scholarly journals CT-based thermometry with virtual monoenergetic images by dual-energy of fat, muscle and bone using FBP, iterative and deep learning–based reconstruction

2021 ◽  
Author(s):  
Andreas Heinrich ◽  
Sebastian Schenkl ◽  
David Buckreus ◽  
Felix V. Güttler ◽  
Ulf K-M. Teichgräber
Keyword(s):  
Deep Learning ◽  
Temperature Sensitivity ◽  
Dual Energy ◽  
Clinical Applications ◽  
Adaptive Statistical Iterative Reconstruction ◽  
Statistical Iterative Reconstruction ◽  
Virtual Monoenergetic Images ◽  
Higher Temperature ◽  
Dose Reductions ◽  
Monoenergetic Images

Abstract Objectives The aim of this study was to evaluate the sensitivity of CT-based thermometry for clinical applications regarding a three-component tissue phantom of fat, muscle and bone. Virtual monoenergetic images (VMI) by dual-energy measurements and conventional polychromatic 120-kVp images with modern reconstruction algorithms adaptive statistical iterative reconstruction-Volume (ASIR-V) and deep learning image reconstruction (DLIR) were compared. Methods A temperature-regulating water circuit system was developed for the systematic evaluation of the correlation between temperature and Hounsfield units (HU). The measurements were performed on a Revolution CT with gemstone spectral imaging technology (GSI). Complementary measurements were performed without GSI (voltage 120 kVp, current 130–545 mA). The measured object was a tissue equivalent phantom in a temperature range of 18 to 50°C. The evaluation was carried out for VMI at 40 to 140 keV and polychromatic 120-kVp images. Results The regression analysis showed a significant inverse linear dependency between temperature and average HU regardless of ASIR-V and DLIR. VMI show a higher temperature sensitivity compared to polychromatic images. The temperature sensitivities were 1.25 HU/°C (120 kVp) and 1.35 HU/°C (VMI at 140 keV) for fat, 0.38 HU/°C (120 kVp) and 0.47 HU/°C (VMI at 40 keV) for muscle and 1.15 HU/°C (120 kVp) and 3.58 HU/°C (VMI at 50 keV) for bone. Conclusions Dual-energy with VMI enables a higher temperature sensitivity for fat, muscle and bone. The reconstruction with ASIR-V and DLIR has no significant influence on CT-based thermometry, which opens up the potential of drastic dose reductions. Key Points • Virtual monoenergetic images (VMI) enable a higher temperature sensitivity for fat (8%), muscle (24%) and bone (211%) compared to conventional polychromatic 120-kVp images. • With VMI, there are parameters, e.g. monoenergy and reconstruction kernel, to modulate the temperature sensitivity. In contrast, there are no parameters to influence the temperature sensitivity for conventional polychromatic 120-kVp images. • The application of adaptive statistical iterative reconstruction-Volume (ASIR-V) and deep learning–based image reconstruction (DLIR) has no effect on CT-based thermometry, opening up the potential of drastic dose reductions in clinical applications.

scholarly journals First experience with combined use of adaptive statistical iterative reconstruction and gemstone spectral imaging in spinal fusion CT images

2015 ◽  
Author(s):  
Fengdan Wang ◽  
Yan Zhang ◽  
Zhengyu Jin ◽  
Richard Zwar
Keyword(s):  
Image Quality ◽  
Iterative Reconstruction ◽  
Dual Energy ◽  
Dual Energy Ct ◽  
Metal Artifacts ◽  
Adaptive Statistical Iterative Reconstruction ◽  
Subjective Image Quality ◽  
Gemstone Spectral Imaging ◽  
Statistical Iterative Reconstruction ◽  
Combined Use

