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Weichsel L, Giesen A, André F, Renker M, Baumann S, Breitbart P, Beer M, Maurovitch-Horvat P, Szilveszter B, Vattay B, Buss SJ, Marwan M, Giannopoulos AA, Kelle S, Frey N, Korosoglou G. Comparison of Two Contemporary Quantitative Atherosclerotic Plaque Assessment Tools for Coronary Computed Tomography Angiography: Single-Center Analysis and Multi-Center Patient Cohort Validation. Diagnostics (Basel) 2024; 14:154. [PMID: 38248031 PMCID: PMC10814854 DOI: 10.3390/diagnostics14020154] [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: 12/10/2023] [Revised: 01/01/2024] [Accepted: 01/02/2024] [Indexed: 01/23/2024] Open
Abstract
BACKGROUND Coronary computed tomography angiography (CCTA) provides non-invasive quantitative assessments of plaque burden and composition. The quantitative assessment of plaque components requires the use of analysis software that provides reproducible semi-automated plaque detection and analysis. However, commercially available plaque analysis software can vary widely in the degree of automation, resulting in differences in terms of reproducibility and time spent. AIM To compare the reproducibility and time spent of two CCTA analysis software tools using different algorithms for the quantitative assessment of coronary plaque volumes and composition in two independent patient cohorts. METHODS The study population included 100 patients from two different cohorts: 50 patients from a single-center (Siemens Healthineers, SOMATOM Force (DSCT)) and another 50 patients from a multi-center study (5 different > 64 slice CT scanner types). Quantitative measurements of total calcified and non-calcified plaque volume of the right coronary artery (RCA), left anterior descending (LAD), and left circumflex coronary artery (LCX) were performed on a total of 300 coronaries by two independent readers, using two different CCTA analysis software tools (Tool #1: Siemens Healthineers, syngo.via Frontier CT Coronary Plaque Analysis and Tool #2: Siemens Healthineers, successor CT Coronary Plaque Analysis prototype). In addition, the total time spent for the analysis was recorded with both programs. RESULTS The patients in cohorts 1 and 2 were 62.8 ± 10.2 and 70.9 ± 11.7 years old, respectively, 10 (20.0%) and 35 (70.0%) were female and 34 (68.0%) and 20 (40.0%), respectively, had hyperlipidemia. In Cohort #1, the inter- and intra-observer variabilities for the assessment of plaque volumes per patient for Tool #1 versus Tool #2 were 22.8%, 22.0%, and 26.0% versus 2.3%, 3.9%, and 2.5% and 19.7%, 21.4%, and 22.1% versus 0.2%, 0.1%, and 0.3%, respectively, for total, noncalcified, and calcified lesions (p < 0.001 for all between Tools #1 and 2 both for inter- and intra-observer). The inter- and intra-observer variabilities using Tool #2 remained low at 2.9%, 2.7%, and 3.0% and 3.8%, 3.7%, and 4.0%, respectively, for total, non-calcified, and calcified lesions in Cohort #2. For each dataset, the median processing time was higher for Tool #1 versus Tool #2 (459.5 s IQR = 348.0-627.0 versus 208.5 s; IQR = 198.0-216.0) (p < 0.001). CONCLUSION The plaque analysis Tool #2 (CT-guided PCI) encompassing a higher degree of automated support required less manual editing, was more time-efficient, and showed a higher intra- and inter-observer reproducibility for the quantitative assessment of plaque volumes both in a representative single-center and in a multi-center validation cohort.
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Affiliation(s)
- Loris Weichsel
- GRN Hospital Weinheim, Cardiology, Vascular Medicine & Pneumology, 69469 Weinheim, Germany; (L.W.); (A.G.)
- Cardiac Imaging Center Weinheim, Hector Foundations, 69469 Weinheim, Germany
| | - Alexander Giesen
- GRN Hospital Weinheim, Cardiology, Vascular Medicine & Pneumology, 69469 Weinheim, Germany; (L.W.); (A.G.)
- Cardiac Imaging Center Weinheim, Hector Foundations, 69469 Weinheim, Germany
| | - Florian André
- Department of Cardiology, Angiology and Pneumology, University of Heidelberg, 69120 Heidelberg, Germany; (F.A.); (N.F.)
