Perfusion, Calcium Scoring, and CTA

2021 ◽  
pp. 47-58
Author(s):  
Kenji Fukushima ◽  
Michinobu Nagao
Keyword(s):  
Calcium Scoring

Value of Coronary Calcium Scoring in Symptomatic and Asymptomatic Coronary Artery Disease Patients

2020 ◽  
Vol 16 ◽  
Author(s):  
Hala T. Salem ◽  
Eman A.S. Sabek
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Sensitivity And Specificity ◽  
High Sensitivity ◽  
Coronary Calcium ◽  
Risk Estimate ◽  
Calcium Scoring ◽  
Coronary Calcium Scoring ◽  
Framingham Risk ◽  
Artery Disease

Aim and Objective: To estimate the relationship between Coronary Calcium Scoring (CCS)and presence of different degrees of obstructive coronary artery disease (CAD) to avoid unnecessary examinations and hence unnecessary radiation exposure and contrast injection. Background: Coronary Calcium Scoring (CCS) is a test uses x-ray equipment to produce pictures of the coronary arteries to determine the degree of its narrowing by the build-up of calcified plaques. Despite the lack of definitive data linking ionizing radiation with cancer, the American Heart Association supports widely that practitioners of Computed tomography Coronary Angiography (CTCA) should keep “patient radiation doses as low as reasonably achievable but consistent with obtaining the desired medical information”. Methods: Data obtained from 275 CTCA examinations were reviewed. Radiation effective doses were estimated for both CCS and CTCA, measures to keep it as low as possible were presented, CCS and Framingham risk estimate were compared to the final results of CTCA to detect sensitivity and specificity of each one in detecting obstructive lesions. Results: CCS is a strong discriminator for obstructive CAD and can with high sensitivity and specificity and correlates well with the degree of obstruction even more than Framingham risk estimate which has high sensitivity and low specificity. Conclusion: CCS helps reducing the effective radiation dose if properly evaluated to skip unnecessary CTCA if obstructive lesions was unlikely, and as a test does not use contrast material, harmful effect on the kidney will be avoided as most of coronary atherosclerotic patients have renal problems.

scholarly journals Evaluation of an AI-based, automatic coronary artery calcium scoring software

2019 ◽  
Vol 30 (3) ◽  
pp. 1671-1678 ◽  
Author(s):  
Mårten Sandstedt ◽  
Lilian Henriksson ◽  
Magnus Janzon ◽  
Gusten Nyberg ◽  
Jan Engvall ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Coronary Artery ◽  
Coronary Artery Calcium ◽  
Rank Test ◽  
Agatston Score ◽  
Risk Category ◽  
Automatic Method ◽  
Calcium Scoring ◽  
Excellent Correlation ◽  
Automatic Software

Abstract Objectives To evaluate an artificial intelligence (AI)–based, automatic coronary artery calcium (CAC) scoring software, using a semi-automatic software as a reference. Methods This observational study included 315 consecutive, non-contrast-enhanced calcium scoring computed tomography (CSCT) scans. A semi-automatic and an automatic software obtained the Agatston score (AS), the volume score (VS), the mass score (MS), and the number of calcified coronary lesions. Semi-automatic and automatic analysis time were registered, including a manual double-check of the automatic results. Statistical analyses were Spearman’s rank correlation coefficient (⍴), intra-class correlation (ICC), Bland Altman plots, weighted kappa analysis (κ), and Wilcoxon signed-rank test. Results The correlation and agreement for the AS, VS, and MS were ⍴ = 0.935, 0.932, 0.934 (p < 0.001), and ICC = 0.996, 0.996, 0.991, respectively (p < 0.001). The correlation and agreement for the number of calcified lesions were ⍴ = 0.903 and ICC = 0.977 (p < 0.001), respectively. The Bland Altman mean difference and 1.96 SD upper and lower limits of agreements for the AS, VS, and MS were − 8.2 (− 115.1 to 98.2), − 7.4 (− 93.9 to 79.1), and − 3.8 (− 33.6 to 25.9), respectively. Agreement in risk category assignment was 89.5% and κ = 0.919 (p < 0.001). The median time for the semi-automatic and automatic method was 59 s (IQR 35–100) and 36 s (IQR 29–49), respectively (p < 0.001). Conclusions There was an excellent correlation and agreement between the automatic software and the semi-automatic software for three CAC scores and the number of calcified lesions. Risk category classification was accurate but showing an overestimation bias tendency. Also, the automatic method was less time-demanding. Key Points • Coronary artery calcium (CAC) scoring is an excellent candidate for artificial intelligence (AI) development in a clinical setting. • An AI-based, automatic software obtained CAC scores with excellent correlation and agreement compared with a conventional method but was less time-consuming.

Electron-Beam Computed Tomography for Symptomatic Coronary Disease

2000 ◽  
Vol 8 (1) ◽  
pp. 46-49
Author(s):  
Bernard Kwok Wing Kuin ◽  
Yean Teng Lim ◽  
Swee Tian Quek ◽  
Lenny Tan Kheng Ann
Keyword(s):  
Computed Tomography ◽  
Electron Beam ◽  
Coronary Artery ◽  
Coronary Disease ◽  
Coronary Artery Calcium Score ◽  
Calcium Score ◽  
High Specificity ◽  
Calcium Scoring ◽  
Electron Beam Computed Tomography ◽  
Low Sensitivity

Forty-two symptomatic patients underwent both electron-beam computed tomo-graphic calcium scoring and coronary angiography. Correlation between coronary artery calcium score and angiographic coronary disease showed a high specificity (90%) but low sensitivity (50%). The low negative predictive value of 36% suggests that electron-beam computed tomography is not useful in symptomatic patients.

Coronary Artery Calcium Scoring for Adults at Borderline 10-Year ASCVD Risk

2021 ◽  
Vol 78 (5) ◽  
pp. 537-538
Author(s):  
S.M. Iftekhar Uddin ◽  
Albert D. Osei ◽  
Olufunmilayo Obisesan ◽  
Omar Dzaye ◽  
Zeina Dardari ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Coronary Artery Calcium ◽  
Calcium Scoring ◽  
Coronary Artery Calcium Scoring ◽  
Ascvd Risk
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