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Fink N, Emrich T, Schoepf UJ, Zsarnoczay E, O'Doherty J, Halfmann MC, Griffith JP, Pinos D, Suranyi P, Baruah D, Kabakus IM, Ricke J, Varga-Szemes A. Improved Detection of Small and Low-Density Plaques in Virtual Noncontrast Imaging-based Calcium Scoring at Photon-Counting Detector CT. Radiol Cardiothorac Imaging 2024; 6:e230328. [PMID: 39023373 DOI: 10.1148/ryct.230328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Purpose To investigate the impact of plaque size and density on virtual noncontrast (VNC)-based coronary artery calcium scoring (CACS) using photon-counting detector CT and to provide safety net reconstructions for improved detection of subtle plaques in patients whose VNC-based CACS would otherwise be erroneously zero when compared with true noncontrast (TNC)-based CACS. Materials and Methods In this prospective study, CACS was evaluated in a phantom containing calcifications with different diameters (5, 3, and 1 mm) and densities (800, 400, and 200 mg/cm3) and in participants who underwent TNC and contrast-enhanced cardiac photon-counting detector CT (July 2021-March 2022). VNC images were reconstructed at different virtual monoenergetic imaging (55-80 keV) and quantum iterative reconstruction (QIR) levels (QIR,1-4). TNC scans at 70 keV with QIR off served as the reference standard. In vitro CACS was analyzed using standard settings (3.0-mm sections, kernel Qr36, 130-HU threshold). Calcification detectability and CACS of small and low-density plaques were also evaluated using 1.0-mm sections, kernel Qr44, and 120- or 110-HU thresholds. Safety net reconstructions were defined based on background Agatston scores and evaluated in vivo in TNC plaques initially nondetectable using standard VNC reconstructions. Results The in vivo cohort included 63 participants (57.8 years ± 15.5 [SD]; 37 [59%] male, 26 [41%] female). Correlation and agreement between standard CACSVNC and CACSTNC were higher in large- and medium-sized and high- and medium-density than in low-density plaques (in vitro: intraclass correlation coefficient [ICC] ≥ 0.90; r > 0.9 vs ICC = 0.20-0.48; r = 0.5-0.6). Small plaques were not detectable using standard VNC reconstructions. Calcification detectability was highest using 1.0-mm sections, kernel Qr44, 120- and 110-HU thresholds, and QIR level of 2 or less VNC reconstructions. Compared with standard VNC, using safety net reconstructions (55 keV, QIR 2, 110-HU threshold) for in vivo subtle plaque detection led to higher detection (increased by 89% [50 of 56]) and improved correlation and agreement of CACSVNC with CACSTNC (in vivo: ICC = 0.51-0.61; r = 0.6). Conclusion Compared with TNC-based calcium scoring, VNC-based calcium scoring was limited for small and low-density plaques but improved using safety net reconstructions, which may be particularly useful in patients with low calcium scores who would otherwise be treated based on potentially false-negative results. Keywords: Coronary Artery Calcium CT, Photon-Counting Detector CT, Virtual Noncontrast, Plaque Size, Plaque Density Supplemental material is available for this article. © RSNA, 2024.
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Affiliation(s)
- Nicola Fink
- From the Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MUSC 226, Charleston, SC 29425-2260 (N.F., T.E., U.J.S., E.Z., J.O., J.P.G., D.P., P.S., D.B., I.M.K., A.V.S.); Department of Radiology, University Hospital, LMU Munich, Munich, Germany (N.F., J.R.); Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany (T.E., M.C.H.); German Centre for Cardiovascular Research, Mainz, Germany (T.E.); Medical Imaging Center, Semmelweis University, Budapest, Hungary (E.Z.); and Siemens Medical Solutions, Malvern, Pa (J.O.)
| | - Tilman Emrich
- From the Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MUSC 226, Charleston, SC 29425-2260 (N.F., T.E., U.J.S., E.Z., J.O., J.P.G., D.P., P.S., D.B., I.M.K., A.V.S.); Department of Radiology, University Hospital, LMU Munich, Munich, Germany (N.F., J.R.); Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany (T.E., M.C.H.); German Centre for Cardiovascular Research, Mainz, Germany (T.E.); Medical Imaging Center, Semmelweis University, Budapest, Hungary (E.Z.); and Siemens Medical Solutions, Malvern, Pa (J.O.)
| | - U Joseph Schoepf
- From the Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MUSC 226, Charleston, SC 29425-2260 (N.F., T.E., U.J.S., E.Z., J.O., J.P.G., D.P., P.S., D.B., I.M.K., A.V.S.); Department of Radiology, University Hospital, LMU Munich, Munich, Germany (N.F., J.R.); Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany (T.E., M.C.H.); German Centre for Cardiovascular Research, Mainz, Germany (T.E.); Medical Imaging Center, Semmelweis University, Budapest, Hungary (E.Z.); and Siemens Medical Solutions, Malvern, Pa (J.O.)
| | - Emese Zsarnoczay
- From the Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MUSC 226, Charleston, SC 29425-2260 (N.F., T.E., U.J.S., E.Z., J.O., J.P.G., D.P., P.S., D.B., I.M.K., A.V.S.); Department of Radiology, University Hospital, LMU Munich, Munich, Germany (N.F., J.R.); Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany (T.E., M.C.H.); German Centre for Cardiovascular Research, Mainz, Germany (T.E.); Medical Imaging Center, Semmelweis University, Budapest, Hungary (E.Z.); and Siemens Medical Solutions, Malvern, Pa (J.O.)
| | - Jim O'Doherty
- From the Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MUSC 226, Charleston, SC 29425-2260 (N.F., T.E., U.J.S., E.Z., J.O., J.P.G., D.P., P.S., D.B., I.M.K., A.V.S.); Department of Radiology, University Hospital, LMU Munich, Munich, Germany (N.F., J.R.); Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany (T.E., M.C.H.); German Centre for Cardiovascular Research, Mainz, Germany (T.E.); Medical Imaging Center, Semmelweis University, Budapest, Hungary (E.Z.); and Siemens Medical Solutions, Malvern, Pa (J.O.)
| | - Moritz C Halfmann
- From the Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MUSC 226, Charleston, SC 29425-2260 (N.F., T.E., U.J.S., E.Z., J.O., J.P.G., D.P., P.S., D.B., I.M.K., A.V.S.); Department of Radiology, University Hospital, LMU Munich, Munich, Germany (N.F., J.R.); Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany (T.E., M.C.H.); German Centre for Cardiovascular Research, Mainz, Germany (T.E.); Medical Imaging Center, Semmelweis University, Budapest, Hungary (E.Z.); and Siemens Medical Solutions, Malvern, Pa (J.O.)
| | - Joseph P Griffith
- From the Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MUSC 226, Charleston, SC 29425-2260 (N.F., T.E., U.J.S., E.Z., J.O., J.P.G., D.P., P.S., D.B., I.M.K., A.V.S.); Department of Radiology, University Hospital, LMU Munich, Munich, Germany (N.F., J.R.); Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany (T.E., M.C.H.); German Centre for Cardiovascular Research, Mainz, Germany (T.E.); Medical Imaging Center, Semmelweis University, Budapest, Hungary (E.Z.); and Siemens Medical Solutions, Malvern, Pa (J.O.)
| | - Daniel Pinos
- From the Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MUSC 226, Charleston, SC 29425-2260 (N.F., T.E., U.J.S., E.Z., J.O., J.P.G., D.P., P.S., D.B., I.M.K., A.V.S.); Department of Radiology, University Hospital, LMU Munich, Munich, Germany (N.F., J.R.); Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany (T.E., M.C.H.); German Centre for Cardiovascular Research, Mainz, Germany (T.E.); Medical Imaging Center, Semmelweis University, Budapest, Hungary (E.Z.); and Siemens Medical Solutions, Malvern, Pa (J.O.)
| | - Pal Suranyi
- From the Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MUSC 226, Charleston, SC 29425-2260 (N.F., T.E., U.J.S., E.Z., J.O., J.P.G., D.P., P.S., D.B., I.M.K., A.V.S.); Department of Radiology, University Hospital, LMU Munich, Munich, Germany (N.F., J.R.); Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany (T.E., M.C.H.); German Centre for Cardiovascular Research, Mainz, Germany (T.E.); Medical Imaging Center, Semmelweis University, Budapest, Hungary (E.Z.); and Siemens Medical Solutions, Malvern, Pa (J.O.)
| | - Dhiraj Baruah
- From the Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MUSC 226, Charleston, SC 29425-2260 (N.F., T.E., U.J.S., E.Z., J.O., J.P.G., D.P., P.S., D.B., I.M.K., A.V.S.); Department of Radiology, University Hospital, LMU Munich, Munich, Germany (N.F., J.R.); Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany (T.E., M.C.H.); German Centre for Cardiovascular Research, Mainz, Germany (T.E.); Medical Imaging Center, Semmelweis University, Budapest, Hungary (E.Z.); and Siemens Medical Solutions, Malvern, Pa (J.O.)
| | - Ismail M Kabakus
- From the Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MUSC 226, Charleston, SC 29425-2260 (N.F., T.E., U.J.S., E.Z., J.O., J.P.G., D.P., P.S., D.B., I.M.K., A.V.S.); Department of Radiology, University Hospital, LMU Munich, Munich, Germany (N.F., J.R.); Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany (T.E., M.C.H.); German Centre for Cardiovascular Research, Mainz, Germany (T.E.); Medical Imaging Center, Semmelweis University, Budapest, Hungary (E.Z.); and Siemens Medical Solutions, Malvern, Pa (J.O.)
| | - Jens Ricke
- From the Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MUSC 226, Charleston, SC 29425-2260 (N.F., T.E., U.J.S., E.Z., J.O., J.P.G., D.P., P.S., D.B., I.M.K., A.V.S.); Department of Radiology, University Hospital, LMU Munich, Munich, Germany (N.F., J.R.); Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany (T.E., M.C.H.); German Centre for Cardiovascular Research, Mainz, Germany (T.E.); Medical Imaging Center, Semmelweis University, Budapest, Hungary (E.Z.); and Siemens Medical Solutions, Malvern, Pa (J.O.)
| | - Akos Varga-Szemes
- From the Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MUSC 226, Charleston, SC 29425-2260 (N.F., T.E., U.J.S., E.Z., J.O., J.P.G., D.P., P.S., D.B., I.M.K., A.V.S.); Department of Radiology, University Hospital, LMU Munich, Munich, Germany (N.F., J.R.); Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany (T.E., M.C.H.); German Centre for Cardiovascular Research, Mainz, Germany (T.E.); Medical Imaging Center, Semmelweis University, Budapest, Hungary (E.Z.); and Siemens Medical Solutions, Malvern, Pa (J.O.)
