TY - JOUR
T1 - Clinical implementation of dual-energy CT for gastrointestinal imaging
AU - Mileto, Achille
AU - Ananthakrishnan, Lakshmi
AU - Morgan, Desiree E.
AU - Yeh, Benjamin M.
AU - Marin, Daniele
AU - Kambadakone, Avinash R.
N1 - Funding Information:
A. Mileto is a consultant for Bayer HealthCare and received a research grant from GE Healthcare. D. E. Morgan receives research support from GE Healthcare. B. M. Yeh receives grants from GE Healthcare, Philips Healthcare, and Guerbet; is a speaker for GE Healthcare and Philips Healthcare; is a consultant for GE Healthcare; is a shareholder of Nextrast, Inc.; and receives book royalties from Oxford University Press and patent royalties from the University of California, San Francisco. D. Marin receives research support from Siemens Healthineers and GE Healthcare. A. R. Kambadakone receives grants from GE Healthcare, Philips, and PanCAN. The remaining author declares that there are no other disclosures relevant to the subject matter of this article.
Funding Information:
Submitted: Nov 6, 2020 Revision requested: Nov 23, 2020 Revision received: Dec 12, 2020 Accepted: Dec 18, 2020 First published online: Dec 30, 2020 A. Mileto is a consultant for Bayer HealthCare and received a research grant from GE Healthcare. D. E. Morgan receives research support from GE Healthcare. B. M. Yeh receives grants from GE Healthcare, Philips Healthcare, and Guerbet; is a speaker for GE Healthcare and Philips Healthcare; is a consultant for GE Healthcare; is a shareholder of Nextrast, Inc.; and receives book royalties from Oxford University Press and patent royalties from the University of California, San Francisco. D. Marin receives research support from Siemens Healthineers and GE Healthcare. A. R. Kambadakone receives grants from GE Healthcare, Philips, and PanCAN. The remaining author declares that there are no other disclosures relevant to the subject matter of this article.
Publisher Copyright:
© American Roentgen Ray Society.
PY - 2021/9
Y1 - 2021/9
N2 - Dual-energy CT (DECT) overcomes several limitations of conventional single-energy CT (SECT) for the evaluation of gastrointestinal diseases. This article provides an overview of practical aspects of the DECT technology and acquisition protocols, reviews existing clinical applications, discusses current challenges, and describes future directions, with a focus on gastrointestinal imaging. A head-to-head comparison of technical specifications among DECT scanner implementations is provided. Energy- and material-specific DECT image reconstructions enable retrospective (i.e., after examination acquisition) image quality adjustments that are not possible using SECT. Such adjustments may, for example, correct insufficient contrast bolus or metal artifacts, thereby potentially avoiding patient recalls. A combination of low-energy monochromatic images, iodine maps, and virtual unenhanced images can be included in protocols to improve lesion detection and disease characterization. Relevant literature is reviewed regarding use of DECT for evaluation of the liver, gallbladder, pancreas, and bowel. Challenges involving cost, workflow, body habitus, and variability in DECT measurements are considered. Artificial intelligence and machine-learning image reconstruction algorithms, PACS integration, photon-counting hardware, and novel contrast agents are expected to expand the multienergy capability of DECT and further augment its value.
AB - Dual-energy CT (DECT) overcomes several limitations of conventional single-energy CT (SECT) for the evaluation of gastrointestinal diseases. This article provides an overview of practical aspects of the DECT technology and acquisition protocols, reviews existing clinical applications, discusses current challenges, and describes future directions, with a focus on gastrointestinal imaging. A head-to-head comparison of technical specifications among DECT scanner implementations is provided. Energy- and material-specific DECT image reconstructions enable retrospective (i.e., after examination acquisition) image quality adjustments that are not possible using SECT. Such adjustments may, for example, correct insufficient contrast bolus or metal artifacts, thereby potentially avoiding patient recalls. A combination of low-energy monochromatic images, iodine maps, and virtual unenhanced images can be included in protocols to improve lesion detection and disease characterization. Relevant literature is reviewed regarding use of DECT for evaluation of the liver, gallbladder, pancreas, and bowel. Challenges involving cost, workflow, body habitus, and variability in DECT measurements are considered. Artificial intelligence and machine-learning image reconstruction algorithms, PACS integration, photon-counting hardware, and novel contrast agents are expected to expand the multienergy capability of DECT and further augment its value.
KW - Bowel
KW - Dual-energy CT
KW - Gastrointestinal
KW - Liver
KW - Pancreas
UR - http://www.scopus.com/inward/record.url?scp=85113540776&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85113540776&partnerID=8YFLogxK
U2 - 10.2214/AJR.20.25093
DO - 10.2214/AJR.20.25093
M3 - Review article
C2 - 33377415
AN - SCOPUS:85113540776
SN - 0361-803X
VL - 217
SP - 651
EP - 663
JO - American Journal of Roentgenology
JF - American Journal of Roentgenology
IS - 3
ER -