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Konst B, Ohlsson L, Henriksson L, Sandstedt M, Persson A, Ebbers T. Optimization of photon counting CT for cardiac imaging in patients with left ventricular assist devices: An in-depth assessment of metal artifacts. J Appl Clin Med Phys 2024; 25:e14386. [PMID: 38739330 PMCID: PMC11244676 DOI: 10.1002/acm2.14386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 03/22/2024] [Accepted: 04/21/2024] [Indexed: 05/14/2024] Open
Abstract
PURPOSE Photon counting CT (PCCT) holds promise for mitigating metal artifacts and can produce virtual mono-energetic images (VMI), while maintaining temporal resolution, making it a valuable tool for characterizing the heart. This study aimed to evaluate and optimize PCCT for cardiac imaging in patients during left ventricular assistance device (LVAD) therapy by conducting an in-depth objective assessment of metal artifacts and visual grading. METHODS Various scan and reconstruction settings were tested on a phantom and further evaluated on a patient acquisition to identify the optimal protocol settings. The phantom comprised an empty thoracic cavity, supplemented with heart and lungs from a cadaveric lamb. The heart was implanted with an LVAD (HeartMate 3) and iodine contrast. Scans were performed on a PCCT (NAEOTOM Alpha, Siemens Healthcare). Metal artifacts were assessed by three objective methods: Hounsfield units (HU)/SD measurements (DiffHU and SDARTIFACT), Fourier analysis (AmplitudeLowFreq), and depicted LVAD volume in the images (BloomVol). Radiologists graded metal artifacts and the diagnostic interpretability in the LVAD lumen, cardiac tissue, lung tissue, and spinal cord using a 5-point rating scale. Regression and correlation analysis were conducted to determine the assessment method most closely associated with acquisition and reconstruction parameters, as well as the objective method demonstrating the highest correlation with visual grading. RESULTS Due to blooming artifacts, the LVAD volume fluctuated between 27.0 and 92.7 cm3. This variance was primarily influenced by kVp, kernel, keV, and iMAR (R2 = 0.989). Radiologists favored pacemaker iMAR, 3 mm slice thickness, and T3D keV and kernel Bv56f for minimal metal artifacts in cardiac tissue assessment, and 110 keV and Qr40f for lung tissue interpretation. The model adequacy for DiffHU SDARTIFACT, AmplitueLowFreq, and BloomVol was 0.28, 0.76, 0.29, and 0.99 respectively for phantom data, and 0.95, 0.98, 1.00, and 0.99 for in-vivo data. For in-vivo data, the correlation between visual grading (VGSUM) and DiffHU SDARTIFACT, AmplitueLowFreq, and BloomVol was -0.16, -0.01, -0.48, and -0.40 respectively. CONCLUSION We found that optimal scan settings for LVAD imaging involved using 120 kVp and IQ level 80. Employing T3D with pacemaker iMAR, the sharpest allowed vascular kernel (Bv56f), and VMI at 110 keV with kernel Qr40 yields images suitable for cardiac imaging during LVAD-therapy. Volumetric measurements of the LVAD for determination of the extent of blooming artifacts was shown to be the best objective method to assess metal artifacts.
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Affiliation(s)
- Bente Konst
- Department of Health, Medicine and Caring SciencesLinköping UniversityLinköpingSweden
- Center for Medical Image Science and Visualization (CMIV)Linköping UniversityLinköpingSweden
- Department of RadiologyVestfold HospitalTønsbergNorway
| | - Linus Ohlsson
- Center for Medical Image Science and Visualization (CMIV)Linköping UniversityLinköpingSweden
- Department of Thoracic and Vascular Surgery in Östergötland, and Department of HealthMedicine and Caring SciencesLinköping UniversityLinköpingSweden
| | - Lilian Henriksson
- Center for Medical Image Science and Visualization (CMIV)Linköping UniversityLinköpingSweden
- Department of Radiology in Linköpingand Department of HealthMedicine and Caring SciencesLinköping UniversityLinköpingSweden
| | - Mårten Sandstedt
- Center for Medical Image Science and Visualization (CMIV)Linköping UniversityLinköpingSweden
- Department of Radiology in Linköpingand Department of HealthMedicine and Caring SciencesLinköping UniversityLinköpingSweden
| | - Anders Persson
- Center for Medical Image Science and Visualization (CMIV)Linköping UniversityLinköpingSweden
- Department of Radiology in Linköpingand Department of HealthMedicine and Caring SciencesLinköping UniversityLinköpingSweden
| | - Tino Ebbers
- Department of Health, Medicine and Caring SciencesLinköping UniversityLinköpingSweden
- Center for Medical Image Science and Visualization (CMIV)Linköping UniversityLinköpingSweden
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Vecsey-Nagy M, Varga-Szemes A, Schoepf UJ, Tremamunno G, Fink N, Zsarnoczay E, Szilveszter B, Graafen D, Halfmann MC, Vattay B, Boussoussou M, O'Doherty J, Suranyi PS, Maurovich-Horvat P, Emrich T. Ultra-high resolution coronary CT angiography on photon-counting detector CT: bi-centre study on the impact of quantum iterative reconstruction on image quality and accuracy of stenosis measurements. Eur J Radiol 2024; 176:111517. [PMID: 38805884 DOI: 10.1016/j.ejrad.2024.111517] [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: 05/13/2024] [Accepted: 05/17/2024] [Indexed: 05/30/2024]
Abstract
