/cc and a 35-cm phantom. For the same condition and an 8-mm lesion, iodine detectability from iodine maps (AUC  =  0.95  ±  0.01) was significantly lower (P  <  0.001) than both TLIs (AUC  =  0.99  ±  0.00) and VMIs (AUC  =  0.99  ±  0.01). VMIs at 50 keV had similar detectability to TLIs and both outperformed iodine maps. The lowest detectable iodine concentration was 0.5 mgI/cc for an 8-mm lesion and 1.0 mgI/cc for a 4-mm lesion. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Medical Imaging SPIE

Determination of iodine detectability in different types of multiple-energy images for a photon-counting detector computed tomography system

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Publisher
SPIE
Copyright
© 2019 Society of Photo-Optical Instrumentation Engineers (SPIE)
ISSN
2329-4302
eISSN
2329-4310
DOI
10.1117/1.JMI.6.4.043501
Publisher site
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Abstract

Abstract.In addition to low-energy-threshold images (TLIs), photon-counting detector (PCD) computed tomography (CT) can generate virtual monoenergetic images (VMIs) and iodine maps. Our study sought to determine the image type that maximizes iodine detectability. Adult abdominal phantoms with iodine inserts of various concentrations and lesion sizes were scanned on a PCD-CT system. TLIs, VMIs at 50 keV, and iodine maps were generated, and iodine contrast-to-noise ratio (CNR) was measured. A channelized Hotelling observer was used to determine the area under the receiver-operating-characteristic curve (AUC) for iodine detectability. Iodine map CNR (0.57  ±  0.42) was significantly higher (P  <  0.05) than for TLIs (0.46  ±  0.26) and lower (P  <  0.001) than for VMIs at 50 keV (0.74  ±  0.33) for 0.5 mgI/cc and a 35-cm phantom. For the same condition and an 8-mm lesion, iodine detectability from iodine maps (AUC  =  0.95  ±  0.01) was significantly lower (P  <  0.001) than both TLIs (AUC  =  0.99  ±  0.00) and VMIs (AUC  =  0.99  ±  0.01). VMIs at 50 keV had similar detectability to TLIs and both outperformed iodine maps. The lowest detectable iodine concentration was 0.5 mgI/cc for an 8-mm lesion and 1.0 mgI/cc for a 4-mm lesion.

Journal

Journal of Medical Imaging – SPIE

Published: Oct 1, 2019

Keywords: iodine detectability; iodine maps; virtual monoenergetic images; photon-counting detector computed tomography; channelized Hotelling observer

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