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Wang M, Chen H, Ma Y, Bai R, Gao S, Yang L, Guo W, Zhang C, Kang C, Lan Y, Sun Y, Zhang Y, Xiao X, Hou Y. Dual-layer spectral-detector CT for detecting liver steatosis by using proton density fat fraction as reference. Insights Imaging 2024; 15:210. [PMID: 39145877 PMCID: PMC11327236 DOI: 10.1186/s13244-024-01716-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 04/15/2024] [Indexed: 08/16/2024] Open
Abstract
OBJECTIVES To evaluate the diagnostic accuracy of liver dual-layer spectral-detector CT (SDCT) derived parameters of liver parenchyma for grading steatosis with reference to magnetic resonance imaging-based proton density fat fraction (MRI-PDFF). METHODS Altogether, 320 consecutive subjects who underwent MRI-PDFF and liver SDCT examinations were recruited and prospectively enrolled from four Chinese hospital centers. Participants were classified into normal (n = 152), mild steatosis (n = 110), and moderate/severe(mod/sev) steatosis (n = 58) groups based on MRI-PDFF. SDCT liver parameters were evaluated using conventional polychromatic CT images (CTpoly), virtual mono-energetic images at 40 keV (CT40kev), the slope of the spectral attenuation curve (λ), the effective atomic number (Zeff), and liver to spleen attenuation ratio (L/S ratio). Linearity between SDCT liver parameters and MRI-PDFF was examined using Spearman correlation. Cutoff values for SDCT liver parameters in determining steatosis grades were identified using the area under the receiver-operating characteristic curve analyses. RESULTS SDCT liver parameters demonstrated a strong correlation with PDFF, particularly Zeff (rs = -0.856; p < 0.001). Zeff achieved an area under the curve (AUC) of 0.930 for detecting the presence of steatosis with a sensitivity of 89.4%, a specificity of 82.4%, and an AUC of 0.983 for detecting mod/sev steatosis with a sensitivity of 93.1%, a specificity of 93.5%, the corresponding cutoff values were 7.12 and 6.94, respectively. Zeff also exhibited good diagnostic performance for liver steatosis grading in subgroups, independent of body mass index. CONCLUSION SDCT liver parameters, particularly Zeff, exhibit excellent diagnostic accuracy for grading steatosis. CRITICAL RELEVANCE STATEMENT Dual-layer SDCT parameter, Zeff, as a more convenient and accurate imaging biomarker may serve as an alternative indicator for MRI-based proton density fat fraction, exploring the stage and prognosis of liver steatosis, and even metabolic risk assessment. KEY POINTS Liver biopsy is the standard for grading liver steatosis, but is limited by its invasive nature. The diagnostic performance of liver steatosis using SDCT-Zeff outperforms conventional CT parameters. SDCT-Zeff accurately and noninvasively assessed the grade of liver steatosis.
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Affiliation(s)
- Min Wang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China
| | - Hongyu Chen
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China
| | - Yue Ma
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China
| | - Ruobing Bai
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China
| | - Sizhe Gao
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China
| | - Linlin Yang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China
| | - Wenli Guo
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China
| | - Cong Zhang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China
| | - Chengjun Kang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China
| | - Yu Lan
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China
| | - Yanqiu Sun
- Department of Radiology, Qinghai Provincial People's Hospital, Qinghai, P.R. China
| | - Yonggao Zhang
- Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Xigang Xiao
- Department of Radiology, The First Affiliated Hospital of Harbin Medical University, Harbin, P.R. China
| | - Yang Hou
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, P.R. China.
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Mellander H, Bengtsson P, Fransson V, Ramgren B, Undrén P, Drake M, Ydström K, Lätt J, Hilal A, Wassélius J, Ullberg T. Virtual monoenergetic images by spectral detector computed tomography may improve image quality and diagnostic ability for ischemic lesions in acute ischemic stroke. Acta Radiol 2023; 64:1631-1640. [PMID: 36255120 PMCID: PMC10588276 DOI: 10.1177/02841851221130612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 09/08/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND Acute ischemic lesions are challenging to detect by conventional computed tomography (CT). Virtual monoenergetic images may improve detection rates by increased tissue contrast. PURPOSE To compare the ability to detect ischemic lesions of virtual monoenergetic with conventional images in patients with acute stroke. MATERIAL AND METHODS We included consecutive patients at our center that underwent brain CT in a spectral scanner for suspicion of acute stroke, onset <12 h, with or without (negative controls) a confirmed cortical ischemic lesion in the initial scan or a follow-up CT or magnetic resonance imaging. Attenuation was measured in predefined areas in ischemic gray (guided by follow-up exams), normal gray, and white matter in conventional images and retrieved in spectral diagrams for the same locations in monoenergetic series at 40-200 keV. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Visual assessment of diagnostic measures was performed by independent review by two neuroradiologists blinded to reconstruction details. RESULTS In total, 29 patients were included (January 2018 to July 2019). SNR was higher in virtual monoenergetic compared to conventional images, significantly at 60-150 keV. CNR between ischemic gray and normal white matter was higher in monoenergetic images at 40-70 keV compared to conventional images. Virtual monoenergetic images received higher scores in overall image quality. The sensitivity for diagnosing acute ischemia was 93% and 97%, respectively, for the reviewers, compared to 55% of the original report based on conventional images. CONCLUSION Virtual monoenergetic reconstructions of spectral CIs may improve image quality and diagnostic ability in stroke assessment.