- DZHK (German Centre for Cardiovascular Research), Partner Site Heidelberg/Mannheim, 69120 Heidelberg, Germany
| | - Matthias Renker
- Department of Cardiology, Campus Kerckhoff, Justus Liebig University Giessen, 61231 Bad Nauheim, Germany;
- DZHK (German Centre for Cardiovascular Research), Partner Site Rhein Main, 61231 Bad Nauheim, Germany
| | - Stefan Baumann
- Department of Cardiology, District Hospital Bergstraße, 64646 Heppenheim, Germany;
- First Department of Medicine-Cardiology, University Medical Center Mannheim, 68167 Mannheim, Germany
| | - Philipp Breitbart
- Department of Cardiology and Angiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, 79189 Bad Krozingen, Germany;
| | - Meinrad Beer
- Department for Diagnostic and Interventional Radiology, University Hospital Ulm, 89081 Ulm, Germany;
| | - Pal Maurovitch-Horvat
- Heart and Vascular Center, Semmelweis University, 1122 Budapest, Hungary; (P.M.-H.); (B.S.); (B.V.)
| | - Bálint Szilveszter
- Heart and Vascular Center, Semmelweis University, 1122 Budapest, Hungary; (P.M.-H.); (B.S.); (B.V.)
| | - Borbála Vattay
- Heart and Vascular Center, Semmelweis University, 1122 Budapest, Hungary; (P.M.-H.); (B.S.); (B.V.)
| | | | - Mohamed Marwan
- Department of Cardiology, University of Erlangen, 91054 Erlangen, Germany;
| | - Andreas A. Giannopoulos
- Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, 8091 Zurich, Switzerland;
| | - Sebastian Kelle
- Deutsches Herzzentrum der Charité, Department of Cardiology, Angiology and Intensive Care Medicine, Charité-University Medicine Berlin, 10117 Berlin, Germany;
| | - Norbert Frey
- Department of Cardiology, Angiology and Pneumology, University of Heidelberg, 69120 Heidelberg, Germany; (F.A.); (N.F.)
- DZHK (German Centre for Cardiovascular Research), Partner Site Heidelberg/Mannheim, 69120 Heidelberg, Germany
| | - Grigorios Korosoglou
- GRN Hospital Weinheim, Cardiology, Vascular Medicine & Pneumology, 69469 Weinheim, Germany; (L.W.); (A.G.)
- Cardiac Imaging Center Weinheim, Hector Foundations, 69469 Weinheim, Germany
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Dell’Aversana S, Ascione R, Vitale RA, Cavaliere F, Porcaro P, Basile L, Napolitano G, Boccalatte M, Sibilio G, Esposito G, Franzone A, Di Costanzo G, Muscogiuri G, Sironi S, Cuocolo R, Cavaglià E, Ponsiglione A, Imbriaco M. CT Coronary Angiography: Technical Approach and Atherosclerotic Plaque Characterization. J Clin Med 2023; 12:7615. [PMID: 38137684 PMCID: PMC10744060 DOI: 10.3390/jcm12247615] [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: 11/11/2023] [Revised: 12/08/2023] [Accepted: 12/08/2023] [Indexed: 12/24/2023] Open
Abstract
Coronary computed tomography angiography (CCTA) currently represents a robust imaging technique for the detection, quantification and characterization of coronary atherosclerosis. However, CCTA remains a challenging task requiring both high spatial and temporal resolution to provide motion-free images of the coronary arteries. Several CCTA features, such as low attenuation, positive remodeling, spotty calcification, napkin-ring and high pericoronary fat attenuation index have been proved as associated to high-risk plaques. This review aims to explore the role of CCTA in the characterization of high-risk atherosclerotic plaque and the recent advancements in CCTA technologies with a focus on radiomics plaque analysis.
