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Pitteloud J, Moser LJ, Klambauer K, Mergen V, Flohr T, Eberhard M, Alkadhi H. Effect of Vessel Attenuation, VMI Level, and Reconstruction Kernel on Pericoronary Adipose Tissue Attenuation for EID CT and PCD CT: An Ex Vivo Porcine Heart Study. AJR Am J Roentgenol 2024. [PMID: 39166723 DOI: 10.2214/ajr.24.31607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/23/2024]
Abstract
Background: Pericoronary adipose tissue (PCAT) attenuation and fat attenuation index (FAI) may serve as markers of inflammation and risk of adverse cardiac events. However, standardization of relevant CT acquisition and reconstruction parameters is lacking. Objective: To investigate the influence of vessel attenuation, virtual monoenergetic image (VMI) level, and reconstruction kernel on PCAT attenuation and FAI using energy-integrating detector (EID) and photon-counting detector (PCD) CT systems in an ex-vivo porcine heart model. Methods: A porcine heart's right coronary artery (RCA) was injected with saline or varying contrast media dilutions to achieve vessel attenuations ranging from 0 to 1000 HU. After each injection, the heart was scanned with EID CT at 120 kVp and PCD CT at 140 kVp, at constant CTDIvol (10 mGy). For EID CT, polychromatic images were reconstructed with Qr40 kernel. For PCD CT, VMI (40-80 keV at 10-keV increments) were reconstructed with Qr40, Bv40, and Bv56 kernels. ROIs were placed to measure RCA and PCAT attenuation. FAI was determined using software; histogram analysis was performed of voxel attenuations in the volumes of interest for FAI calculation. Results: Correlations were observed between attenuation in the RCA and adjacent PCAT (r=0.3-1.0), and between vessel attenuation and FAI (r=-0.9-1.0). For PCAT attenuation and FAI, these associations became progressively weaker for progressively sharper kernels. For increasing vessel attenuation for EID CT and for increasing VMI level for PCD CT, FAI histograms showed right shifts of the peak attenuation; the percentage of histogram voxels meeting the threshold range for inclusion in FAI calculation for EID CT was 8-29% and for PCD CT at VMI levels of 70-80 keV was 5-42%. For PCD CT, sharper kernels were associated with left shifts in peak attenuations and greater percentages of voxels within the threshold range for inclusion in FAI calculations. Conclusion: PCAT attenuation and FAI are influenced by vessel lumen attenuation, VMI level, and reconstruction kernel. A minority of pericoronary voxels contribute to FAI measurements for polychromatic EID CT and for PCD CT at high VMI levels. Clinical Impact: These findings may help standardize acquisition and reconstruction parameters for PCAT attenuation and FAI measurements.
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Affiliation(s)
- Janique Pitteloud
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Lukas Jakob Moser
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Konstantin Klambauer
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Victor Mergen
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Thomas Flohr
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Matthias Eberhard
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Hatem Alkadhi
- Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland
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Candreva A, Lodi Rizzini M, Calò K, Pagnoni M, Munhoz D, Chiastra C, Aben JP, Fournier S, Muller O, De Bruyne B, Collet C, Gallo D, Morbiducci U. Association Between Automated 3D Measurement of Coronary Luminal Narrowing and Risk of Future Myocardial Infarction. J Cardiovasc Transl Res 2024; 17:893-900. [PMID: 38427153 PMCID: PMC11371893 DOI: 10.1007/s12265-024-10500-2] [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: 11/26/2023] [Accepted: 02/13/2024] [Indexed: 03/02/2024]
Abstract
This study focuses on identifying anatomical markers with predictive capacity for long-term myocardial infarction (MI) in focal coronary artery disease (CAD). Eighty future culprit lesions (FCL) and 108 non-culprit lesions (NCL) from 80 patients underwent 3D quantitative coronary angiography. The minimum lumen area (MLA), minimum lumen ratio (MLR), and vessel fractional flow reserve (vFFR) were evaluated. MLR was defined as the ratio between MLA and the cross-sectional area at the proximal lesion edge, with lower values indicating more abrupt luminal narrowing. Significant differences were observed between FCL and NCL in MLR (0.41 vs. 0.53, p < 0.001). MLR correlated inversely with translesional vFFR (r = - 0.26, p = 0.0004) and was the strongest predictor of MI at 5 years (AUC = 0.75). Lesions with MLR < 0.40 had a fourfold increased MI incidence at 5 years. MLR is a robust predictor of future adverse coronary events.