Objective. To explore whether the image noises and the metal artifacts could be further managed by the combined use of two technologies, the adaptive statistical iterative reconstruction (ASIR) and the monochromatic imaging generated by gemstone spectral imaging (GSI) dual-energy CT. Materials and Methods. Fifty-one patients with 318 spinal pedicle screws were prospectively scanned with dual energy CT by using fast kV-switching GSI between 80 and 140 kVp. The monochromatic GSI images at 110 keV were reconstructed either without ASIR or with ASIR of various levels (30%, 50%, 70% and 100%). For these five sets of images, both objective and subjective image quality assessments were performed to evaluate the image quality. Results. With objective image quality assessment, the metal artifacts (measured by an artifacts index) significantly decreased when increasing levels of ASIR was utilized (p < 0.001). Moreover, adding ASIR to GSI also decreased the image noise (p < 0.001) and improved the signal-to-noise ratio (SNR, p < 0.001). With subjective image quality analysis, the inter-reader agreements were good, with intra-class correlation coefficients (ICC) of 0.89 to 0.99. Meanwhile, the visualization of the peri-implant soft tissue was improved at higher ASIR levels (p < 0.001). Conclusion. Combined use of ASIR and GSI is shown to decrease the image noise and improve the image quality in post-spinal fusion CT scans. Optimal results were achieved with ASIR levels of over 70%.

Advanced virtual monoenergetic images: improving the contrast of dual-energy CT pulmonary angiography

2015 ◽  
Vol 70 (11) ◽  
pp. 1244-1251 ◽  
Author(s):  
A. Meier ◽  
M. Wurnig ◽  
L. Desbiolles ◽  
S. Leschka ◽  
T. Frauenfelder ◽  
...  
Keyword(s):  
Pulmonary Angiography ◽  
Dual Energy ◽  
Dual Energy Ct ◽  
Ct Pulmonary Angiography ◽  
Virtual Monoenergetic Images ◽  
Monoenergetic Images

Optimizing window settings for improved presentation of virtual monoenergetic images in dual-energy computed tomography

2017 ◽  
Vol 44 (11) ◽  
pp. 5686-5696 ◽  
Author(s):  
Wanyi Fu ◽  
Daniele Marin ◽  
Juan Carlos Ramirez-Giraldo ◽  
Kingshuk Roy Choudhury ◽  
Justin Solomon ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Dual Energy ◽  
Dual Energy Computed Tomography ◽  
Virtual Monoenergetic Images ◽  
Monoenergetic Images

Reducing contrast medium dose with low photon energy images in renal dual-energy spectral CT angiography and adaptive statistical iterative reconstruction (ASIR)

2021 ◽  
pp. 20200974
Author(s):  
Xirong Zhang ◽  
Jing Chen ◽  
Nan Yu ◽  
Zhanli Ren ◽  
Qian Tian ◽  
...  
Keyword(s):  
Renal Artery ◽  
Contrast Medium ◽  
Iterative Reconstruction ◽  
Dual Energy ◽  
Spectral Ct ◽  
Adaptive Statistical Iterative Reconstruction ◽  
Statistical Iterative Reconstruction ◽  
Group A ◽  
Group B ◽  
Medium Dose

Objective: To evaluate the value of using low energy (keV) images in renal dual-energy spectral CT angiography (CTA) and adaptive statistical iterative reconstruction (ASIR) to reduce contrast medium dose. Methods: 40 patients with renal CTA on a Discovery CT750HD were randomly divided into two groups: 20 cases (Group A) with 600 mgI kg−1 and 20 cases (Group B) with 300 mgI kg−1. The scan protocol for both groups was: dual-energy mode with mA selection for noise index of 10 HU, pitch 1.375:1, rotating speed 0.6 s/r. Images were reconstructed at 0.625 mm thickness with 40%ASIR, Group A used the conventional 70keV monochromatic images, and Group B used monochromatic images from 40 to 70 keV at 5 keV interval for analysis. The CT values and standard deviation (SD) values of the renal artery and erector spine in the plain and arterial phases were measured with the erector spine SD value representing image noise. The enhancement degree of the renal artery (ΔCT = CT(arterial) -CT(plain)), signal-to-noise ratio (SNR=CTrenal-artery/SDrenal-artery) and contrast-to-noise ratio (CNR=(CTrenal-artery-CTerector spine)/SDerector-spine) were calculated. The single factor analysis of variance was used to analyze the difference of ΔCT, SNR and CNR among image groups with p < 0.05 being statistically significant. The subjective image scores of the groups were assessed blindly by two experienced physicians using a 5-point system and the score consistency was compared by the κ test. Results: Contrast medium dose in the 300 mgI kg−1 group was reduced by 50% compared with the 600 mgI kg−1 group, while radiation dose was similar between the two groups. The subjective scores were 4.00 ± 0.65, 4.50 ± 0.60 and 3.70 ± 0.80 for images at 70 keV (600 mgI kg−1 group), 40 keV (300 mgI kg−1 group) and 45 keV (300 mgI kg−1 group), respectively with good consistency between the two reviewers (p > 0.05). The 40 keV images in the 300 mgI kg−1 group had similar ΔCT (469.77 ± 86.95 HU vs 398.54 ± 73.68 HU) and CNR (15.52 ± 3.32 vs 18.78 ± 6.71) values as the 70 keV images in the 600 mgI kg−1) group but higher SNR values (30.19 ± 4.41 vs 16.91 ± 11.12, p < 0,05) Conclusion: Contrast dose may be reduced by 50% while maintaining image quality by using lower energy images combined with ASIR in renal dual-energy CTA. Advances in knowledge: Combined with ASIR and energy spectrum, can reduce the amount of contrast dose in renal CTA.