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Affiliation(s)
- Serena Dell’Aversana
- Department of Radiology, Santa Maria Delle Grazie Hospital, ASL Napoli 2 Nord, 80078 Pozzuoli, Italy; (S.D.); (G.D.C.); (E.C.)
| | - Raffaele Ascione
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Raffaella Antonia Vitale
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Fabrizia Cavaliere
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Piercarmine Porcaro
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Luigi Basile
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | | | - Marco Boccalatte
- Coronary Care Unit, Santa Maria delle Grazie Hospital, ASL Napoli 2 Nord, 80078 Pozzuoli, Italy; (M.B.); (G.S.)
| | - Gerolamo Sibilio
- Coronary Care Unit, Santa Maria delle Grazie Hospital, ASL Napoli 2 Nord, 80078 Pozzuoli, Italy; (M.B.); (G.S.)
| | - Giovanni Esposito
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Anna Franzone
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Giuseppe Di Costanzo
- Department of Radiology, Santa Maria Delle Grazie Hospital, ASL Napoli 2 Nord, 80078 Pozzuoli, Italy; (S.D.); (G.D.C.); (E.C.)
| | - Giuseppe Muscogiuri
- Department of Radiology, ASST Papa Giovanni XXIII Hospital, Piazza OMS 1, 24127 Bergamo, Italy; (G.M.); (S.S.)
| | - Sandro Sironi
- Department of Radiology, ASST Papa Giovanni XXIII Hospital, Piazza OMS 1, 24127 Bergamo, Italy; (G.M.); (S.S.)
- School of Medicine and Surgery, University of Milano Bicocca, 20126 Milan, Italy
| | - Renato Cuocolo
- Department of Medicine, Surgery and Dentistry, University of Salerno, 84081 Baronissi, Italy;
| | - Enrico Cavaglià
- Department of Radiology, Santa Maria Delle Grazie Hospital, ASL Napoli 2 Nord, 80078 Pozzuoli, Italy; (S.D.); (G.D.C.); (E.C.)
| | - Andrea Ponsiglione
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
| | - Massimo Imbriaco
- Department of Advanced Biomedical Sciences, University of Naples Federico II, 80131 Naples, Italy; (R.A.); (R.A.V.); (F.C.); (P.P.); (L.B.); (G.E.); (A.F.); (M.I.)
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Jawaid MM, Riaz A, Rajani R, Reyes-Aldasoro CC, Slabaugh G. Framework for detection and localization of coronary non-calcified plaques in cardiac CTA using mean radial profiles. Comput Biol Med 2017; 89:84-95. [PMID: 28797740 DOI: 10.1016/j.compbiomed.2017.07.021] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Revised: 06/29/2017] [Accepted: 07/28/2017] [Indexed: 12/18/2022]
Abstract
BACKGROUND AND OBJECTIVE The high mortality rate associated with coronary heart disease (CHD) has driven intensive research in cardiac imaging and image analysis. The advent of computed tomography angiography (CTA) has turned non-invasive diagnosis of cardiovascular anomalies into reality as calcified coronary plaques can be easily identified due to their high intensity values. However, the detection of non-calcified plaques in CTA is still a challenging problem because of lower intensity values, which are often similar to the nearby blood and muscle tissues. In this work, we propose the use of mean radial profiles for the detection of non-calcified plaques in CTA imagery. METHODS Accordingly, we computed radial profiles by averaging the image intensity in concentric rings around the vessel centreline in a first stage. In the subsequent stage, an SVM classifier is applied to identify the abnormal coronary segments. For occluded segments, we further propose a derivative-based method to localize the position and length of the plaque inside the segment. RESULTS A total of 32 CTA volumes were analysed and a detection accuracy of 88.4% with respect to the manual expert was achieved. The plaque localization accuracy was computed using the Dice similarity coefficient and a mean of 83.2% was achieved. CONCLUSION The consistent performance for multi-vendor, multi-institution data demonstrates the reproducibility of our method across different CTA datasets with a good agreement with manual expert annotations.
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Affiliation(s)
- Muhammad Moazzam Jawaid
- City University of London, Northampton Square, London EC1V 0HB, UK; Mehran University of Engineering & Technology, Jamshoro, Pakistan.
| | - Atif Riaz
- City University of London, Northampton Square, London EC1V 0HB, UK
| | - Ronak Rajani
- St Thomas' Hospital, Westminster Bridge Road, London SE1 7EH, UK
| | | | - Greg Slabaugh
- City University of London, Northampton Square, London EC1V 0HB, UK
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Abstract
OBJECTIVE. In this article, we review the histopathologic classification of coronary atherosclerotic plaques and describe the possibilities and limitations of CT regarding the evaluation of coronary artery plaques. CONCLUSION. The composition of atherosclerotic plaques in the coronary arteries displays substantial variability and is associated with the likelihood for rupture and downstream ischemic events. Accurate identification and quantification of coronary plaque components on CT is challenging because of the limited temporal, spatial, and contrast resolutions of current scanners. Nonetheless, CT may provide valuable information that has potential for characterization of coronary plaques. For example, the extent of calcification can be determined, lipid-rich lesions can be separated from more fibrous ones, and positive remodeling can be identified.