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Affiliation(s)
- Alessandro Candreva
- PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico Di Torino, Corso Duca Degli Abruzzi 24, 10129, Turin, Italy
- Department of Cardiology, Zurich University Hospital, Zurich, Switzerland
| | - Maurizio Lodi Rizzini
- PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico Di Torino, Corso Duca Degli Abruzzi 24, 10129, Turin, Italy
| | - Karol Calò
- PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico Di Torino, Corso Duca Degli Abruzzi 24, 10129, Turin, Italy
| | - Mattia Pagnoni
- Department of Cardiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Daniel Munhoz
- Cardiovascular Center Aalst, OLV-Clinic, Aalst, Belgium
| | - Claudio Chiastra
- PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico Di Torino, Corso Duca Degli Abruzzi 24, 10129, Turin, Italy
| | | | - Stephane Fournier
- Department of Cardiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Olivier Muller
- Department of Cardiology, Lausanne University Hospital, Lausanne, Switzerland
| | | | - Carlos Collet
- Cardiovascular Center Aalst, OLV-Clinic, Aalst, Belgium
| | - Diego Gallo
- PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico Di Torino, Corso Duca Degli Abruzzi 24, 10129, Turin, Italy
| | - Umberto Morbiducci
- PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico Di Torino, Corso Duca Degli Abruzzi 24, 10129, Turin, Italy.
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Westwood M, Armstrong N, Krijkamp E, Perry M, Noake C, Tsiachristas A, Corro-Ramos I. A cloud-based medical device for predicting cardiac risk in suspected coronary artery disease: a rapid review and conceptual economic model. Health Technol Assess 2024; 28:1-105. [PMID: 39023142 PMCID: PMC11299050 DOI: 10.3310/wygc4096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2024] Open
Abstract
Background The CaRi-Heart® device estimates risk of 8-year cardiac death, using a prognostic model, which includes perivascular fat attenuation index, atherosclerotic plaque burden and clinical risk factors. Objectives To provide an Early Value Assessment of the potential of CaRi-Heart Risk to be an effective and cost-effective adjunctive investigation for assessment of cardiac risk, in people with stable chest pain/suspected coronary artery disease, undergoing computed tomography coronary angiography. This assessment includes conceptual modelling which explores the structure and evidence about parameters required for model development, but not development of a full executable cost-effectiveness model. Data sources Twenty-four databases, including MEDLINE, MEDLINE In-Process and EMBASE, were searched from inception to October 2022. Methods Review methods followed published guidelines. Study quality was assessed using Prediction model Risk Of Bias ASsessment Tool. Results were summarised by research question: prognostic performance; prevalence of risk categories; clinical effects; costs of CaRi-Heart. Exploratory searches were conducted to inform conceptual cost-effectiveness modelling. Results The only included study indicated that CaRi-Heart Risk may be predictive of 8 years cardiac death. The hazard ratio, per unit increase in CaRi-Heart Risk, adjusted for smoking, hypercholesterolaemia, hypertension, diabetes mellitus, Duke index, presence of high-risk plaque features and epicardial adipose tissue volume, was 1.04 (95% confidence interval 1.03 to 1.06) in the model validation cohort. Based on Prediction model Risk Of Bias ASsessment Tool, this study was rated as having high risk of bias and high concerns regarding its applicability to the decision problem specified for this Early Value Assessment. We did not identify any studies that reported information about the clinical effects or costs of using CaRi-Heart to assess cardiac risk. Exploratory searches, conducted to inform the conceptual cost-effectiveness modelling, indicated that there is a deficiency with respect to evidence about the effects of changing existing treatments or introducing new treatments, based on assessment of cardiac risk (by any method), or on measures of vascular inflammation (e.g. fat attenuation index). A de novo conceptual decision-analytic model that could be used to inform an early assessment of the cost effectiveness of CaRi-Heart is described. A combination of a short-term diagnostic model component and a long-term model component that evaluates the downstream consequences is anticipated to capture the diagnosis and the progression of coronary artery disease. Limitations The rapid review methods and pragmatic additional searches used to inform this Early Value Assessment mean that, although areas of potential uncertainty have been described, we cannot definitively state where there are evidence gaps. Conclusions The evidence about the clinical utility of CaRi-Heart Risk is underdeveloped and has considerable limitations, both in terms of risk of bias and applicability to United Kingdom clinical practice. There is some evidence that CaRi-Heart Risk may be predictive of 8-year risk of cardiac death, for patients undergoing computed tomography coronary angiography for suspected coronary artery disease. However, whether and to what extent CaRi-Heart represents an improvement relative to current standard of care remains uncertain. The evaluation of the CaRi-Heart device is ongoing and currently available data are insufficient to fully inform the cost-effectiveness modelling. Future work A large (n = 15,000) ongoing study, NCT05169333, the Oxford risk factors and non-invasive imaging study, with an estimated completion date of February 2030, may address some of the uncertainties identified in this Early Value Assessment. Study registration This study is registered as PROSPERO CRD42022366496. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135672) and is published in full in Health Technology Assessment; Vol. 28, No. 31. See the NIHR Funding and Awards website for further award information.