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Lennartz S, Zopfs D, Große Hokamp N. Dual-energy CT revisited: a focused review of clinical use cases. ROFO-FORTSCHR RONTG 2024; 196:794-806. [PMID: 38176436 DOI: 10.1055/a-2203-2945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
Affiliation(s)
- Simon Lennartz
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - David Zopfs
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Nils Große Hokamp
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
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Sharma SP, van der Bie J, van Straten M, Hirsch A, Bos D, Dijkshoorn ML, Booij R, Budde RPJ. Coronary calcium scoring on virtual non-contrast and virtual non-iodine reconstructions compared to true non-contrast images using photon-counting computed tomography. Eur Radiol 2024; 34:3699-3707. [PMID: 37940711 PMCID: PMC11166815 DOI: 10.1007/s00330-023-10402-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 08/17/2023] [Accepted: 09/17/2023] [Indexed: 11/10/2023]
Abstract
OBJECTIVES To compare coronary artery calcification (CAC) scores measured on virtual non-contrast (VNC) and virtual non-iodine (VNI) reconstructions computed from coronary computed tomography angiography (CCTA) using photon-counting computed tomography (PCCT) to true non-contrast (TNC) images. METHODS We included 88 patients (mean age = 59 years ± 13.5, 69% male) who underwent a TNC coronary calcium scan followed by CCTA on PCCT. VNC images were reconstructed in 87 patients and VNI in 88 patients by virtually removing iodine from the CCTA images. For all reconstructions, CAC scores were determined, and patients were classified into risk categories. The overall agreement of the reconstructions was analyzed by Bland-Altman plots and the level of matching classifications. RESULTS The median CAC score on TNC was 27.8 [0-360.4] compared to 8.5 [0.2-101.6] (p < 0.001) on VNC and 72.2 [1.3-398.8] (p < 0.001) on VNI. Bland-Altman plots depicted a bias of 148.8 (ICC = 0.82, p < 0.001) and - 57.7 (ICC = 0.95, p < 0.001) for VNC and VNI, respectively. Of all patients with CACTNC = 0, VNC reconstructions scored 63% of the patients correctly, while VNI scored 54% correctly. Of the patients with CACTNC > 0, VNC and VNI reconstructions detected the presence of coronary calcium in 90% and 92% of the patients. CACVNC tended to underestimate CAC score, whereas CACVNI overestimated, especially in the lower risk categories. According to the risk categories, VNC misclassified 55% of the patients, while VNI misclassified only 32%. CONCLUSION Compared to TNC images, VNC underestimated and VNI overestimated the actual CAC scores. VNI reconstructions quantify and classify coronary calcification scores more accurately than VNC reconstructions. CLINICAL RELEVANCE STATEMENT Photon-counting CT enables spectral imaging, which might obviate the need for non-contrast enhanced coronary calcium scoring, but optimization is necessary for the clinical implementation of the algorithms. KEY POINTS • Photon-counting computed tomography uses spectral information to virtually remove the signal of contrast agents from contrast-enhanced scans. • Virtual non-contrast reconstructions tend to underestimate coronary artery calcium scores compared to true non-contrast images, while virtual non-iodine reconstructions tend to overestimate the calcium scores. • Virtual non-iodine reconstructions might obviate the need for non-contrast enhanced calcium scoring, but optimization is necessary for the clinical implementation of the algorithms.
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Affiliation(s)
- Simran P Sharma
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Judith van der Bie
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marcel van Straten
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Alexander Hirsch
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Daniel Bos
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marcel L Dijkshoorn
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Ronald Booij
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Ricardo P J Budde
- Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
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Haag F, Emmrich SS, Hertel A, Rink JS, Nörenberg D, Schoenberg SO, Froelich MF. Virtual Non-Contrast versus True Native in Photon-Counting CT: Stability of Density of Upper Abdominal Organs and Vessels. Diagnostics (Basel) 2024; 14:1130. [PMID: 38893656 PMCID: PMC11171968 DOI: 10.3390/diagnostics14111130] [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: 03/20/2024] [Revised: 05/10/2024] [Accepted: 05/20/2024] [Indexed: 06/21/2024] Open
Abstract
The clinical use of photon-counting CT (PCCT) allows for the generation of virtual non-contrast (VNC) series from contrast-enhanced images. In routine clinical practice, specific issues such as ruling out acute bleeding require non-contrast images. The aim of this study is to evaluate the use of PCCT-derived VNC reconstructions in abdominal imaging. PCCT scans of 17 patients including early arterial, portal venous and native sequences were enrolled. VNC reconstructions have been calculated. In every sequence and VNC reconstruction, 10 ROIs were measured (portal vein, descending aorta, inferior vena cava, liver parenchyma, spleen parenchyma, erector spinae muscle, subcutaneous adipose tissue, first lumbar vertebral body, air, and psoas muscle) and density values were compared. The VNC reconstructions show significant changes in density compared to the contrast-enhanced images. However, there were no significant differences present between the true non-contrast (TNC) and any VNC reconstructions in the observed organs and vessels. Significant differences (p < 0.05) between the measured mean density values in the TNC versus VNC reconstructions were found in fat and bone tissue. The PCCT-derived VNC reconstructions seemed to be comparable to the TNC images, despite some deviations shown in the adipose tissue and bone structures. However, the further benefits in terms of specific clinical issues need to be evaluated.
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Affiliation(s)
- Florian Haag
- Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1–3, 68167 Mannheim, Germany
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Dobrolinska MM, Koetzier LR, Greuter MJW, Vliegenthart R, van der Bie J, Prakken NHJ, Slart RHJA, Leiner T, Budde RPJ, Mastrodicasa D, Booij R, Fleischmann D, Willemink MJ, van Straten M, van der Werf NR. Feasibility of virtual non-iodine coronary calcium scoring on dual source photon-counting coronary CT angiography: a dynamic phantom study. Eur Radiol 2024:10.1007/s00330-024-10806-4. [PMID: 38789792 DOI: 10.1007/s00330-024-10806-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 03/23/2024] [Accepted: 04/05/2024] [Indexed: 05/26/2024]
Abstract
BACKGROUND The aim of our current systematic dynamic phantom study was first, to optimize reconstruction parameters of coronary CTA (CCTA) acquired on photon counting CT (PCCT) for coronary artery calcium (CAC) scoring, and second, to assess the feasibility of calculating CAC scores from CCTA, in comparison to reference calcium scoring CT (CSCT) scans. METHODS In this phantom study, an artificial coronary artery was translated at velocities corresponding to 0, < 60, and 60-75 beats per minute (bpm) within an anthropomorphic phantom. The density of calcifications was 100 (very low), 200 (low), 400 (medium), and 800 (high) mgHA/cm3, respectively. CCTA was reconstructed with the following parameters: virtual non-iodine (VNI), with and without iterative reconstruction (QIR level 2, QIR off, respectively); kernels Qr36 and Qr44f; slice thickness/increment 3.0/1.5 mm and 0.4/0.2 mm. The agreement in risk group classification between CACCCTA and CACCSCT scoring was measured using Cohen weighted linear κ with 95% CI. RESULTS For CCTA reconstructed with 0.4 mm slice thickness, calcium detectability was perfect (100%). At < 60 bpm, CACCCTA of low, and medium density calcification was underestimated by 53%, and 15%, respectively. However, CACCCTA was not significantly different from CACCSCT of very low, and high-density calcifications. The best risk agreement was achieved when CCTA was reconstructed with QIR off, Qr44f, and 0.4 mm slice thickness (κ = 0.762, 95% CI 0.671-0.853). CONCLUSION In this dynamic phantom study, the detection of calcifications with different densities was excellent with CCTA on PCCT using thin-slice VNI reconstruction. Agatston scores were underestimated compared to CSCT but agreement in risk classification was substantial. CLINICAL RELEVANCE STATEMENT Photon counting CT may enable the implementation of coronary artery calcium scoring from coronary CTA in daily clinical practice. KEY POINTS Photon-counting CTA allows for excellent detectability of low-density calcifications at all heart rates. Coronary artery calcium scoring from coronary CTA acquired on photon counting CT is feasible, although improvement is needed. Adoption of the standard acquisition and reconstruction protocol for calcium scoring is needed for improved quantification of coronary artery calcium to fully employ the potential of photon counting CT.