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Affiliation(s)
- Helena Mellander
- Department of Neuroradiology and Odontology, Center for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
- Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Pär Bengtsson
- Department of Neuroradiology and Odontology, Center for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
- Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Veronica Fransson
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Malmö, Sweden
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
| | - Birgitta Ramgren
- Department of Neuroradiology and Odontology, Center for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
- Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Per Undrén
- Department of Neuroradiology and Odontology, Center for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
- Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Mattias Drake
- Department of Neuroradiology and Odontology, Center for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
- Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Kristina Ydström
- Department of Clinical Sciences, Lund University, Lund, Sweden
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Malmö, Sweden
| | - Jimmy Lätt
- Center for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - Amir Hilal
- Department of Neuroradiology and Odontology, Center for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
- Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Johan Wassélius
- Department of Neuroradiology and Odontology, Center for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
- Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Teresa Ullberg
- Department of Neuroradiology and Odontology, Center for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
- Department of Clinical Sciences, Lund University, Lund, Sweden
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Metal artifact reduction by virtual monoenergetic reconstructions from spectral brain CT. Eur J Radiol Open 2023; 10:100479. [PMID: 36819113 PMCID: PMC9932346 DOI: 10.1016/j.ejro.2023.100479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 01/29/2023] [Indexed: 02/05/2023] Open
Abstract
Purpose Conventional computed tomography (CT) images are severely affected by metal artifacts in patients with intracranial coils. Monoenergetic images have been suggested to reduce metal artifacts.The aim of this study was to assess metal artifacts in virtual monoenergetic images (VMIs) reconstructed from spectral brain CT. Methods Thirty-two consecutive patients with intracranial coils examined by spectral non contrast brain CT (NCCT) at our center between November 2017 and April 2019 were included. Attenuation and standard deviations were measured in regions of interest (ROIs) at predefined areas in artifact-free and artifact-affected areas. Measurements were performed in conventional polyenergetic images (CIs) and the corresponding data for VMIs were retrieved through spectral diagrams for the each ROI. Subjective analysis was performed by visual grading of CIs and specific VMIs by two neuroradiologists, independently. Results In artefact-affected image areas distal from the metal objects, the attenuation values decreased with higher energy level VMIs. The same effect was not seen for artefact-affected image areas close to the metal.Subjective rating of the artefact severity was significantly better in VMIs at 50 keV for one of the two reviewers compared to the CIs. Overall image quality and tissue differentiation scores were significantly higher for both reviewers in VMIs at 60 and 70 keV compared to CIs. Conclusion Our quantitative and qualitative image analysis shown that there is a small significant reduction of intracranial coils artifacts severity by all monoenergetic reconstructions from 50 to 200 keV with preserved or increased overall subjective image quality compared to conventional images.
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Key Words
- Aneurysm
- CIs, conventional images
- CSF, cerebrospinal fluid
- CT, computed tomography
- DECT, dual energy computed tomography
- DLP, dose length product
- DSA, digital subtraction angiography
- Diagnostic imaging
- HU, Hounsfield units
- IQR, interquartile range
- MRI, magnetic resonance imaging
- Metal artifacts
- Monoenergetic imaging
- PACS, Picture Archiving and Communication System
- ROI, region of interest
- SD, standard deviation
- SNR, signal-to-noise ratio
- VMIs, virtual monoenergetic images
- WM, white matter
- X-ray computed tomography
- keV, kiloelectron volt
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Yoon H, Kang Y, Kim HJ, Lee E, Ahn JM, Lee JW. Dual-layer spectral detector CT arthrography of the shoulder: assessment of image quality and value in differentiating calcium from iodine. Acta Radiol 2023; 64:638-647. [PMID: 35300534 DOI: 10.1177/02841851221087991] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Dual-layer spectral detector computed tomography (DLCT) may potentially improve CT arthrography through enhanced image quality and analysis of the chemical composition of tissue. PURPOSE To evaluate the image quality of monoenergetic reconstructions from DLCT arthrography of the shoulder and assess the additional diagnostic value in differentiating calcium from iodine. MATERIAL AND METHODS Images from consecutive shoulder DLCT arthrography examinations performed between December 2016 and February 2018 were retrospectively reviewed for hyperattenuating lesions within the labrum and tendons. The mean attenuation of the target lesion, noise, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) of the virtual monoenergetic images obtained at 40-200 keV were compared with conventional 140-kVp images. Two evaluators independently classified each target lesion as contrast media or calcification, without and with DLCT spectral data. Receiver operating curve (ROC) analysis was performed to assess the diagnostic performance of shoulder DLCT arthrography, without and with the aid of spectral data. RESULTS The study included 20 target lesions (18 DLCT arthrography examinations of 17 patients). The SNRs of the monoenergetic images at 40-60 keV were significantly higher than those of conventional images (P < 0.05). The CNRs of the monoenergetic images at 40-70 keV were significantly higher than those of conventional images (P < 0.001). The ability to differentiate calcium from iodine, without and with DLCT spectral data, did not significantly differ (P = 0.441 and P = 0.257 for reviewers 1 and 2, respectively). CONCLUSION DLCT had no additive value in differentiating calcium from iodine in small, hyperattenuating lesions in the labrum and tendons.
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Affiliation(s)
- Hyeyoung Yoon
- Department of Radiology, 65462Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Yusuhn Kang
- Department of Radiology, 65462Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Hyo Jin Kim
- Department of Radiology, 65462Seoul National University Bundang Hospital, Seongnam, Republic of Korea.,Department of Radiology, Seoul Metropolitan Government - Seoul National University Boramae Medical Center, 65633Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Eugene Lee
- Department of Radiology, 65462Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Joong Mo Ahn
- Department of Radiology, 65462Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Joon Woo Lee
- Department of Radiology, 65462Seoul National University Bundang Hospital, Seongnam, Republic of Korea
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Zhao H, Liang P, Yong L, Cheng M, Zhang Y, Huang M, Gao J. Development and external validation of a radiomics model for assessment of HER2 positivity in men and women presenting with gastric cancer. Insights Imaging 2023; 14:20. [PMID: 36720737 PMCID: PMC9889592 DOI: 10.1186/s13244-022-01361-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 12/19/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND To develop and externally validate a conventional CT-based radiomics model for identifying HER2-positive status in gastric cancer (GC). METHODS 950 GC patients who underwent pretreatment CT were retrospectively enrolled and assigned into a training cohort (n = 388, conventional CT), an internal validation cohort (n = 325, conventional CT) and an external validation cohort (n = 237, dual-energy CT, DECT). Radiomics features were extracted from venous phase images to construct the "Radscore". On the basis of univariate and multivariate analyses, a conventional CT-based radiomics model was built in the training cohort, combining significant clinical-laboratory characteristics and Radscore. The model was assessed and validated regarding its diagnostic effectiveness and clinical practicability using AUC and decision curve analysis, respectively. RESULTS Location, clinical TNM staging, CEA, CA199, and Radscore were independent predictors of HER2 status (all p < 0.05). Integrating these five indicators, the proposed model exerted a favorable diagnostic performance with AUCs of 0.732 (95%CI 0.683-0.781), 0.703 (95%CI 0.624-0.783), and 0.711 (95%CI 0.625-0.798) observed for the training, internal validation, and external validation cohorts, respectively. Meanwhile, the model would offer more net benefits than the default simple schemes and its performance was not affected by the age, gender, location, immunohistochemistry results, and type of tissue for confirmation (all p > 0.05). CONCLUSIONS The conventional CT-based radiomics model had a good diagnostic performance of HER2 positivity in GC and the potential to generalize to DECT, which is beneficial to simplify clinical workflow and help clinicians initially identify potential candidates who might benefit from HER2-targeted therapy.