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Affiliation(s)
| | | | - Eline Krijkamp
- Erasmus School of Health Policy and Management, Department of Health Technology Assessment, Erasmus University, Rotterdam, the Netherlands
| | - Mark Perry
- Kleijnen Systematic Reviews (KSR) Ltd, York, UK
| | - Caro Noake
- Kleijnen Systematic Reviews (KSR) Ltd, York, UK
| | | | - Isaac Corro-Ramos
- Institute for Medical Technology Assessment (iMTA), Erasmus University, Rotterdam, the Netherlands
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Hu T, Freeze J, Singh P, Kim J, Song Y, Wu H, Lee J, Al-Kindi S, Rajagopalan S, Wilson DL, Hoori A. AI prediction of cardiovascular events using opportunistic epicardial adipose tissue assessments from CT calcium score. ARXIV 2024:arXiv:2401.16190v1. [PMID: 38351935 PMCID: PMC10862931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/19/2024]
Abstract
Background Recent studies have used basic epicardial adipose tissue (EAT) assessments (e.g., volume and mean HU) to predict risk of atherosclerosis-related, major adverse cardiovascular events (MACE). Objectives Create novel, hand-crafted EAT features, "fat-omics", to capture the pathophysiology of EAT and improve MACE prediction. Methods We segmented EAT using a previously-validated deep learning method with optional manual correction. We extracted 148 radiomic features (morphological, spatial, and intensity) and used Cox elastic-net for feature reduction and prediction of MACE. Results Traditional fat features gave marginal prediction (EAT-volume/EAT-mean-HU/BMI gave C-index 0.53/0.55/0.57, respectively). Significant improvement was obtained with 15 fat-omics features (C-index=0.69, test set). High-risk features included volume-of-voxels-having-elevated-HU-[-50, -30-HU] and HU-negative-skewness, both of which assess high HU, which as been implicated in fat inflammation. Other high-risk features include kurtosis-of-EAT-thickness, reflecting the heterogeneity of thicknesses, and EAT-volume-in-the-top-25%-of-the-heart, emphasizing adipose near the proximal coronary arteries. Kaplan-Meyer plots of Cox-identified, high- and low-risk patients were well separated with the median of the fat-omics risk, while high-risk group having HR 2.4 times that of the low-risk group (P<0.001). Conclusion Preliminary findings indicate an opportunity to use more finely tuned, explainable assessments on EAT for improved cardiovascular risk prediction.
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Affiliation(s)
- Tao Hu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Joshua Freeze
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Prerna Singh
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Justin Kim
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Yingnan Song
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Hao Wu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Juhwan Lee
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Sadeer Al-Kindi
- Harrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH, 44106, USA
- School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Sanjay Rajagopalan
- Harrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH, 44106, USA
- School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - David L Wilson
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
- Department of Radiology, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Ammar Hoori
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
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Shahbaz R, Charpentier E, Ponnaiah M, Deshours F, Kokabi H, Brochériou I, Le Naour G, Redheuil A, Koskas F, Davaine JM. In vitro analysis of carotid lesions using a preliminary microwave sensor to detect vulnerable plaques: Correlation with histology, Duplex ultrasound examination, and computed tomography scanner: The Imaging and Microwave Phenotyping Assessment of Carotid stenosis Threat (IMPACT) study. JVS Vasc Sci 2023; 5:100182. [PMID: 38384784 PMCID: PMC10879004 DOI: 10.1016/j.jvssci.2023.100182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 11/03/2023] [Indexed: 02/23/2024] Open
Abstract
Objective Progress in best medical treatment have made identification of best candidates for carotid surgery more difficult. New diagnostic modalities could be helpful in this perspective. Microwaves (MWs) can quantify dielectric properties (complex relative permittivity) of biological tissues and MW technology has emerged as a promising field of research for distinguishing abnormal tissues from healthy ones. We here evaluated the ability of a dedicated MW sensor developed in our laboratory to identify vulnerable carotid lesions. Methods We included 50 carotid lesions in this study. The plaques were analyzed and classified preoperatively by ultrasound (US) examination, computed tomography angiography and tested postoperatively using a MW sensor. Histopathological analysis was used as a gold standard to separate vulnerable plaques (VPs) from nonvulnerable plaques (NVPs). Results VPs were more frequently types 2 or 3 plaques (on US examination), had a greater proportion of low (<60 Hounsfield unit) and moderate (60-130 Hounsfield unit) attenuation components (computed tomography angiography) and displayed higher dielectric constant values (MW) than NVPs, which had an opposite profile. NVPs were more frequently asymptomatic plaques compared with VPs (P = .035). Multivariate analysis showed that US examination and MW identified VPs with a sensitivity of 77% and a specificity of 76% (cutoff value, -0.045; area under the curve, 0.848; P < .0001). Conclusions We found that the presence of types 2 to 3 (on US examination) and high dielectric constant plaques in vitro was highly indicative of a VP based on histological analysis. Further studies are needed to determine the potential of MW to identify the most dangerous asymptomatic carotid lesions.