PURPOSE To assess the impact of different quantum iterative reconstruction (QIR) levels on objective and subjective image quality of ultra-high resolution (UHR) coronary CT angiography (CCTA) images and to determine the effect of strength levels on stenosis quantification using photon-counting detector (PCD)-CT. METHOD A dynamic vessel phantom containing two calcified lesions (25 % and 50 % stenosis) was scanned at heart rates of 60, 80 and 100 beats per minute with a PCD-CT system. In vivo CCTA examinations were performed in 102 patients. All scans were acquired in UHR mode (slice thickness0.2 mm) and reconstructed with four different QIR levels (1-4) using a sharp vascular kernel (Bv64). Image noise, signal-to-noise ratio (SNR), sharpness, and percent diameter stenosis (PDS) were quantified in the phantom, while noise, SNR, contrast-to-noise ratio (CNR), sharpness, and subjective quality metrics (noise, sharpness, overall image quality) were assessed in patient scans. RESULTS Increasing QIR levels resulted in significantly lower objective image noise (in vitro and in vivo: both p < 0.001), higher SNR (both p < 0.001) and CNR (both p < 0.001). Sharpness and PDS values did not differ significantly among QIRs (all pairwise p > 0.008). Subjective noise of in vivo images significantly decreased with increasing QIR levels, resulting in significantly higher image quality scores at increasing QIR levels (all pairwise p < 0.001). Qualitative sharpness, on the other hand, did not differ across different levels of QIR (p = 0.15). CONCLUSIONS The QIR algorithm may enhance the image quality of CCTA datasets without compromising image sharpness or accurate stenosis measurements, with the most prominent benefits at the highest strength level.
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Affiliation(s)
- Milan Vecsey-Nagy
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, United States; Heart and Vascular Centre, Semmelweis University, 68. Varosmajor street, Budapest 1122, Hungary
| | - Akos Varga-Szemes
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, United States
| | - U Joseph Schoepf
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, United States.
| | - Giuseppe Tremamunno
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, United States; Department of Medical Surgical Sciences and Translational Medicine, Sapienza University of Rome - Sant'Andrea University, Hospital Via di Grottarossa 1035-1039 00189 Rome, Italy
| | - Nicola Fink
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, United States; Department of Radiology, University Hospital, LMU Munich, Marchioninistraße 15, Munich 81377, Germany
| | - Emese Zsarnoczay
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, United States; MTA-SE Cardiovascular Imaging Research Group, Medical Imaging Centre, Semmelweis University, Koranyi Sandor street 2, Budapest 1083, Hungary
| | - Bálint Szilveszter
- Heart and Vascular Centre, Semmelweis University, 68. Varosmajor street, Budapest 1122, Hungary
| | - Dirk Graafen
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University, Langenbeckstraße 1, Mainz 55131, Germany
| | - Moritz C Halfmann
- Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University, Langenbeckstraße 1, Mainz 55131, Germany
| | - Borbála Vattay
- Heart and Vascular Centre, Semmelweis University, 68. Varosmajor street, Budapest 1122, Hungary
| | - Melinda Boussoussou
- Heart and Vascular Centre, Semmelweis University, 68. Varosmajor street, Budapest 1122, Hungary
| | - Jim O'Doherty
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, United States; Siemens Medical Solutions USA Inc, 40 Liberty Boulevard, Malvern, PA 19355, United States
| | - Pal Spruill Suranyi
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, United States
| | - Pál Maurovich-Horvat
- MTA-SE Cardiovascular Imaging Research Group, Medical Imaging Centre, Semmelweis University, Koranyi Sandor street 2, Budapest 1083, Hungary
| | - Tilman Emrich
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Dr, Charleston, SC 29425, United States; Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University, Langenbeckstraße 1, Mainz 55131, Germany
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Cui M, Bao S, Li J, Dong H, Xu Z, Yan F, Yang W. CT radiomic features reproducibility of virtual non-contrast series derived from photon-counting CCTA datasets using a novel calcium-preserving reconstruction algorithm compared with standard non-contrast series: focusing on epicardial adipose tissue. THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2024; 40:1257-1267. [PMID: 38587689 DOI: 10.1007/s10554-024-03096-w] [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: 11/16/2023] [Accepted: 03/26/2024] [Indexed: 04/09/2024]
Abstract
PURPOSE We aimed to evaluate the reproducibility of computed tomography (CT) radiomic features (RFs) about Epicardial Adipose Tissue (EAT). The features derived from coronary photon-counting computed tomography (PCCT) angiography datasets using the PureCalcium (VNCPC) and conventional virtual non-contrast (VNCConv) algorithm were compared with true non-contrast (TNC) series. METHODS RFs of EAT from 52 patients who underwent PCCT were quantified using VNCPC, VNCConv, and TNC series. The agreement of EAT volume (EATV) and EAT density (EATD) was evaluated using Pearson's correlation coefficient and Bland-Altman analysis. A total of 1530 RFs were included. They are divided into 17 feature categories, each containing 90 RFs. The intraclass correlation coefficients (ICCs) and concordance correlation coefficients (CCCs) were calculated to assess the reproducibility of RFs. The cutoff value considered indicative of reproducible features was > 0.75. RESULTS the VNCPC and VNCConv tended to underestimate EATVs and overestimate EATDs. Both EATV and EATD of VNCPC series showed higher correlation and agreement with TNC than VNCConv series. All types of RFs from VNCPC series showed greater reproducibility than VNCConv series. Across all image filters, the Square filter exhibited the highest level of reproducibility (ICC = 67/90, 74.4%; CCC = 67/90, 74.4%). GLDM_GrayLevelNonUniformity feature had the highest reproducibility in the original image (ICC = 0.957, CCC = 0.958), exhibiting a high degree of reproducibility across all image filters. CONCLUSION The accuracy evaluation of EATV and EATD and the reproducibility of RFs from VNCPC series make it an excellent substitute for TNC series exceeding VNCConv series.
