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Lisi C, Moser LJ, Mergen V, Klambauer K, Uçar E, Eberhard M, Alkadhi H. Advanced myocardial characterization and function with cardiac CT. THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2024:10.1007/s10554-024-03229-1. [PMID: 39240440 DOI: 10.1007/s10554-024-03229-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 08/21/2024] [Indexed: 09/07/2024]
Abstract
Non-invasive imaging with characterization and quantification of the myocardium with computed tomography (CT) became feasible owing to recent technical developments in CT technology. Cardiac CT can serve as an alternative modality when cardiac magnetic resonance imaging and/or echocardiography are contraindicated, not feasible, inconclusive, or non-diagnostic. This review summarizes the current and potential future role of cardiac CT for myocardial characterization including a summary of late enhancement techniques, extracellular volume quantification, and strain analysis. In addition, this review highlights potential fields for research about myocardial characterization with CT to possibly include it in clinical routine in the future.
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Affiliation(s)
- Costanza Lisi
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Biomedical Sciences, Humanitas University, via Rita Levi Montalcini 4, Pieve Emanuele, 20072, Milan, Italy
| | - Lukas J Moser
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Victor Mergen
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Konstantin Klambauer
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Eda Uçar
- Faculty of Medicine, Marmara University, Istanbul, Turkey
| | - Matthias Eberhard
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Hatem Alkadhi
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
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Gonciar D, Berciu AG, Dulf EH, Orzan RI, Mocan T, Danku AE, Lorenzovici N, Agoston-Coldea L. Computer-Assisted Algorithm for Quantification of Fibrosis by Native Cardiac CT: A Pilot Study. J Clin Med 2024; 13:4807. [PMID: 39200950 PMCID: PMC11355413 DOI: 10.3390/jcm13164807] [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: 08/04/2024] [Revised: 08/08/2024] [Accepted: 08/09/2024] [Indexed: 09/02/2024] Open
Abstract
Background/Objectives: Recent advances in artificial intelligence, particularly in cardiac imaging, can potentially enhance patients' diagnosis and prognosis and identify novel imaging markers. We propose an automated, computer-aided algorithm utilizing native cardiac computed tomography (CT) imaging to identify myocardial fibrosis. This study aims to evaluate its performance compared to CMR markers of fibrosis in a cohort of patients diagnosed with breast cancer. Methods: The study included patients diagnosed with early HER2+ breast cancer, who presented LV dysfunction (LVEF < 50%) and myocardial fibrosis detected on CMR at the time of diagnosis. The patients were also evaluated by cardiac CT, and the extracted images were processed for the implementation of the automatic, computer-assisted algorithm, which marked as fibrosis every pixel that fell within the range of 60-90 HU. The percentage of pixels with fibrosis was subsequently compared with CMR parameters. Results: A total of eight patients (n = 8) were included in the study. High positive correlations between the algorithm's result and the ECV fraction (r = 0.59, p = 0.126) and native T1 (r = 0.6, p = 0.112) were observed, and a very high positive correlation with LGE of the LV(g) and the LV-LGE/LV mass percentage (r = 0.77, p = 0.025; r = 0.81, p = 0.015). A very high negative correlation was found with GLS (r = -0.77, p = 0.026). The algorithm presented an intraclass correlation coefficient of 1 (95% CI 0.99-1), p < 0.001. Conclusions: The present pilot study proposes a novel promising imaging marker for myocardial fibrosis, generated by an automatic algorithm based on native cardiac CT images.
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Affiliation(s)
- Diana Gonciar
- 2nd Department of Internal Medicine, Iuliu Hațieganu University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania; (D.G.); (R.I.O.); (L.A.-C.)
| | - Alexandru-George Berciu
- Automation Department, Faculty of Automation and Computer Science, Energy Transition Research Center, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania; (E.-H.D.); (A.E.D.); (N.L.)
| | - Eva-Henrietta Dulf
- Automation Department, Faculty of Automation and Computer Science, Energy Transition Research Center, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania; (E.-H.D.); (A.E.D.); (N.L.)
- Physiological Controls Research Center, University Research and Innovation Center, Obuda University, 1034 Budapest, Hungary
| | - Rares Ilie Orzan
- 2nd Department of Internal Medicine, Iuliu Hațieganu University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania; (D.G.); (R.I.O.); (L.A.-C.)
| | - Teodora Mocan
- Physiology Department, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania;
- Department of Nanomedicine, Regional Institute of Gastroenterology and Hepatology, 400158 Cluj-Napoca, Romania
| | - Alex Ede Danku
- Automation Department, Faculty of Automation and Computer Science, Energy Transition Research Center, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania; (E.-H.D.); (A.E.D.); (N.L.)
| | - Noemi Lorenzovici
- Automation Department, Faculty of Automation and Computer Science, Energy Transition Research Center, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania; (E.-H.D.); (A.E.D.); (N.L.)
| | - Lucia Agoston-Coldea
- 2nd Department of Internal Medicine, Iuliu Hațieganu University of Medicine and Pharmacy, 400012 Cluj-Napoca, Romania; (D.G.); (R.I.O.); (L.A.-C.)