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Affiliation(s)
- Magdalena M Dobrolinska
- Department of Radiology and Nuclear Medicine Rotterdam, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Medical Imaging Center, Groningen, The Netherlands.
| | - Lennart R Koetzier
- Department of Radiology and Nuclear Medicine Rotterdam, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Radiology Stanford, Stanford University School of Medicine, Stanford, CA, USA
| | - Marcel J W Greuter
- Department of Radiology, University of Groningen, University Medical Center Groningen, Medical Imaging Center, Groningen, The Netherlands
| | - Rozemarijn Vliegenthart
- Department of Radiology, University of Groningen, University Medical Center Groningen, Medical Imaging Center, Groningen, The Netherlands
| | - Judith van der Bie
- Department of Radiology and Nuclear Medicine Rotterdam, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Niek H J Prakken
- Department of Radiology, University of Groningen, University Medical Center Groningen, Medical Imaging Center, Groningen, The Netherlands
| | - Riemer H J A Slart
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Medical Imaging Center, Groningen, The Netherlands
| | - Tim Leiner
- Department of Radiology Rochester, Mayo Clinic, Rochester, MN, USA
| | - Ricardo P J Budde
- Department of Radiology and Nuclear Medicine Rotterdam, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Domenico Mastrodicasa
- Department of Radiology Stanford, Stanford University School of Medicine, Stanford, CA, USA
| | - Ronald Booij
- Department of Radiology and Nuclear Medicine Rotterdam, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Dominik Fleischmann
- Department of Radiology Stanford, Stanford University School of Medicine, Stanford, CA, USA
| | - Martin J Willemink
- Department of Radiology Stanford, Stanford University School of Medicine, Stanford, CA, USA
| | - Marcel van Straten
- Department of Radiology and Nuclear Medicine Rotterdam, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Niels R van der Werf
- Department of Radiology and Nuclear Medicine Rotterdam, Erasmus MC University Medical Center, Rotterdam, The Netherlands
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Zhang J, Li S, Wu L, Wang H, Wang C, Zhou Y, Sui B, Zhao X. Application of Dual-Layer Spectral-Detector Computed Tomography Angiography in Identifying Symptomatic Carotid Atherosclerosis: A Prospective Observational Study. J Am Heart Assoc 2024; 13:e032665. [PMID: 38497470 PMCID: PMC11010034 DOI: 10.1161/jaha.123.032665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 02/20/2024] [Indexed: 03/19/2024]
Abstract
BACKGROUND Dual-layer spectral-detector dual-energy computed tomography angiography (DLCTA) can distinguish components of carotid plaques. Data on identifying symptomatic carotid plaques in patients using DLCTA are not available. METHODS AND RESULTS In this prospective observational study, patients with carotid plaques were enrolled and received DLCTA. The attenuation for both polyenergetic image and virtual monoenergetic images (40, 70, 100, and 140 keV), as well as Z-effective value, were recorded in the noncalcified regions of plaques. Logistic regression models were used to assess the association between attenuations of DLCTA and the presence of symptomatic carotid plaques. In total, 100 participants (mean±SD age, 64.37±8.31 years; 82.0% were men) were included, and 36% of the cases were identified with the symptomatic group. DLCTA parameters were different between 2 groups (symptomatic versus asymptomatic: computed tomography [CT] 40 keV, 152.63 [interquartile range (IQR), 70.22-259.78] versus 256.78 [IQR, 150.34-408.13]; CT 70 keV, 81.28 [IQR, 50.13-119.33] versus 108.87 [IQR, 77.01-165.88]; slope40-140 keV, 0.91 [IQR, 0.35-1.87] versus 1.92 [IQR, 0.96-3.00]; Z-effective value, 7.92 [IQR, 7.53-8.46] versus 8.41 [IQR, 7.94-8.92]), whereas no difference was found in conventional polyenergetic images. The risk of symptomatic plaque was lower in the highest tertiles of attenuations in CT 40 keV (adjusted odds ratio [OR], 0.243 [95% CI, 0.078-0.754]), CT 70 keV (adjusted OR, 0.313 [95% CI, 0.104-0.940]), Z-effective values (adjusted OR, 0.138 [95% CI, 0.039-0.490]), and slope40-140 keV (adjusted OR, 0.157 [95% CI, 0.046-0.539]), with all P values and P trends <0.05. The areas under the curve for CT 40 keV, CT 70 keV, slope 40 to 140 keV, and Z-effective values were 0.64, 0.61, 0.64, and 0.63, respectively. CONCLUSIONS Parameters of DLCTA might help assist in distinguishing symptomatic carotid plaques. Further studies with a larger sample size may address the overlap and improve the diagnostic accuracy.
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Affiliation(s)
- Jia Zhang
- Department of NeurologyBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Sijia Li
- Department of NeurologyBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Lei Wu
- Department of NeurologyBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Haoyuan Wang
- Department of NeurologyBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Chuanying Wang
- Department of NeurologyBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
| | - Yinan Zhou
- CT Clinical SpecialistPhilips HealthcareBeijingChina
| | - Binbin Sui
- China National Clinical Research Center for Neurological DiseasesBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- Tiantan Neuroimaging Center of ExcellenceChina National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Xingquan Zhao
- Department of NeurologyBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijing Tiantan Hospital, Capital Medical UniversityBeijingChina
- Research Unit of Artificial Intelligence in Cerebrovascular DiseaseChinese Academy of Medical SciencesBeijingChina
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7
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Cundari G, Marchitelli L, Pambianchi G, Catapano F, Conia L, Stancanelli G, Catalano C, Galea N. Imaging biomarkers in cardiac CT: moving beyond simple coronary anatomical assessment. LA RADIOLOGIA MEDICA 2024; 129:380-400. [PMID: 38319493 PMCID: PMC10942914 DOI: 10.1007/s11547-024-01771-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 01/03/2024] [Indexed: 02/07/2024]
Abstract
Cardiac computed tomography angiography (CCTA) is considered the standard non-invasive tool to rule-out obstructive coronary artery disease (CAD). Moreover, several imaging biomarkers have been developed on cardiac-CT imaging to assess global CAD severity and atherosclerotic burden, including coronary calcium scoring, the segment involvement score, segment stenosis score and the Leaman-score. Myocardial perfusion imaging enables the diagnosis of myocardial ischemia and microvascular damage, and the CT-based fractional flow reserve quantification allows to evaluate non-invasively hemodynamic impact of the coronary stenosis. The texture and density of the epicardial and perivascular adipose tissue, the hypodense plaque burden, the radiomic phenotyping of coronary plaques or the fat radiomic profile are novel CT imaging features emerging as biomarkers of inflammation and plaque instability, which may implement the risk stratification strategies. The ability to perform myocardial tissue characterization by extracellular volume fraction and radiomic features appears promising in predicting arrhythmogenic risk and cardiovascular events. New imaging biomarkers are expanding the potential of cardiac CT for phenotyping the individual profile of CAD involvement and opening new frontiers for the practice of more personalized medicine.
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Affiliation(s)
- Giulia Cundari
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Viale Regina Elena 324, 00161, Rome, Italy
| | - Livia Marchitelli
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Viale Regina Elena 324, 00161, Rome, Italy
| | - Giacomo Pambianchi
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Viale Regina Elena 324, 00161, Rome, Italy
| | - Federica Catapano
- Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, 4, Pieve Emanuele, 20090, Milano, Italy
- Humanitas Research Hospital IRCCS, Via Alessandro Manzoni, 56, Rozzano, 20089, Milano, Italy
| | - Luca Conia
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Viale Regina Elena 324, 00161, Rome, Italy
| | - Giuseppe Stancanelli
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Viale Regina Elena 324, 00161, Rome, Italy
| | - Carlo Catalano
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Viale Regina Elena 324, 00161, Rome, Italy
| | - Nicola Galea
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Viale Regina Elena 324, 00161, Rome, Italy.
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Risch F, Schwarz F, Kroencke T, Decker JA. Heart rate sensitivity of virtual non-contrast calcium scores derived from photon counting detector CT data: a phantom study. LA RADIOLOGIA MEDICA 2024; 129:401-410. [PMID: 38319495 PMCID: PMC10943147 DOI: 10.1007/s11547-024-01773-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 01/03/2024] [Indexed: 02/07/2024]
Abstract
PURPOSE To assess the reliability of virtual non-contrast (VNC) derived coronary artery calcium quantities in relation to heart rate and the VNC algorithm used compared to reference true non-contrast (TNC), considering several clinically established acquisition modes. MATERIAL AND METHODS An ad hoc built coronary phantom containing four calcified lesions and an iodinated lumen was scanned using three cardiac acquisition modes three times within an anthropomorphic cardiac motion phantom simulating different heart rates (0, 60, 80, 100 bpm) and reconstructed with a conventional (VNCconv) and a calcium-sensitive (VNCpc) VNC algorithm. TNC reference was scanned at 0 bpm with non-iodinated lumen. Calcium scores were assessed in terms of number of lesions detected, Agatston and volume scores and global noise was measured. Paired t-test and Wilcoxon test were performed to test measurements for significant difference. RESULTS For both VNC algorithms used, calcium levels or noise were not significantly affected by heart rate. Measurements on VNCpc reconstructions best reproduced TNC results, but with increased variability (Agatston scores at 0 bpm for TNC, VNCconv, and VNCpc were 47.1 ± 1.1, 6.7 ± 2.8 (p < 0.001), and 45.3 ± 7.6 (p > 0.05), respectively). VNC reconstructions showed lower noise levels compared to TNC, especially for VNCpc (noiseheart on TNC, VNCconv and VNCpc at 0 bpm was 5.0 ± 0.4, 4.5 ± 0.2, 4.2 ± 0.2). CONCLUSION No significant heart rate dependence of VNC-based calcium scores was observed in an intra-reconstruction comparison. VNCpc reproduces TNC scores better than VNCconv without significant differences and decreased noise, however, with an increasing average deviation with rising heart rates. VNC-based CACS should be used with caution as the measures show higher variability compared to reference TNC and therefore hold the potential of incorrect risk categorization.
