Phantom Validation of Spectral Detector Computed Tomography-Derived Virtual Monoenergetic, Virtual Noncontrast, and Iodine Quantification Images

Lakshmi Ananthakrishnan, Xinhui Duan, Prabhakar Rajiah, Todd C Soesbe, Matthew A. Lewis, Yin Xi, Julia Fielding, Robert E Lenkinski, John Leyendecker, Suhny Abbara

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Abstract

PURPOSE: Spectral detector computed tomography (SDCT) is a new CT technology that uses a dual-layer detector to perform energy separation. We aim to assess 3 clinical concepts using a phantom model: noise profile across the virtual monoenergetic (VME) spectrum, accuracy of iodine quantification, and virtual noncontrast (VNC) reconstructions' ability to remove iodine contribution to attenuation. METHODS: Six vials containing varying concentrations of iodinated contrast (0-6 mg/mL) diluted in water were placed in a water bath and scanned on an SDCT scanner. Virtual monoenergetic (40-200 keV at 10-keV increments), iodine-no-water, and VNC reconstructions were created. Attenuation (in Hounsfield units [HU]), VME noise at each energy level, CT-derived iodine concentration, and VNC attenuation were recorded. RESULTS: Virtual monoenergetic noise was improved at all energies compared with conventional images (conventional, 9.8-11.2; VME, 7.5-9.5). Noise profile showed a slightly higher image noise at 40 keV, but was otherwise relatively flat across the energy spectrum. On iodine-no-water reconstructions, measured varied from actual iodine concentration by ±0.1 mg/mL (SD, 0.16-0.36). Virtual noncontrast attenuation was within 5 HU of water attenuation at all iodine concentrations. CONCLUSION: Reconstructions of SDCT show lower VME image noise, accurate iodine quantification, and VNC attenuation values within 5 HU of expected in a phantom model.

Original languageEnglish (US)
Pages (from-to)959-964
Number of pages6
JournalJournal of Computer Assisted Tomography
Volume42
Issue number6
DOIs
StatePublished - Nov 1 2018

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Iodine
Tomography
Noise
Water
X-Ray Computed Tomography Scanners
Baths
Technology

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

@article{5675a21359814cd88fa6c280b1aa5b1e,
title = "Phantom Validation of Spectral Detector Computed Tomography-Derived Virtual Monoenergetic, Virtual Noncontrast, and Iodine Quantification Images",
abstract = "PURPOSE: Spectral detector computed tomography (SDCT) is a new CT technology that uses a dual-layer detector to perform energy separation. We aim to assess 3 clinical concepts using a phantom model: noise profile across the virtual monoenergetic (VME) spectrum, accuracy of iodine quantification, and virtual noncontrast (VNC) reconstructions' ability to remove iodine contribution to attenuation. METHODS: Six vials containing varying concentrations of iodinated contrast (0-6 mg/mL) diluted in water were placed in a water bath and scanned on an SDCT scanner. Virtual monoenergetic (40-200 keV at 10-keV increments), iodine-no-water, and VNC reconstructions were created. Attenuation (in Hounsfield units [HU]), VME noise at each energy level, CT-derived iodine concentration, and VNC attenuation were recorded. RESULTS: Virtual monoenergetic noise was improved at all energies compared with conventional images (conventional, 9.8-11.2; VME, 7.5-9.5). Noise profile showed a slightly higher image noise at 40 keV, but was otherwise relatively flat across the energy spectrum. On iodine-no-water reconstructions, measured varied from actual iodine concentration by ±0.1 mg/mL (SD, 0.16-0.36). Virtual noncontrast attenuation was within 5 HU of water attenuation at all iodine concentrations. CONCLUSION: Reconstructions of SDCT show lower VME image noise, accurate iodine quantification, and VNC attenuation values within 5 HU of expected in a phantom model.",
author = "Lakshmi Ananthakrishnan and Xinhui Duan and Prabhakar Rajiah and Soesbe, {Todd C} and Lewis, {Matthew A.} and Yin Xi and Julia Fielding and Lenkinski, {Robert E} and John Leyendecker and Suhny Abbara",
year = "2018",
month = "11",
day = "1",
doi = "10.1097/RCT.0000000000000763",
language = "English (US)",
volume = "42",
pages = "959--964",
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TY - JOUR