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Mergen V, Ehrbar N, Moser LJ, Harmes JC, Manka R, Alkadhi H, Eberhard M. Synthetic hematocrit from virtual non-contrast images for myocardial extracellular volume evaluation with photon-counting detector CT. Eur Radiol 2024:10.1007/s00330-024-10865-7. [PMID: 38935123 DOI: 10.1007/s00330-024-10865-7] [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: 02/05/2024] [Revised: 04/07/2024] [Accepted: 04/30/2024] [Indexed: 06/28/2024]
Abstract
OBJECTIVES To assess the accuracy of a synthetic hematocrit derived from virtual non-contrast (VNC) and virtual non-iodine images (VNI) for myocardial extracellular volume (ECV) computation with photon-counting detector computed tomography (PCD-CT). MATERIALS AND METHODS Consecutive patients undergoing PCD-CT including a coronary CT angiography (CCTA) and a late enhancement (LE) scan and having a blood hematocrit were retrospectively included. In the first 75 patients (derivation cohort), CCTA and LE scans were reconstructed as VNI at 60, 70, and 80 keV and as VNC with quantum iterative reconstruction (QIR) strengths 2, 3, and 4. Blood pool attenuation (BPmean) was correlated to blood hematocrit. In the next 50 patients (validation cohort), synthetic hematocrit was calculated using BPmean. Myocardial ECV was computed using the synthetic hematocrit and compared with the ECV using the blood hematocrit as a reference. RESULTS In the derivation cohort (49 men, mean age 79 ± 8 years), a correlation between BPmean and blood hematocrit ranged from poor for VNI of CCTA at 80 keV, QIR2 (R2 = 0.12) to moderate for VNI of LE at 60 keV, QIR4; 70 keV, QIR3 and 4; and VNC of LE, QIR3 and 4 (all, R2 = 0.58). In the validation cohort (29 men, age 75 ± 14 years), synthetic hematocrit was calculated from VNC of the LE scan, QIR3. Median ECV was 26.9% (interquartile range (IQR), 25.5%, 28.8%) using the blood hematocrit and 26.8% (IQR, 25.4%, 29.7%) using synthetic hematocrit (VNC, QIR3; mean difference, -0.2%; limits of agreement, -2.4%, 2.0%; p = 0.33). CONCLUSION Synthetic hematocrit calculated from VNC images enables an accurate computation of myocardial ECV with PCD-CT. CLINICAL RELEVANCE STATEMENT Virtual non-contrast images from cardiac late enhancement scans with photon-counting detector CT allow the calculation of a synthetic hematocrit, which enables accurate computation of myocardial extracellular volume. KEY POINTS Blood hematocrit is mandatory for conventional myocardial extracellular volume computation. Synthetic hematocrit can be calculated from virtual non-iodine and non-contrast photon-counting detector CT images. Synthetic hematocrit from virtual non-contrast images enables computation of the myocardial extracellular volume.
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Affiliation(s)
- Victor Mergen
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Nicolas Ehrbar
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Lukas J Moser
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Johannes C Harmes
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Robert Manka
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Cardiology, University Heart Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Hatem Alkadhi
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Matthias Eberhard
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
- Radiology, Spitäler fmi AG, Spital Interlaken, Unterseen, Switzerland.