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Affiliation(s)
- Huiping Zhao
- grid.440288.20000 0004 1758 0451Department of CT, Shaanxi Provincial People’s Hospital, No. 256, Youyi West Road, Xi’an, 710068 Shaanxi Province China ,grid.412633.10000 0004 1799 0733Department of Radiology, The First Affiliated Hospital of Zhengzhou University, No. 1, East Jianshe Road, Zhengzhou, 450052 Henan Province China ,Henan Key Laboratory of Image Diagnosis and Treatment for Digestive System Tumor & Henan International Joint Laboratory of Medical Imaging & Henan Engineering Laboratory of Tumor Imaging & Henan Key Laboratory of CT Imaging & Zhengzhou Key Laboratory of Medical Imaging Technology and Diagnosis, No. 1, East Jianshe Road, Zhengzhou, 450052 Henan Province China
| | - Pan Liang
- grid.412633.10000 0004 1799 0733Department of Radiology, The First Affiliated Hospital of Zhengzhou University, No. 1, East Jianshe Road, Zhengzhou, 450052 Henan Province China ,Henan Key Laboratory of Image Diagnosis and Treatment for Digestive System Tumor & Henan International Joint Laboratory of Medical Imaging & Henan Engineering Laboratory of Tumor Imaging & Henan Key Laboratory of CT Imaging & Zhengzhou Key Laboratory of Medical Imaging Technology and Diagnosis, No. 1, East Jianshe Road, Zhengzhou, 450052 Henan Province China
| | - Liuliang Yong
- grid.412633.10000 0004 1799 0733Department of Radiology, The First Affiliated Hospital of Zhengzhou University, No. 1, East Jianshe Road, Zhengzhou, 450052 Henan Province China ,Henan Key Laboratory of Image Diagnosis and Treatment for Digestive System Tumor & Henan International Joint Laboratory of Medical Imaging & Henan Engineering Laboratory of Tumor Imaging & Henan Key Laboratory of CT Imaging & Zhengzhou Key Laboratory of Medical Imaging Technology and Diagnosis, No. 1, East Jianshe Road, Zhengzhou, 450052 Henan Province China
| | - Ming Cheng
- Henan Key Laboratory of Image Diagnosis and Treatment for Digestive System Tumor & Henan International Joint Laboratory of Medical Imaging & Henan Engineering Laboratory of Tumor Imaging & Henan Key Laboratory of CT Imaging & Zhengzhou Key Laboratory of Medical Imaging Technology and Diagnosis, No. 1, East Jianshe Road, Zhengzhou, 450052 Henan Province China ,grid.412633.10000 0004 1799 0733Department of Medical Information, The First Affiliated Hospital of Zhengzhou University, No. 1, East Jianshe Road, Zhengzhou, 450052 Henan Province China
| | - Yan Zhang
- grid.440288.20000 0004 1758 0451Department of CT, Shaanxi Provincial People’s Hospital, No. 256, Youyi West Road, Xi’an, 710068 Shaanxi Province China
| | - Minggang Huang
- grid.440288.20000 0004 1758 0451Department of CT, Shaanxi Provincial People’s Hospital, No. 256, Youyi West Road, Xi’an, 710068 Shaanxi Province China
| | - Jianbo Gao
- grid.412633.10000 0004 1799 0733Department of Radiology, The First Affiliated Hospital of Zhengzhou University, No. 1, East Jianshe Road, Zhengzhou, 450052 Henan Province China ,Henan Key Laboratory of Image Diagnosis and Treatment for Digestive System Tumor & Henan International Joint Laboratory of Medical Imaging & Henan Engineering Laboratory of Tumor Imaging & Henan Key Laboratory of CT Imaging & Zhengzhou Key Laboratory of Medical Imaging Technology and Diagnosis, No. 1, East Jianshe Road, Zhengzhou, 450052 Henan Province China
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Image-Quality Assessment of Polyenergetic and Virtual Monoenergetic Reconstructions of Unenhanced CT Scans of the Head: Initial Experiences with the First Photon-Counting CT Approved for Clinical Use. Diagnostics (Basel) 2022; 12:diagnostics12020265. [PMID: 35204356 PMCID: PMC8871064 DOI: 10.3390/diagnostics12020265] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 01/14/2022] [Accepted: 01/19/2022] [Indexed: 01/31/2023] Open
Abstract
In 2021, the first clinical photon-counting CT (PCCT) was introduced. The purpose of this study is to evaluate the image quality of polyenergetic and virtual monoenergetic reconstructions in unenhanced PCCTs of the head. A total of 49 consecutive patients with unenhanced PCCTs of the head were retrospectively included. The signals ± standard deviations of the gray and white matter were measured at three different locations in axial slices, and a measure of the artifacts below the cranial calvaria and in the posterior fossa between the petrous bones was also obtained. The signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) were calculated for all reconstructions. In terms of the SNRs and CNRs, the polyenergetic reconstruction is superior to all virtual monoenergetic reconstructions (p < 0.001). In the MERs, the highest SNR is found in the 70 keV MER, and the highest CNR is in the 65 keV MER. In terms of artifacts below the cranial calvaria and in the posterior fossa, certain MERs are superior to polyenergetic reconstruction (p < 0.001). The PCCT provided excellent image contrast and low-noise profiles for the differentiation of the grey and white matter. Only the artifacts below the calvarium and in the posterior fossa still underperform, which is attributable to the lack of an artifact reduction algorithm in image postprocessing. It is conceivable that the usual improvements in image postprocessing, especially with regard to glaring artifacts, will lead to further improvements in image quality.