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Accuracy of coronary computed tomography angiography vs intravascular ultrasound for evaluation of vessel area. J Cardiovasc Comput Tomogr 2014; 8:141-8. [DOI: 10.1016/j.jcct.2013.12.014] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2013] [Revised: 11/12/2013] [Accepted: 12/16/2013] [Indexed: 11/23/2022]
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Reproducibility of noncalcified coronary artery plaque burden quantification from coronary CT angiography across different image analysis platforms. AJR Am J Roentgenol 2014; 202:W43-9. [PMID: 24370164 DOI: 10.2214/ajr.13.11225] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
OBJECTIVE The objective of our study was to evaluate the reproducibility of noncalcified coronary artery plaque burden quantification from coronary CT angiography (CTA) across different commercial analysis platforms. MATERIALS AND METHODS For this study, 47 patients (36 men, 11 women; mean age ± SD, 62 ± 13 years) with noncalcified plaques on coronary CTA were included. Automated quantification of noncalcified coronary artery plaque volume was performed on identical datasets using three commercially available image analysis software platforms (software platforms 1-3). Identical tissue attenuation ranges between 0 and 50 HU for low-attenuation plaques and 50-130 HU for medium-attenuation plaques were consistently applied. Log volume data were compared with the Pearson correlation coefficient and Bland-Altman analysis. RESULTS Differences in plaque volume measurements on intraplatform repeat measurements were statistically insignificant (p = 0.923). At the low-attenuation threshold, software platform 3 had significantly higher log volumes (p < 0.001) than both software platforms 1 and 2 and software platform 1 had significantly higher log volumes than software platform 2 (p < 0.001). The results at the medium-attenuation level were identical except that the log volumes for software platforms 1 and 2 were not significantly different (p > 0.05) in the left anterior descending artery and left circumflex artery. The Pearson correlation coefficient was found to be 0.677 (p < 0.001; 95% CI, 0.608-0.735) between software platforms 1 and 2, 0.672 (p < 0.001; 95% CI, 0.603-0.732) between software platforms 1 and 3, and 0.550 (p < 0.001; 95% CI, 0.463-0.627) between software platforms 2 and 3. CONCLUSION Currently available noncalcified plaque quantification software provides good intraplatform reproducibility but poor interplatform reproducibility. Serial or comparative assessments require evaluation using the same software. Industry standards should be developed to enable reproducible assessments across manufacturers.
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Jon AF, Cheema AR, Khan AN, Raptopoulos V, Hauser T, Nasser I, Welty FK, Karellas A, Clouse ME. Assessment of liver fat in an obese patient population using noncontrast CT fat percent index. Clin Imaging 2014; 38:259-64. [PMID: 24559751 DOI: 10.1016/j.clinimag.2014.01.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2013] [Revised: 12/23/2013] [Accepted: 01/08/2014] [Indexed: 02/06/2023]
Abstract
OBJECTIVE To develop a simplified method to quantify liver fat using computed tomography (CT) fat % index (CTFPI) compared to liver spleen method (CTL/S, CTL-S). METHODS Noncontrast CT of the liver was performed in 89 patients (overweight, obese, severely obese) to quantify fat, using the following: CTFPI=[(65-patient HU)/65]×100, normal live r=65 HU. RESULTS There was a strong linear correlation between CTFPI and the standard method of assessing liver fat using CTL/S (r=-0.901), CTL-S (r=-0.911). Hepatic HU and CTFPI were significantly different in the severely obese group compared to other two groups (P<.05). CONCLUSION Significant correlation indicates equal diagnostic accuracy of the two methods in appropriately calibrated scanners.