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Kim NY, Im DJ, Hong YJ, Choi BW, Kang SM, Youn JC, Lee HJ. Feasibility of the Threshold-Based Quantification of Myocardial Fibrosis on Cardiac CT as a Prognostic Marker in Nonischemic Dilated Cardiomyopathy. Korean J Radiol 2024; 25:540-549. [PMID: 38807335 PMCID: PMC11136943 DOI: 10.3348/kjr.2023.1271] [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: 12/21/2023] [Revised: 02/26/2024] [Accepted: 03/22/2024] [Indexed: 05/30/2024] Open
Abstract
OBJECTIVE This study investigated the feasibility and prognostic relevance of threshold-based quantification of myocardial delayed enhancement (MDE) on CT in patients with nonischemic dilated cardiomyopathy (NIDCM). MATERIALS AND METHODS Forty-three patients with NIDCM (59.3 ± 17.1 years; 21 male) were included in the study and underwent cardiac CT and MRI. MDE was quantified manually and with a threshold-based quantification method using cutoffs of 2, 3, and 4 standard deviations (SDs) on three sets of CT images (100 kVp, 120 kVp, and 70 keV). Interobserver agreement in MDE quantification was assessed using the intraclass correlation coefficient (ICC). Agreement between CT and MRI was evaluated using the Bland-Altman method and the concordance correlation coefficient (CCC). Patients were followed up for the subsequent occurrence of the primary composite outcome, including cardiac death, heart transplantation, heart failure hospitalization, or appropriate use of an implantable cardioverter-defibrillator. The Kaplan-Meier method was used to estimate event-free survival according to MDE levels. RESULTS Late gadolinium enhancement (LGE) was observed in 29 patients (67%, 29/43), and the mean LGE found with the 5-SD threshold was 4.1% ± 3.6%. The 4-SD threshold on 70-keV CT showed excellent interobserver agreement (ICC = 0.810) and the highest concordance with MRI (CCC = 0.803). This method also yielded the smallest bias with the narrowest range of 95% limits of agreement compared to MRI (bias, -0.119%; 95% limits of agreement, -4.216% to 3.978%). During a median follow-up of 1625 days (interquartile range, 712-1430 days), 10 patients (23%, 10/43) experienced the primary composite outcome. Event-free survival significantly differed between risk subgroups divided by the optimal MDE cutoff of 4.3% (log-rank P = 0.005). CONCLUSION The 4-SD threshold on 70-keV monochromatic CT yielded results comparable to those of MRI for quantifying MDE as a marker of myocardial fibrosis, which showed prognostic value in patients with NIDCM.
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Affiliation(s)
- Na Young Kim
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Dong Jin Im
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yoo Jin Hong
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Byoung Wook Choi
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Seok-Min Kang
- Division of Cardiology, Department of Internal Medicine, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jong-Chan Youn
- Division of Cardiology, Department of Internal Medicine, Seoul St. Mary's Hospital, Catholic Research Institute for Intractable Cardiovascular Disease, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
| | - Hye-Jeong Lee
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
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Meloni A, Maffei E, Clemente A, De Gori C, Occhipinti M, Positano V, Berti S, La Grutta L, Saba L, Cau R, Bossone E, Mantini C, Cavaliere C, Punzo B, Celi S, Cademartiri F. Spectral Photon-Counting Computed Tomography: Technical Principles and Applications in the Assessment of Cardiovascular Diseases. J Clin Med 2024; 13:2359. [PMID: 38673632 PMCID: PMC11051476 DOI: 10.3390/jcm13082359] [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: 03/16/2024] [Revised: 04/15/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
Spectral Photon-Counting Computed Tomography (SPCCT) represents a groundbreaking advancement in X-ray imaging technology. The core innovation of SPCCT lies in its photon-counting detectors, which can count the exact number of incoming x-ray photons and individually measure their energy. The first part of this review summarizes the key elements of SPCCT technology, such as energy binning, energy weighting, and material decomposition. Its energy-discriminating ability represents the key to the increase in the contrast between different tissues, the elimination of the electronic noise, and the correction of beam-hardening artifacts. Material decomposition provides valuable insights into specific elements' composition, concentration, and distribution. The capability of SPCCT to operate in three or more energy regimes allows for the differentiation of several contrast agents, facilitating quantitative assessments of elements with specific energy thresholds within the diagnostic energy range. The second part of this review provides a brief overview of the applications of SPCCT in the assessment of various cardiovascular disease processes. SPCCT can support the study of myocardial blood perfusion and enable enhanced tissue characterization and the identification of contrast agents, in a manner that was previously unattainable.
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Affiliation(s)
- Antonella Meloni
- Bioengineering Unit, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.M.); (V.P.)
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Erica Maffei
- Department of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico SYNLAB SDN, 80131 Naples, Italy; (E.M.); (C.C.); (B.P.)
| | - Alberto Clemente
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Carmelo De Gori
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Mariaelena Occhipinti
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Vicenzo Positano
- Bioengineering Unit, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.M.); (V.P.)