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van Ommen F, Kauw F, Bennink E, Heit JJ, Wolman DN, Dankbaar JW, de Jong HWAM, Wintermark M. Image Quality of Virtual Monochromatic Reconstructions of Noncontrast CT on a Dual-Source CT Scanner in Adult Patients. Acad Radiol 2021; 28:e323-e330. [PMID: 32616420 DOI: 10.1016/j.acra.2020.05.038] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 05/13/2020] [Accepted: 05/30/2020] [Indexed: 12/26/2022]
Abstract
RATIONALE AND OBJECTIVES To evaluate the image quality of virtual monochromatic images (VMI) reconstructed from dual-energy dual-source noncontrast head CT with different reconstruction kernels. MATERIALS AND METHODS Twenty-five consecutive adult patients underwent noncontrast dual-energy CT. VMI were retrospectively reconstructed at 5-keV increments from 40 to 140 keV using quantitative and head kernels. CT-number, noise levels (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in the gray and white matter and artifacts using the posterior fossa artifact index (PFAI) were evaluated. RESULTS CT-number increased with decreasing VMI energy levels, and SD was lowest at 85 keV. SNR was maximized at 80 keV and 85 keV for the head and quantitative kernels, respectively. CNR was maximum at 40 keV; PFAI was lowest at 90 (head kernel) and 100 (quantitative kernel) keV. Optimal VMI image quality was significantly better than conventional CT. CONCLUSION Optimal image quality of VMI energies can improve brain parenchymal image quality compared to conventional CT but are reconstruction kernel dependent and depend on indication for performing noncontrast CT.
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Affiliation(s)
- Fasco van Ommen
- Department of Neuroradiology, Stanford University, Palo Alto, CA; Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Mail E01.132, P.O. Box 85500, Utrecht 3508GA, the Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands.
| | - Frans Kauw
- Department of Neuroradiology, Stanford University, Palo Alto, CA; Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Mail E01.132, P.O. Box 85500, Utrecht 3508GA, the Netherlands
| | - Edwin Bennink
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Mail E01.132, P.O. Box 85500, Utrecht 3508GA, the Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Jeremy J Heit
- Department of Neuroradiology, Stanford University, Palo Alto, CA
| | - Dylan N Wolman
- Department of Neuroradiology, Stanford University, Palo Alto, CA
| | - Jan Willem Dankbaar
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Mail E01.132, P.O. Box 85500, Utrecht 3508GA, the Netherlands
| | - Hugo W A M de Jong
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Mail E01.132, P.O. Box 85500, Utrecht 3508GA, the Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Max Wintermark
- Department of Neuroradiology, Stanford University, Palo Alto, CA
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Detection of Perfusion Deficits in Multiphase Computed Tomography Angiography-A Stroke Imaging Technique Based on Iodine Mapping on Spectral Computed Tomography: Initial Findings. J Comput Assist Tomogr 2021; 45:618-624. [PMID: 34176878 DOI: 10.1097/rct.0000000000001173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE The purpose of this study was to explore a novel method for brain tissue differentiation using quantitative analysis of multiphase computed tomography (CT) angiography (MP-CTA) on spectral CT, to assess whether it can distinguish underperfused from normal tissue, using CT perfusion (CTP) as reference. METHODS Noncontrast CT and MP-CTA images from 10 patients were analyzed in vascular regions through measurements of Hounsfield unit (HU) at 120 kV, HU at 40 keV, and iodine density. Regions were categorized as normal or ischemic according to CTP. Hounsfield unit and iodine density were compared regarding ability to separate normal and ischemic tissue, the difference in maximum time derivative of the right over left hemisphere ratio. RESULTS Iodine density had the highest maximum time derivatives and generated the largest mean separation between normal and ischemic tissue. CONCLUSIONS The method can be used to categorize tissue as normal or underperfused. Using iodine quantification seems to give a more distinct differentiation of perfusion defects compared with conventional HU.
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Wang G, Gao Q, Wang Z, Lu X, Yu S, Jin Z. Reduction of microwave ablation needle related metallic artifacts using virtual monoenergetic images from dual-layer detector spectral CT in a rabbit model with VX2 tumor. Sci Rep 2021; 11:9295. [PMID: 33927327 PMCID: PMC8085209 DOI: 10.1038/s41598-021-88853-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 04/16/2021] [Indexed: 12/03/2022] Open
Abstract
The purpose of the study was to investigate the application of virtual monoenergetic images (VMIs) in reducing metal artifacts in rabbit VX2 liver cancer models treated with microwave ablation (MWA) therapy. A total of 31 VX2 liver cancer models that accepted CT-guided percutaneous microwave ablation were analyzed. Conventional images (CIs) with the most severe metallic artifacts and their corresponding energy levels from 40 to 200 keV with 10 keV increment of VMIs were reconstructed for further analysis. Objective image analysis was assessed by recording the attenuation (HU) and standard deviation of the most severe hyper/hypodense artifacts as well as artifact-impaired liver parenchyma tissue. Two radiologists visually evaluated the extent of artifact reduction, assessed data obtained by a diagnostic evaluation of liver tissues, and appraised the appearance of new artifacts according to the grade score. Statistical analysis was performed to compare the difference between CIs and each energy level of VMIs. For subjective assessment, reductions in hyperdense and hypodense artifacts were observed at 170–200 keV and 160–200 keV, respectively. The outcomes of the diagnostic evaluation of adjacent liver tissue were statistically higher at 140–200 keV for VMIs than for CIs. In terms of objective evaluation results, VMIs at 90–200 keV reduced the corrected attenuation of hyperdense and of artifact-impaired liver parenchyma compared with CIs (P < 0.001). When VMIs at 80–200 keV decreased the hypodense artifacts (P < 0.001). Therefore, we concluded that VMIs at 170–200 keV can obviously decrease the microwave ablation needle-related metal artifacts objectively and subjectively in rabbit VX2 liver cancer models.