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Affiliation(s)
- Ali F Jon
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Ahmad R Cheema
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Atif N Khan
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Vassilios Raptopoulos
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Thomas Hauser
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Imad Nasser
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Francine K Welty
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Andrew Karellas
- Department of Radiology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Melvin E Clouse
- Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
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A voxel-map quantitative analysis approach for atherosclerotic noncalcified plaques of the coronary artery tree. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2013; 2013:957195. [PMID: 24348749 PMCID: PMC3855949 DOI: 10.1155/2013/957195] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/05/2013] [Accepted: 10/22/2013] [Indexed: 11/17/2022]
Abstract
Noncalcified plaques (NCPs) are associated with the presence of lipid-core plaques that are prone to rupture. Thus, it is important to detect and monitor the development of NCPs. Contrast-enhanced coronary Computed Tomography Angiography (CTA) is a potential imaging technique to identify atherosclerotic plaques in the whole coronary tree, but it fails to provide information about vessel walls. In order to overcome the limitations of coronary CTA and provide more meaningful quantitative information for percutaneous coronary intervention (PCI), we proposed a Voxel-Map based on mathematical morphology to quantitatively analyze the noncalcified plaques on a three-dimensional coronary artery wall model (3D-CAWM). This approach is a combination of Voxel-Map analysis techniques, plaque locating, and anatomical location related labeling, which show more detailed and comprehensive coronary tree wall visualization.
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The effect of iterative reconstruction on quantitative computed tomography assessment of coronary plaque composition. Int J Cardiovasc Imaging 2013; 30:155-63. [PMID: 24046026 DOI: 10.1007/s10554-013-0293-8] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2013] [Accepted: 09/07/2013] [Indexed: 10/26/2022]
Abstract
To compare coronary plaque size and composition as well as degree of coronary artery stenosis on coronary Computed Tomography angiography (CCTA) using three levels of iterative reconstruction (IR) with standard filtered back projection (FBP). In 63 consecutive patients with a clinical indication for CCTA 55 coronary plaques were analysed. Raw data were reconstructed using standard FBP and levels 2, 4 and 6 of a commercially available IR algorithm (iDose(4)). CT attenuation and noise were measured in the aorta and two coronary arteries. Both signal-to-noise-ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The amount of lipid, fibrous and calcified plaque components and mean cross-sectional luminal area were analysed using dedicated software. Image noise was reduced by 41.6% (p < 0.0001) and SNR and CNR in the aorta were improved by 73.4% (p < 0.0001) and 72.9% (p < 0.0001) at IR level 6, respectively. IR improved objective image quality measures more in the aorta than in the coronary arteries. Furthermore, IR had no significant effect on measurements of plaque volume and cross-sectional luminal area. The application of IR significantly improves objective image quality, and does not alter quantitative analysis of coronary plaque volume, composition and luminal area.
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Comparison of coronary plaque subtypes in male and female patients using 320-row MDCTA. Atherosclerosis 2012; 226:428-32. [PMID: 23287639 DOI: 10.1016/j.atherosclerosis.2012.11.033] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2012] [Revised: 11/09/2012] [Accepted: 11/22/2012] [Indexed: 02/08/2023]
Abstract
OBJECTIVE Determine plaque subtype and volume difference in male and female patients with obstructive and non-obstructive CAD using 320-row MDCTA. MATERIALS AND METHODS 128 patients with suspected CAD underwent MDCTA. All studies were divided into two groups based on disease severity. 0-70% stenosis (non-obstructive CAD) & >70% (obstructive). All were compared for plaque quantity and subtypes by gender. Main arteries, RCA, LM, LAD and LCX were analyzed using Vitrea 5.2 software to quantify fatty, fibrous and calcified plaque. Thresholds for coronary plaque quantification (volume in mm(3)) were preset at 35 ± 12 HU for fatty, 90 ± 24 HU for fibrous and >130 HU for calcified/mixed plaque and analyzed using STATA software. RESULTS Total plaque burden in 118 patients [65M: 53F] was significantly higher in all arteries in males compared to females with non-obstructive disease. Total plaque volume for males vs. females was: RCA: 10.10 ± 5.02 mm(3) vs. 6.89 ± 2.75 mm(3), respectively, p = 0.001; LAD: 7.21 ± 3.38 mm(3) vs. 5.89 ± 1.93 mm(3), respectively, p = 0.04; LCX: 9.13 ± 3.27 mm(3) vs. 7.16 ± 1.73 mm(3), respectively, p = 0.002; LM 15.13 ± 4.51 mm(3) vs. 11.85 ± 4.03 mm(3), respectively, p = 0.001. In sub-analyses, males had significantly more fibrous and fatty plaque in LM, LAD & LCX than females. However in the RCA, only fibrous plaque was significantly greater in males. Calcified plaque volume was not significantly different in both genders. Only 8% of patients had obstructive CAD (>70% stenosis); there was no significant difference in plaque volume or subtypes. CONCLUSION In patients with non-obstructive CAD, males were found to have significantly higher total coronary plaque volume with predominance of fibrous and fatty subtypes compared to females of the same age and BMI. There was no significant difference in plaque subtype or volume in patients with obstructive disease.