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Affiliation(s)
- Rania Shahbaz
- Sorbonne Université, CNRS UMR8507, Laboratoire Génie Électrique et Électronique de Paris (GeePs), Paris, France
| | - Etienne Charpentier
- Sorbonne Université, Unité d'imagerie cardiovasculaire et thoracique, Hôpital La Pitié Salpêtrière (AP-HP), Laboratoire d’Imagerie Biomédicale, INSERM, CNRS, Institute of Cardiometabolism and Nutrition, Paris, France
| | - Maharajah Ponnaiah
- IHU ICAN, Foundation for Innovation in Cardiometabolism and Nutrition, Pitié Salpêtrière Hospital, Paris, France
| | - Frédérique Deshours
- Sorbonne Université, CNRS UMR8507, Laboratoire Génie Électrique et Électronique de Paris (GeePs), Paris, France
| | - Hamid Kokabi
- Sorbonne Université, CNRS UMR8507, Laboratoire Génie Électrique et Électronique de Paris (GeePs), Paris, France
| | | | - Gilles Le Naour
- Sorbonne Université, CNRS UMR8507, Laboratoire Génie Électrique et Électronique de Paris (GeePs), Paris, France
| | - Alban Redheuil
- Sorbonne Université, Unité d'imagerie cardiovasculaire et thoracique, Hôpital La Pitié Salpêtrière (AP-HP), Laboratoire d’Imagerie Biomédicale, INSERM, CNRS, Institute of Cardiometabolism and Nutrition, Paris, France
| | - Fabien Koskas
- Department of Vascular and Endovascular Surgery, Pitié-Salpêtrière University Hospital, Paris, France
| | - Jean-Michel Davaine
- Medicine Faculty, Sorbonne Université, Paris, France
- Department of Vascular and Endovascular Surgery, Pitié-Salpêtrière University Hospital, Paris, France
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Kuno T, Arce J, Fattouh M, Sarkar S, Skendelas JP, Daich J, Schenone AL, Zhang L, Rodriguez CJ, Virani SS, Slomka PJ, Shaw LJ, Williamson EE, Berman DS, Garcia MJ, Dey D, Slipczuk L. Cardiometabolic predictors of high-risk CCTA phenotype in a diverse patient population. Am J Prev Cardiol 2023; 15:100578. [PMID: 37675408 PMCID: PMC10477443 DOI: 10.1016/j.ajpc.2023.100578] [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: 06/04/2023] [Revised: 08/06/2023] [Accepted: 08/13/2023] [Indexed: 09/08/2023] Open
Abstract
Introduction Low-attenuation non-calcified plaque (LAP) burden and vascular inflammation by pericoronary adipose tissue (PCAT) measured from coronary CT angiography (CCTA) have shown to be predictors of cardiovascular outcomes. We aimed to investigate the relationships of cardiometabolic risk factors including lipoprotein(a) and epicardial adipose tissue (EAT) with CCTA high-risk imaging biomarkers, LAP and vascular inflammation. Methods The patient population consisted of consecutive patients who underwent CCTA for stable chest pain and had a complete cardiometabolic panel including lipoprotein(a). Plaque, PCAT and EAT were measured from CT using semiautomated software. Elevated LAP burden and PCAT attenuation were defined as ≥4% and ≥70.5 HU, respectively. The primary clinical end-point was a composite of myocardial infarction, revascularization or cardiovascular death. Results A total of 364 consecutive patients were included (median age 56 years, 64% female); the majority of patients were of Hispanic (60%), and the rest were of non-Hispanic Black (21%), non-Hispanic White (6%) and non-Hispanic Asian (4%) race/ethnicity. The prevalence of elevated LAP burden and PCAT attenuation was 31 and 18%, respectively, while only 8% had obstructive stenosis. There were significant differences in plaque characteristics among different racial/ethnic groups (p<0.001). Lipoprotein(a) correlated with LAP burden in Hispanic patients. Patients with elevated LAP were older, more likely to be have diabetes, hypertension, hyperlipidemia and smoke with higher CAC and EAT volume (all P<0.05). Patients with elevated LAP were more likely to develop the primary clinical outcome (p<0.001) but those with elevated PCAT were not (p=0.797). Conclusion The prevalence of LAP and PCAT attenuation were 31 and 18%, respectively. Lipoprotein(a) levels correlated with LAP burden in Hispanic patients. Age, male sex, hypertension and hyperlipidemia increased the odds of elevated LAP, which showed prognostic significance.
