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CT Number Stability Across Patient Sizes Using Virtual-Monoenergetic Dual-Energy CT

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G Michalak

G Michalak1*, J Grimes2 , A Halaweish3 , J Fletcher4 , C McCollough5 , (1) Mayo Clinic, Rochester, MN (2) Mayo Clinic, Rochester, MN, (3) Siemens Healthcare, Rochester, MN, (4) Mayo Clinic, Rochester, MN (5) Mayo Clinic, Rochester, MN


TU-F-18A-9 Tuesday 4:30PM - 6:00PM Room: 18A


Virtual-monoenergetic imaging uses dual-energy CT data to synthesize images corresponding to a single photon energy, thereby reducing beam-hardening artifacts. This work evaluated the ability of a commercial virtual-monoenergetic algorithm to achieve stable CT numbers across patient sizes.


Test objects containing a range of iodine and calcium hydroxyapatite concentrations were placed inside 8 torso-shaped water phantoms, ranging in lateral width from 15 to 50 cm, and scanned on a dual-source CT system (Siemens Somatom Force). Single-energy scans were acquired from 70-150 kV in 10 kV increments; dual-energy scans were acquired using 4 energy pairs (low energy: 70, 80, 90, and 100 kV; high energy: 150 kV + 0.6 mm Sn). CTDIvol was matched for all single- and dual-energy scans for a given phantom size. All scans used 128x0.6 mm collimation and were reconstructed with 1-mm thickness at 0.8-mm increment and a medium smooth body kernel. Monoenergetic images were generated using commercial software (syngo Via Dual Energy, VA30). Iodine contrast was calculated as the difference in mean iodine and water CT numbers from respective regions-of-interest in 10 consecutive images.


CT numbers remained stable as phantom width varied from 15 to 50 cm for all dual-energy data sets (except for at 50 cm using 70/150Sn due to photon starvation effects). Relative to the 15 cm phantom, iodine contrast was within 5.2% of the 70 keV value for phantom sizes up to 45 cm. At 90/150Sn, photon starvation did not occur at 50 cm, and iodine contrast in the 50-cm phantom was within 1.4% of the 15-cm phantom.


Monoenergetic imaging, as implemented in the evaluated commercial system, eliminated the variation in CT numbers due to patient size, and may provide more accurate data for quantitative tasks, including radiation therapy treatment planning.

Funding Support, Disclosures, and Conflict of Interest: Siemens Healthcare

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