K-edge eliminated material decomposition method for dual-energy X-ray CT

Zhao, Tiao; Li, Liang; Chen, Zhiqiang

doi:10.1016/j.apradiso.2017.06.018

Cited by 7 publications

(3 citation statements)

References 13 publications

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“…This is critical in DECT as high K-edges cause discontinuities in the attenuation spectrum that cannot be well delineated by two-basis material decomposition. [33][34][35][36] Development of a CT-based theranostic compared to other imaging TA B L E 4 Mean HU and standard deviation of the mean for each chemical solution in a gelatin phantom for dual-source and split-filter systems. modalities, such as MRI, is advantageous because of the relative availability of CT for procedural image guidance.…”

Section: Discussionmentioning

confidence: 99%

“…The K‐edge of cesium is 36.0 keV, which is similar to that of iodine (33.2 keV). This is critical in DECT as high K‐edges cause discontinuities in the attenuation spectrum that cannot be well delineated by two‐basis material decomposition 33–36 . Development of a CT‐based theranostic compared to other imaging modalities, such as MRI, is advantageous because of the relative availability of CT for procedural image guidance.…”

Section: Discussionmentioning

confidence: 99%

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Quantitative dual‐energy computed tomography with cesium as a novel contrast agent for localization of thermochemical ablation in phantoms and ex vivo models

et al. 2023

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BackgroundThermochemical ablation (TCA) is a minimally invasive therapy under development for hepatocellular carcinoma. TCA simultaneously delivers an acid (acetic acid, AcOH) and base (sodium hydroxide, NaOH) directly into the tumor, where the acid/base chemical reaction produces an exotherm that induces local ablation. However, AcOH and NaOH are not radiopaque, making monitoring TCA delivery difficult.PurposeWe address the issue of image guidance for TCA by utilizing cesium hydroxide (CsOH) as a novel theranostic component of TCA that is detectable and quantifiable with dual‐energy CT (DECT).Materials and methodsTo quantify the minimum concentration of CsOH that can be positively identified by DECT, the limit of detection (LOD) was established in an elliptical phantom (Multi‐Energy CT Quality Assurance Phantom, Kyoto Kagaku, Kyoto, Japan) with two DECT technologies: a dual‐source system (SOMATOM Force, Siemens Healthineers, Forchheim, Germany) and a split‐filter, single‐source system (SOMATOM Edge, Siemens Healthineers). The dual‐energy ratio (DER) and LOD of CsOH were determined for each system. Cesium concentration quantification accuracy was evaluated in a gelatin phantom before quantitative mapping was performed in ex vivo models.ResultsOn the dual‐source system, the DER and LOD were 2.94 and 1.36‐mM CsOH, respectively. For the split‐filter system, the DER and LOD were 1.41‐ and 6.11‐mM CsOH, respectively. The signal on cesium maps in phantoms tracked linearly with concentration (R2 = 0.99) on both systems with an RMSE of 2.56 and 6.72 on the dual‐source and split‐filter system, respectively. In ex vivo models, CsOH was detected following delivery of TCA at all concentrations.ConclusionsDECT can be used to detect and quantify the concentration of cesium in phantom and ex vivo tissue models. When incorporated in TCA, CsOH performs as a theranostic agent for quantitative DECT image‐guidance.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Quantitative dual‐energy computed tomography with cesium as a novel contrast agent for localization of thermochemical ablation in phantoms and ex vivo models

et al. 2023

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“…The direct iterative reconstruction method incorporates the models of the material decomposition and the physics of spectral CT transmission. [17][18][19][20] For example, in Ref. 20, the iterative reconstruction method can even perform MMD of traditional integral detectors using angle-dependent filters.…”

Section: Introductionmentioning

confidence: 99%

Robust multimaterial decomposition of spectral CT using convolutional neural networks

Chen

2019

Opt. Eng.

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Spectral computed tomography (CT) can reconstruct scanned objects at different energy-bins and thus solve the multimaterial decomposition (MMD) problem. Because the linear attenuation coefficients of different basis materials may be extremely close, the decomposition problem is often ill-conditioned. Meanwhile, traditional material decompositions with image-domain algorithms are usually voxelwise based. Therefore, these algorithms rely heavily on image quality. Ring artifacts often exist in the reconstructed images of spectral CT due to the inconsistency feature of energy-resolved detectors and beam-hardening effect. Considering the enlargement of the receptive field and taking advantage of the modeling ability of convolutional neural networks in deep learning, we proposed a convolutional material decomposition algorithm to solve the MMD problem through a basis of patches instead of pixels of the spectral CT images. Simulations and physical experiments were performed to validate the proposed algorithm, and its quality was compared with a traditional MMD algorithm in the image domain. Results show that the proposed method achieves good accuracy, reduces mean squared errors by one to two orders, and exhibits robustness in the MMD of spectral CT images even in the case that obvious ring artifacts is presented.

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X-ray computed tomography for effective atomic number and density evaluation: A review

Gruener Lima,

Inocente Jussiani

2024

Radiation Physics and Chemistry

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K-edge eliminated material decomposition method for dual-energy X-ray CT

Cited by 7 publications

References 13 publications

Quantitative dual‐energy computed tomography with cesium as a novel contrast agent for localization of thermochemical ablation in phantoms and ex vivo models

Quantitative dual‐energy computed tomography with cesium as a novel contrast agent for localization of thermochemical ablation in phantoms and ex vivo models

Robust multimaterial decomposition of spectral CT using convolutional neural networks

X-ray computed tomography for effective atomic number and density evaluation: A review

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