Iodine quantification and detectability thresholds among major dual-energy CT platforms

Taylor, Ross Edward; Mager, Pamela; Yu, Nam C.; Katz, David P.; Brady, Jett R.; Gupta, Nakul

doi:10.1259/bjr.20190530

Cited by 13 publications

(12 citation statements)

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“…Dual-energy CT uses data from two different X-ray spectra, typically with low energy of 80 kVp and high energy of 140–150 kVp ( 18 ). Various types of images can be obtained through data processing using dual-energy CT, such as mixed energy images, iodine maps, virtual non-contrast images, and monoenergetic images ( 12 , 13 , 19 ).…”

Section: Introductionmentioning

confidence: 99%

Detecting lymph node metastasis of esophageal cancer on dual-energy computed tomography

et al. 2020

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Background Using conventional computed tomography (CT), the accurate diagnosis of lymph node (LN) metastasis of esophageal cancer is difficult. Purpose To examine dual-energy CT parameters to predict LN metastasis preoperatively in patients with esophageal cancer. Material and Methods Twenty-six consecutive patients who underwent dual-energy CT before an esophageal cancer surgery (19 patients with LN metastases) were analyzed. The included LNs had a short-axis diameter of ≥4 mm and were confirmed to be resected on postoperative CT. Their short-axis diameter, CT value, iodine concentration (IC), and fat fraction were measured on early- and late-phase contrast-enhanced dual-energy CT images and compared between pathologically confirmed metastatic and non-metastatic LNs. Results In total, 51 LNs (34 metastatic and 17 non-metastatic) were included. In the early phase, IC and fat fraction were significantly lower in the metastatic than in the non-metastatic LNs (IC = 1.6 mg/mL vs. 2.2 mg/mL; fat fraction = 20.3% vs. 32.5%; both P < 0.05). Furthermore, in the late phase, IC and fat fraction were significantly lower in the metastatic than in the non-metastatic LNs (IC = 2.0 mg/mL vs. 3.0 mg/mL; fat fraction = 20.4% vs. 33.0%; both P < 0.05). Fat fraction exhibited accuracies of 82.4% and 78.4% on early- and late-phase images, respectively. Conversely, short-axis diameter and CT value on both early- and late-phase images were not significantly different between the metastatic and non-metastatic LNs ( P > 0.05). Conclusion Using dual-energy CT images, IC and fat fraction are useful for diagnosing LN metastasis in patients with esophageal cancer.

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Section: Introductionmentioning

confidence: 99%

Detecting lymph node metastasis of esophageal cancer on dual-energy computed tomography

et al. 2020

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“…Studies comparing iodine sensitivity among DECT scanners concluded that it correlates mainly with better spectral performance and is also influenced by other factors such as image reconstruction techniques, patient size, and lesion location [ 34 , 47 , 48 , 49 , 50 ].…”

Section: Resultsmentioning

confidence: 99%

Pros and Cons of Dual-Energy CT Systems: “One Does Not Fit All”

2023

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Dual-energy computed tomography (DECT) uses different energy spectrum X-ray beams for differentiating materials with similar attenuation at a certain energy. Compared with single-energy CT, it provides images with better diagnostic performance and a potential reduction of contrast agent and radiation doses. There are different commercially available DECT technologies, with machines that may display two X-ray sources and two detectors, a single source capable of fast switching between two energy levels, a specialized detector capable of acquiring high- and low-energy data sets, and a filter splitting the beam into high- and low-energy beams at the output. Sequential acquisition at different tube voltages is an alternative approach. This narrative review describes the DECT technique using a Q&A format and visual representations. Physical concepts, parameters influencing image quality, postprocessing methods, applicability in daily routine workflow, and radiation considerations are discussed. Differences between scanners are described, regarding design, image quality variabilities, and their advantages and limitations. Additionally, current clinical applications are listed, and future perspectives for spectral CT imaging are addressed. Acknowledging the strengths and weaknesses of different DECT scanners is important, as these could be adapted to each patient, clinical scenario, and financial capability. This technology is undoubtedly valuable and will certainly keep improving.

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“…This prospective, single-center study was approved by the IRB of our university hospital (ClinicalTrials.gov number NCT03146117). We enrolled patients with suspected or confirmed NSCLC, who were referred to undergo a clinically indicated 18 F-FDG-PET/CT staging examination between May 2017 and June 2018, whose age was between 18 and 90 years at the time of the baseline examination, and who provided written informed consent before undergoing any study-related procedures. We excluded patients who (1) were pregnant or nursing females, (2) were in an acute unstable condition, (3) reported prior reactions against iodinated contrast agents, (4) had impaired renal function (glomerular filtration ratio < 30 mL/min × 1.73 m 2 ).…”

Section: Patient Selection and Study Designmentioning

confidence: 99%

“…[14][15][16][17] The material decomposition algorithm for DECT data sets facilitates a precise separation of iodine from other elements and enables the quantification of iodine in a single voxel. 18 Iodine quantification was studied for applications in malignancies diagnosis and prognosis. 14,[19][20][21][22] The integration of a PET/CT and DECT in a single scanner could improve lung cancer staging and provide additional information on tumor pathophysiology.…”

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confidence: 99%

Prospective Evaluation of the First Integrated Positron Emission Tomography/Dual-Energy Computed Tomography System in Patients With Lung Cancer

Martin

Assen

Burchett

et al. 2021

Journal of Thoracic Imaging

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The aim of this pilot study was to prospectively evaluate the first integrated positron emission tomography (PET)/dualenergy computed tomography (DECT) system performance in patients with non-small cell lung cancer (NSCLC). Materials and Methods:In this single-center, prospective trial, consecutive patients with NSCLC referred for a PET study between May 2017 and June 2018 were enrolled. All patients received contrast-enhanced imaging on a clinical PET/DECT system. Data analysis included PET-based standard uptake values (SUV max ) and DECT-based iodine densities of tumor masses, lymph nodes, and distant metastases. Results were analyzed using correlation tests and receiver operating characteristics curves. Results:The study population was composed of 21 patients (median age 62 y, 14 male patients). A moderate positive correlation was found between iodine density values (2.2 mg/mL) and SUV max (10.5) in tumor masses (ρ = 0.53, P < 0.01). Iodine density values (2.3 mg/mL) and SUV max (5.4) of lymph node metastases showed a weak positive correlation (ρ = 0.23, P = 0.14). In addition, iodine quantification analysis provided no added value in differentiating between pathologic and nonpathologic lymph nodes with an area under the curve (AUC) of 0.55 using PET-based SUV max as the reference standard. A weak positive correlation was observed between iodine density (2.2 mg/mL) and SUV max in distant metastases (14.9, ρ = 0.23, P = 0.52). Conclusions:The application of an integrated PET/DECT system in lung cancer might provide additional insights in the assessment of tumor masses. However, the added value of iodine density quantification for the evaluation of lymph nodes and distant metastases seems limited.

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Iodine quantification and detectability thresholds among major dual-energy CT platforms

Cited by 13 publications

References 50 publications

Detecting lymph node metastasis of esophageal cancer on dual-energy computed tomography

Detecting lymph node metastasis of esophageal cancer on dual-energy computed tomography

Pros and Cons of Dual-Energy CT Systems: “One Does Not Fit All”

Prospective Evaluation of the First Integrated Positron Emission Tomography/Dual-Energy Computed Tomography System in Patients With Lung Cancer

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