Deep-learning-based direct synthesis of low-energy virtual monoenergetic images with multi-energy CT

2021 ◽  
Vol 8 (05) ◽  
Author(s):  
Hao Gong ◽  
Jeffrey F. Marsh ◽  
Karen N. D’Souza ◽  
Nathan R. Huber ◽  
Kishore Rajendran ◽  
...  
Keyword(s):  
Deep Learning ◽  
Direct Synthesis ◽  
Low Energy ◽  
Virtual Monoenergetic Images ◽  
Monoenergetic Images

Image Quality on Dual-energy CTPA Virtual Monoenergetic Images

2018 ◽  
Vol 25 (8) ◽  
pp. 1075-1086 ◽  
Author(s):  
Bari Dane ◽  
Hersh Patel ◽  
Thomas O'Donnell ◽  
Francis Girvin ◽  
Geraldine Brusca-Augello ◽  
...  
Keyword(s):  
Image Quality ◽  
Dual Energy ◽  
Virtual Monoenergetic Images ◽  
Monoenergetic Images

scholarly journals Iodine load reduction in dual-energy spectral CT portal venography with low energy images combined with adaptive statistical iterative reconstruction

2019 ◽  
Vol 92 (1100) ◽  
pp. 20180414
Author(s):  
Dong Han ◽  
Xiaoxia Chen ◽  
Yuxin Lei ◽  
Chunling Ma ◽  
Jieli Zhou ◽  
...  
Keyword(s):  
Image Quality ◽  
Portal Vein ◽  
Dual Energy ◽  
Spectral Ct ◽  
Adaptive Statistical Iterative Reconstruction ◽  
Contrast Dose ◽  
Statistical Iterative Reconstruction ◽  
Group A ◽  
Group B ◽  
Portal Venography

Objective: To study the application of using low energy images combined with adaptive statistical iterative reconstruction (ASiR) in dual-energy spectral CT portal venography (CTPV) to reduce iodine load. Methods: 41 patients for CTPV were prospectively and randomly divided into two groups. Group A ( n = 21) used conventional 120 kVp scanning protocol with contrast dose at 0.6 gI/kg while group B ( n = 20) used dual-energy spectral imaging with reduced contrast dose at 0.3 gI/kg. The 120 kVp images in Group A and 50 keV images in Group B were reconstructed with 40% ASiR. The contrast-to-noise ratio of portal vein was calculated. The image quality and the numbers of intrahepatic portal vein branches were evaluated by two experienced radiologists using a 5-point scoring system. Results: Group B reduced iodine load by 52% compared to Group A (17.21 ± 3.30 gI vs 35.80 ± 6.18 gI, p < 0.001). All images in both groups were acceptable for diagnosis. CT values and standard deviations in portal veins of Group B were higher than Group A (all p < 0.05); There were no statistical differences in contrast-to-noise ratio, image quality score and the number of observed portal vein branches between the two groups (all p > 0.05), and the two observers had excellent agreement in image quality assessment (all κ > 0.75). Conclusion: The use of 50 keV images in dual-energy spectral CTPV with ASiR reduces total iodine load by 52% while maintaining good image quality. Advances in knowledge: Spectral CT images combined with ASiR can be used in low contrast dose CTPV portal venography to maintain image quality and reduce contrast dose.

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