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Affiliation(s)
- MengXu Cui
- Department of Radiology, Ruijin Hospital affiliated to School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - ShouYu Bao
- Department of Radiology, Ruijin Hospital affiliated to School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - JiQiang Li
- Department of Radiology, Ruijin Hospital affiliated to School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - HaiPeng Dong
- Department of Radiology, Ruijin Hospital affiliated to School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - ZhiHan Xu
- Siemens Healthineers CT Collaboration, Erlangen, Germany
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital affiliated to School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wenjie Yang
- Department of Radiology, Ruijin Hospital affiliated to School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
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Michallek F, Nakamura S, Kurita T, Ota H, Nishimiya K, Ogawa R, Shizuka T, Nakashima H, Wang YN, Ito T, Sakuma H, Dewey M, Kitagawa K. Differentiating Macrovascular and Microvascular Ischemia Using Fractal Analysis of Dynamic Myocardial Perfusion Stress-CT. Invest Radiol 2024; 59:413-423. [PMID: 37812495 DOI: 10.1097/rli.0000000000001027] [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: 10/10/2023]
Abstract
OBJECTIVES Fractal analysis of dynamic myocardial stress computed tomography perfusion imaging (4D-CTP) has shown potential to noninvasively differentiate obstructive coronary artery disease (CAD) and coronary microvascular disease (CMD). This study validates fractal analysis of 4D-CTP in a multicenter setting and assesses its diagnostic accuracy in subgroups with ischemia and nonobstructed coronary arteries (INOCA) and with mild to moderate stenosis. MATERIALS AND METHODS From the AMPLIFiED multicenter trial, patients with suspected or known chronic myocardial ischemia and an indication for invasive coronary angiography were included. Patients underwent dual-source CT angiography, 4D-CTP, and CT delayed-enhancement imaging. Coronary artery disease, CMD, and normal perfusion were defined by a combined reference standard comprising invasive coronary angiography with fractional flow reserve, and absolute or relative CT-derived myocardial blood flow. Nonobstructed coronary arteries were defined as ≤25% stenosis and mild to moderate stenosis as 26%-80%. RESULTS In 127 patients (27% female), fractal analysis accurately differentiated CAD (n = 61, 23% female), CMD (n = 23, 30% female), and normal perfusion (n = 34, 35% female) with a multiclass area under the receiver operating characteristic curve (AUC) of 0.92 and high agreement (multiclass κ = 0.89). In patients with ischemia (n = 84), fractal analysis detected CAD (n = 61) over CMD (n = 23) with sensitivity of 95%, specificity of 74%, accuracy of 89%, and AUC of 0.83. In patients with nonobstructed coronary arteries (n = 33), INOCA (n = 15) was detected with sensitivity of 100%, specificity of 78%, accuracy of 88%, and AUC of 0.94. In patients with mild to moderate stenosis (n = 27), fractal analysis detected CAD (n = 19) over CMD with sensitivity of 84%, specificity of 100%, accuracy of 89%, and AUC of 0.95. CONCLUSIONS In this multicenter study, fractal analysis of 4D-CTP accurately differentiated CAD and CMD including subgroups with INOCA and with mild to moderate stenosis.
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Affiliation(s)
- Florian Michallek
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany (F.M., M.D.); Department of Advanced Diagnostic Imaging, Mie University Graduate School of Medicine, Tsu, Japan (F.M., K.K.); Department of Radiology, Mie University Graduate School of Medicine, Tsu, Japan (S.N., H.S.); Department of Cardiology and Nephrology, Mie University Graduate School of Medicine, Tsu, Japan (T.K.); Department of Advanced MRI Collaborative Research, Tohoku University Graduate School of Medicine, Sendai, Japan (H.O.); Department of Cardiology, Tohoku University Graduate School of Medicine, Sendai, Japan (K.N.); Saiseikai Matsuyama Hospital, Matsuyama, Japan (R.O.); Takasaki General Medical Center, Takasaki, Japan (T.S.); National Hospital Organization Kagoshima Medical Center, Kagoshima, Japan (H.N.); Peking Union Medical College Hospital, Beijing, China (Y.-N.W.); Kobe University Graduate School of Medicine, Kobe, Japan (T.I.); German Center for Cardiovascular Research, Berlin, Germany (M.D.); and Deutsches Herzzentrum der Charité (M.D.), Berlin, Germany
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Aquino GJ, Mastrodicasa D, Alabed S, Abohashem S, Wen L, Gill RR, Bardo DME, Abbara S, Hanneman K. Radiology: Cardiothoracic Imaging Highlights 2023. Radiol Cardiothorac Imaging 2024; 6:e240020. [PMID: 38602468 PMCID: PMC11056755 DOI: 10.1148/ryct.240020] [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: 01/17/2024] [Revised: 02/15/2024] [Accepted: 02/28/2024] [Indexed: 04/12/2024]
Abstract
Radiology: Cardiothoracic Imaging publishes novel research and technical developments in cardiac, thoracic, and vascular imaging. The journal published many innovative studies during 2023 and achieved an impact factor for the first time since its inaugural issue in 2019, with an impact factor of 7.0. The current review article, led by the Radiology: Cardiothoracic Imaging trainee editorial board, highlights the most impactful articles published in the journal between November 2022 and October 2023. The review encompasses various aspects of coronary CT, photon-counting detector CT, PET/MRI, cardiac MRI, congenital heart disease, vascular imaging, thoracic imaging, artificial intelligence, and health services research. Key highlights include the potential for photon-counting detector CT to reduce contrast media volumes, utility of combined PET/MRI in the evaluation of cardiac sarcoidosis, the prognostic value of left atrial late gadolinium enhancement at MRI in predicting incident atrial fibrillation, the utility of an artificial intelligence tool to optimize detection of incidental pulmonary embolism, and standardization of medical terminology for cardiac CT. Ongoing research and future directions include evaluation of novel PET tracers for assessment of myocardial fibrosis, deployment of AI tools in clinical cardiovascular imaging workflows, and growing awareness of the need to improve environmental sustainability in imaging. Keywords: Coronary CT, Photon-counting Detector CT, PET/MRI, Cardiac MRI, Congenital Heart Disease, Vascular Imaging, Thoracic Imaging, Artificial Intelligence, Health Services Research © RSNA, 2024.