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Affiliation(s)
- Franka Risch
- Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, Stenglinstr. 2, 86156, Augsburg, Germany
| | - Florian Schwarz
- Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, Stenglinstr. 2, 86156, Augsburg, Germany
- Medical Faculty, Ludwig Maximilian University Munich, Munich, Germany
- Clinic for Diagnostic and Interventional Radiology, Donau-Isar-Klinikum, Deggendorf, Germany
| | - Thomas Kroencke
- Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, Stenglinstr. 2, 86156, Augsburg, Germany.
- Centre for Advanced Analytics and Predictive Sciences (CAAPS), University Augsburg, Augsburg, Germany.
| | - Josua A Decker
- Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, Stenglinstr. 2, 86156, Augsburg, Germany
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9
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Haag NP, Michael AE, Lennartz S, Panknin C, Niehoff JH, Borggrefe J, Shahzadi I, Zwanenburg A, Kroeger JR. Coronary Artery Calcium Scoring Using Virtual Versus True Noncontrast Images From Photon-Counting Coronary CT Angiography. Radiology 2024; 310:e230545. [PMID: 38530174 DOI: 10.1148/radiol.230545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Background Coronary artery calcium scoring (CACS) for coronary artery disease requires true noncontrast (TNC) CT alongside contrast-enhanced coronary CT angiography (CCTA). Photon-counting CT provides an algorithm (PureCalcium) for reconstructing virtual noncontrast images from CCTA specifically for CACS. Purpose To assess CACS differences based on PureCalcium images derived from contrast-enhanced photon-counting CCTA compared with TNC images and evaluate the impact of these differences on the clinically relevant classification of patients into plaque burden groups. Materials and Methods Photon-counting CCTA images acquired between August 2022 and May 2023 were retrospectively identified. Agatston scores were derived from both TNC and PureCalcium images and tested for differences with use of the Wilcoxon signed-rank test. The agreement was assessed with use of equivalence tests, Bland-Altman analysis, and intraclass correlation coefficient. Plaque burden groups were established based on Agatston scores, and agreement was evaluated using weighted Cohen kappa. The dose-length product was analyzed. Results Among 170 patients (mean age, 63 years ± 13 [SD]; 92 male), 111 had Agatston scores higher than 0. Median Agatston scores did not differ between TNC and PureCalcium images (4.8 [IQR, 0-84.4; range, 0.0-2151.8] vs 2.7 [IQR, 0-90.7; range, 0.0-2377.1]; P = .99), with strong correlation (intraclass correlation coefficient, 0.98 [95% CI: 0.97, 0.99]). The equivalence test was inconclusive, with a 95% CI of 0.90, 1.19. Bland-Altman analysis showed wide repeatability limits, indicating low agreement between the two scores. With use of the PureCalcium algorithm, 125 of 170 patients (74%) were correctly classified into plaque burden groups (excellent agreement, κ = 0.88). Patients without plaque burden were misclassified at higher than normal rates (P < .001). TNC image acquisition contributed a mean of 19.7% ± 8.8 of the radiation dose of the entire examination. Conclusion PureCalcium images show potential to replace TNC images for measuring Agatston scores, thereby reducing radiation dose in CCTA. There was strong correlation in calcium scores between TNC and PureCalcium, but limited agreement. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Sakuma in this issue.
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Affiliation(s)
- Nina P Haag
- From the Department of Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling University Hospital, Ruhr University Bochum, Hans-Nolte-Strasse 1, 32429 Minden, Germany (N.P.H., A.E.M., J.H.N., J.B., J.R.K.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (S.L.); Siemens Healthcare, Erlangen, Germany (C.P., I.S.); and National Center for Tumor Diseases, Dresden, Germany (A.Z.)
| | - Arwed E Michael
- From the Department of Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling University Hospital, Ruhr University Bochum, Hans-Nolte-Strasse 1, 32429 Minden, Germany (N.P.H., A.E.M., J.H.N., J.B., J.R.K.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (S.L.); Siemens Healthcare, Erlangen, Germany (C.P., I.S.); and National Center for Tumor Diseases, Dresden, Germany (A.Z.)
| | - Simon Lennartz
- From the Department of Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling University Hospital, Ruhr University Bochum, Hans-Nolte-Strasse 1, 32429 Minden, Germany (N.P.H., A.E.M., J.H.N., J.B., J.R.K.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (S.L.); Siemens Healthcare, Erlangen, Germany (C.P., I.S.); and National Center for Tumor Diseases, Dresden, Germany (A.Z.)
| | - Christoph Panknin
- From the Department of Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling University Hospital, Ruhr University Bochum, Hans-Nolte-Strasse 1, 32429 Minden, Germany (N.P.H., A.E.M., J.H.N., J.B., J.R.K.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (S.L.); Siemens Healthcare, Erlangen, Germany (C.P., I.S.); and National Center for Tumor Diseases, Dresden, Germany (A.Z.)
| | - Julius H Niehoff
- From the Department of Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling University Hospital, Ruhr University Bochum, Hans-Nolte-Strasse 1, 32429 Minden, Germany (N.P.H., A.E.M., J.H.N., J.B., J.R.K.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (S.L.); Siemens Healthcare, Erlangen, Germany (C.P., I.S.); and National Center for Tumor Diseases, Dresden, Germany (A.Z.)
| | - Jan Borggrefe
- From the Department of Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling University Hospital, Ruhr University Bochum, Hans-Nolte-Strasse 1, 32429 Minden, Germany (N.P.H., A.E.M., J.H.N., J.B., J.R.K.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (S.L.); Siemens Healthcare, Erlangen, Germany (C.P., I.S.); and National Center for Tumor Diseases, Dresden, Germany (A.Z.)
| | - Iram Shahzadi
- From the Department of Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling University Hospital, Ruhr University Bochum, Hans-Nolte-Strasse 1, 32429 Minden, Germany (N.P.H., A.E.M., J.H.N., J.B., J.R.K.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (S.L.); Siemens Healthcare, Erlangen, Germany (C.P., I.S.); and National Center for Tumor Diseases, Dresden, Germany (A.Z.)
| | - Alex Zwanenburg
- From the Department of Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling University Hospital, Ruhr University Bochum, Hans-Nolte-Strasse 1, 32429 Minden, Germany (N.P.H., A.E.M., J.H.N., J.B., J.R.K.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (S.L.); Siemens Healthcare, Erlangen, Germany (C.P., I.S.); and National Center for Tumor Diseases, Dresden, Germany (A.Z.)
| | - Jan Robert Kroeger
- From the Department of Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling University Hospital, Ruhr University Bochum, Hans-Nolte-Strasse 1, 32429 Minden, Germany (N.P.H., A.E.M., J.H.N., J.B., J.R.K.); Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany (S.L.); Siemens Healthcare, Erlangen, Germany (C.P., I.S.); and National Center for Tumor Diseases, Dresden, Germany (A.Z.)
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10
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Lorenzatti D, Piña P, Daich J, Scotti A, Perez-Cervera J, Miranda R, Feinberg AJ, Halliburton SS, Ivanc TB, Schenone AL, Kuno T, Latib A, Dey D, Pibarot P, Dweck MR, Garcia MJ, Slipczuk L. Diagnostic accuracy of virtual non-contrast CT for aortic valve stenosis severity evaluation. J Cardiovasc Comput Tomogr 2024; 18:50-55. [PMID: 38314547 DOI: 10.1016/j.jcct.2023.10.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 10/13/2023] [Indexed: 02/06/2024]
Abstract
BACKGROUND Computed tomography aortic valve calcium (AVC) score has accepted value for diagnosing and predicting outcomes in aortic stenosis (AS). Multi-energy CT (MECT) allows virtual non-contrast (VNC) reconstructions from contrast scans. We aim to compare the VNC-AVC score to the true non-contrast (TNC)-AVC score for assessing AS severity. METHODS We prospectively included patients undergoing a MECT for transcatheter aortic valve replacement (TAVR) planning. TNC-AVC was acquired before contrast, and VNC-AVC was derived from a retrospectively gated contrast-enhanced scan. The Agatston scoring method was used for quantification, and linear regression analysis to derive adjusted-VNC values. RESULTS Among 109 patients (55% female) included, 43% had concordant severe and 14% concordant moderate AS. TNC scan median dose-length product was 116 mGy∗cm. The median TNC-AVC was 2,107 AU (1,093-3,372), while VNC-AVC was 1,835 AU (1293-2,972) after applying the coefficient (1.46) and constant (743) terms. A strong correlation was demonstrated between methods (r = 0.93; p < 0.001). Using accepted thresholds (>1,300 AU for women and >2,000 AU for men), 65% (n = 71) of patients had severe AS by TNC-AVC and 67% (n = 73) by adjusted-VNC-AVC. After estimating thresholds for adjusted-VNC (>1,564 AU for women and >2,375 AU for men), 56% (n = 61) had severe AS, demonstrating substantial agreement with TNC-AVC (κ = 0.77). CONCLUSIONS MECT-derived VNC-AVC showed a strong correlation with TNC-AVC. After adjustment, VNC-AVC demonstrated substantial agreement with TNC-AVC, potentially eliminating the requirement for an additional scan and enabling reductions in both radiation exposure and acquisition time.