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
| | - Sergio Berti
- Diagnostic and Interventional Cardiology Department, Fondazione G. Monasterio CNR-Regione Toscana, 54100 Massa, Italy;
| | - Ludovico La Grutta
- Department of Radiology, University Hospital “P. Giaccone”, 90127 Palermo, Italy;
| | - Luca Saba
- Department of Radiology, University Hospital of Cagliari, 09042 Monserrato (CA), Italy; (L.S.); (R.C.)
| | - Riccardo Cau
- Department of Radiology, University Hospital of Cagliari, 09042 Monserrato (CA), Italy; (L.S.); (R.C.)
| | - Eduardo Bossone
- Department of Cardiology, Ospedale Cardarelli, 80131 Naples, Italy;
| | - Cesare Mantini
- Department of Radiology, “G. D’Annunzio” University, 66100 Chieti, Italy;
| | - Carlo Cavaliere
- Department of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico SYNLAB SDN, 80131 Naples, Italy; (E.M.); (C.C.); (B.P.)
| | - Bruna Punzo
- Department of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico SYNLAB SDN, 80131 Naples, Italy; (E.M.); (C.C.); (B.P.)
| | - Simona Celi
- BioCardioLab, Fondazione G. Monasterio CNR-Regione Toscana, 54100 Massa, Italy;
| | - Filippo Cademartiri
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.C.); (C.D.G.); (M.O.)
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Sachdeva R, Armstrong AK, Arnaout R, Grosse-Wortmann L, Han BK, Mertens L, Moore RA, Olivieri LJ, Parthiban A, Powell AJ. Novel Techniques in Imaging Congenital Heart Disease: JACC Scientific Statement. J Am Coll Cardiol 2024; 83:63-81. [PMID: 38171712 PMCID: PMC10947556 DOI: 10.1016/j.jacc.2023.10.025] [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: 07/21/2023] [Revised: 10/05/2023] [Accepted: 10/13/2023] [Indexed: 01/05/2024]
Abstract
Recent years have witnessed exponential growth in cardiac imaging technologies, allowing better visualization of complex cardiac anatomy and improved assessment of physiology. These advances have become increasingly important as more complex surgical and catheter-based procedures are evolving to address the needs of a growing congenital heart disease population. This state-of-the-art review presents advances in echocardiography, cardiac magnetic resonance, cardiac computed tomography, invasive angiography, 3-dimensional modeling, and digital twin technology. The paper also highlights the integration of artificial intelligence with imaging technology. While some techniques are in their infancy and need further refinement, others have found their way into clinical workflow at well-resourced centers. Studies to evaluate the clinical value and cost-effectiveness of these techniques are needed. For techniques that enhance the value of care for congenital heart disease patients, resources will need to be allocated for education and training to promote widespread implementation.
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Affiliation(s)
- Ritu Sachdeva
- Department of Pediatrics, Division of Pediatric Cardiology, Emory University School of Medicine and Children's Healthcare of Atlanta, Atlanta, Georgia, USA.
| | - Aimee K Armstrong
- The Heart Center, Nationwide Children's Hospital, Department of Pediatrics, Division of Cardiology, Ohio State University, Columbus, Ohio, USA
| | - Rima Arnaout
- Division of Cardiology, Department of Medicine, University of California-San Francisco, San Francisco, California, USA
| | - Lars Grosse-Wortmann
- Division of Cardiology, Department of Pediatrics, Oregon Health and Science University, Portland, Oregon, USA
| | - B Kelly Han
- Division of Cardiology, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Luc Mertens
- Division of Cardiology, Department of Pediatrics, University of Toronto and The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Ryan A Moore
- The Heart Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Laura J Olivieri
- Division of Cardiology, Department of Pediatrics, Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Anitha Parthiban
- Department of Cardiology, Texas Children's Hospital, Baylor College of Medicine, Houston, Texas, USA
| | - Andrew J Powell
- Department of Cardiology, Boston Children's Hospital, Boston, Massachusetts, USA; Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
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Rajiah PS, Alkadhi H, Van Mieghem NM, Budde RPJ. Utility of Photon Counting CT in Transcatheter Structural Heart Disease Interventions. Semin Roentgenol 2024; 59:32-43. [PMID: 38388095 DOI: 10.1053/j.ro.2023.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 11/19/2023] [Accepted: 11/20/2023] [Indexed: 02/24/2024]
Affiliation(s)
| | - Hatem Alkadhi
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Nicolas M Van Mieghem
- Department of Cardiology, Cardiovascular Institute, Thorax Center, Erasmus University Medical Center, 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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Sun S, Huang B, Li Q, Wang C, Zhang W, Xu L, Xu Q, Zhang Y. Prediction of pancreatic fibrosis by dual-energy CT-derived extracellular volume fraction: Comparison with MRI. Eur J Radiol 2024; 170:111204. [PMID: 37988962 DOI: 10.1016/j.ejrad.2023.111204] [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: 09/13/2023] [Revised: 11/03/2023] [Accepted: 11/14/2023] [Indexed: 11/23/2023]
Abstract
OBJECTIVES To investigate the correlation between dual-energy CT (DECT) and MRI measurements of the extracellular volume fraction (ECV) and to assess the accuracy of both methods in predicting pancreatic fibrosis (PF). METHODS We retrospectively analyzed 43 patients who underwent pancreatectomy and preoperative pancreatic DECT and MRI between November 2018 and May 2022. The ECV was calculated using the T1 relaxation time (for MR-ECV) or absolute enhancement (for DECT-ECV) at equilibrium phase (180 s after contrast injection in our study). Pearson coefficient and Bland-Altman analysis were used to compare the correlation between the two ECVs, Spearman correlations were used to investigate the association between imaging parameters and PF, Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of the ECVs for advanced fibrosis (F2-F3), and multivariate logistic regression analysis was used to examine the relationship between PF and imaging parameters. RESULTS There was a strong correlation between DECT- and MR-derived ECVs (r = 0.948; p < 0.001). The two ECVs were positively correlated with PF (DECT: r = 0.647, p < 0.001; MR: r = 0.614, p < 0.001), and the mean values were 0.34 ± 0.08 (range: 0.22-0.62) and 0.35 ± 0.09 (range: 0.24-0.66), respectively. The area under the operating characteristic curve (AUC) for subjects with advanced fibrosis diagnosed by ECV was 0.86 for DECT-ECV and 0.87 for MR-ECV. Multivariate logistic regression analysis showed that the DECT-ECV was an independent predictor of PF. CONCLUSIONS The ECV could be an effective predictor of histological fibrosis, and DECT is equivalent to MRI for characterizing pancreatic ECV changes.