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Affiliation(s)
- Toshiki Kuno
- Cardiology Division, Montefiore Medical Center, Montefiore Medical Center/Albert Einstein Colalege of Medicine, Cardiology Division. 111 E210th, Bronx, NY 10467, United States
| | - Javier Arce
- Cardiology Division, Montefiore Medical Center, Montefiore Medical Center/Albert Einstein Colalege of Medicine, Cardiology Division. 111 E210th, Bronx, NY 10467, United States
| | - Michael Fattouh
- Cardiology Division, Montefiore Medical Center, Montefiore Medical Center/Albert Einstein Colalege of Medicine, Cardiology Division. 111 E210th, Bronx, NY 10467, United States
| | - Sharmila Sarkar
- Cardiology Division, Montefiore Medical Center, Montefiore Medical Center/Albert Einstein Colalege of Medicine, Cardiology Division. 111 E210th, Bronx, NY 10467, United States
| | - John P Skendelas
- Cardiothoracic and Vascular Surgery Department, Montefiore Medical Center/Albert Einstein College of Medicine, Bronx, NY, United States
| | - Jonathan Daich
- Cardiology Division, Montefiore Medical Center, Montefiore Medical Center/Albert Einstein Colalege of Medicine, Cardiology Division. 111 E210th, Bronx, NY 10467, United States
| | - Aldo L Schenone
- Cardiology Division, Montefiore Medical Center, Montefiore Medical Center/Albert Einstein Colalege of Medicine, Cardiology Division. 111 E210th, Bronx, NY 10467, United States
| | - Lili Zhang
- Cardiology Division, Montefiore Medical Center, Montefiore Medical Center/Albert Einstein Colalege of Medicine, Cardiology Division. 111 E210th, Bronx, NY 10467, United States
| | - Carlos J Rodriguez
- Cardiology Division, Montefiore Medical Center, Montefiore Medical Center/Albert Einstein Colalege of Medicine, Cardiology Division. 111 E210th, Bronx, NY 10467, United States
| | - Salim S Virani
- Office of the Vice Provost (Research), The Aga Khan University, Karachi, Pakistan
- Division of Cardiology, The Texas Heart Institute/Baylor College of Medicine, Houston, TX, United States
| | - Piotr J Slomka
- Division of Cardiology, The Texas Heart Institute/Baylor College of Medicine, Houston, TX, United States
| | - Leslee J Shaw
- Departments of Medicine (Cardiology) and Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | | | - Daniel S Berman
- Division of Cardiology, The Texas Heart Institute/Baylor College of Medicine, Houston, TX, United States
| | - Mario J Garcia
- Cardiology Division, Montefiore Medical Center, Montefiore Medical Center/Albert Einstein Colalege of Medicine, Cardiology Division. 111 E210th, Bronx, NY 10467, United States
| | - Damini Dey
- Department of Imaging, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, United States
| | - Leandro Slipczuk
- Cardiology Division, Montefiore Medical Center, Montefiore Medical Center/Albert Einstein Colalege of Medicine, Cardiology Division. 111 E210th, Bronx, NY 10467, United States
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7
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Kuronuma K, van Diemen PA, Han D, Lin A, Grodecki K, Kwiecinski J, Motwani M, McElhinney P, Tomasino GF, Park C, Kwan A, Tzolos E, Klein E, Shou B, Tamarappoo B, Cadet S, Danad I, Driessen RS, Berman DS, Slomka PJ, Dey D, Knaapen P. Relationship between impaired myocardial blood flow by positron emission tomography and low-attenuation plaque burden and pericoronary adipose tissue attenuation from coronary computed tomography: From the prospective PACIFIC trial. J Nucl Cardiol 2023; 30:1558-1569. [PMID: 36645580 DOI: 10.1007/s12350-022-03194-z] [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: 07/31/2022] [Accepted: 12/02/2022] [Indexed: 01/17/2023]
Abstract
BACKGROUND Positron emission tomography (PET) is the clinical gold standard for quantifying myocardial blood flow (MBF). Pericoronary adipose tissue (PCAT) attenuation may detect vascular inflammation indirectly. We examined the relationship between MBF by PET and plaque burden and PCAT on coronary CT angiography (CCTA). METHODS This post hoc analysis of the PACIFIC trial included 208 patients with suspected coronary artery disease (CAD) who underwent [15O]H2O PET and CCTA. Low-attenuation plaque (LAP, < 30HU), non-calcified plaque (NCP), and PCAT attenuation were measured by CCTA. RESULTS In 582 vessels, 211 (36.3%) had impaired per-vessel hyperemic MBF (≤ 2.30 mL/min/g). In multivariable analysis, LAP burden was independently and consistently associated with impaired hyperemic MBF (P = 0.016); over NCP burden (P = 0.997). Addition of LAP burden improved predictive performance for impaired hyperemic MBF from a model with CAD severity and calcified plaque burden (P < 0.001). There was no correlation between PCAT attenuation and hyperemic MBF (r = - 0.11), and PCAT attenuation was not associated with impaired hyperemic MBF in univariable or multivariable analysis of all vessels (P > 0.1). CONCLUSION In patients with stable CAD, LAP burden was independently associated with impaired hyperemic MBF and a stronger predictor of impaired hyperemic MBF than NCP burden. There was no association between PCAT attenuation and hyperemic MBF.