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Affiliation(s)
- Daniel Lorenzatti
- Division of Cardiology, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA
| | - Pamela Piña
- Division of Cardiology, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA; Division of Cardiology, CEDIMAT, Santo Domingo, Dominican Republic
| | - Jonathan Daich
- Division of Cardiology, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA
| | - Andrea Scotti
- Division of Cardiology, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA
| | | | - Rita Miranda
- Division of Cardiology, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA
| | - Ari J Feinberg
- Division of Cardiology, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA
| | | | - Thomas B Ivanc
- CT Clinical Science, Philips Healthcare, Cleveland, OH, USA
| | - Aldo L Schenone
- Division of Cardiology, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA
| | - Toshiki Kuno
- Division of Cardiology, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA
| | - Azeem Latib
- Division of Cardiology, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA
| | - Damini Dey
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Philippe Pibarot
- Institut Universitaire de Cardiologie et de Pneumologie de Québec/Québec Heart and Lung Institute, Université Laval, Québec, Canada
| | - Marc R Dweck
- British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom
| | - Mario J Garcia
- Division of Cardiology, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA
| | - Leandro Slipczuk
- Division of Cardiology, Montefiore Medical Center/Albert Einstein College of Medicine. Bronx, NY, USA.
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11
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Flohr T, Schmidt B, Ulzheimer S, Alkadhi H. Cardiac imaging with photon counting CT. Br J Radiol 2023; 96:20230407. [PMID: 37750856 PMCID: PMC10646663 DOI: 10.1259/bjr.20230407] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 08/17/2023] [Accepted: 08/24/2023] [Indexed: 09/27/2023] Open
Abstract
CT of the heart, in particular ECG-controlled coronary CT angiography (cCTA), has become clinical routine due to rapid technical progress with ever new generations of CT equipment. Recently, CT scanners with photon-counting detectors (PCD) have been introduced which have the potential to address some of the remaining challenges for cardiac CT, such as limited spatial resolution and lack of high-quality spectral data. In this review article, we briefly discuss the technical principles of photon-counting detector CT, and we give an overview on how the improved spatial resolution of photon-counting detector CT and the routine availability of spectral data can benefit cardiac applications. We focus on coronary artery calcium scoring, cCTA, and on the evaluation of the myocardium.
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Affiliation(s)
- Thomas Flohr
- Siemens Healthcare GmbH, Computed Tomography, Forchheim, Germany
| | - Bernhard Schmidt
- Siemens Healthcare GmbH, Computed Tomography, Forchheim, Germany
| | - Stefan Ulzheimer
- Siemens Healthcare GmbH, Computed Tomography, Forchheim, Germany
| | - Hatem Alkadhi
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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12
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Wu Y, Ye Z, Chen J, Deng L, Song B. Photon Counting CT: Technical Principles, Clinical Applications, and Future Prospects. Acad Radiol 2023; 30:2362-2382. [PMID: 37369618 DOI: 10.1016/j.acra.2023.05.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 05/27/2023] [Accepted: 05/28/2023] [Indexed: 06/29/2023]
Abstract
Photon-counting computed tomography (PCCT) is a new technique that utilizes photon-counting detectors to convert individual X-ray photons directly into an electrical signal, which can achieve higher spatial resolution, improved iodine signal, radiation dose reduction, artifact reduction, and multienergy imaging. This review introduces the technical principles of PCCT, and summarizes its first-in-human experience and current applications in clinical settings, and discusses the future prospects of PCCT.
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Affiliation(s)
- Yingyi Wu
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China (Y.Y.W., Z.Y., J.C., L.P.D., B.S.)
| | - Zheng Ye
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China (Y.Y.W., Z.Y., J.C., L.P.D., B.S.)
| | - Jie Chen
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China (Y.Y.W., Z.Y., J.C., L.P.D., B.S.)
| | - Liping Deng
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China (Y.Y.W., Z.Y., J.C., L.P.D., B.S.)
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu 610041, China (Y.Y.W., Z.Y., J.C., L.P.D., B.S.); Department of Radiology, Sanya People' s Hospital, Sanya, Hainan, China (B.S.).
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13
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Liu LP, Shapira N, Sahbaee P, Gang GJ, Knollman FD, Chen MY, Litt HI, Noël PB. Consistency of spectral results in cardiac dual-source photon-counting CT. Sci Rep 2023; 13:14895. [PMID: 37689744 PMCID: PMC10492823 DOI: 10.1038/s41598-023-41969-7] [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: 05/09/2023] [Accepted: 09/04/2023] [Indexed: 09/11/2023] Open
Abstract
We evaluate stability of spectral results at different heart rates, acquisition modes, and cardiac phases in first-generation clinical dual-source photon-counting CT (PCCT). A cardiac motion simulator with a coronary stenosis mimicking a 50% eccentric calcium plaque was scanned at five different heart rates (0, 60-100 bpm) with the three available cardiac scan modes (high pitch prospectively ECG-triggered spiral, prospectively ECG-triggered axial, retrospectively ECG-gated spiral). Subsequently, full width half max (FWHM) of the stenosis, Dice score (DSC) for the stenosed region, and eccentricity of the non-stenosed region were calculated for virtual monoenergetic images (VMI) at 50, 70, and 150 keV and iodine density maps at both diastole and systole. FWHM averaged differences of - 0.20, - 0.28, and - 0.15 mm relative to static FWHM at VMI 150 keV across acquisition parameters for high pitch prospectively ECG-triggered spiral, prospectively ECG-triggered axial, and retrospectively ECG-gated spiral scans, respectively. Additionally, there was no effect of heart rate and acquisition mode on FWHM at diastole (p-values < 0.001). DSC demonstrated similarity among parameters with standard deviations of 0.08, 0.09, 0.11, and 0.08 for VMI 50, 70, and 150 keV, and iodine density maps, respectively, with insignificant differences at diastole (p-values < 0.01). Similarly, eccentricity illustrated small differences across heart rate and acquisition mode for each spectral result. Consistency of spectral results at different heart rates and acquisition modes for different cardiac phase demonstrates the added benefit of spectral results from PCCT to dual-source CT to further increase confidence in quantification and advance cardiovascular diagnostics.
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Affiliation(s)
- Leening P Liu
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
| | - Nadav Shapira
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Grace J Gang
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Marcus Y Chen
- National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Harold I Litt
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Peter B Noël
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Diagnostic and Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, 81675, Munich, Germany.
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14
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Vecsey-Nagy M, Varga-Szemes A, Emrich T, Zsarnoczay E, Nagy N, Fink N, Schmidt B, Nowak T, Kiss M, Vattay B, Boussoussou M, Kolossváry M, Kubovje A, Merkely B, Maurovich-Horvat P, Szilveszter B. Calcium scoring on coronary computed angiography tomography with photon-counting detector technology: Predictors of performance. J Cardiovasc Comput Tomogr 2023; 17:328-335. [PMID: 37635032 DOI: 10.1016/j.jcct.2023.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/10/2023] [Accepted: 08/05/2023] [Indexed: 08/29/2023]
Abstract
INTRODUCTION Obtaining accurate coronary artery calcium (CAC) score measurements from CCTA datasets with virtual non-iodine (VNI) algorithms would reduce acquisition time and radiation dose. We aimed to assess the agreement of VNI-derived and conventional true non-contrast (TNC)-based CAC scores and to identify the predictors of accuracy. METHODS CCTA datasets were acquired with either 120 or 140 kVp. CAC scores and volumes were calculated from TNC and VNI images in 197 consecutive patients undergoing CCTA. CAC density score, mean volume/lesion, aortic Hounsfield units and standard deviations were then measured. Finally, percentage deviation (VNI - TNC/TNC∗100) of CTA-derived CAC scores from non-enhanced scans was calculated for each patient. Predictors (including anthropometric and acquisition parameters, as well as CAC characteristics) of the degree of discrepancy were evaluated using linear regression analysis. RESULTS While the agreement between TNC and VNI was substantial (mean bias, 6.6; limits of agreement, 178.5/145.3), a non-negligible proportion of patients (36/197, 18.3%) were falsely reclassified as CAC score = 0 on VNI. The use of higher tube voltage significantly decreased the percentage deviation relative to TNC-based values (β = -0.21 [95%CI: 0.38 to -0.03], p = 0.020) and a higher CAC density score also proved to be an independent predictor of a smaller difference (β = -0.22 [95%CI: 0.37 to -0.07], p = 0.006). CONCLUSION The performance of VNI-based calcium scoring may be improved by increased tube voltage protocols, while the accuracy may be compromised for calcified lesions of lower density. The implementation of VNI in clinical routine, however, needs to be preceded by a solution for detecting smaller lesions as well.