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Affiliation(s)
- Guorong Wang
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Qinzong Gao
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China
| | - Zhiwei Wang
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
| | - Xiaomei Lu
- CT Clinical Science, Philips Healthcare, Shenyang, 110016, China
| | - Shenghui Yu
- CT Clinical Science, Philips Healthcare, Beijing, 100600, China
| | - Zhengyu Jin
- Department of Radiology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
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Hamid S, Nasir MU, So A, Andrews G, Nicolaou S, Qamar SR. Clinical Applications of Dual-Energy CT. Korean J Radiol 2021; 22:970-982. [PMID: 33856133 PMCID: PMC8154785 DOI: 10.3348/kjr.2020.0996] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 11/16/2020] [Accepted: 11/22/2020] [Indexed: 01/05/2023] Open
Abstract
Dual-energy CT (DECT) provides insights into the material properties of tissues and can differentiate between tissues with similar attenuation on conventional single-energy imaging. In the conventional CT scanner, differences in the X-ray attenuation between adjacent structures are dependent on the atomic number of the materials involved, whereas in DECT, the difference in the attenuation is dependent on both the atomic number and electron density. The basic principle of DECT is to obtain two datasets with different X-ray energy levels from the same anatomic region and material decomposition based on attenuation differences at different energy levels. In this article, we discuss the clinical applications of DECT and its potential robust improvements in performance and postprocessing capabilities.
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Affiliation(s)
- Saira Hamid
- Department of Radiology, University of British Columbia Hospital, University of British Columbia, Vancouver, Canada.
| | - Muhammad Umer Nasir
- Department of Medical Imaging, Vancouver General Hospital, University of British Columbia, Vancouver, Canada
| | - Aaron So
- Department of Medical Biophyics, Schulich School of Medicine and Dentistry Western University London, Ontario, Canada
| | - Gordon Andrews
- Department of Radiology, University of British Columbia Hospital, University of British Columbia, Vancouver, Canada
| | - Savvas Nicolaou
- Department of Medical Imaging, Vancouver General Hospital, University of British Columbia, Vancouver, Canada
| | - Sadia Raheez Qamar
- Department of Medical Imaging, Sunnybrook Hospital, University of Toronto, Toronto, Canada
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11
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van Ommen F, Bennink E, Dankbaar JW, Kauw F, de Jong HWAM. Improving the Quality of Cerebral Perfusion Maps With Monoenergetic Dual-Energy Computed Tomography Reconstructions. J Comput Assist Tomogr 2021; 45:103-109. [PMID: 32176156 DOI: 10.1097/rct.0000000000000981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE We compared 40- to 70-keV virtual monoenergetic to conventional computed tomography (CT) perfusion reconstructions with respect to quality of perfusion maps. METHODS Conventional CT perfusion (CTP) images were acquired at 80 kVp in 25 patients, and 40- to 70-keV images were acquired with a dual-layer CT at 120 kVp in 25 patients. First, time-attenuation-curve contrast-to-noise ratio was assessed. Second, the perfusion maps of both groups were qualitatively analyzed by observers. Last, the monoenergetic reconstruction with the highest quality was compared with the clinical standard 80-kVp CTP acquisitions. RESULTS Contrast-to-noise ratio was significantly better for 40 to 60 keV as compared with 70 keV and conventional images (P < 0.001). Visually, the difference between the blood volume maps among reconstructions was minimal. The 50-keV perfusion maps had the highest quality compared with the other monoenergetic and conventional maps (P < 0.002). CONCLUSIONS The quality of 50-keV CTP images is superior to the quality of conventional 80- and 120-kVp images.
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Affiliation(s)
| | | | | | - Frans Kauw
- From the Departments of Radiology and Nuclear Medicine
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12
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Ståhl F, Gontu V, Almqvist H, Mazya MV, Falk Delgado A. Performance of dual layer dual energy CT virtual monoenergetic images to identify early ischemic changes in patients with anterior circulation large vessel occlusion. J Neuroradiol 2020; 48:75-81. [PMID: 33340643 DOI: 10.1016/j.neurad.2020.12.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 12/07/2020] [Accepted: 12/07/2020] [Indexed: 10/22/2022]
Abstract
BACKGROUND AND PURPOSE Dual energy CT is increasingly available and used in the standard diagnostic setting of ischemic stroke patients. We aimed to evaluate how different dual energy CT virtual monoenergetic energy levels impact identification of early ischemic changes, compared to conventional polyenergetic CT images. MATERIALS AND METHODS This retrospective single-center study included patients presenting with acute ischemic stroke caused by an occlusion of the intracranial internal carotid artery or proximal middle cerebral artery. Data was gathered on consecutive patients admitted to our institution who underwent initial diagnostic stroke imaging with dual layer dual energy CT and a subsequent follow-up CT one to three days after admission. Automated ASPECTS results from conventional polyenergetic and different virtual monoenergetic energy level reconstructions at admission were generated and compared to reference standard ASPECTS. Confidence intervals (CI) for sensitivity, specificity, negative and positive predictive value were calculated. RESULTS A total of 24 patients were included. Virtual monoenergetic reconstructions of 70 keV had the highest region-based ASPECTS accuracy, 0.90 (sensitivity 0.82 (95% CI 0.72-0.93), specificity 0.92 (0.88-0.97), negative predictive value 0.94 (0.90-0.96)), whereas virtual monoenergetic reconstructions of 40 keV had the lowest, 0.77 (sensitivity 0.34 (0.26-0.42), specificity 0.90 (0.89-0.96), negative predictive value 0.80 (0.77-0.83)). CONCLUSIONS Automated 70 keV ASPECTS had the highest diagnostic accuracy, sensitivity and negative predictive value overall. Our results indicate that virtual monoenergetic energy levels impact the identification of early ischemic changes on CT.
