Assessment of 70-keV virtual monoenergetic spectral images in abdominal CT imaging: A comparison study to conventional polychromatic 120-kVp images

Rassouli, Negin; Chalian, Hamid; Rajiah, Prabhakar; Dhanantwari, Amar; Landeras, Luis

doi:10.1007/s00261-017-1151-2

Cited by 53 publications

(21 citation statements)

References 16 publications

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“…In terms of background attenuation, different in vivo phantom and in vivo studies of monoenergetic extrapolation of DECT have demonstrated a lowest level of image noise at 70 keV. 10,[12][13][14] In our study, low keV (70 keV) reconstruction also demonstrates the lowest image noise compared to both high keV (150 keV) reconstruction and SECT. However, in terms of mean attenuation values at the site of greatest artifact, 150 keV have shown significantly higher values in the surrounding muscle and fat compared to both 70 keV and SECT.…”

Section: Discussionsupporting

confidence: 49%

Metal artifact reduction by monoenergetic extrapolation of dual-energy CT in patients with metallic implants

Lee

Cheng

Chu

et al. 2019

J Orthop Surg (Hong Kong)

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The objective of this study is to assess artifact reduction and image quality using dual-energy computed tomography (DECT) and metal artifact reduction techniques in patients with metallic implants. Methods: Forty patients with metallic implants, who had targeted CT performed by DECT during March to September 2018, were prospectively recruited. Post-processing with monoenergetic extrapolation at 70 and 150 keV was performed. Forty matched controls with metallic implants with single-energy CT (SECT) performed were selected. Attenuation value, noise, and signal-tonoise ratio (SNR) at the site of maximal artifact were measured at muscle and fat areas. Image quality of three sets of images (70 keV, 150 keV, and SECT) was assessed by two independent reviewers using a 5-point Likert-type scale. Statistical analysis of measured values, Likert-type scales, and radiation doses (volume CT dose index (CTDI vol)) of DECT and SECT were performed with Mann-Whitney U test. Results: As compared to SECT, high keV reconstruction of DECT show (1) significantly higher values within muscle and fat surrounding the implant (DECT vs. SECT-muscle: À96 Hounsfield units (HU) vs. À405 HU, fat: À115 HU vs. À301 HU; p < 0.001), (2) significantly lower mean image noise (75 HU vs. 129 HU; p ¼ 0.02), and (3) higher SNR (À0.8 vs. À4.3; p < 0.001). In addition, image quality of high keV reconstruction was rated superior to the other two groups on Likert-type scales (p < 0.001). The mean radiation doses (CTDI vol) were comparable between DECT and SECT (14.2 mGy vs. 19.3 mGy; p ¼ 0.08). Conclusion: For patients with metallic implants, monoenergetic extrapolation of DECT at high keV can reduce metal artifacts, increase SNR, and improve qualitative image quality at comparable radiation dose.

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Section: Discussionsupporting

confidence: 49%

Metal artifact reduction by monoenergetic extrapolation of dual-energy CT in patients with metallic implants

Lee

Cheng

Chu

et al. 2019

J Orthop Surg (Hong Kong)

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“…According to our research, the use of VMIs of 40 keV from SDCT may be an effective way to characterize SPN. Many studies on other types of dual-energy technologies have focused on 70 keV images in disease diagnosis (4,23,25). The reason for this may be that lower keV VMIs have increased image noise, which lowers the potential of these reconstructions for diagnosing disease (26,27).…”

Section: Discussionmentioning

confidence: 99%

The application of dual-layer spectral detector computed tomography in solitary pulmonary nodule identification

Wen

Yue

Shang

et al. 2021

Quant Imaging Med Surg

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Background: Differentiating between malignant solitary pulmonary nodules (SPNs) and other lung diseases remains a substantial challenge. The latest generation of dual-energy computed tomography (CT), which realizes dual-energy technology at the detector level, has clinical potential for distinguishing lung cancer from other benign SPNs. This study aimed to evaluate the performance of dual-layer spectral detector CT (SDCT) for the differentiation of SPNs.Methods: Spectral images of 135 SPNs confirmed by pathology were retrospectively analyzed in both the arterial phase (AP) and the venous phase (VP). Patients were classified into two groups [the malignant group (n=93) and the benign group (n=42)], with the malignant group further divided into small cell lung cancer (SCLC, n=30) and non-small cell lung cancer (NSCLC, n=63) subtypes. The slope of the spectral Hounsfield Unit (HU) curve (λ HU ), normalized iodine concentration (NIC), CT values of 40 keV monochromatic images (CT 40keV ), and normalized arterial enhancement fraction (NAEF) in contrast-enhanced images were calculated and compared between the benign and malignant groups, as well as between the SCLC and NSCLC subgroups. ROC curve analysis was performed to assess the diagnostic performance of the above parameters. Seventy cases were randomly selected and independently measured by two radiologists, and intraclass correlation coefficient (ICC) and Bland-Altman analyses were performed to calculate the reliability of the measurements.Results: Except for NAEF (P=0.23), the values of the parameters were higher in the malignant group than in the benign group (all P<0.05). NIC, λ HU , and CT 40keV performed better in the VP (NIC VP , λ VPHU , and CT VP40keV ) (P<0.001), with an area under the ROC curve (AUC) of 0.93, 0.89, and 0.89 respectively. With respective cutoffs of 0.31, 1.83, and 141.00 HU, the accuracy of NIC VP , λ VPHU , and CT VP40keV was 91.11%, 85.19%, and 88.15%, respectively. In the subgroup differentiating NSCLC and SCLC, the diagnostic performances of NIC AP (AUC =0.89) were greater than other parameters. NIC AP had an accuracy of 86.02% when the cutoff was 0.14. ICC and Bland-Altman analyses indicated that the measurement of SDCT has great reproducibility.Conclusions: Quantitative measures from SDCT can help to differentiate benign from malignant SPNs and may help with the further subclassification of malignant cancer into SCLC and NSCLC.

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“…This generates two data records with different attenuation values based on the corresponding energy levels, which allow the reconstruction o f m a t e r i a l d e c o m p o s i t i o n i m a g e s a n d v i r t u a l monoenergetic images (VMI). VMI demonstrated significantly better signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and subjective score compared to conventional 120-kVp polychromatic images [20].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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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.

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Assessment of 70-keV virtual monoenergetic spectral images in abdominal CT imaging: A comparison study to conventional polychromatic 120-kVp images

Cited by 53 publications

References 16 publications

Metal artifact reduction by monoenergetic extrapolation of dual-energy CT in patients with metallic implants

Metal artifact reduction by monoenergetic extrapolation of dual-energy CT in patients with metallic implants

The application of dual-layer spectral detector computed tomography in solitary pulmonary nodule identification

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

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