PurposeAutomatically extracted coronary artery trees (CATs) from coronary computed tomography angiography images could contain incorrect extractions which require manual corrections before they can... Show morePurposeAutomatically extracted coronary artery trees (CATs) from coronary computed tomography angiography images could contain incorrect extractions which require manual corrections before they can be used in clinical practice. A model-guided method for improving the extracted CAT is described to automatically detect potential incorrect extractions and improve them.MethodsThe proposed method is a coarse-to-fine approach. A coarse improvement is first applied on all vessels in the extracted CAT, and then a fine improvement is applied only on vessels with higher clinical significance. Based upon a decision tree, the proposed method automatically and iteratively performs improvement operations for the entire extracted CAT until it meets the stop criteria. The improvement in the extraction quality obtained by the proposed method is measured using a scoring system. 18 datasets were used to determine optimal values for the parameters involved in the model-guided method and 122 datasets were used for evaluation.ResultsCompared to the initial automatic extractions, the proposed method improves the CATs for 122 datasets from an average quality score of 876 to 93 +/- 4. The developed method is able to run within 2min on a typical workstation. The difference in extraction quality after automatic improvement is negatively correlated with the initial extraction quality (R=-0.694, P<0.001).Conclusion Without deteriorating the initially extracted CATs, the presented method automatically detects incorrect extractions and improves the CATs to an average quality score of 93 guided by anatomical statistical models. Show less
Deseive, S.; Straub, R.; Kupke, M.; Broersen, A.; Kitslaar, P.H.; Stocker, T.J.; ... ; Hausleiter, J. 2019
Background: To investigate the impact of diabetes on coronary artery total plaque volume (TPV) and adverse events in long-term follow-up.Methods: One-hundred-and-eight diabetic patients were... Show moreBackground: To investigate the impact of diabetes on coronary artery total plaque volume (TPV) and adverse events in long-term follow-up.Methods: One-hundred-and-eight diabetic patients were matched to 324 non-diabetic patients, with respect to age, sex, body-mass index, hypertension, smoking habits, LDL and HDL cholesterol, family history for CAD as well as aspirin and statin medication. In all patients, TPV was quantified from coronary CT angiographies (CTA) using dedicated software. All-cause mortality, acute coronary syndrome and late revascularisation ( > 90 days) served as combined endpoint.Results: Patients were followed for 5.6 years. The endpoint occurred in 18 (16.7%) diabetic and 26 (8.0%) nondiabetic patients (odds ratio 2.3, p = 0.03). Diabetic patients had significantly higher TPV than non-diabetic patients (55.1 mm 3 [IQR: 6.2 and 220.4 mm(3)] vs. 24.9 mm 3 [IQR: 0 and 166.7 mm(3)], p = 0.02). A TPV threshold of 110.5 mm(3) provided good separation of diabetic and non-diabetic patients at higher and lower risk for adverse events. Noteworthy, diabetic and non-diabetic patients with a TPV < 110.5 mm(3) had comparable outcome (hazard ratio: 1.3, p = 0.59), while diabetic patients with TPV > 110.5 mm(3) had significantly higher incidence of adverse events (hazard ratio 2.3, p = 0.03) compared to non-diabetic patients with TPV > 110.5 mm(3). There was incremental prognostic value in diabetic and non-diabetic patients over the Framingham Risk Score (Integrated Discrimination Improvement: 0.052 and 0.012, p for both < 0.05).Conclusion: Diabetes is associated with significantly higher TPV, which is independent of other CAD risk factors. Quantification of TPV improves the identification of diabetic patients at higher risk for future adverse events. Show less
OBJECTIVES The aim of this study was to determine whether coronary artery calcium (CAC) progression was associated with coronary plaque progression on coronary computed tomographic angiography... Show moreOBJECTIVES The aim of this study was to determine whether coronary artery calcium (CAC) progression was associated with coronary plaque progression on coronary computed tomographic angiography.BACKGROUND CAC progression and coronary plaque characteristics are associated with incident coronary heart disease. However, natural history of coronary atherosclerosis has not been well described to date, and the understanding of the association between CAC progression and coronary plaque subtypes such as noncalcified plaque progression remains unclear.METHODS Consecutive patients who were referred to our clinic for evaluation and had serial coronary computed tomography angiography scans performed were included in the study. Coronary artery