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Affiliation(s)
- Shanshan Sun
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, NO. 300, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Ben Huang
- Department of Medical Laboratory, First Affiliated Hospital of Nanjing Medical University, NO. 300, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Qiong Li
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, NO. 300, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Chuanbing Wang
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, NO. 300, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Weiming Zhang
- Department of Pathology, First Affiliated Hospital of Nanjing Medical University, NO. 300, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Lulu Xu
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, NO. 300, Guangzhou Road, Nanjing, Jiangsu 210029, China
| | - Qing Xu
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, NO. 300, Guangzhou Road, Nanjing, Jiangsu 210029, China.
| | - Yele Zhang
- Department of Radiology, First Affiliated Hospital of Nanjing Medical University, NO. 300, Guangzhou Road, Nanjing, Jiangsu 210029, China.
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Zhang H, Guo H, Liu G, Wu C, Ma Y, Li S, Zheng Y, Zhang J. CT for the evaluation of myocardial extracellular volume with MRI as reference: a systematic review and meta-analysis. Eur Radiol 2023; 33:8464-8476. [PMID: 37378712 DOI: 10.1007/s00330-023-09872-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 03/18/2023] [Accepted: 04/14/2023] [Indexed: 06/29/2023]
Abstract
OBJECTIVE Myocardial extracellular volume (ECV) fraction is an important imaging biomarker in clinical decision-making. CT-ECV is a potential alternative to MRI for ECV quantification. We conducted a meta-analysis to comprehensively assess the reliability of CT for ECV quantification with MRI as a reference. METHODS We systematically searched PubMed, EMBASE, and the Cochrane Library for relevant articles published since the establishment of the database in July 2022. The articles comparing CT-ECV with MRI as a reference were included. Meta-analytic methods were applied to determine the pooled weighted bias, limits of agreement (LOA), and correlation coefficient (r) between CT-ECV and MRI-ECV. RESULTS Seventeen studies with a total of 459 patients and 2231 myocardial segments were included. The pooled mean difference (MD), LOA, and r for ECV quantification at the per-patient level was (0.07%; 95% LOA: - 0.42 to 0.55%) and 0.89 (95% CI: 0.86-0.91), respectively, while on the per-segment level was (0.44%; 95% LOA: 0.16-0.72%) and 0.84 (95% CI: 0.82-0.85), respectively. The pooled r from studies with the ECViodine method for ECV quantification was significantly higher compared to those with the ECVsub method (0.94 (95% CI: 0.91-0.96) vs. 0.84 (95% CI: 0.80-0.88), respectively, p = 0.03). The pooled r from septal segments was significantly higher than those from non-septal segments (0.88 (95% CI: 0.86-0.90) vs. 0.76 (95% CI: 0.71-0.90), respectively, p = 0.009). CONCLUSION CT showed a good agreement and excellent correlation with MRI for ECV quantification and is a potentially attractive alternative to MRI. CLINICAL RELEVANCE STATEMENT The myocardial extracellular volume fraction can be acquired using a CT scan, which is not only a viable alternative to myocardial extracellular volume fraction derived from MRI but is also less time-consuming and costly for patients. KEY POINTS • Noninvasive CT-ECV is a viable alternative to MRI-ECV for ECV quantification. • CT-ECV using the ECViodine method showed more accurate myocardial ECV quantification than ECVsub. • Septal myocardial segments showed lower measurement variability than non-septal segments for the ECV quantification.