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Affiliation(s)
- M Vecsey-Nagy
- Heart and Vascular Center of Semmelweis University, Budapest, Hungary; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA
| | - A Varga-Szemes
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA
| | - T Emrich
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
| | - E Zsarnoczay
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Medical Imaging Center of Semmelweis University, Budapest, Hungary
| | - N Nagy
- Medical Imaging Center of Semmelweis University, Budapest, Hungary
| | - N Fink
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - B Schmidt
- Siemens Healthcare GmbH, Forchheim, Germany
| | - T Nowak
- Siemens Healthcare GmbH, Forchheim, Germany
| | - M Kiss
- Siemens Healthcare GmbH, Forchheim, Germany
| | - B Vattay
- Heart and Vascular Center of Semmelweis University, Budapest, Hungary
| | - M Boussoussou
- Heart and Vascular Center of Semmelweis University, Budapest, Hungary
| | - M Kolossváry
- Gottsegen National Cardiovascular Center, Budapest, Hungary; Physiological Controls Research Center, Budapest, Hungary
| | - A Kubovje
- Medical Imaging Center of Semmelweis University, Budapest, Hungary
| | - B Merkely
- Heart and Vascular Center of Semmelweis University, Budapest, Hungary
| | | | - B Szilveszter
- Heart and Vascular Center of Semmelweis University, Budapest, Hungary.
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Yamaoka T, Watanabe S. Artificial intelligence in coronary artery calcium measurement: Barriers and solutions for implementation into daily practice. Eur J Radiol 2023; 164:110855. [PMID: 37167685 DOI: 10.1016/j.ejrad.2023.110855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/29/2023] [Accepted: 04/28/2023] [Indexed: 05/13/2023]
Abstract
Coronary artery calcification (CAC) measurement is a valuable predictor of cardiovascular risk. However, its measurement can be time-consuming and complex, thus driving the desire for artificial intelligence (AI)-based approaches. The aim of this review is to explore the current status of CAC volume measurement using AI-based systems for the automated prediction of cardiovascular events. We also make proposals for the implementation of these systems into clinical practice. Research to date on applying AI to CAC scoring has shown the potential for automation and risk stratification, and, overall, efficacy and a high level of agreement with categorisation by trained clinicians have been demonstrated. However, research in this field has not been uniform or directed. One contributing factor may be a lack of integration and communication between computer scientists and cardiologists. Clinicians, institutions, and organisations should work together towards applying this technology to improve processes, preserve healthcare resources, and improve patient outcomes.
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Affiliation(s)
- Toshihide Yamaoka
- Department of Diagnostic Imaging and Interventional Radiology, Kyoto Katsura Hospital, Japan.
| | - Sachika Watanabe
- Department of Diagnostic Imaging and Interventional Radiology, Kyoto Katsura Hospital, Japan
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Zsarnóczay E, Varga-Szemes A, Emrich T, Szilveszter B, van der Werf NR, Mastrodicasa D, Maurovich-Horvat P, Willemink MJ. Characterizing the Heart and the Myocardium With Photon-Counting CT. Invest Radiol 2023; 58:505-514. [PMID: 36822653 DOI: 10.1097/rli.0000000000000956] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
ABSTRACT Noninvasive cardiac imaging has rapidly evolved during the last decade owing to improvements in computed tomography (CT)-based technologies, among which we highlight the recent introduction of the first clinical photon-counting detector CT (PCD-CT) system. Multiple advantages of PCD-CT have been demonstrated, including increased spatial resolution, decreased electronic noise, and reduced radiation exposure, which may further improve diagnostics and may potentially impact existing management pathways. The benefits that can be obtained from the initial experiences with PCD-CT are promising. The implementation of this technology in cardiovascular imaging allows for the quantification of coronary calcium, myocardial extracellular volume, myocardial radiomics features, epicardial and pericoronary adipose tissue, and the qualitative assessment of coronary plaques and stents. This review aims to discuss these major applications of PCD-CT with a focus on cardiac and myocardial characterization.
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Affiliation(s)
| | - Akos Varga-Szemes
- From the Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston
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Mergen V, Ghouse S, Sartoretti T, Manka R, Euler A, Kasel AM, Alkadhi H, Eberhard M. Cardiac Virtual Noncontrast Images for Calcium Quantification with Photon-counting Detector CT. Radiol Cardiothorac Imaging 2023; 5:e220307. [PMID: 37404795 PMCID: PMC10316300 DOI: 10.1148/ryct.220307] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 03/29/2023] [Accepted: 05/08/2023] [Indexed: 07/06/2023]
Abstract
Purpose To assess the accuracy of aortic valve calcium (AVC), mitral annular calcium (MAC), and coronary artery calcium (CAC) quantification and risk stratification using virtual noncontrast (VNC) images from late enhancement photon-counting detector CT as compared with true noncontrast images. Materials and Methods This retrospective, institutional review board-approved study evaluated patients undergoing photon-counting detector CT between January and September 2022. VNC images were reconstructed from late enhancement cardiac scans at 60, 70, 80, and 90 keV using quantum iterative reconstruction (QIR) strengths of 2-4. AVC, MAC, and CAC were quantified on VNC images and compared with quantification of AVC, MAC, and CAC on true noncontrast images using Bland-Altman analyses, regression models, intraclass correlation coefficients (ICC), and Wilcoxon tests. Agreement between severe aortic stenosis likelihood categories and CAC risk categories determined from VNC and true noncontrast images was assessed by weighted κ analysis. Results Ninety patients were included (mean age, 80 years ± 8 [SD]; 49 male patients). Scores were similar on true noncontrast images and VNC images at 80 keV for AVC and MAC, regardless of QIR strengths, and VNC images at 70 keV with QIR 4 for CAC (all P > .05). The best results were achieved using VNC images at 80 keV with QIR 4 for AVC (mean difference, 3; ICC = 0.992; r = 0.98) and MAC (mean difference, 6; ICC = 0.998; r = 0.99), and VNC images at 70 keV with QIR 4 for CAC (mean difference, 28; ICC = 0.996; r = 0.99). Agreement between calcification categories was excellent on VNC images at 80 keV for AVC (κ = 0.974) and on VNC images at 70 keV for CAC (κ = 0.967). Conclusion VNC images from cardiac photon-counting detector CT enables patient risk stratification and accurate quantification of AVC, MAC, and CAC.Keywords: Coronary Arteries, Aortic Valve, Mitral Valve, Aortic Stenosis, Calcifications, Photon-counting Detector CT Supplemental material is available for this article © RSNA, 2023.
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18
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Fink N, Zsarnoczay E, Schoepf UJ, O'Doherty J, Griffith JP, Pinos D, Tesche C, Ricke J, Willemink MJ, Varga-Szemes A, Emrich T. Radiation Dose Reduction for Coronary Artery Calcium Scoring Using a Virtual Noniodine Algorithm on Photon-Counting Detector Computed-Tomography Phantom Data. Diagnostics (Basel) 2023; 13:diagnostics13091540. [PMID: 37174932 PMCID: PMC10177425 DOI: 10.3390/diagnostics13091540] [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] [Received: 03/14/2023] [Revised: 04/14/2023] [Accepted: 04/24/2023] [Indexed: 05/15/2023] Open
Abstract
Background: On the basis of the hypothesis that virtual noniodine (VNI)-based coronary artery calcium scoring (CACS) is feasible at reduced radiation doses, this study assesses the impact of radiation dose reduction on the accuracy of this VNI algorithm on a photon-counting detector (PCD)-CT. Methods: In a systematic in vitro setting, a phantom for CACS simulating three chest sizes was scanned on a clinical PCD-CT. The standard radiation dose was chosen at volumetric CT dose indices (CTDIVol) of 1.5, 3.3, 7.0 mGy for small, medium-sized, and large phantoms, and was gradually reduced by adjusting the tube current resulting in 100, 75, 50, and 25%, respectively. VNI images were reconstructed at 55 keV, quantum iterative reconstruction (QIR)1, and at 60 keV/QIR4, and evaluated regarding image quality (image noise (IN), contrast-to-noise ratio (CNR)), and CACS. All VNI results were compared to true noncontrast (TNC)-based CACS at 70 keV and standard radiation dose (reference). Results: INTNC was significantly higher than INVNI, and INVNI at 55 keV/QIR1 higher than at 60 keV/QIR4 (100% dose: 16.7 ± 1.9 vs. 12.8 ± 1.7 vs. 7.7 ± 0.9; p < 0.001 for every radiation dose). CNRTNC was higher than CNRVNI, but it was better to use 60 keV/QIR4 (p < 0.001). CACSVNI showed strong correlation and agreement at every radiation dose (p < 0.001, r > 0.9, intraclass correlation coefficient > 0.9). The coefficients of the variation in root-mean squared error were less than 10% and thus clinically nonrelevant for the CACSVNI of every radiation dose. Conclusion: This phantom study suggests that CACSVNI is feasible on PCD-CT, even at reduced radiation dose while maintaining image quality and CACS accuracy.