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Affiliation(s)
| | | | - Samer Alabed
- From the Department of Radiology, SUNY Upstate Medical University,
750 E Adams St, Syracuse, NY, 13210 (G.J.A); Department of Radiology, University
of Washington School of Medicine, UW Medical Center Montlake, Seattle, Wash
(D.M.); Department of Radiology, OncoRad/Tumor Imaging Metrics Core (TIMC),
University of Washington School of Medicine, Seattle, Wash (D.M.); Division of
Clinical Medicine, School of Medicine and Population Health, University of
Sheffield, Sheffield, United Kingdom (S. Alabed); National Institute for Health
and Care Research, Sheffield Biomedical Research Centre, Sheffield, United
Kingdom (S. Alabed); Department of Radiology, Cardiovascular Imaging Research
Center, Massachusetts General Hospital and Harvard Medical School, Boston, Mass
(S. Abohashem); Department of Radiology, Key Laboratory of Birth Defects and
Related Diseases of Women and Children, Ministry of Education, West China Second
University Hospital, Sichuan University, Sichuan, China (L.W.); Department of
Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
Mass (R.R.G.); Department of Medical Imaging, Ann & Robert H. Lurie
Children’s Hospital of Chicago, Chicago, Ill (D.M.E.B.); Department of
Radiology, UT Southwestern Medical Center, Dallas, Tex (S. Abbara); Department
of Medical Imaging, University Medical Imaging Toronto, University of Toronto,
Toronto, Ontario, Canada (K.H.); and Peter Munk Cardiac Centre, Toronto General
Hospital, University of Toronto, Toronto, Ontario, Canada (K.H.)
| | - Shady Abohashem
- From the Department of Radiology, SUNY Upstate Medical University,
750 E Adams St, Syracuse, NY, 13210 (G.J.A); Department of Radiology, University
of Washington School of Medicine, UW Medical Center Montlake, Seattle, Wash
(D.M.); Department of Radiology, OncoRad/Tumor Imaging Metrics Core (TIMC),
University of Washington School of Medicine, Seattle, Wash (D.M.); Division of
Clinical Medicine, School of Medicine and Population Health, University of
Sheffield, Sheffield, United Kingdom (S. Alabed); National Institute for Health
and Care Research, Sheffield Biomedical Research Centre, Sheffield, United
Kingdom (S. Alabed); Department of Radiology, Cardiovascular Imaging Research
Center, Massachusetts General Hospital and Harvard Medical School, Boston, Mass
(S. Abohashem); Department of Radiology, Key Laboratory of Birth Defects and
Related Diseases of Women and Children, Ministry of Education, West China Second
University Hospital, Sichuan University, Sichuan, China (L.W.); Department of
Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
Mass (R.R.G.); Department of Medical Imaging, Ann & Robert H. Lurie
Children’s Hospital of Chicago, Chicago, Ill (D.M.E.B.); Department of
Radiology, UT Southwestern Medical Center, Dallas, Tex (S. Abbara); Department
of Medical Imaging, University Medical Imaging Toronto, University of Toronto,
Toronto, Ontario, Canada (K.H.); and Peter Munk Cardiac Centre, Toronto General
Hospital, University of Toronto, Toronto, Ontario, Canada (K.H.)