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Affiliation(s)
- Fredrik Ståhl
- Department of Neuroradiology, Karolinska University Hospital, Eugeniavaegen 3, 17176 Stockholm, Sweden; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
| | - Vamsi Gontu
- Department of Neuroradiology, Karolinska University Hospital, Eugeniavaegen 3, 17176 Stockholm, Sweden; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Håkan Almqvist
- Department of Neuroradiology, Karolinska University Hospital, Eugeniavaegen 3, 17176 Stockholm, Sweden; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Michael V Mazya
- Department of Neurology, Karolinska University Hospital, Eugeniavaegen 3, 17176 Stockholm, Sweden; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Anna Falk Delgado
- Department of Neuroradiology, Karolinska University Hospital, Eugeniavaegen 3, 17176 Stockholm, Sweden; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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13
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Lacroix M, Mulé S, Herin E, Pigneur F, Richard P, Zegai B, Baranes L, Djabbari M, Brunetti F, de'Angelis N, Laurent A, Tacher V, Kobeiter H, Luciani A. Virtual unenhanced imaging of the liver derived from 160-mm rapid-switching dual-energy CT (rsDECT): Comparison of the accuracy of attenuation values and solid liver lesion conspicuity with native unenhanced images. Eur J Radiol 2020; 133:109387. [PMID: 33166833 DOI: 10.1016/j.ejrad.2020.109387] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 09/06/2020] [Accepted: 10/27/2020] [Indexed: 11/28/2022]
Abstract
OBJECTIVES To evaluate the reliability of attenuation values of the liver parenchyma and focal liver lesions on virtual unenhanced images from arterial (VUEart) and portal venous phases (VUEport) compared to native unenhanced (NU) attenuation values in patients referred for assessment of malignant liver lesions. METHODS Seventy-three patients with confirmed primary or metastatic liver tumors who underwent a multiphase contrast-enhanced rapid-switching kVp dual-energy CT (rsDECT) were included in this IRB-approved retrospective study. Both qualitative and quantitative analyses - including the lesion-to-liver contrast-to-noise ratio (LL-CNR) - were performed and compared between NU and both VUEart and VUEport images. RESULTS The mean liver attenuation values were significantly lower in VUEart images (56.7 ± 6.7 HU) than in NU images (59.6 ± 7.5 HU, p = 0.008), and were comparable between VUEart and VUEport images (57.9 ± 6 UH, p = 0.38) and between VUEport and NU images (p = 0.051). The mean liver lesions attenuation values were comparable between NU, VUEart and VUEport images (p = 0.60). Strong and significant correlations values were found both in liver lesions and tumor-free parenchyma (r = 0.82-0.91, p < 0.01). The mean LL-CNR was significantly higher in VUEart and VUEport images than in NU images (1.7 ± 1 and 1.6 ± 1.1 vs 0.9 ± 0.6; p < 0.001), but was comparable between VUEart and VUEport images (p > 0.9). Lesion conspicuity was significantly higher in VUEport images than in NU images (p < 0.001). CONCLUSION VUEport images derived from 3rd generation rsDECT could confidently replace NU images in patients undergoing assessment for malignant liver lesions. These images provide comparable attenuation values in both liver lesions and liver parenchyma while reducing the radiation dose and scanning time.
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Affiliation(s)
- Maxime Lacroix
- Service d'Imagerie Médicale, AP-HP, Hôpitaux Universitaires Henri Mondor, 94010 Créteil, France.
| | - Sébastien Mulé
- Service d'Imagerie Médicale, AP-HP, Hôpitaux Universitaires Henri Mondor, 94010 Créteil, France; Faculté de Médecine de Créteil, Université Paris Est Créteil, 94000 Créteil, France; INSERM IMRB, U 955, Equipe 18, Créteil, France
| | - Edouard Herin
- Service d'Imagerie Médicale, AP-HP, Hôpitaux Universitaires Henri Mondor, 94010 Créteil, France
| | - Frédéric Pigneur
- Service d'Imagerie Médicale, AP-HP, Hôpitaux Universitaires Henri Mondor, 94010 Créteil, France
| | | | - Benhalima Zegai
- Service d'Imagerie Médicale, AP-HP, Hôpitaux Universitaires Henri Mondor, 94010 Créteil, France
| | - Laurence Baranes
- Service d'Imagerie Médicale, AP-HP, Hôpitaux Universitaires Henri Mondor, 94010 Créteil, France
| | - Marjan Djabbari
- Service d'Imagerie Médicale, AP-HP, Hôpitaux Universitaires Henri Mondor, 94010 Créteil, France
| | - Francesco Brunetti
- Service de chirurgie digestive, AP-HP, Hôpital Henri Mondor, 94010 Créteil, France
| | - Nicola de'Angelis
- Faculté de Médecine de Créteil, Université Paris Est Créteil, 94000 Créteil, France; Service de chirurgie digestive, AP-HP, Hôpital Henri Mondor, 94010 Créteil, France
| | - Alexis Laurent
- Faculté de Médecine de Créteil, Université Paris Est Créteil, 94000 Créteil, France; Service de chirurgie digestive, AP-HP, Hôpital Henri Mondor, 94010 Créteil, France
| | - Vania Tacher
- Service d'Imagerie Médicale, AP-HP, Hôpitaux Universitaires Henri Mondor, 94010 Créteil, France
| | - Hicham Kobeiter
- Service d'Imagerie Médicale, AP-HP, Hôpitaux Universitaires Henri Mondor, 94010 Créteil, France; Faculté de Médecine de Créteil, Université Paris Est Créteil, 94000 Créteil, France
| | - Alain Luciani
- Service d'Imagerie Médicale, AP-HP, Hôpitaux Universitaires Henri Mondor, 94010 Créteil, France; Faculté de Médecine de Créteil, Université Paris Est Créteil, 94000 Créteil, France; INSERM IMRB, U 955, Equipe 18, Créteil, France
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Garnett R. A comprehensive review of dual-energy and multi-spectral computed tomography. Clin Imaging 2020; 67:160-169. [PMID: 32795784 DOI: 10.1016/j.clinimag.2020.07.030] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Revised: 06/19/2020] [Accepted: 07/27/2020] [Indexed: 01/21/2023]
Abstract
This review will provide a brief introduction to the development of the first Computed Tomography (CT) scan, from the beginnings of x-ray imaging to the first functional CT system introduced by Godfrey Houndsfield. The principles behind photon interactions and the methods by which they can be leveraged to generate dual-energy or multi-spectral CT images are discussed. The clinical applications of these methodologies are investigated, showing the immense potential for dual-energy or multi-spectral CT to change the fields of in-vivo and non-destructive imaging for quantitative analysis of tissues and materials. Lastly the current trends of research for dual-energy and multi-spectral CT are covered, showing that the majority of instrument development is focused on photon counting detectors for mutli-spectral CT and that clinical research is dominated by validation studies for the implementation of dual-energy and multi-spectral CT.