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Affiliation(s)
- Nicola Fink
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, USA
- Department of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany
| | - Emese Zsarnoczay
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, USA
- Medical Imaging Center, Semmelweis University, Korányi Sándor utca 2, 1083 Budapest, Hungary
| | - U Joseph Schoepf
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, USA
| | - Jim O'Doherty
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, USA
- Siemens Medical Solutions, 40 Liberty Boulevard, Malvern, PA 19355, USA
| | - Joseph P Griffith
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, USA
| | - Daniel Pinos
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, USA
| | - Christian Tesche
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, USA
- Department of Cardiology, Munich University Clinic, Ludwig-Maximilians-University, Marchioninistr. 15, 81377 Munich, Germany
| | - Jens Ricke
- Department of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 Munich, Germany
| | - Martin J Willemink
- Department of Radiology, Stanford University School of Medicine, 291 Campus Drive, Stanford, CA 94305, USA
| | - Akos Varga-Szemes
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, USA
| | - Tilman Emrich
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, USA
- Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes-Gutenberg-University, Langenbeckstr. 1, 55131 Mainz, Germany
- German Centre for Cardiovascular Research, Partner Site Rhine-Main, 55131 Mainz, Germany
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19
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Photon Counting Detector CT-Based Virtual Noniodine Reconstruction Algorithm for In Vitro and In Vivo Coronary Artery Calcium Scoring: Impact of Virtual Monoenergetic and Quantum Iterative Reconstructions. Invest Radiol 2023:00004424-990000000-00091. [PMID: 36822677 DOI: 10.1097/rli.0000000000000959] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
OBJECTIVES The aim of this study was to evaluate the impact of virtual monoenergetic imaging (VMI) and quantum iterative reconstruction (QIR) on the accuracy of coronary artery calcium scoring (CACS) using a virtual noniodine (VNI) reconstruction algorithm on a first-generation, clinical, photon counting detector computed tomography system. MATERIALS AND METHODS Coronary artery calcium scoring was evaluated in an anthropomorphic chest phantom simulating 3 different patient sizes by using 2 extension rings (small: 300 × 200 mm, medium: 350 × 250 mm, large: 400 × 300 mm) and in patients (n = 61; final analyses only in patients with coronary calcifications [n = 34; 65.4 ± 10.0 years; 73.5% male]), who underwent nonenhanced and contrast-enhanced, electrocardiogram-gated, cardiac computed tomography on a photon counting detector system. Phantom and patient data were reconstructed using a VNI reconstruction algorithm at different VMI (55-80 keV) and QIR (strength 1-4) levels (CACSVNI). True noncontrast (TNC) scans at 70 keV and QIR "off" were used as reference for phantom and patient studies (CACSTNC). RESULTS In vitro and in vivo CACSVNI showed strong correlation (r > 0.9, P < 0.001 for all) and excellent agreement (intraclass correlation coefficient > 0.9 for all) with CACSTNC at all investigated VMI and QIR levels. Phantom and patient CACSVNI significantly increased with decreasing keV levels (in vitro: from 475.2 ± 26.3 at 80 keV up to 652.5 ± 42.2 at 55 keV; in vivo: from 142.5 [7.4/737.7] at 80 keV up to 248.1 [31.2/1144] at 55 keV; P < 0.001 for all), resulting in an overestimation of CACSVNI at 55 keV compared with CACSTNC at 70 keV in some cases (in vitro: 625.8 ± 24.4; in vivo: 225.4 [35.1/959.7]). In vitro CACS increased with rising QIR at low keV. In vivo scores were significantly higher at QIR 1 compared with QIR 4 only at 60 and 80 keV (60 keV: 220.3 [29.6-1060] vs 219.5 [23.7/1048]; 80 keV: 152.0 [12.0/735.6] vs 142.5 [7.4/737.7]; P < 0.001). CACSVNI was closest to CACSTNC at 60 keV, QIR 2 (+0.1%) in the small; 55 keV, QIR 1 (±0%) in the medium; 55 keV, QIR 4 (-0.1%) in the large phantom; and at 60 keV, QIR 1 (-2.3%) in patients. CONCLUSIONS Virtual monoenergetic imaging reconstructions have a significant impact on CACSVNI. The effects of different QIR levels are less consistent and seem to depend on several individual conditions, which should be further investigated.
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20
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Langenbach IL, Wienemann H, Klein K, Scholtz JE, Pennig L, Langzam E, Pahn G, Holz JA, Maintz D, Naehle CP, Langenbach MC. Coronary calcium scoring using virtual non-contrast reconstructions on a dual-layer spectral CT system: Feasibility in the clinical practice. Eur J Radiol 2023; 159:110681. [PMID: 36592582 DOI: 10.1016/j.ejrad.2022.110681] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 12/22/2022] [Accepted: 12/23/2022] [Indexed: 12/27/2022]
Abstract
PURPOSE To evaluate the clinical applicability of a prototype virtual non-contrast (VNC) reconstruction algorithm based on coronary CT angiography (cCTA) to assess calcified coronary plaques by calcium scoring (CACS). METHODS Eighty consecutive patients suspected of coronary artery disease were retrospectively included. All patients underwent a cardiac CT using a dual-layer spectral-detector CT system. The standardized acquisition protocol included unenhanced CACS and cCTA. Datasets were acquired using 120 keV. VNC-reconstructions were calculated from the cCTA images at 2.5 mm (VNC group 1), 2.5 of 0.9 mm (group 2), and 0.9 mm (group 3) slice thickness. We compared the Agatston score and Coronary Artery Calcium Data and Reporting System (CAC-DRS) of all VNC reconstructions with the true non-contrast (TNC)-dataset as the gold standard. RESULTS In total, 73 patients were evaluated. Fifty patients (68.5 %) had a CACS > 0 based on TNC. We found a significant difference in the Agatston score comparing all VNC-reconstructions (1: 1.35, 2: 3.7, 3: 10.4) with the TNC dataset (3.8) (p < 0.001). Correlation analysis of the datasets showed an excellent correlation of the TNC results with the different VNC-reconstructions (r = 0.904-0.974, p < 0.001) with a slope of 1.89-2.53. Mean differences and limits of agreement by Bland-Altman analysis between TNC and group 1 were 83 and -196 to 362, respectively. By using the VNC-reconstructions, in group 1 23 patients (31.5 %), in group 2 10 (13.7 %), and in group 3 23 (31.5 %) were reclassified according to CAC-DRS compared to TNC. Classification according to CAC-DRS revealed a significant difference between TNC and group 1 (p = 0.024) and no significance compared to groups 2 and 3 (p = 0.670 and 0.273). CONCLUSION The investigated VNC reconstruction algorithm of routine cCTA allows the detection and evaluation of coronary calcium burden without the requirement for an additional acquisition of an unenhanced CT scan for CACS and, therefore, a reduction of radiation exposure.
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Affiliation(s)
- I L Langenbach
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany; Cardiovascular Imaging Research Center, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
| | - H Wienemann
- Clinic III for Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - K Klein
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - J E Scholtz
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Frankfurt, University of Frankfurt, Frankfurt, Germany
| | - L Pennig
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - E Langzam
- Philips Healthcare, Best, the Netherlands
| | - G Pahn
- Philips CT Clinical Science, Hamburg, Germany
| | - J A Holz
- Department of Radiation Oncology, University Hospital Bonn, University of Bonn, Bonn, Germany
| | - D Maintz
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - C P Naehle
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany; Radiologische Allianz, Hamburg, Germany
| | - M C Langenbach
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany; Cardiovascular Imaging Research Center, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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21
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Yang P, Zhao R, Deng W, An S, Li Y, Sheng M, Chen X, Qian Y, Yu Y, Mu D, Wang Y, Li X. Feasibility and accuracy of coronary artery calcium score on virtual non-contrast images derived from a dual-layer spectral detector CT: A retrospective multicenter study. Front Cardiovasc Med 2023; 10:1114058. [PMID: 36937907 PMCID: PMC10018184 DOI: 10.3389/fcvm.2023.1114058] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 02/10/2023] [Indexed: 03/06/2023] Open
Abstract
Rationale and objective This retrospective study was to evaluate the feasibility and accuracy of coronary artery calcium score (CACS) from virtual non-contrast (VNC) images in comparison with that from true non-contrast (TNC) images. Materials and methods A total of 540 patients with suspected of coronary artery disease (CAD) who underwent a dual-layer spectral detector CT (SDCT) in three hospitals were eligible for this study and 233 patients were retrospectively enrolled for further analysis. The CACS was calculated from both TNC and VNC images and compared. Linear regression analysis of the CACS was performed between TNC and VNC images. Results The correlation of overall CACS from VNC and TNC images was very strong (r = 0.923, p < 0.001). The CACS from VNC images were lower than that from TNC images (221 versus. 69, p < 0.001). When the regression equation of the overall coronary artery was applied, the mean calibrated CACS-VNC was 221 which had a significant difference from the CACS-TNC (p = 0.017). When the regression equation of each coronary branch artery was applied, the mean calibrated CACS-VNC was 221, which had a significant difference from the CACS-TNC (p = 0.003). But the mean difference between the CACS-TNC and the calibrated CACS-VNC in either way was less than 1. The agreement on risk stratification with CACS-TNC and CCACS-VNC was almost perfect. Conclusion This multicenter study with dual-layer spectral detector CT showed that it was feasible to calculate CACS from the VNC images derived from the spectral coronary artery CT angiography scan, and the results were in good accordance with the TNC images after correction. Therefore, the TNC scan could be omitted, reducing the radiation dose to patients and saving examination time while using dual-layer spectral detector CT.