plaque (total, fibrous, fibrous-fatty, low-attenuation, densely calcified) volumes were calculated using semiautomated plaque analysis software.RESULTS A total of 211 patients (61.3 +/- 12.7 years of age, 75.4% men) were included in the analysis. The mean interval between baseline and follow-up scans was 3.3 +/- 1.7 years. CAC progression was associated with a significant linear increase in all types of coronary plaque and no plaque progression was observed in subjects without CAC progression. In multivariate analysis, annualized and normalized total plaque (beta = 0.38; p < 0.001), noncalcified plaque (beta = 0.35; p = 0.001), fibrous plaque (beta = 0.56; p < 0.001), and calcified plaque (beta = 0.63; p = 0.001) volume progression, but not fibrous-fatty (beta = 0.03; p = 0.28) or low-attenuation plaque (beta = 0.11; p = 0.1) progression, were independently associated with CAC progression. Plaque progression did not differ between the sexes. A significantly increased total and calcified plaque progression was observed in statin users.CONCLUSIONS In a clinical practice setting, progression of CAC was significantly associated with an increase in both calcified and noncalcified plaque volume, except fibrous-fatty and low-attenuation plaque. Serial CAC measurements may be helpful in determining the need for intensification of preventive treatment. (C) 2018 by the American College of Cardiology Foundation. Show less
Background: High-risk plaque (HRP) features as detected by coronary computed tomography angiography (CTA) predict acute coronary syndrome (ACS). We sought to determine whether coronary CTA-specific... Show moreBackground: High-risk plaque (HRP) features as detected by coronary computed tomography angiography (CTA) predict acute coronary syndrome (ACS). We sought to determine whether coronary CTA-specific definitions of HRP improve discrimination of patients with ACS as compared with definitions from intravascular ultrasound (IVUS).Methods and Results: In patients with suspected ACS, randomized to coronary CTA in the ROMICAT II (Rule Out Myocardial Infarction/Ischemia Using Computer Assisted Tomography II) trial, we retrospectively performed semiautomated quantitative analysis of HRP (including remodeling index, plaque burden as derived by plaque area, low computed tomography attenuation plaque volume) and degree of luminal stenosis and analyzed the performance of traditional IVUS thresholds to detect ACS. Furthermore, we derived CTA-specific thresholds in patients with ACS to detect culprit lesions and applied those to all patients to calculate the discriminatory ability to detect ACS in comparison to IVUS thresholds. Of 472 patients, 255 patients (56 +/- 7.8 years; 63% men) had coronary plaque. In 32 patients (6.8%) with ACS, culprit plaques (n=35) differed from nonculprit plaques (n=172) with significantly greater values for all HRP features except minimal luminal area (significantly lower; all P<0.01). IVUS definitions showed good performance while minimal luminal area (odds ratio: 6.82; P=0.014) and plaque burden (odds ratio: 5.71; P=0.008) were independently associated with ACS but not remodeling index (odds ratio: 0.78; P=0.673). Optimized CTA-specific thresholds for plaque burden (area under the curve: 0.832 versus 0.676) and degree of stenosis (area under the curve: 0.826 versus 0.721) showed significantly higher diagnostic performance for ACS as compared with IVUS-based thresholds (all P<0.05) with borderline significance for minimal luminal area (area under the curve: 0.817 versus 0.742; P=0.066).Conclusions: CTA-specific definitions of HRP features may improve the discrimination of patients with ACS as compared with IVUS-based definitions. Show less
Deseive, S.; Straub, R.; Kupke, M.; Broersen, A.; Kitslaar, P.H.; Massberg, S.; ... ; Hausleiter, J. 2018
Serial measurements of coronary plaque volume have been used to evaluate drug efficacy in atherosclerotic progression. However, the usefulness of computed tomography for this purpose is unknown. We... Show moreSerial measurements of coronary plaque volume have been used to evaluate drug efficacy in atherosclerotic progression. However, the usefulness of computed tomography for this purpose is unknown. We investigated whether the change in total plaque volume on coronary computed tomographic angiography is associated with the change in segment plaque volume on intravascular ultrasound.We prospectively enrolled 11 consecutive patients (mean age, 56.3 +/- 5 yr; 6 men) who were to undergo serial invasive coronary angiographic examinations with use of grayscale intravascular ultrasound and coronary computed tomography, performed <180 days apart at baseline and from 1 to 2 years later. Subjects underwent 186 serial measurements of total plaque volume on coronary computed tomography and 22 of segmental plaque volume on intravascular