Dual-Energy Computed Tomography Virtual Monoenergetic Imaging of Lung Cancer: Assessment of Optimal Energy Levels

Publikation

Dual-Energy Computed Tomography Virtual Monoenergetic Imaging of Lung Cancer: Assessment of Optimal Energy Levels

Wissenschaftlicher Artikel/Review - 01.01.2016

Kaup Moritz, Vogl Thomas J, Lehnert Thomas, Beeres Martin, Kerl J Matthias, Bauer Ralf, Albrecht Moritz H, Engler Alexander, Scholtz Jan-Erik, Wichmann Julian L

Zitation

Kaup M, Vogl T, Lehnert T, Beeres M, Kerl J, Bauer R, Albrecht M, Engler A, Scholtz J, Wichmann J. Dual-Energy Computed Tomography Virtual Monoenergetic Imaging of Lung Cancer: Assessment of Optimal Energy Levels. J Comput Assist Tomogr 2016; 40:80-5.

Art

Wissenschaftlicher Artikel/Review (Englisch)

Zeitschrift

J Comput Assist Tomogr 2016; 40

Veröffentlichungsdatum

01.01.2016

eISSN (Online)

1532-3145

Seiten

80-5

Kurzbeschreibung/Zielsetzung

OBJECTIVE
The aim of the study was to evaluate objective and subjective image qualities of virtual monoenergetic imaging (VMI) in dual-source dual-energy computed tomography (DECT) and optimal kiloelectron-volt (keV) levels for lung cancer.

METHODS
Fifty-nine lung cancer patients underwent chest DECT. Images were reconstructed as VMI series at energy levels of 40, 60, 80, and 100 keV and standard linear blending (M_0.3) for comparison. Objective and subjective image qualities were assessed.

RESULTS
Lesion contrast peaked in 40-keV VMI reconstructions (2.5 ± 2.9) and 60 keV (1.9 ± 3.0), which was superior to M_0.3 (0.5 ± 2.7) for both comparisons (P < 0.001). Compared with M_0.3, subjective ratings were highest for 60-keV VMI series regarding general image quality (4.48 vs 4.52; P = 0.74) and increased for lesion demarcation (4.07 vs 4.84; P < 0.001), superior to all other VMI series (P < 0.001). Image sharpness was similar between both series. Image noise was rated superior in the 80-keV and M_0.3 series, followed by 60 keV.

CONCLUSIONS
Virtual monoenergetic imaging reconstructions at 60-keV provided the best combination of subjective and objective image qualities in DECT of lung cancer.