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Affiliation(s)
- Hui Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, No.82 Cuiyingmen, Chengguan District, Lanzhou, 730030, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, 730030, China
| | - Huimin Guo
- Department of Radiology, Zhengzhou University People's Hospital, Fuwai Central China Cardiovascular Hospital, Zhengzhou, 450003, China
| | - Guangyao Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, No.82 Cuiyingmen, Chengguan District, Lanzhou, 730030, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, 730030, China
| | - Chuang Wu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, No.82 Cuiyingmen, Chengguan District, Lanzhou, 730030, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, 730030, China
| | - Yurong Ma
- Department of Magnetic Resonance, Lanzhou University Second Hospital, No.82 Cuiyingmen, Chengguan District, Lanzhou, 730030, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, 730030, China
| | - Shilan Li
- Department of Magnetic Resonance, Lanzhou University Second Hospital, No.82 Cuiyingmen, Chengguan District, Lanzhou, 730030, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, 730030, China
| | - Yurong Zheng
- Department of Magnetic Resonance, Lanzhou University Second Hospital, No.82 Cuiyingmen, Chengguan District, Lanzhou, 730030, China
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, 730030, China
| | - Jing Zhang
- Department of Magnetic Resonance, Lanzhou University Second Hospital, No.82 Cuiyingmen, Chengguan District, Lanzhou, 730030, China.
- Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou, 730030, China.
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10
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Han D, Lin A, Kuronuma K, Gransar H, Dey D, Friedman JD, Berman DS, Tamarappoo BK. Cardiac Computed Tomography for Quantification of Myocardial Extracellular Volume Fraction: A Systematic Review and Meta-Analysis. JACC Cardiovasc Imaging 2023; 16:1306-1317. [PMID: 37269267 DOI: 10.1016/j.jcmg.2023.03.021] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/30/2023] [Accepted: 03/30/2023] [Indexed: 06/05/2023]
Abstract
BACKGROUND Extracellular volume (ECV) is a quantitative measure of extracellular compartment expansion, and an increase in ECV is a marker of myocardial fibrosis. Although cardiac magnetic resonance (CMR) is considered the standard imaging tool for ECV quantification, cardiac computed tomography (CT) has also been used for ECV assessment. OBJECTIVES The aim of this meta-analysis was to evaluate the correlation and agreement in the quantification of myocardial ECV by CT and CMR. METHODS PubMed and Web of Science were searched for relevant publications reporting on the use of CT for ECV quantification compared with CMR as the reference standard. The authors employed a meta-analysis using the restricted maximum-likelihood estimator with a random-effects method to estimate summary correlation and mean difference. A subgroup analysis was performed to compare the correlation and mean differences between single-energy CT (SECT) and dual-energy CT (DECT) techniques for the ECV quantification. RESULTS Of 435 papers, 13 studies comprising 383 patients were identified. The mean age range was 57.3 to 82 years, and 65% of patients were male. Overall, there was an excellent correlation between CT-derived ECV and CMR-derived ECV (mean: 0.90 [95% CI: 0.86-0.95]). The pooled mean difference between CT and CMR was 0.96% (95% CI: 0.14%-1.78%). Seven studies reported correlation values using SECT, and 4 studies reported those using DECT. The pooled correlation from studies utilizing DECT for ECV quantification was significantly higher compared with those with SECT (mean: 0.94 [95% CI: 0.91-0.98] vs 0.87 [95% CI: 0.80-0.94], respectively; P = 0.01). There was no significant difference in pooled mean differences between SECT vs DECT (P = 0.85). CONCLUSIONS CT-derived ECV showed an excellent correlation and mean difference of <1% with CMR-derived ECV. However, the overall quality of the included studies was low, and larger, prospective studies are needed to examine the accuracy and diagnostic and prognostic utility of CT-derived ECV.
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Affiliation(s)
- Donghee Han
- Department of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Andrew Lin
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Keiichiro Kuronuma
- Department of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Heidi Gransar
- Department of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Damini Dey
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - John D Friedman
- Department of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Daniel S Berman
- Department of Imaging and Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA.
