Spectral detector CT-derived virtual non-contrast images: comparison of attenuation values with unenhanced CT

Ananthakrishnan, Lakshmi; Rajiah, Prabhakar; Ahn, Richard W.; Rassouli, Negin; Xi, Yin; Soesbe, Todd C.; Lewis, Matthew; Lenkinski, Robert E.; Leyendecker, John R.; Abbara, Suhny

doi:10.1007/s00261-016-1036-9

Cited by 103 publications

(101 citation statements)

References 15 publications

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“…Furthermore, their method to obtain this diagnostic equation combining ICs from both non‐enhanced and contrast‐enhanced CT images inevitably doubled the patients' radiation exposure. In this study, we used a recently implemented DECT scanner, which only a few studies used . This scanner achieves spectral separation using a different method from the previous fast‐kVp switching scanner in which the X‐ray tube rapidly modulates tube voltage .…”

Section: Discussionmentioning

confidence: 99%

“…In this study, we used a recently implemented DECT scanner, which only a few studies used. [30][31][32][33][34][35] This scanner achieves spectral separation using a different method from the previous fast-kVp switching scanner in which the X-ray tube rapidly modulates tube voltage. 7,8,10 In contrast, our DECT scanner built with 2 scintillating layers has a single X-ray source that operates at a fixed tube potential, typically 120 or 140 kVp.…”

Section: Discussionmentioning

confidence: 99%

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Dual‐energy CT iodine quantification for characterizing focal thyroid lesions

Lee

Seo

et al. 2018

Head & Neck

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Background To determine the usefulness of dual‐energy CT (DECT) iodine quantification to classify the focal thyroid lesions. Methods We retrospectively enrolled a total of 76 cytopathologically confirmed focal thyroid lesions (mean size: 1.9 cm). After drawing a region of interest on the DECT‐derived iodine maps, the obtained iodine concentration values of thyroid nodules (IC_N) and normalized IC_N were compared between 3 groups: papillary thyroid carcinoma (PTC), benign nodule, and cyst. Results From all lesions, 46, 17, and 13 were assigned to the PTC, benign nodule, and cyst groups. IC_N was the highest in the benign nodule, lower in the PTC, and the lowest in the cyst (median [interquartile range]: 4.3 [3.13‐5.48], 3.15 [2.29‐4.01], 0.60 [0.33‐0.88], all P < .001). Similarly, the normalized IC_N values were all statistically different from each other (P < .05).The multi‐class area under the curves using the optimal cutoff values were 0.931 for IC_N and 0.918, 0.920 for normalized IC, respectively. Conclusion DECT iodine quantification could be helpful to classify the focal thyroid lesions.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Dual‐energy CT iodine quantification for characterizing focal thyroid lesions

Lee

Seo

et al. 2018

Head & Neck

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“…(b) Fast kilovolt peak-switching (FS) scanners (HD-750 and Revolution CT; GE Healthcare, Waukesha, Wis) allow acquisition of dual-energy data by modulating the voltage of a single xray generator from low to high kilovolt peaks between alternating projections. (c) Dual-layered (DL) detector arrays have been implemented (IQon scanner; Philips, Best, the Netherlands) to create dual-energy projection data from a conventional 120 or 140 kVp scan (4,5). (d) A split-filter (SF) dual-energy mode has been implemented in a recent model (Edge CT, Siemens).…”

Section: Methodsmentioning

confidence: 99%

Intermanufacturer Comparison of Dual-Energy CT Iodine Quantification and Monochromatic Attenuation: A Phantom Study

et al. 2018

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Purpose To determine the accuracy of dual-energy computed tomographic (CT) quantitation in a phantom system comparing fast kilovolt peak-switching, dual-source, split-filter, sequential-scanning, and dual-layer detector systems. Materials and Methods A large elliptical phantom containing iodine (2, 5, and 15 mg/mL), simulated contrast material-enhanced blood, and soft-tissue inserts with known elemental compositions was scanned three to five times with seven dual-energy CT systems and a total of 10 kilovolt peak settings. Monochromatic images (50, 70, and 140 keV) and iodine concentration images were created. Mean iodine concentration and monochromatic attenuation for each insert and reconstruction energy level were recorded. Measurement bias was assessed by using the sum of the mean signed errors measured across relevant inserts for each monochromatic energy level and iodine concentration. Iodine and monochromatic errors were assessed by using the root sum of the squared error of all measurements. Results At least one acquisition paradigm per scanner had iodine biases (range, -2.6 to 1.5 mg/mL) with significant differences from zero. There were no significant differences in iodine error (range, 0.44-1.70 mg/mL) among the top five acquisition paradigms (one fast kilovolt peak switching, three dual source, and one sequential scanning). Monochromatic bias was smallest for 70 keV (-12.7 to 15.8 HU) and largest for 50 keV (-80.6 to 35.2 HU). There were no significant differences in monochromatic error (range, 11.4-52.0 HU) among the top three acquisition paradigms (one dual source and two fast kilovolt peak switching). The lowest accuracy for both measures was with a split-filter system. Conclusion Iodine and monochromatic accuracy varies among systems, but dual-source and fast kilovolt-switching generally provided the most accurate results in a large phantom. RSNA, 2017 Online supplemental material is available for this article.