| | - Lingyi Wen
- From the Department of Radiology, SUNY Upstate Medical University,
750 E Adams St, Syracuse, NY, 13210 (G.J.A); Department of Radiology, University
of Washington School of Medicine, UW Medical Center Montlake, Seattle, Wash
(D.M.); Department of Radiology, OncoRad/Tumor Imaging Metrics Core (TIMC),
University of Washington School of Medicine, Seattle, Wash (D.M.); Division of
Clinical Medicine, School of Medicine and Population Health, University of
Sheffield, Sheffield, United Kingdom (S. Alabed); National Institute for Health
and Care Research, Sheffield Biomedical Research Centre, Sheffield, United
Kingdom (S. Alabed); Department of Radiology, Cardiovascular Imaging Research
Center, Massachusetts General Hospital and Harvard Medical School, Boston, Mass
(S. Abohashem); Department of Radiology, Key Laboratory of Birth Defects and
Related Diseases of Women and Children, Ministry of Education, West China Second
University Hospital, Sichuan University, Sichuan, China (L.W.); Department of
Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
Mass (R.R.G.); Department of Medical Imaging, Ann & Robert H. Lurie
Children’s Hospital of Chicago, Chicago, Ill (D.M.E.B.); Department of
Radiology, UT Southwestern Medical Center, Dallas, Tex (S. Abbara); Department
of Medical Imaging, University Medical Imaging Toronto, University of Toronto,
Toronto, Ontario, Canada (K.H.); and Peter Munk Cardiac Centre, Toronto General
Hospital, University of Toronto, Toronto, Ontario, Canada (K.H.)
| | - Ritu R. Gill
- From the Department of Radiology, SUNY Upstate Medical University,
750 E Adams St, Syracuse, NY, 13210 (G.J.A); Department of Radiology, University
of Washington School of Medicine, UW Medical Center Montlake, Seattle, Wash
(D.M.); Department of Radiology, OncoRad/Tumor Imaging Metrics Core (TIMC),
University of Washington School of Medicine, Seattle, Wash (D.M.); Division of
Clinical Medicine, School of Medicine and Population Health, University of
Sheffield, Sheffield, United Kingdom (S. Alabed); National Institute for Health
and Care Research, Sheffield Biomedical Research Centre, Sheffield, United
Kingdom (S. Alabed); Department of Radiology, Cardiovascular Imaging Research
Center, Massachusetts General Hospital and Harvard Medical School, Boston, Mass
(S. Abohashem); Department of Radiology, Key Laboratory of Birth Defects and
Related Diseases of Women and Children, Ministry of Education, West China Second
University Hospital, Sichuan University, Sichuan, China (L.W.); Department of
Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
Mass (R.R.G.); Department of Medical Imaging, Ann & Robert H. Lurie
Children’s Hospital of Chicago, Chicago, Ill (D.M.E.B.); Department of
Radiology, UT Southwestern Medical Center, Dallas, Tex (S. Abbara); Department
of Medical Imaging, University Medical Imaging Toronto, University of Toronto,
Toronto, Ontario, Canada (K.H.); and Peter Munk Cardiac Centre, Toronto General
Hospital, University of Toronto, Toronto, Ontario, Canada (K.H.)
| | - Dianna M. E. Bardo
- From the Department of Radiology, SUNY Upstate Medical University,
750 E Adams St, Syracuse, NY, 13210 (G.J.A); Department of Radiology, University
of Washington School of Medicine, UW Medical Center Montlake, Seattle, Wash
(D.M.); Department of Radiology, OncoRad/Tumor Imaging Metrics Core (TIMC),
University of Washington School of Medicine, Seattle, Wash (D.M.); Division of
Clinical Medicine, School of Medicine and Population Health, University of
Sheffield, Sheffield, United Kingdom (S. Alabed); National Institute for Health
and Care Research, Sheffield Biomedical Research Centre, Sheffield, United
Kingdom (S. Alabed); Department of Radiology, Cardiovascular Imaging Research
Center, Massachusetts General Hospital and Harvard Medical School, Boston, Mass
(S. Abohashem); Department of Radiology, Key Laboratory of Birth Defects and
Related Diseases of Women and Children, Ministry of Education, West China Second
University Hospital, Sichuan University, Sichuan, China (L.W.); Department of
Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
Mass (R.R.G.); Department of Medical Imaging, Ann & Robert H. Lurie
Children’s Hospital of Chicago, Chicago, Ill (D.M.E.B.); Department of
Radiology, UT Southwestern Medical Center, Dallas, Tex (S. Abbara); Department
of Medical Imaging, University Medical Imaging Toronto, University of Toronto,
Toronto, Ontario, Canada (K.H.); and Peter Munk Cardiac Centre, Toronto General
Hospital, University of Toronto, Toronto, Ontario, Canada (K.H.)
| | - Suhny Abbara
- From the Department of Radiology, SUNY Upstate Medical University,
750 E Adams St, Syracuse, NY, 13210 (G.J.A); Department of Radiology, University
of Washington School of Medicine, UW Medical Center Montlake, Seattle, Wash
(D.M.); Department of Radiology, OncoRad/Tumor Imaging Metrics Core (TIMC),
University of Washington School of Medicine, Seattle, Wash (D.M.); Division of
Clinical Medicine, School of Medicine and Population Health, University of
Sheffield, Sheffield, United Kingdom (S. Alabed); National Institute for Health
and Care Research, Sheffield Biomedical Research Centre, Sheffield, United
Kingdom (S. Alabed); Department of Radiology, Cardiovascular Imaging Research
Center, Massachusetts General Hospital and Harvard Medical School, Boston, Mass
(S. Abohashem); Department of Radiology, Key Laboratory of Birth Defects and
Related Diseases of Women and Children, Ministry of Education, West China Second
University Hospital, Sichuan University, Sichuan, China (L.W.); Department of
Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
Mass (R.R.G.); Department of Medical Imaging, Ann & Robert H. Lurie
Children’s Hospital of Chicago, Chicago, Ill (D.M.E.B.); Department of
Radiology, UT Southwestern Medical Center, Dallas, Tex (S. Abbara); Department
of Medical Imaging, University Medical Imaging Toronto, University of Toronto,
Toronto, Ontario, Canada (K.H.); and Peter Munk Cardiac Centre, Toronto General
Hospital, University of Toronto, Toronto, Ontario, Canada (K.H.)