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Affiliation(s)
- Keiichiro Kuronuma
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Cardiology, Nihon University, Tokyo, Japan
| | | | - Donghee Han
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Andrew Lin
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Boulevard, Los Angeles, CA, 90048, USA
| | - Kajetan Grodecki
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Boulevard, Los Angeles, CA, 90048, USA
| | - Jacek Kwiecinski
- Department of Interventional Cardiology and Angiology, Institute of Cardiology, Warsaw, Poland
| | - Manish Motwani
- Manchester Heart Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Priscilla McElhinney
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Boulevard, Los Angeles, CA, 90048, USA
| | - Guadalupe Flores Tomasino
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Boulevard, Los Angeles, CA, 90048, USA
| | - Caroline Park
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Boulevard, Los Angeles, CA, 90048, USA
| | - Alan Kwan
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Evangelos Tzolos
- BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
| | - Eyal Klein
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Benjamin Shou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Boulevard, Los Angeles, CA, 90048, USA
| | - Balaji Tamarappoo
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Sebastien Cadet
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Boulevard, Los Angeles, CA, 90048, USA
| | - Ibrahim Danad
- Department of Cardiology, Amsterdam UMC, VUmc, Amsterdam, The Netherlands
| | - Roel S Driessen
- Department of Cardiology, Amsterdam UMC, VUmc, Amsterdam, The Netherlands
| | - Daniel S Berman
- Department of Imaging and Medicine and the Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Piotr J Slomka
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Damini Dey
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, 116 N Robertson Boulevard, Los Angeles, CA, 90048, USA.
| | - Paul Knaapen
- Department of Cardiology, Amsterdam UMC, VUmc, Amsterdam, The Netherlands
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Pontone G, Mushtaq S, Al'Aref SJ, Andreini D, Baggiano A, Canan A, Cavalcante JL, Chelliah A, Chen M, Choi A, Damini D, De Cecco CN, Farooqi KM, Ferencik M, Feuchtner G, Hecht H, Gransar H, Kolossváry M, Leipsic J, Lu MT, Marwan M, Ng MY, Maurovich-Horvat P, Nagpal P, Nicol E, Weir-McCall J, Whelton SP, Williams MC, Reid A, Fairbairn TA, Villines T, Vliegenthart R, Arbab-Zadeh A. The journal of cardiovascular computed tomography: A year in review: 2022. J Cardiovasc Comput Tomogr 2023; 17:86-95. [PMID: 36934047 DOI: 10.1016/j.jcct.2023.03.001] [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: 03/07/2023] [Accepted: 03/08/2023] [Indexed: 03/20/2023]
Abstract
This review aims to summarize key articles published in the Journal of Cardiovascular Computed Tomography (JCCT) in 2022, focusing on those that had the most scientific and educational impact. The JCCT continues to expand; the number of submissions, published manuscripts, cited articles, article downloads, social media presence, and impact factor continues to grow. The articles selected by the Editorial Board of the JCCT in this review highlight the role of cardiovascular computed tomography (CCT) to detect subclinical atherosclerosis, assess the functional relevance of stenoses, and plan invasive coronary and valve procedures. A section is dedicated to CCT in infants and other patients with congenital heart disease, in women, and to the importance of training in CT. In addition, we highlight key consensus documents and guidelines published in JCCT last year. The Journal values the tremendous work by authors, reviewers, and editors to accomplish these contributions.