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Affiliation(s)
- Panpan Yang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui, China
| | - Ren Zhao
- Department of Cardiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Wei Deng
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui, China
| | - Shutian An
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui, China
| | - Yuguo Li
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui, China
| | - Mao Sheng
- Department of Radiology, The Second People's Hospital of Hefei, Hefei Hospital Affiliated to Anhui Medical University, Hefei, Anhui, China
| | - Xingbiao Chen
- Clinical Science, Philips Healthcare, Shanghai, China
| | - Yingfeng Qian
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui, China
| | - Dan Mu
- Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
- *Correspondence: Dan Mu, ; Yining Wang, ; Xiaohu Li,
| | - Yining Wang
- Department of Radiology, Peking Union Medical College Hospital, Beijing, China
- *Correspondence: Dan Mu, ; Yining Wang, ; Xiaohu Li,
| | - Xiaohu Li
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui, China
- *Correspondence: Dan Mu, ; Yining Wang, ; Xiaohu Li,
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Jungblut L, Sartoretti T, Kronenberg D, Mergen V, Euler A, Schmidt B, Alkadhi H, Frauenfelder T, Martini K. Performance of virtual non-contrast images generated on clinical photon-counting detector CT for emphysema quantification: proof of concept. Br J Radiol 2022; 95:20211367. [PMID: 35357902 PMCID: PMC10996315 DOI: 10.1259/bjr.20211367] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 03/09/2022] [Accepted: 03/22/2022] [Indexed: 12/23/2022] Open
Abstract
OBJECTIVE To evaluate the performance of virtual non-contrast images (VNC) compared to true non-contrast (TNC) images in photon-counting detector computed tomography (PCD-CT) for the evaluation of lung parenchyma and emphysema quantification. METHODS 65 (mean age 73 years; 48 male) consecutive patients who underwent a three-phase (non-contrast, arterial and venous) chest/abdomen CT on a first-generation dual-source PCD-CT were retrospectively included. Scans were performed in the multienergy (QuantumPlus) mode at 120 kV with 70 ml intravenous contrast agent at an injection rate of 4 ml s-1. VNC were reconstructed from the arterial (VNCart) and venous phase (VNCven). TNC and VNC images of the lung were assessed quantitatively by calculating the global noise index (GNI) and qualitatively by two independent, blinded readers (overall image quality and emphysema assessment). Emphysema quantification was performed using a commercially available software tool at a threshold of -950 HU for all data sets. TNC images served as reference standard for emphysema quantification. Low attenuation values (LAV) were compared in a Bland-Altman plot. RESULTS GNI was similar in VNCart (103.0 ± 30.1) and VNCven (98.2 ± 22.2) as compared to TNC (100.9 ± 19.0, p = 0.546 and p = 0.272, respectively). Subjective image quality (emphysema assessment and overall image quality) was highest for TNC (p = 0.001), followed by VNCven and VNCart. Both, VNCart and VNCven showed no significant difference in emphysema quantification as compared to TNC (p = 0.409 vs. p = 0.093; respectively). CONCLUSION Emphysema evaluation is feasible using virtual non-contrast images from PCD-CT. ADVANCES IN KNOWLEDGE Emphysema quantification is feasible and accurate using VNC images in PCD-CT. Based on these findings, additional TNC scans for emphysema quantification could be omitted in the future.
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Affiliation(s)
- Lisa Jungblut
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
| | - Thomas Sartoretti
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
| | - Daniel Kronenberg
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
| | - Victor Mergen
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
| | - Andre Euler
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
| | - Bernhard Schmidt
- Siemens Healthcare GmbH, Computed Tomography,
Forchheim, Germany
| | - Hatem Alkadhi
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
| | - Thomas Frauenfelder
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
| | - Katharina Martini
- Institute of Diagnostic and Interventional Radiology,
University Hospital Zurich, University of Zurich,
Zurich, Switzerland
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Coronary Computed Tomography Angiography-Based Calcium Scoring: In Vitro and In Vivo Validation of a Novel Virtual Noniodine Reconstruction Algorithm on a Clinical, First-Generation Dual-Source Photon Counting-Detector System. Invest Radiol 2022; 57:536-543. [PMID: 35318969 DOI: 10.1097/rli.0000000000000868] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE The aim of this study was to evaluate coronary computed tomography angiography (CCTA)-based in vitro and in vivo coronary artery calcium scoring (CACS) using a novel virtual noniodine reconstruction (PureCalcium) on a clinical first-generation photon-counting detector-computed tomography system compared with virtual noncontrast (VNC) reconstructions and true noncontrast (TNC) acquisitions. MATERIALS AND METHODS Although CACS and CCTA are well-established techniques for the assessment of coronary artery disease, they are complementary acquisitions, translating into increased scan time and patient radiation dose. Hence, accurate CACS derived from a single CCTA acquisition would be highly desirable. In this study, CACS based on PureCalcium, VNC, and TNC, reconstructions was evaluated in a CACS phantom and in 67 patients (70 [59/80] years, 58.2% male) undergoing CCTA on a first-generation photon counting detector-computed tomography system. Coronary artery calcium scores were quantified for the 3 reconstructions and compared using Wilcoxon test. Agreement was evaluated by Pearson and Spearman correlation and Bland-Altman analysis. Classification of coronary artery calcium score categories (0, 1-10, 11-100, 101-400, and >400) was compared using Cohen κ. RESULTS Phantom studies demonstrated strong agreement between CACSPureCalcium and CACSTNC (60.7 ± 90.6 vs 67.3 ± 88.3, P = 0.01, r = 0.98, intraclass correlation [ICC] = 0.98; mean bias, 6.6; limits of agreement [LoA], -39.8/26.6), whereas CACSVNC showed a significant underestimation (42.4 ± 75.3 vs 67.3 ± 88.3, P < 0.001, r = 0.94, ICC = 0.89; mean bias, 24.9; LoA, -87.1/37.2). In vivo comparison confirmed a high correlation but revealed an underestimation of CACSPureCalcium (169.3 [0.7/969.4] vs 232.2 [26.5/1112.2], P < 0.001, r = 0.97, ICC = 0.98; mean bias, -113.5; LoA, -470.2/243.2). In comparison, CACSVNC showed a similarly high correlation, but a substantially larger underestimation (24.3 [0/272.3] vs 232.2 [26.5/1112.2], P < 0.001, r = 0.97, ICC = 0.54; mean bias, -551.6; LoA, -2037.5/934.4). CACSPureCalcium showed superior agreement of CACS classification (κ = 0.88) than CACSVNC (κ = 0.60). CONCLUSIONS The accuracy of CACS quantification and classification based on PureCalcium reconstructions of CCTA outperforms CACS derived from VNC reconstructions.
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Impact of Contrast Enhancement and Virtual Monoenergetic Image Energy Levels on Emphysema Quantification. Invest Radiol 2022; 57:359-365. [DOI: 10.1097/rli.0000000000000848] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Mu D, Bai J, Chen W, Yu H, Liang J, Yin K, Li H, Qing Z, He K, Yang HY, Zhang J, Yin Y, McLellan HW, Schoepf UJ, Zhang B. Calcium Scoring at Coronary CT Angiography Using Deep Learning. Radiology 2021; 302:309-316. [PMID: 34812674 DOI: 10.1148/radiol.2021211483] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Background Separate noncontrast CT to quantify the coronary artery calcium (CAC) score often precedes coronary CT angiography (CTA). Quantifying CAC scores directly at CTA would eliminate the additional radiation produced at CT but remains challenging. Purpose To quantify CAC scores automatically from a single CTA scan. Materials and Methods In this retrospective study, a deep learning method to quantify CAC scores automatically from a single CTA scan was developed on training and validation sets of 292 patients and 73 patients collected from March 2019 to July 2020. Virtual noncontrast scans obtained with a spectral CT scanner were used to develop the algorithm to alleviate tedious manual annotation of calcium regions. The proposed method was validated on an independent test set of 240 CTA scans collected from three different CT scanners from August 2020 to November 2020 using the Pearson correlation coefficient, the coefficient of determination, or r2, and the Bland-Altman plot against the semiautomatic Agatston score at noncontrast CT. The cardiovascular risk categorization performance was evaluated using weighted κ based on the Agatston score (CAC score risk categories: 0-10, 11-100, 101-400, and >400). Results Two hundred forty patients (mean age, 60 years ± 11 [standard deviation]; 146 men) were evaluated. The positive correlation between the automatic deep learning CTA and semiautomatic noncontrast CT CAC score was excellent (Pearson correlation = 0.96; r2 = 0.92). The risk categorization agreement based on deep learning CTA and noncontrast CT CAC scores was excellent (weighted κ = 0.94 [95% CI: 0.91, 0.97]), with 223 of 240 scans (93%) categorized correctly. All patients who were miscategorized were in the direct neighboring risk groups. The proposed method's differences from the noncontrast CT CAC score were not statistically significant with regard to scanner (P = .15), sex (P = .051), and section thickness (P = .67). Conclusion A deep learning automatic calcium scoring method accurately quantified coronary artery calcium from CT angiography images and categorized risk. © RSNA, 2021 See also the editorial by Goldfarb and Cao et al in this issue.
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Affiliation(s)
- Dan Mu
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - Junjie Bai
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - Wenping Chen
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - Hongming Yu
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - Jing Liang
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - Kejie Yin
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - Hui Li
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - Zhao Qing
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - Kelei He
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - Hao-Yu Yang
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - Jinyao Zhang
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - Youbing Yin
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - Hunter W McLellan
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - U Joseph Schoepf
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
| | - Bing Zhang
- From the Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing, China (D.M., W.C., H.Y., J.L., K.Y., H.L., Z.Q., B.Z.); Keya Medical, Shenzhen, China (J.B., H.Y.Y., J.Z., Y.Y.); Medical School of Nanjing University, Nanjing, China (K.H.); National Institutes of Healthcare Data Science at Nanjing University, Nanjing, China (K.H.); University of South Carolina School of Medicine-Columbia, Columbia, SC (H.W.M.); Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC (U.J.S.); Institute of Brain Science, Nanjing University, Nanjing 210008, China (B.Z.)
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