| | - Kate Hanneman
- From the Department of Radiology, SUNY Upstate Medical University,
750 E Adams St, Syracuse, NY, 13210 (G.J.A); Department of Radiology, University
of Washington School of Medicine, UW Medical Center Montlake, Seattle, Wash
(D.M.); Department of Radiology, OncoRad/Tumor Imaging Metrics Core (TIMC),
University of Washington School of Medicine, Seattle, Wash (D.M.); Division of
Clinical Medicine, School of Medicine and Population Health, University of
Sheffield, Sheffield, United Kingdom (S. Alabed); National Institute for Health
and Care Research, Sheffield Biomedical Research Centre, Sheffield, United
Kingdom (S. Alabed); Department of Radiology, Cardiovascular Imaging Research
Center, Massachusetts General Hospital and Harvard Medical School, Boston, Mass
(S. Abohashem); Department of Radiology, Key Laboratory of Birth Defects and
Related Diseases of Women and Children, Ministry of Education, West China Second
University Hospital, Sichuan University, Sichuan, China (L.W.); Department of
Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston,
Mass (R.R.G.); Department of Medical Imaging, Ann & Robert H. Lurie
Children’s Hospital of Chicago, Chicago, Ill (D.M.E.B.); Department of
Radiology, UT Southwestern Medical Center, Dallas, Tex (S. Abbara); Department
of Medical Imaging, University Medical Imaging Toronto, University of Toronto,
Toronto, Ontario, Canada (K.H.); and Peter Munk Cardiac Centre, Toronto General
Hospital, University of Toronto, Toronto, Ontario, Canada (K.H.)
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Wolf EV, Halfmann MC, Varga-Szemes A, Fink N, Kloeckner R, Bockius S, Allmendinger T, Hagenauer J, Koehler T, Kreitner KF, Schoepf UJ, Münzel T, Düber C, Gori T, Yang Y, Hell MM, Emrich T. Photon-Counting Detector CT Virtual Monoenergetic Images for Coronary Artery Stenosis Quantification: Phantom and In Vivo Evaluation. AJR Am J Roentgenol 2024; 222:e2330481. [PMID: 38197760 DOI: 10.2214/ajr.23.30481] [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: 01/11/2024]
Abstract
BACKGROUND. Calcium blooming causes stenosis overestimation on coronary CTA. OBJECTIVE. The purpose of this article was to evaluate the impact of virtual monoenergetic imaging (VMI) reconstruction level on coronary artery stenosis quantification using photon-counting detector (PCD) CT. METHODS. A phantom containing two custom-made vessels (representing 25% and 50% stenosis) underwent PCD CT acquisitions without and with simulated cardiac motion. A retrospective analysis was performed of 33 patients (seven women, 26 men; mean age, 71.3 ± 9.0 [SD] years; 64 coronary artery stenoses) who underwent coronary CTA by PCD CT followed by invasive coronary angiography (ICA). Scans were reconstructed at nine VMI energy levels (40-140 keV). Percentage diameter stenosis (PDS) was measured, and bias was determined from the ground-truth stenosis percentage in the phantom and ICA-derived quantitative coronary angiography measurements in patients. Extent of blooming artifact was measured in the phantom and in calcified and mixed plaques in patients. RESULTS. In the phantom, PDS decreased for 25% stenosis from 59.9% (40 keV) to 13.4% (140 keV) and for 50% stenosis from 81.6% (40 keV) to 42.3% (140 keV). PDS showed lowest bias for 25% stenosis at 90 keV (bias, 1.4%) and for 50% stenosis at 100 keV (bias, -0.4%). Blooming artifacts decreased for 25% stenosis from 61.5% (40 keV) to 35.4% (140 keV) and for 50% stenosis from 82.7% (40 keV) to 52.1% (140 keV). In patients, PDS for calcified plaque decreased from 70.8% (40 keV) to 57.3% (140 keV), for mixed plaque decreased from 69.8% (40 keV) to 56.3% (140 keV), and for noncalcified plaque was 46.6% at 40 keV and 54.6% at 140 keV. PDS showed lowest bias for calcified plaque at 100 keV (bias, 17.2%), for mixed plaque at 140 keV (bias, 5.0%), and for noncalcified plaque at 40 keV (bias, -0.5%). Blooming artifacts decreased for calcified plaque from 78.4% (40 keV) to 48.6% (140 keV) and for mixed plaque from 73.1% (40 keV) to 44.7% (140 keV). CONCLUSION. For calcified and mixed plaque, stenosis severity measurements and blooming artifacts decreased at increasing VMI reconstruction levels. CLINICAL IMPACT. PCD CT with VMI reconstruction helps overcome current limitations in stenosis quantification on coronary CTA.