| | - Balaji K Tamarappoo
- Cardiovascular Institute, Indiana University School of Medicine, Indianapolis, Indiana, USA
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11
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Gerrits W, Danad I, Velthuis B, Mushtaq S, Cramer MJ, van der Harst P, van Slochteren FJ, Meine M, Suchá D, Guglielmo M. Cardiac CT in CRT as a Singular Imaging Modality for Diagnosis and Patient-Tailored Management. J Clin Med 2023; 12:6212. [PMID: 37834855 PMCID: PMC10573271 DOI: 10.3390/jcm12196212] [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: 08/25/2023] [Revised: 09/16/2023] [Accepted: 09/20/2023] [Indexed: 10/15/2023] Open
Abstract
Between 30-40% of patients with cardiac resynchronization therapy (CRT) do not show an improvement in left ventricular (LV) function. It is generally known that patient selection, LV lead implantation location, and device timing optimization are the three main factors that determine CRT response. Research has shown that image-guided CRT placement, which takes into account both anatomical and functional cardiac properties, positively affects the CRT response rate. In current clinical practice, a multimodality imaging approach comprised of echocardiography, cardiac magnetic resonance imaging, or nuclear medicine imaging is used to capture these features. However, with cardiac computed tomography (CT), one has an all-in-one acquisition method for both patient selection and the division of a patient-tailored, image-guided CRT placement strategy. This review discusses the applicability of CT in CRT patient identification, selection, and guided placement, offering insights into potential advancements in optimizing CRT outcomes.
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Affiliation(s)
- Willem Gerrits
- Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Ibrahim Danad
- Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Birgitta Velthuis
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Saima Mushtaq
- Department of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, Via Parea 4, 20138 Milan, Italy
| | - Maarten J. Cramer
- Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Frebus J. van Slochteren
- Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
- CART-Tech BV, Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Mathias Meine
- Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Dominika Suchá
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Marco Guglielmo
- Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
- Department of Cardiology, Haga Teaching Hospital, Els Borst-Eilersplein 275, 2545 AA The Hague, The Netherlands
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12
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Cundari G, Galea N, Mergen V, Alkadhi H, Eberhard M. Myocardial extracellular volume quantification with computed tomography-current status and future outlook. Insights Imaging 2023; 14:156. [PMID: 37749293 PMCID: PMC10519917 DOI: 10.1186/s13244-023-01506-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 08/18/2023] [Indexed: 09/27/2023] Open
Abstract
Non-invasive quantification of the extracellular volume (ECV) is a method for the evaluation of focal and diffuse myocardial fibrosis, potentially obviating the need for invasive endomyocardial biopsy. While ECV quantification with cardiac magnetic resonance imaging (ECVMRI) is already an established method, ECV quantification with CT (ECVCT) is an attractive alternative to ECVMRI, similarly using the properties of extracellular contrast media for ECV calculation. In contrast to ECVMRI, ECVCT provides a more widely available, cheaper and faster tool for ECV quantification and allows for ECV calculation also in patients with contraindications for MRI. Many studies have already shown a high correlation between ECVCT and ECVMRI and accumulating evidence suggests a prognostic value of ECVCT quantification in various cardiovascular diseases. Adding a late enhancement scan (for dual energy acquisitions) or a non-enhanced and late enhancement scan (for single-energy acquisitions) to a conventional coronary CT angiography scan improves risk stratification, requiring only minor adaptations of the contrast media and data acquisition protocols and adding only little radiation dose to the entire scan.Critical relevance statementThis article summarizes the technical principles of myocardial extracellular volume (ECV) quantification with CT, reviews the literature comparing ECVCT with ECVMRI and histopathology, and reviews the prognostic value of myocardial ECV quantification for various cardiovascular disease.Key points• Non-invasive quantification of myocardial fibrosis can be performed with CT.• Myocardial ECV quantification with CT is an alternative in patients non-eligible for MRI.• Myocardial ECV quantification with CT strongly correlates with ECV quantification using MRI.• Myocardial ECV quantification provides incremental prognostic information for various pathologies affecting the heart (e.g., cardiac amyloidosis).
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Affiliation(s)
- Giulia Cundari
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Rome, Italy
| | - Nicola Galea
- Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Rome, Italy
| | - Victor Mergen
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
| | - Hatem Alkadhi
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091, Zurich, Switzerland.
| | - Matthias Eberhard
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Raemistrasse 100, 8091, Zurich, Switzerland
- Radiology, Spital Interlaken, Spitäler FMI AG, Unterseen, Switzerland
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13
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Meloni A, Cademartiri F, Positano V, Celi S, Berti S, Clemente A, La Grutta L, Saba L, Bossone E, Cavaliere C, Punzo B, Maffei E. Cardiovascular Applications of Photon-Counting CT Technology: A Revolutionary New Diagnostic Step. J Cardiovasc Dev Dis 2023; 10:363. [PMID: 37754792 PMCID: PMC10531582 DOI: 10.3390/jcdd10090363] [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: 08/04/2023] [Revised: 08/16/2023] [Accepted: 08/18/2023] [Indexed: 09/28/2023] Open
Abstract
Photon-counting computed tomography (PCCT) is an emerging technology that can potentially transform clinical CT imaging. After a brief description of the PCCT technology, this review summarizes its main advantages over conventional CT: improved spatial resolution, improved signal and contrast behavior, reduced electronic noise and artifacts, decreased radiation dose, and multi-energy capability with improved material discrimination. Moreover, by providing an overview of the existing literature, this review highlights how the PCCT benefits have been harnessed to enhance and broaden the diagnostic capabilities of CT for cardiovascular applications, including the detection of coronary artery calcifications, evaluation of coronary plaque extent and composition, evaluation of coronary stents, and assessment of myocardial tissue characteristics and perfusion.