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“…For example, Durieux et al 2018 evaluated VNC images for abdominal depiction from a third generation dual-source dual-energy CT and pointed out that despite high accuracies of attenuation values for the liver and spleen with mean attenuation differences between 0-2 HU, there have been substantial differences in fluid, fat and renal tissue with mean differences as high as 32 HU. Other recent dual-energy studies also showed accurate iodine subtraction by VNC for depiction of the liver 23,24,35,36 . Further, overestimation of fat by VNC has also been reported for spectral-detector CT by Ananthakrishnan Our study showed differences between TNC and VNC of 1.8 ± 4.6 HU for CTA-Chest and −1.1 ± 5.9 HU in CTA-Abdomen in liver.…”

Section: Resultsmentioning

confidence: 82%

“…In this cohort we were able to show that VNC of TNC can reliably reduce increased liver density due to amiodarone deposition. As frequently applied in comparable studies, we used ROI-based measurements of mean attenuation [22][23][24][25]35 . Still, a volumetric assessment of attenuation covering an entire organ might be less susceptible for any measuring bias.…”

Section: Resultsmentioning

confidence: 99%

Iodine accumulation of the liver in patients treated with amiodarone can be unmasked using material decomposition from multiphase spectral-detector CT

Laukamp

Lennartz

Hashmi

et al. 2020

Sci Rep

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Amiodarone accumulates in the liver, where it increases x-ray attenuation due to its iodine content. We evaluated liver attenuation in patients treated and not treated with amiodarone using true-noncontrast (TNC) and virtual-non-contrast (VNC) images acquired with spectral-detector-CT (SDCT). 142 patients, of which 21 have been treated with amiodarone, receiving SDCT-examinations (unenhancedchest CT [TNC], CT-angiography of chest and abdomen [CTA-Chest, CTA-Abdomen]) were included. TNC, CTA-Chest, CTA-Abdomen, and corresponding VNC-images (VNC-Chest, VNC-Abdomen) were reconstructed. Liver-attenuation-index (LAI) was calculated as difference between liver-and spleenattenuation. Liver-attenuation and LAI derived from TNC-images of patients receiving amiodarone were higher. Contrary to TNC, liver-attenuation and LAI were not higher in amiodarone patients in VNC-Chest and in VNC-Abdomen. To verify these initial results, a phantom scan was performed and an additional patient cohort included, both confirming that VNC is viable of accurately subtracting iodine of hepatic amiodarone-deposits. This might help to monitor liver-attenuation more accurately and thereby detect liver steatosis as a sign of liver damage earlier as well as to verify amiodarone accumulation in the liver.Amiodarone is an antiarrhythmic drug that has shown its effectiveness for several decades to treat various forms of tachyarrhythmia 1,2 . However, oral absorption and bioavailability are poor and greatly variable. Onset of therapeutic effects using oral application range between 2-21 days and after long-term treatment plasma half-life is around 100 days. Because of its lipophilic properties, iodine-containing amiodarone accumulates, among others, in hepatocytes. Here, it inhibits the enzyme phospholipase which subsequentially stops the removal of lysosomal phospholipids. Consequently, amiodarone forms a nondigestible complex with the phospholipids, resulting in phospholipidosis and extended amiodarone accumulation. Amiodarone concentrations in the liver can be up to 500-times higher than in the blood serum and release from hepatocytes is slow after treatment discontinuation 1-6 . Earlier studies found that this condition can lead to steatohepatitis and liver cirrhosis 1,7,8 .Iodinated contrast media is broadly applied in CT imaging. Due to its high physical density and k-edge effects of iodine, it increases attenuation and image contrast that improves depiction of anatomical structures (e.g. organ parenchyma and vessels) 9,10 . For intravascular injections in CT imaging almost exclusively non-ionic low-or iso-osmotic iodinated contrast media is applied. Molecular structures between agents are similar, a commonly applied agent is for example Ioversol (C 18 H 24 I 3 N 3 O 9 , molecular mass of 807.1 g/mol). It contains three iodine atoms that constitute almost 50% of its molecular mass 9-12 . Amiodarone shows several similarities to iodinated contrast media regarding the molecular structure. It is a di-iodinated benzofuran derivate, as a drug it is u...

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Spectral detector CT-derived virtual non-contrast images: comparison of attenuation values with unenhanced CT

Cited by 103 publications

References 15 publications

Dual‐energy CT iodine quantification for characterizing focal thyroid lesions

Dual‐energy CT iodine quantification for characterizing focal thyroid lesions

Intermanufacturer Comparison of Dual-Energy CT Iodine Quantification and Monochromatic Attenuation: A Phantom Study

Iodine accumulation of the liver in patients treated with amiodarone can be unmasked using material decomposition from multiphase spectral-detector CT

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