T1 - Phantom Validation of Spectral Detector Computed Tomography-Derived Virtual Monoenergetic, Virtual Noncontrast, and Iodine Quantification Images

AU - Ananthakrishnan, Lakshmi

AU - Duan, Xinhui

AU - Rajiah, Prabhakar

AU - Soesbe, Todd C

AU - Lewis, Matthew A.

AU - Xi, Yin

AU - Fielding, Julia

AU - Lenkinski, Robert E

AU - Leyendecker, John

AU - Abbara, Suhny

PY - 2018/11/1

Y1 - 2018/11/1

N2 - PURPOSE: Spectral detector computed tomography (SDCT) is a new CT technology that uses a dual-layer detector to perform energy separation. We aim to assess 3 clinical concepts using a phantom model: noise profile across the virtual monoenergetic (VME) spectrum, accuracy of iodine quantification, and virtual noncontrast (VNC) reconstructions' ability to remove iodine contribution to attenuation. METHODS: Six vials containing varying concentrations of iodinated contrast (0-6 mg/mL) diluted in water were placed in a water bath and scanned on an SDCT scanner. Virtual monoenergetic (40-200 keV at 10-keV increments), iodine-no-water, and VNC reconstructions were created. Attenuation (in Hounsfield units [HU]), VME noise at each energy level, CT-derived iodine concentration, and VNC attenuation were recorded. RESULTS: Virtual monoenergetic noise was improved at all energies compared with conventional images (conventional, 9.8-11.2; VME, 7.5-9.5). Noise profile showed a slightly higher image noise at 40 keV, but was otherwise relatively flat across the energy spectrum. On iodine-no-water reconstructions, measured varied from actual iodine concentration by ±0.1 mg/mL (SD, 0.16-0.36). Virtual noncontrast attenuation was within 5 HU of water attenuation at all iodine concentrations. CONCLUSION: Reconstructions of SDCT show lower VME image noise, accurate iodine quantification, and VNC attenuation values within 5 HU of expected in a phantom model.

AB - PURPOSE: Spectral detector computed tomography (SDCT) is a new CT technology that uses a dual-layer detector to perform energy separation. We aim to assess 3 clinical concepts using a phantom model: noise profile across the virtual monoenergetic (VME) spectrum, accuracy of iodine quantification, and virtual noncontrast (VNC) reconstructions' ability to remove iodine contribution to attenuation. METHODS: Six vials containing varying concentrations of iodinated contrast (0-6 mg/mL) diluted in water were placed in a water bath and scanned on an SDCT scanner. Virtual monoenergetic (40-200 keV at 10-keV increments), iodine-no-water, and VNC reconstructions were created. Attenuation (in Hounsfield units [HU]), VME noise at each energy level, CT-derived iodine concentration, and VNC attenuation were recorded. RESULTS: Virtual monoenergetic noise was improved at all energies compared with conventional images (conventional, 9.8-11.2; VME, 7.5-9.5). Noise profile showed a slightly higher image noise at 40 keV, but was otherwise relatively flat across the energy spectrum. On iodine-no-water reconstructions, measured varied from actual iodine concentration by ±0.1 mg/mL (SD, 0.16-0.36). Virtual noncontrast attenuation was within 5 HU of water attenuation at all iodine concentrations. CONCLUSION: Reconstructions of SDCT show lower VME image noise, accurate iodine quantification, and VNC attenuation values within 5 HU of expected in a phantom model.

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DO - 10.1097/RCT.0000000000000763

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SN - 0363-8715

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