Iodine quantification with dual-energy CT: phantom study and preliminary experience with VX2 residual tumour in rabbits after radiofrequency ablation

Li, Y; Shi, Guo‐Ming; S, Wang; Wu, Runze

doi:10.1259/bjr.20130143

Cited by 36 publications

(34 citation statements)

References 37 publications

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“…Lee JA et al applied colour-coded iodine CT maps in HCC and documented a median HU value of 65.13 ± 26.10 [15]. In a VX2 carcinoma rabbit model after radiofrequency ablation, the residual tumour showed a concentration of 1.83 ± 0.21 mg/mL concentration in the arterial phase [24] and, therefore, similar to our results.…”

Section: Discussionsupporting

confidence: 90%

Iodine concentration as a perfusion surrogate marker in oncology: Further elucidation of the underlying mechanisms using Volume Perfusion CT with 80 kVp

et al. 2015

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• Iodine concentration derived from low kVp CT is regarded as perfusion surrogate • Correlation with Perfusion CT was performed to elucidate timing and histology dependencies • Highest correlation was present 7 sec after aortic peak enhancement in hepatocellular carcinoma • In lymphoma, highest correlation was calculated 3.5 sec after aortic peak enhancement • With these results, further optimization of Dual energy CT protocols is possible.

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Section: Discussionsupporting

confidence: 90%

Iodine concentration as a perfusion surrogate marker in oncology: Further elucidation of the underlying mechanisms using Volume Perfusion CT with 80 kVp

et al. 2015

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“…With dual energy CT, two measurements of the imaging objects acquired with different beam spectra enable differentiation and quantification of two or more materials based on the energy dependence of each material (Alvarez and Macovski, 1976). For example, a patient image can be decomposed into iodine and water images and the amount of iodine at each location can be quantified (Johnson et al, 2007, Chandarana et al, 2011, Li et al, 2013). Another common application of dual energy CT is to generate virtual monoenergetic images (VMI) (Goodsitt et al, 2011, Matsumoto et al, 2011, Yu et al, 2011, Yu et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Spectral performance of a whole-body research photon counting detector CT: quantitative accuracy in derived image sets

et al. 2017

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Photon-counting computed tomography (PCCT) uses a photon counting detector to count individual photons and allocate them to specific energy bins by comparing photon energy to preset thresholds. This enables simultaneous multi-energy CT with a single source and detector. Phantom studies were performed to assess the spectral performance of a research PCCT scanner by assessing the accuracy of derived images sets. Specifically, we assessed the accuracy of iodine quantification in iodine map images and of CT number accuracy in virtual monoenergetic images (VMI). Vials containing iodine with 5 known concentrations were scanned on the PCCT scanner after being placed in phantoms representing the attenuation of different size patients. For comparison, the same vials and phantoms were also scanned on 2nd and 3rd generation dual-source, dual-energy (DSDE) scanners. After material decomposition, iodine maps were generated, from which iodine concentration was measured for each vial and phantom size and compared with the known concentration. Additionally, VMIs were generated and CT number accuracy was compared to the reference standard, which was calculated based on known iodine concentration and attenuation coefficients at each keV obtained from the U.S. National Institute of Standards and Technology. Results showed accurate iodine quantification (root mean square error of 0.5 mgI/cc) and accurate CT number of VMIs (percentage error of 8.9%) using the PCCT scanner. The overall performance of the PCCT scanner, in terms of iodine quantification and VMI CT number accuracy, was comparable to that of EID-based dual-source, dual-energy scanners.

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“…Recent advances in CT technologies, especially the launch of dual-source CT, significantly improve the CT image quality and scan speed. DECT has been increasingly used for automatic bone removal [2], [3], iodine quantification [4], [5], material characterization [6]–[8], creating monochromatic images [9], [10], and virtual non-enhanced imaging [11]–[13]. The clinical applications have a continuously growing list, including diagnosis of aortic pathologies [14], lung perfusion and ventilation imaging [15], neurological and cerebral vascular imaging [16], [17], and kidney stone characterization [6]–[8].…”

Section: Introductionmentioning

confidence: 99%

Noise Suppression for Dual-Energy CT Through Entropy Minimization

Petrongolo

Zhu

2015

IEEE Trans. Med. Imaging

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In dual energy CT (DECT), noise amplification during signal decomposition significantly limits the utility of basis material images. Since clinically relevant objects typically contain a limited number of different materials, we propose an Image-domain Decomposition method through Entropy Minimization (IDEM) for noise suppression in DECT. Pixels of decomposed images are first linearly transformed into 2D clusters of data points, which are highly asymmetric due to strong signal correlation. An optimal axis is identified in the 2D space via numerical search such that the projection of data clusters onto the axis has minimum entropy. Noise suppression is performed on each image pixel by estimating the center-of-mass value of each data cluster along the direction perpendicular to the projection axis. The IDEM method is distinct from other noise suppression techniques in that it does not suppress pixel noise by reducing spatial variation between neighboring pixels. As supported by studies on Catphan©600 and anthropomorphic head phantoms, this feature endows our algorithm with a unique capability of reducing noise standard deviation on DECT decomposed images by approximately one order of magnitude while preserving spatial resolution and image noise power spectra (NPS). Compared with a filtering method and recently developed iterative method at the same level of noise suppression, the IDEM algorithm obtains high-resolution images with less artifacts. It also maintains accuracy of electron density measurements with less than 2% bias error. The IDEM method effectively suppresses noise of DECT for quantitative use, with appealing features on preservation of image spatial resolution and NPS.

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Iodine quantification with dual-energy CT: phantom study and preliminary experience with VX2 residual tumour in rabbits after radiofrequency ablation

Abstract: Iodine quantification with DECT may help in differentiating benign periablational reactive tissue from residual tumour in VX2 carcinoma in rabbits after RFA.

Cited by 36 publications

References 37 publications

Iodine concentration as a perfusion surrogate marker in oncology: Further elucidation of the underlying mechanisms using Volume Perfusion CT with 80 kVp

Iodine concentration as a perfusion surrogate marker in oncology: Further elucidation of the underlying mechanisms using Volume Perfusion CT with 80 kVp

Spectral performance of a whole-body research photon counting detector CT: quantitative accuracy in derived image sets

Noise Suppression for Dual-Energy CT Through Entropy Minimization

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