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Yoon YE, Chang SA, Choi SII, Chun EJ, Cho YS, Youn TJ, Chung WY, Chae IH, Choi DJ, Chang HJ. The absence of coronary artery calcification does not rule out the presence of significant coronary artery disease in Asian patients with acute chest pain. Int J Cardiovasc Imaging 2011; 28:389-98. [DOI: 10.1007/s10554-011-9819-0] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2010] [Accepted: 01/24/2011] [Indexed: 01/17/2023]
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Lee MS, Chun EJ, Kim KJ, Kim JA, Vembar M, Choi SI. Reproducibility in the assessment of noncalcified coronary plaque with 256-slice multi-detector CT and automated plaque analysis software. Int J Cardiovasc Imaging 2010; 26:237-44. [DOI: 10.1007/s10554-010-9710-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2010] [Accepted: 09/15/2010] [Indexed: 10/19/2022]
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Dey D, Schepis T, Marwan M, Slomka PJ, Berman DS, Achenbach S. Automated three-dimensional quantification of noncalcified coronary plaque from coronary CT angiography: comparison with intravascular US. Radiology 2010; 257:516-22. [PMID: 20829536 DOI: 10.1148/radiol.10100681] [Citation(s) in RCA: 145] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE To determine the accuracy of a previously developed automated algorithm (AUTOPLAQ [APQ]) for rapid volumetric quantification of noncalcified and calcified plaque from coronary computed tomographic (CT) angiography in comparison with intravascular ultrasonography (US). MATERIALS AND METHODS This study was approved by the institutional review board and was HIPAA compliant; all patients provided written informed consent. APQ combines derived scan-specific attenuation threshold levels for lumen, plaque, and knowledge-based segmentation of coronary arteries for quantification of plaque components. APQ was validated with retrospective analysis of 22 coronary atherosclerotic plaques in 20 patients imaged with coronary CT angiography and intravascular US within 2 days of each other. Coronary CT angiographic data were acquired by using dual-source CT. For each patient, well-defined plaques without calcifications were selected, and plaque volume was measured with APQ and manual tracing at CT and with intravascular US. Measurements were compared with paired t test, correlation, and Bland-Altman analysis. RESULTS There was excellent correlation between noncalcified plaque volumes quantified with APQ and intravascular US (r = 0.94, P < .001), with no significant differences (P = .08). Mean plaque volume with intravascular US was 105.9 mm³ ± 83.5 (standard deviation) and with APQ was 116.6 mm³ ± 80.1. Mean plaque volume with manual tracing from CT was 100.8 mm³ ± 81.7 and with APQ was 116.6 mm³ ± 80.1, with excellent correlation (r = 0.92, P < .001) and no significant differences (P = .23). CONCLUSION Automated scan-specific threshold level-based quantification of plaque components from coronary CT angiography allows rapid, accurate measurement of noncalcified plaque volumes, compared with intravascular US, and requires a fraction of the time needed for manual analysis.
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Affiliation(s)
- Damini Dey
- Department of Imaging, Cedars-Sinai Medical Center, Cedars-Sinai Heart Institute, and David-Geffen School of Medicine, UCLA, 8700 Beverly Blvd, Taper Building A238, Los Angeles, CA 90048, USA.