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Affiliation(s)
- Elias V Wolf
- Department of Diagnostic and Interventional Radiology, University Medical Center Mainz, Langenbeckstraβe 1, 55131 Mainz, Germany
- Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC
| | - Moritz C Halfmann
- Department of Diagnostic and Interventional Radiology, University Medical Center Mainz, Langenbeckstraβe 1, 55131 Mainz, Germany
- German Centre for Cardiovascular Research, Partner site Rhine-Main, Mainz, Germany
| | - Akos Varga-Szemes
- Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC
| | - Nicola Fink
- Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC
- Department of Radiology, University Hospital, LMU Munich, München, Germany
| | - Roman Kloeckner
- Department of Diagnostic and Interventional Radiology, University Medical Center Mainz, Langenbeckstraβe 1, 55131 Mainz, Germany
- Department for Interventional Radiology, University Hospital of Lübeck, Lübeck, Germany
| | - Stefanie Bockius
- Department of Diagnostic and Interventional Radiology, University Medical Center Mainz, Langenbeckstraβe 1, 55131 Mainz, Germany
| | | | | | | | - Karl-Friedrich Kreitner
- Department of Diagnostic and Interventional Radiology, University Medical Center Mainz, Langenbeckstraβe 1, 55131 Mainz, Germany
| | - U Joseph Schoepf
- Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC
| | - Thomas Münzel
- German Centre for Cardiovascular Research, Partner site Rhine-Main, Mainz, Germany
- Department of Cardiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
| | - Christoph Düber
- Department of Diagnostic and Interventional Radiology, University Medical Center Mainz, Langenbeckstraβe 1, 55131 Mainz, Germany
| | - Tommaso Gori
- German Centre for Cardiovascular Research, Partner site Rhine-Main, Mainz, Germany
- Department of Cardiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
| | - Yang Yang
- Department of Diagnostic and Interventional Radiology, University Medical Center Mainz, Langenbeckstraβe 1, 55131 Mainz, Germany
| | - Michaela M Hell
- Department of Cardiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany
| | - Tilman Emrich
- Department of Diagnostic and Interventional Radiology, University Medical Center Mainz, Langenbeckstraβe 1, 55131 Mainz, Germany
- Department of Radiology and Radiological Science, Division of Cardiovascular Imaging, Medical University of South Carolina, Charleston, SC
- German Centre for Cardiovascular Research, Partner site Rhine-Main, Mainz, Germany
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Moser LJ, Mergen V, Allmendinger T, Manka R, Eberhard M, Alkadhi H. A Novel Reconstruction Technique to Reduce Stair-Step Artifacts in Sequential Mode Coronary CT Angiography. Invest Radiol 2024:00004424-990000000-00195. [PMID: 38284879 DOI: 10.1097/rli.0000000000001066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2024]
Abstract
PURPOSE Prospective electrocardiography-triggering is one of the most commonly used cardiac computed tomography (CT) scan modes but can be susceptible to stair-step artifacts in the transition areas of an acquisition over multiple cardiac cycles. We evaluated a novel reconstruction algorithm to reduce the occurrence and severity of such artifacts in sequential coronary CT angiography. MATERIALS AND METHODS In this institutional review board-approved, retrospective study, 50 consecutive patients (16 females; mean age, 58.9 ± 15.2) were included who underwent coronary CT angiography on a dual-source photon-counting detector CT in the sequential ultra-high-resolution mode with a detector collimation of 120 × 0.2 mm. Each scan was reconstructed without (hereafter called standard reconstruction) and with the novel ZeeFree reconstruction algorithm, which aims to minimize stair-step artifacts. The presence and extent of stair-step artifacts were rated by 2 independent, blinded readers on a 4-point discrete visual scale. The relationship between the occurrences of artifacts was correlated with the average and variability of heart rate and with patient characteristics. RESULTS A total of 504 coronary segments were included into the analyses. In standard reconstructions, reader 1 reported stair-step artifacts in 40/504 (7.9%) segments, from which 12/504 led to nondiagnostic image quality (2.4% of all segments). Reader 2 reported 56/504 (11.1%) stair-step artifacts, from which 11/504 lead to nondiagnostic image quality (2.2% of all segments). With the ZeeFree algorithm, 9/12 (75%) and 8/11 (73%) of the nondiagnostic segments improved to a diagnostic quality for readers 1 and 2, respectively. The ZeeFree reconstruction algorithm significantly reduced the frequency and extent of stair-step artifacts compared with standard reconstructions for both readers (P < 0.001, each). Heart rate variability and body mass index were significantly related to the occurrence of stair-step artifacts (P < 0.05). CONCLUSIONS Our study demonstrates the feasibility and effectiveness of a novel reconstruction algorithm leading to a significant reduction of stair-step artifacts and, hence, a reduction of coronary segments with a nondiagnostic image quality in sequential ultra-high-resolution coronary photon-counting detector CT angiography.
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Affiliation(s)
- Lukas Jakob Moser
- From the Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland (L.J.M., V.M., R.M., M.E., H.A.); Siemens Healthineers AG, Forchheim, Germany (T.A.); and Department of Radiology, Spital Interlaken, Spitäler fmi AG, Unterseen, Switzerland (M.E.)