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Affiliation(s)
- Gianluca Pontone
- Department of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, Milan, Italy; Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy.
| | - Saima Mushtaq
- Department of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, Milan, Italy
| | - Subhi J Al'Aref
- Division of Cardiology, Department of Internal Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Daniele Andreini
- Division of Cardiology and Cardiac Imaging, IRCCS Ospedale Galeazzi Sant'Ambrogio, Milan, Italy; Department of Biomedical and Clinical Sciences, University of Milan, Italy
| | - Andrea Baggiano
- Department of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, Milan, Italy; Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - Arzu Canan
- Department of Radiology, Division of Cardiothoracic Imaging, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Joao L Cavalcante
- Allina Health Minneapolis Heart Institute, Abbott Northwestern Hospital, Minneapolis, MN, USA
| | - Anjali Chelliah
- Department of Pediatrics, Division of Pediatric Cardiology, Goryeb Children's Hospital/Atlantic Medical Center, Morristown, NJ, USA; Columbia University Irving Medical Center, New York, NY, USA
| | - Marcus Chen
- National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Andrew Choi
- Cardiology and Radiology, The George Washington University School of Medicine, Washington, DC, USA
| | - Dey Damini
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | | | - Kanwal M Farooqi
- Division of Pediatric Cardiology, NewYork-Presbyterian, Columbia University Irving Medical Center, New York, NY, USA
| | - Maros Ferencik
- MCR, Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA
| | - Gudrun Feuchtner
- Department of Radiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Harvey Hecht
- Ican School of Medicine at Mount Sinai, Mount Sinai Morningside Medical Center, NYC, USA
| | - Heidi Gransar
- Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Márton Kolossváry
- Gottsegen National Cardiovascular Center, Budapest, Hungary; Physiological Controls Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary
| | - Jonathon Leipsic
- Department of Radiology and Medicine (Cardiology) UBC, Vancouver, Canada
| | - Michael T Lu
- Cardiovascular Imaging Research Center (CIRC), MGH Department of Radiology Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - Mohamed Marwan
- Cardiology Department, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Ming-Yen Ng
- Department of Diagnostic Radiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, China
| | - Pál Maurovich-Horvat
- Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary
| | - Prashant Nagpal
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
| | - Ed Nicol
- Royal Brompton Hospital, Sydney Street, London and School of Biomedical Engineering and Imaging Sciences, King's College, London, UK
| | | | - Seamus P Whelton
- Johns Hopkins Ciccarone Center for the Prevention of Cardiovascular Disease, Baltimore, MD, 21287, USA
| | - Michelle C Williams
- BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
| | - Anna Reid
- Manchester Heart Institute, Manchester University NHS Foundation Trust, Manchester, UK; University of Manchester, Manchester, UK
| | - Timothy A Fairbairn
- Liverpool Centre for Cardiovascular Science, Liverpool Heart and Chest Hospital, Liverpool, UK
| | | | - Rosemarie Vliegenthart
- Department of Radiology, University of Groningen/University Medical Center Groningen, Groningen, the Netherlands
| | - Armin Arbab-Zadeh
- Department of Medicine, Division of Cardiology, Johns Hopkins University, Baltimore, MD, USA
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Ma R, Fari R, van der Harst P, N De Cecco C, E Stillman A, Vliegenthart R, van Assen M. Evaluation of pericoronary adipose tissue attenuation on CT. Br J Radiol 2023; 96:20220885. [PMID: 36607825 PMCID: PMC10161916 DOI: 10.1259/bjr.20220885] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Pericoronary adipose tissue (PCAT) is the fat deposit surrounding coronary arteries. Although PCAT is part of the larger epicardial adipose tissue (EAT) depot, it has different pathophysiological features and roles in the atherosclerosis process. While EAT evaluation has been studied for years, PCAT evaluation is a relatively new concept. PCAT, especially the mean attenuation derived from CT images may be used to evaluate the inflammatory status of coronary arteries non-invasively. The most commonly used measure, PCATMA, is the mean attenuation of adipose tissue of 3 mm thickness around the proximal right coronary artery with a length of 40 mm. PCATMA can be analyzed on a per-lesion, per-vessel or per-patient basis. Apart from PCATMA, other measures for PCAT have been studied, such as thickness, and volume. Studies have shown associations between PCATMA and anatomical and functional severity of coronary artery disease. PCATMA is associated with plaque components and high-risk plaque features, and can discriminate patients with flow obstructing stenosis and myocardial infarction. Whether PCATMA has value on an individual patient basis remains to be determined. Furthermore, CT imaging settings, such as kV levels and clinical factors such as age and sex affect PCATMA measurements, which complicate implementation in clinical practice. For PCATMA to be widely implemented, a standardized methodology is needed. This review gives an overview of reported PCAT methodologies used in current literature and the potential use cases in clinical practice.