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Dey D, Cheng VY, Slomka PJ, Nakazato R, Ramesh A, Gurudevan S, Germano G, Berman DS. Automated 3-dimensional quantification of noncalcified and calcified coronary plaque from coronary CT angiography. J Cardiovasc Comput Tomogr 2009; 3:372-82. [PMID: 20083056 DOI: 10.1016/j.jcct.2009.09.004] [Citation(s) in RCA: 88] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2009] [Revised: 08/21/2009] [Accepted: 09/16/2009] [Indexed: 11/28/2022]
Abstract
INTRODUCTION We aimed to develop an automated algorithm (APQ) for accurate volumetric quantification of non-calcified (NCP) and calcified plaque (CP) from coronary CT angiography (CCTA). METHODS APQ determines scan-specific attenuation thresholds for lumen, NCP, CP and epicardial fat, and applies knowledge-based segmentation and modeling of coronary arteries, to define NCP and CP components in 3D. We tested APQ in 29 plaques for 24 consecutive scans, acquired with dual-source CT scanner. APQ results were compared to volumes obtained by manual slice-by-slice NCP/CP definition and by interactive adjustment of plaque thresholds (ITA) by 2 independent experts. RESULTS APQ analysis time was <2 sec per lesion. There was strong correlation between the 2 readers for manual quantification (r = 0.99, p < 0.0001 for NCP; r = 0.85, p < 0.0001 for CP). The mean HU determined by APQ was 419 +/- 78 for luminal contrast at mid-lesion, 227 +/- 40 for NCP upper threshold, and 511 +/- 80 for the CP lower threshold. APQ showed a significantly lower absolute difference (26.7 mm(3) vs. 42.1 mm(3), p = 0.01), lower bias than ITA (32.6 mm(3) vs 64.4 mm(3), p = 0.01) for NCP. There was strong correlation between APQ and readers (R = 0.94, p < 0.0001 for NCP volumes; R = 0.88, p < 0.0001, for CP volumes; R = 0.90, p < 0.0001 for NCP and CP composition). CONCLUSIONS We developed a fast automated algorithm for quantification of NCP and CP from CCTA, which is in close agreement with expert manual quantification.
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Affiliation(s)
- Damini Dey
- Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Taper Building, A238, Los Angeles, CA 90048, USA.
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Reproducibility of Automated Noncalcified Coronary Artery Plaque Burden Assessment at Coronary CT Angiography. J Thorac Imaging 2009; 24:96-102. [DOI: 10.1097/rti.0b013e31819b674b] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
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Coronary plaque quantification by voxel analysis: dual-source MDCT angiography versus intravascular sonography. AJR Am J Roentgenol 2009; 192:W84-9. [PMID: 19234244 DOI: 10.2214/ajr.08.1381] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
OBJECTIVE The purpose of this study was to evaluate a voxel-based analytic technique for quantification of noncalcified coronary artery plaque with intravascular sonography as a standard of reference. SUBJECTS AND METHODS Intravascular sonography and dual-source MDCT angiography prospectively performed on 12 patients resulted in identification of 20 segments containing noncalcified plaque. Four of these segments were used to establish reference measurements of 0.6-mm proximal wall thickness with a 0-HU cutoff between the epicardial fat and outer wall and an individually adjusted threshold for the interface between the wall and lumen. With these data, consecutive circular layers of the outer wall were subtracted from a 3D volume to determine the plaque plus medial layer and the actual plaque volume in the other 16 segments. Accuracy of the voxel technique was assessed by comparing the results with intravascular sonographic findings. RESULTS Both the total plaque burden (plaque plus medial layer) and the actual plaque volume had good concordance with intravascular sonographic findings (49.6 +/- 20 mm (3) vs 56.7 +/- 23.6 mm (3), p = 0.076; 26.5 +/- 14.8 mm (3) vs 30.9 +/- 15.3 mm (3), p = 0.09). Corresponding correlation coefficients were r = 0.76 and r = 0.79. The method had good reproducibility, the an intraclass correlation coefficients being 0.93 for total plaque burden and 0.90 for actual plaque volume. CONCLUSION Voxel analysis can be used for accurate and reproducible quantification not only of plaque burden but also of actual plaque volume.
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