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Affiliation(s)
- Richard Garnett
- McMaster University, TAB 202, 1280 Main St. W., Hamilton, Ontario L8S 4L8, Canada.
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15
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van Ommen F, Dankbaar JW, Zhu G, Wolman DN, Heit JJ, Kauw F, Bennink E, de Jong HWAM, Wintermark M. Virtual monochromatic dual-energy CT reconstructions improve detection of cerebral infarct in patients with suspicion of stroke. Neuroradiology 2020; 63:41-49. [PMID: 32728777 PMCID: PMC7803871 DOI: 10.1007/s00234-020-02492-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 07/05/2020] [Indexed: 12/12/2022]
Abstract
Purpose Early infarcts are hard to diagnose on non-contrast head CT. Dual-energy CT (DECT) may potentially increase infarct differentiation. The optimal DECT settings for differentiation were identified and evaluated. Methods One hundred and twenty-five consecutive patients who presented with suspected acute ischemic stroke (AIS) and underwent non-contrast DECT and subsequent DWI were retrospectively identified. The DWI was used as reference standard. First, virtual monochromatic images (VMI) of 25 patients were reconstructed from 40 to 140 keV and scored by two readers for acute infarct. Sensitivity, specificity, positive, and negative predictive values for infarct detection were compared and a subset of VMI energies were selected. Next, for a separate larger cohort of 100 suspected AIS patients, conventional non-contrast CT (NCT) and selected VMI were scored by two readers for the presence and location of infarct. The same statistics for infarct detection were calculated. Infarct location match was compared per vascular territory. Subgroup analyses were dichotomized by time from last-seen-well to CT imaging. Results A total of 80–90 keV VMI were marginally more sensitive (36.3–37.3%) than NCT (32.4%; p > 0.680), with marginally higher specificity (92.2–94.4 vs 91.1%; p > 0.509) for infarct detection. Location match was superior for VMI compared with NCT (28.7–27.4 vs 19.5%; p < 0.010). Within 4.5 h from last-seen-well, 80 keV VMI more accurately detected infarct (58.0 vs 54.0%) and localized infarcts (27.1 vs 11.9%; p = 0.004) than NCT, whereas after 4.5 h, 90 keV VMI was more accurate (69.3 vs 66.3%). Conclusion Non-contrast 80–90 keV VMI best differentiates normal from infarcted brain parenchyma. Electronic supplementary material The online version of this article (10.1007/s00234-020-02492-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Fasco van Ommen
- Department of Neuroradiology, Stanford University Medical Center, Palo Alto, CA USA
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, E01.132, P.O. Box 85500, 3508 GA Utrecht, the Netherlands
| | - Jan Willem Dankbaar
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, E01.132, P.O. Box 85500, 3508 GA Utrecht, the Netherlands
| | - Guangming Zhu
- Department of Neuroradiology, Stanford University Medical Center, Palo Alto, CA USA
| | - Dylan N. Wolman
- Department of Neuroradiology, Stanford University Medical Center, Palo Alto, CA USA
| | - Jeremy J. Heit
- Department of Neuroradiology, Stanford University Medical Center, Palo Alto, CA USA
| | - Frans Kauw
- Department of Neuroradiology, Stanford University Medical Center, Palo Alto, CA USA
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, E01.132, P.O. Box 85500, 3508 GA Utrecht, the Netherlands
| | - Edwin Bennink
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, E01.132, P.O. Box 85500, 3508 GA Utrecht, the Netherlands
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Hugo W. A. M. de Jong
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, E01.132, P.O. Box 85500, 3508 GA Utrecht, the Netherlands
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Max Wintermark
- Department of Neuroradiology, Stanford University Medical Center, Palo Alto, CA USA
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Zhang D, Xie Y, Wang Y, Guo N, Wang Y, Jin Z, Xue H. Initial Clinical Experience of Virtual Monoenergetic Imaging Improves Stent Visualization in Lower Extremity Run-Off CT Angiography by Dual-Layer Spectral Detector CT. Acad Radiol 2020; 27:825-832. [PMID: 31623997 DOI: 10.1016/j.acra.2019.07.022] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2019] [Revised: 07/06/2019] [Accepted: 07/22/2019] [Indexed: 11/19/2022]
Abstract
RATIONALE AND OBJECTIVES Virtual monoenergetic imaging (VMI) may improve stent visualization in lower extremity run-off computed tomography angiography. The purpose of this study was to evaluate the image quality (IQ) of stents and to determine the optimal kiloelectron volt (keV) level of VMI images for stent evaluation compared to conventional CT images. MATERIALS AND METHODS This study included 32 patients with prior stent placement who underwent run-off computed tomography angiography on a dual-layer spectral detector CT scanner. Thirteen image series were evaluated for each stent, including conventional CT and 12 VMI datasets from 40 keV to 150 keV obtained in 10-keV intervals. Attenuation, SD, contrast-to-noise ratio, and signal-to-noise ratio of the native vessel and the vessel with a stent were evaluated. The diameter of the stent was measured in all 13 image series. The IQ was evaluated by two readers using a five-point scale (1 = poor IQ, 5 = excellent IQ). RESULTS A total of 39 stents in 29 patients were evaluated. Compared to conventional CT, attenuation of the native vessel and the vessel with a stent was higher at 40-60 keV, and the SD was equal or lower at 50-150 keV. Based on the attenuation and SD of VMI images, the contrast-to-noise ratio and signal-to-noise ratio were higher at 40-70 keV, among which the highest ratios were obtained at 40 keV. The stent diameter was equal or larger at 60-150 keV, and the lowest stent diameter underestimation occurred at 100 keV. The IQ was equal or higher, ranging from 60 to 100 keV in comparison with conventional CT, and the highest IQ score occurred at 90 keV. CONCLUSION This quantitative and qualitative assessment of VMI images and conventional images indicated that IQ improvement and more accurate stent lumen evaluation on lower extremity run-off CT angiography can be achieved by dual-layer spectral detector CT.