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Affiliation(s)
- Antonella Meloni
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.M.); (V.P.); (A.C.); (E.M.)
- Unità Operativa Complessa di Bioingegneria, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy
| | - Filippo Cademartiri
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.M.); (V.P.); (A.C.); (E.M.)
| | - Vicenzo Positano
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.M.); (V.P.); (A.C.); (E.M.)
- Unità Operativa Complessa di Bioingegneria, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy
| | - Simona Celi
- BioCardioLab, Fondazione G. Monasterio CNR-Regione Toscana, 54100 Massa, Italy;
| | - Sergio Berti
- Diagnostic and Interventional Cardiology Department, Fondazione G. Monasterio CNR-Regione Toscana, 54100 Massa, Italy;
| | - Alberto Clemente
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.M.); (V.P.); (A.C.); (E.M.)
| | - Ludovico La Grutta
- Department of Radiology, University Hospital “P. Giaccone”, 90127 Palermo, Italy;
| | - Luca Saba
- Department of Radiology, University Hospital of Cagliari, 09042 Monserrato, CA, Italy;
| | - Eduardo Bossone
- Department of Cardiology, Ospedale Cardarelli, 80131 Naples, Italy;
| | - Carlo Cavaliere
- Department of Radiology, Istituto di Ricerca e Cura a Carattere Scientifico SynLab-SDN, 80131 Naples, Italy; (C.C.); (B.P.)
| | - Bruna Punzo
- Department of Radiology, Istituto di Ricerca e Cura a Carattere Scientifico SynLab-SDN, 80131 Naples, Italy; (C.C.); (B.P.)
| | - Erica Maffei
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, 56124 Pisa, Italy; (A.M.); (V.P.); (A.C.); (E.M.)
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14
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Kay FU, Lumby C, Tanabe Y, Abbara S, Rajiah P. Detection of Low Blood Hemoglobin Levels on Pulmonary CT Angiography: A Feasibility Study Combining Dual-Energy CT and Machine Learning. Tomography 2023; 9:1538-1550. [PMID: 37624116 PMCID: PMC10459752 DOI: 10.3390/tomography9040123] [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: 06/28/2023] [Revised: 08/11/2023] [Accepted: 08/14/2023] [Indexed: 08/26/2023] Open
Abstract
OBJECTIVES To evaluate if dual-energy CT (DECT) pulmonary angiography (CTPA) can detect anemia with the aid of machine learning. METHODS Inclusion of 100 patients (mean age ± SD, 51.3 ± 14.8 years; male-to-female ratio, 42/58) who underwent DECT CTPA and hemoglobin (Hb) analysis within 24 h, including 50 cases with Hb below and 50 controls with Hb ≥ 12 g/dL. Blood pool attenuation was assessed on virtual noncontrast (VNC) images at eight locations. A classification model using extreme gradient-boosted trees was developed on a training set (n = 76) for differentiating cases from controls. The best model was evaluated in a separate test set (n = 24). RESULTS Blood pool attenuation was significantly lower in cases than controls (p-values < 0.01), except in the right atrium (p = 0.06). The machine learning model had sensitivity, specificity, and accuracy of 83%, 92%, and 88%, respectively. Measurements at the descending aorta had the highest relative importance among all features; a threshold of 43 HU yielded sensitivity, specificity, and accuracy of 68%, 76%, and 72%, respectively. CONCLUSION VNC imaging and machine learning shows good diagnostic performance for detecting anemia on DECT CTPA.
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Affiliation(s)
- Fernando U. Kay
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA;
| | - Cynthia Lumby
- Veterans Affairs North Texas Health Care System, Dallas, TX 75216, USA;
| | - Yuki Tanabe
- Department of Radiology, Ehime University, Matsuyama 790-0825, Japan;
| | - Suhny Abbara
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA;
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15
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Williams MC. Improving the Diagnosis of Amyloidosis at Cardiac CT. Radiology 2023; 306:e222406. [PMID: 36255317 DOI: 10.1148/radiol.222406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Michelle C Williams
- From the British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 SUF, UK
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16
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Editor's Notebook: March 2022. AJR Am J Roentgenol 2022; 218:393-395. [PMID: 35192375 DOI: 10.2214/ajr.21.27183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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