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8
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Gruschwitz P, Hartung V, Ergün S, Peter D, Lichthardt S, Huflage H, Hendel R, Pannenbecker P, Augustin AM, Kunz AS, Feldle P, Bley TA, Grunz JP. Comparison of ultrahigh and standard resolution photon-counting CT angiography of the femoral arteries in a continuously perfused in vitro model. Eur Radiol Exp 2023; 7:83. [PMID: 38110729 PMCID: PMC10728414 DOI: 10.1186/s41747-023-00398-x] [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: 07/27/2023] [Accepted: 10/17/2023] [Indexed: 12/20/2023] Open
Abstract
BACKGROUND With the emergence of photon-counting CT, ultrahigh-resolution (UHR) imaging can be performed without dose penalty. This study aims to directly compare the image quality of UHR and standard resolution (SR) scan mode in femoral artery angiographies. METHODS After establishing continuous extracorporeal perfusion in four fresh-frozen cadaveric specimens, photon-counting CT angiographies were performed with a radiation dose of 5 mGy and tube voltage of 120 kV in both SR and UHR mode. Images were reconstructed with dedicated convolution kernels (soft: Body-vascular (Bv)48; sharp: Bv60; ultrasharp: Bv76). Six radiologists evaluated the image quality by means of a pairwise forced-choice comparison tool. Kendall's concordance coefficient (W) was calculated to quantify interrater agreement. Image quality was further assessed by measuring intraluminal attenuation and image noise as well as by calculating signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNR). RESULTS UHR yielded lower noise than SR for identical reconstructions with kernels ≥ Bv60 (p < 0.001). UHR scans exhibited lower intraluminal attenuation compared to SR (Bv60: 406.4 ± 25.1 versus 418.1 ± 30.1 HU; p < 0.001). Irrespective of scan mode, SNR and CNR decreased while noise increased with sharper kernels but UHR scans were objectively superior to SR nonetheless (Bv60: SNR 25.9 ± 6.4 versus 20.9 ± 5.3; CNR 22.7 ± 5.8 versus 18.4 ± 4.8; p < 0.001). Notably, UHR scans were preferred in subjective assessment when images were reconstructed with the ultrasharp Bv76 kernel, whereas SR was rated superior for Bv60. Interrater agreement was high (W = 0.935). CONCLUSIONS Combinations of UHR scan mode and ultrasharp convolution kernel are able to exploit the full image quality potential in photon-counting CT angiography of the femoral arteries. RELEVANCE STATEMENT The UHR scan mode offers improved image quality and may increase diagnostic accuracy in CT angiography of the peripheral arterial runoff when optimized reconstruction parameters are chosen. KEY POINTS • UHR photon-counting CT improves image quality in combination with ultrasharp convolution kernels. • UHR datasets display lower image noise compared with identically reconstructed standard resolution scans. • Scans in UHR mode show decreased intraluminal attenuation compared with standard resolution imaging.
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Affiliation(s)
- Philipp Gruschwitz
- Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany.
| | - Viktor Hartung
- Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany
| | - Süleyman Ergün
- Institute of Anatomy and Cell Biology, University of Würzburg, Würzburg, Germany
| | - Dominik Peter
- Department of General, Visceral, Transplant, Vascular, and Pediatric Surgery, University Hospital of Würzburg, Würzburg, Germany
| | - Sven Lichthardt
- Department of General, Visceral, Transplant, Vascular, and Pediatric Surgery, University Hospital of Würzburg, Würzburg, Germany
| | - Henner Huflage
- Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany
| | - Robin Hendel
- Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany
| | - Pauline Pannenbecker
- Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany
| | - Anne Marie Augustin
- Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany
| | - Andreas Steven Kunz
- Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany
| | - Philipp Feldle
- Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany
| | - Thorsten Alexander Bley
- Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany
| | - Jan-Peter Grunz
- Department of Diagnostic and Interventional Radiology, University Hospital of Würzburg, Würzburg, Germany
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9
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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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10
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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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11
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Flohr T, Schmidt B. Technical Basics and Clinical Benefits of Photon-Counting CT. Invest Radiol 2023; 58:441-450. [PMID: 37185302 PMCID: PMC10259209 DOI: 10.1097/rli.0000000000000980] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Accepted: 03/05/2023] [Indexed: 05/17/2023]
Abstract
ABSTRACT Novel photon-counting detector CT (PCD-CT) has the potential to address the limitations of previous CT systems, such as insufficient spatial resolution, limited accuracy in detecting small low-contrast structures, or missing routine availability of spectral information. In this review article, we explain the basic principles and potential clinical benefits of PCD-CT, with a focus on recent literature that has grown rapidly since the commercial introduction of a clinically approved PCD-CT.
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12
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Abel F, Schubert T, Winklhofer S. Advanced Neuroimaging With Photon-Counting Detector CT. Invest Radiol 2023; 58:472-481. [PMID: 37158466 DOI: 10.1097/rli.0000000000000984] [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: 05/10/2023]
Abstract
ABSTRACT Photon-counting detector computed tomography (PCD-CT) is an emerging technology and promises the next step in CT evolution. Photon-counting detectors count the number of individual incoming photons and assess the energy level of each of them. These mechanisms differ substantially from conventional energy-integrating detectors. The new technique has several advantages, including lower radiation exposure, higher spatial resolution, reconstruction of images with less beam-hardening artifacts, and advanced opportunities for spectral imaging. Research PCD-CT systems have already demonstrated promising results, and recently, the first whole-body full field-of-view PCD-CT scanners became clinically available. Based on published studies of preclinical systems and the first experience with clinically approved scanners, the performance can be translated to valuable neuroimaging applications, including brain imaging, intracranial and extracranial CT angiographies, or head and neck imaging with detailed assessment of the temporal bone. In this review, we will provide an overview of the current status in neuroimaging with upcoming and potential clinical applications.
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Affiliation(s)
- Frederik Abel
- From the Department of Diagnostic and Interventional Radiology
| | - Tilman Schubert
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Sebastian Winklhofer
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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