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Affiliation(s)
- Daming Zhang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 1# Shuaifuyuan, Dongcheng District, Beijing, China
| | - Yanting Xie
- Department of Radiology, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, China
| | - Yining Wang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 1# Shuaifuyuan, Dongcheng District, Beijing, China
| | - Ning Guo
- Clinical Research, Philips Healthcare, Beijing, China
| | - Yun Wang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 1# Shuaifuyuan, Dongcheng District, Beijing, China
| | - Zhengyu Jin
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 1# Shuaifuyuan, Dongcheng District, Beijing, China.
| | - Huadan Xue
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 1# Shuaifuyuan, Dongcheng District, Beijing, China
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Nagayama Y, Tanoue S, Oda S, Sakabe D, Emoto T, Kidoh M, Uetani H, Sasao A, Nakaura T, Ikeda O, Yamada K, Yamashita Y. Metal Artifact Reduction in Head CT Performed for Patients with Deep Brain Stimulation Devices: Effectiveness of a Single-Energy Metal Artifact Reduction Algorithm. AJNR Am J Neuroradiol 2020; 41:231-237. [PMID: 31879332 DOI: 10.3174/ajnr.a6375] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Accepted: 11/15/2019] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Deep brain stimulation electrodes induce massive artifacts on CT images, deteriorating the diagnostic value of examinations. We aimed to investigate the usefulness and potential limitations of a single-energy metal artifact reduction algorithm in head CT performed in patients with implanted deep brain stimulation devices. MATERIALS AND METHODS Thirty-four patients with deep brain stimulation (bilateral, n = 28) who underwent head CT on a 320-detector row scanner and whose images were reconstructed with and without single-energy metal artifact reduction at the examinations were retrospectively included. The severity of artifacts around electrodes was assessed objectively using SDs and an artifact index. Two radiologists subjectively evaluated the severity of artifacts from electrodes, the visibility of electrode localization and surrounding structures, and overall diagnostic confidence on 4-point scales. Background image quality (GM-WM contrast and image noise) was subjectively and objectively assessed. The presence and location of artifacts newly produced by single-energy metal artifact reduction were analyzed. RESULTS Single-energy metal artifact reduction provided lower objective and subjective metal artifacts and improved visualization of electrode localization and surrounding structures and diagnostic confidence compared with non-single-energy metal artifact reduction images, with statistical significance (all, P < .01). No significant differences were observed in GM-WM contrast and image noise (all, P ≥ .11). The new artifacts from single-energy metal artifact reduction were prominently observed in patients with bilateral deep brain stimulation at high convexity, possibly induced by deep brain stimulation leads placed under the parietal scalp. CONCLUSIONS Single-energy metal artifact reduction substantially reduces the metal artifacts from deep brain stimulation electrodes and improves the visibility of intracranial structures without affecting background image quality. However, non-single-energy metal artifact reduction images should be simultaneously reviewed to accurately assess the entire intracranial area, particularly in patients with bilateral deep brain stimulation.
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Affiliation(s)
- Y Nagayama
- From the Department of Diagnostic Radiology (Y.N., S.O., M.K., H.U., A.S., T.N., O.I., Y.Y.)
| | - S Tanoue
- Diagnostic Radiology (S.T.), Graduate School of Life Sciences, Kumamoto University, Kumamoto, Japan
| | - S Oda
- From the Department of Diagnostic Radiology (Y.N., S.O., M.K., H.U., A.S., T.N., O.I., Y.Y.)
| | - D Sakabe
- Department of Central Radiology (D.S., T.E.), Kumamoto University Hospital, Kumamoto, Japan
| | - T Emoto
- Department of Central Radiology (D.S., T.E.), Kumamoto University Hospital, Kumamoto, Japan
| | - M Kidoh
- From the Department of Diagnostic Radiology (Y.N., S.O., M.K., H.U., A.S., T.N., O.I., Y.Y.)
| | - H Uetani
- From the Department of Diagnostic Radiology (Y.N., S.O., M.K., H.U., A.S., T.N., O.I., Y.Y.)
| | - A Sasao
- From the Department of Diagnostic Radiology (Y.N., S.O., M.K., H.U., A.S., T.N., O.I., Y.Y.)
| | - T Nakaura
- From the Department of Diagnostic Radiology (Y.N., S.O., M.K., H.U., A.S., T.N., O.I., Y.Y.)
| | - O Ikeda
- From the Department of Diagnostic Radiology (Y.N., S.O., M.K., H.U., A.S., T.N., O.I., Y.Y.)
| | - K Yamada
- Graduate School of Medical Sciences, and Departments of Neurosurgery (K.Y.)
| | - Y Yamashita
- From the Department of Diagnostic Radiology (Y.N., S.O., M.K., H.U., A.S., T.N., O.I., Y.Y.)
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Albrecht MH, Vogl TJ, Martin SS, Nance JW, Duguay TM, Wichmann JL, De Cecco CN, Varga-Szemes A, van Assen M, Tesche C, Schoepf UJ. Review of Clinical Applications for Virtual Monoenergetic Dual-Energy CT. Radiology 2019; 293:260-271. [DOI: 10.1148/radiol.2019182297] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
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19
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van Ommen F, de Jong H, Dankbaar J, Bennink E, Leiner T, Schilham A. Dose of CT protocols acquired in clinical routine using a dual-layer detector CT scanner: A preliminary report. Eur J Radiol 2019; 112:65-71. [DOI: 10.1016/j.ejrad.2019.01.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Revised: 01/03/2019] [Accepted: 01/12/2019] [Indexed: 11/30/2022]
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