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Affiliation(s)
- Runlei Ma
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Roberto Fari
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Emory University, Atlanta, GA, USA
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Carlo N De Cecco
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Emory University, Atlanta, GA, USA
| | - Arthur E Stillman
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Emory University, Atlanta, GA, USA
| | - Rozemarijn Vliegenthart
- Department of Radiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.,University Medical Center Groningen, Data Science Center in Health (DASH), Groningen, the Netherlands
| | - Marly van Assen
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Emory University, Atlanta, GA, USA
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Boussoussou M, Vattay B, Szilveszter B, Simon J, Lin A, Vecsey-Nagy M, Konkoly G, Merkely B, Maurovich-Horvat P, Dey D, Kolossváry M. The effect of patient and imaging characteristics on coronary CT angiography assessed pericoronary adipose tissue attenuation and gradient. J Cardiovasc Comput Tomogr 2023; 17:34-42. [PMID: 36266205 DOI: 10.1016/j.jcct.2022.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 08/24/2022] [Accepted: 09/30/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND Coronary CT angiography (CCTA) pericoronary adipose tissue (PCAT) markers are promising indicators of inflammation. OBJECTIVE To determine the effect of patient and imaging parameters on the associations between non-calcified plaque (NCP) and PCAT attenuation and gradient. METHODS This was a single-center, retrospective analysis of consecutive patients with stable chest pain who underwent CCTA and had zero calcium scores. CCTA images were evaluated for the presence of NCP, obstructive stenosis, segment stenosis and involvement score (SSS, SIS), and high-risk plaque (HRP). PCAT markers were assessed using semi-automated software. Uni- and multivariable regression models correcting for patient and imaging characteristics between plaque and PCAT markers were evaluated. RESULTS Overall, 1652 patients had zero calcium score (mean age: 51 years ± 11 [SD], 871 women); PCAT attenuation values ranged between -123 HU and -51 HU, and 649 patients had plaque. In univariable analysis, the presence of NCP, SSS, SIS, and HRP were associated with PCAT attenuation (2, 1, 1, 6 HU; respectively; p < .001 all); while obstructive stenosis was not (1 HU, p = .58). In multivariable analysis, none of the plaque markers were associated with PCAT attenuation (0 HU p = .93, 0 HU p = .39, 1 HU p = .18, 2 HU p = .10, 1 HU p = .71, respectively), while patient and imaging characteristics showed significant associations, such as: male sex (1 HU, p = .003), heart rate [1/min] (-0.2 HU, p < .001), 120 kVp (8 HU, p < .001) and pixel spacing [mm3] (32 HU, p < .001). Similar results were observed for PCAT gradient. CONCLUSION PCAT markers were significantly associated with NCP, however the associations did not persist following correction for patient and imaging characteristics.
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Affiliation(s)
- Melinda Boussoussou
- Semmelweis University Heart and Vascular Center, 1122 Budapest, Városmajor street 68., Hungary
| | - Borbála Vattay
- Semmelweis University Heart and Vascular Center, 1122 Budapest, Városmajor street 68., Hungary
| | - Bálint Szilveszter
- Semmelweis University Heart and Vascular Center, 1122 Budapest, Városmajor street 68., Hungary
| | - Judit Simon
- Semmelweis University Medical Imaging Center, 1082 Budapest, Korányi Sándor street 2., Hungary
| | - Andrew Lin
- Cedars-Sinai Medical Center, 8700 Beverly Blvd #2900A, Los Angeles, CA, 90048, USA
| | - Milán Vecsey-Nagy
- Semmelweis University Heart and Vascular Center, 1122 Budapest, Városmajor street 68., Hungary
| | - Gábor Konkoly
- Semmelweis University Heart and Vascular Center, 1122 Budapest, Városmajor street 68., Hungary
| | - Béla Merkely
- Semmelweis University Heart and Vascular Center, 1122 Budapest, Városmajor street 68., Hungary
| | - Pál Maurovich-Horvat
- Semmelweis University Heart and Vascular Center, 1122 Budapest, Városmajor street 68., Hungary; Semmelweis University Medical Imaging Center, 1082 Budapest, Korányi Sándor street 2., Hungary
| | - Damini Dey
- Cedars-Sinai Medical Center, 8700 Beverly Blvd #2900A, Los Angeles, CA, 90048, USA
| | - Márton Kolossváry
- Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Semmelweis University Heart and Vascular Center, 1122 Budapest, Városmajor street 68., Hungary.
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