ultrasound. We used semiautomated software to examine percentage relationships and changes between total plaque and segmental plaque volumes.No significant correlations were found between percentages of total coronary and segment coronary plaque volume, nor between normalized coronary plaque volume. However, in the per-patient analysis, there were strong correlations between the imaging methods for changes in total coronary and segment coronary plaque volume (r=0.62; P=0.04), as well as normalized plaque volume (r=0.82; P=0.002).Per-patient change in plaque volume on coronary computed tomography is significantly associated with that on intravascular ultrasound. Computed tomographic angiography may be safer and more widely available than intravascular ultrasound for evaluating atherosclerotic progression in coronary arteries. Larger studies are warranted. Show less
Deseive, S.; Straub, R.; Kupke, M.; Broersen, A.; Kitslaar, P.H.; Massberg, S.; ... ; Hausleiter, J. 2018
Background: To investigate the incremental prognostic value of low-attenuation plaque volume (LAPV) from coronary CT angiography datasets.Methods: Quantification of LAPV was performed using... Show moreBackground: To investigate the incremental prognostic value of low-attenuation plaque volume (LAPV) from coronary CT angiography datasets.Methods: Quantification of LAPV was performed using dedicated software equipped with an adaptive plaque tissue algorithm in 1577 patients with suspected CAD. A combination of death and acute coronary syndrome was defined as primary endpoint. To assess the incremental prognostic value of LAPV, parameters were added to a baseline model including clinical risk and obstructive coronary artery disease (CAD), a baseline model including clinical risk and calcium scoring (CACS) and a baseline model including clinical risk and segment involvement score (SIS).Results: Patients were followed for 5.5 years either by telephone contact, mail or clinical visits. The primary endpoint occurred in 30 patients. Quantified LAPV provided incremental prognostic information beyond clinical risk and obstructive CAD (c-index 0.701 vs. 0.767, p<.001), clinical risk and CACS (c-index 0.722 vs. 0.771, p<.01) and clinical risk and SIS (c-index 0.735 vs. 0.771, p<.01. A combined approach using quantified LAPV and clinical risk significantly improved the stratification of patients into different risk categories compared to clinical risk alone (categorical net reclassification index 0.69 with 95% CI 0.27 and 0.96, p<.001). The combined approach classified 846 (53.6%) patients as low risk (annual event rate 0.04%), 439 (27.8%) patients as intermediate risk (annual event rate 0.5%) and 292 (18.5%) patients as high risk (annual event rate 0.99%).Conclusion: Quantification of LAPV provides incremental prognostic information beyond established CT risk patterns and permits improved stratification of patients into different risk categories. Show less
Semi-automated software can provide quantitative assessment of atherosclerotic plaques on coronary CT angiography (CTA). The relationship between established qualitative high-risk plaque features... Show moreSemi-automated software can provide quantitative assessment of atherosclerotic plaques on coronary CT angiography (CTA). The relationship between established qualitative high-risk plaque features and quantitative plaque measurements has not been studied. We analyzed the association between quantitative plaque measurements and qualitative high-risk plaque features on coronary CTA. We included 260 patients with plaque who underwent coronary CTA in the Rule Out Myocardial Infarction/Ischemia Using Computer Assisted Tomography (ROMICAT) II trial. Quantitative plaque assessment and qualitative plaque characterization were performed on a per coronary segment basis. Quantitative coronary plaque measurements included plaque volume, plaque burden, remodeling index, and diameter stenosis. In qualitative analysis, high-risk plaque was present if positive remodeling, low CT attenuation plaque, napkin-ring sign or spotty calcium were detected. Univariable and multivariable logistic regression analyses were performed to assess the association between quantitative and qualitative high-risk plaque assessment. Among 888 segments with coronary plaque, high-risk plaque was present in 391 (44.0%) segments by qualitative analysis. In quantitative analysis, segments with high-risk plaque had higher total plaque volume, low CT attenuation plaque volume, plaque burden and remodeling index. Quantitatively assessed low CT attenuation plaque volume (odds ratio 1.12 per 1 mm(3), 95% CI 1.04-1.21), positive remodeling (odds ratio 1.25 per 0.1, 95% CI 1.10-1.41) and plaque burden (odds ratio 1.53 per 0.1, 95% CI 1.08-2.16) were associated with high-risk plaque. Quantitative coronary plaque characteristics (low CT attenuation plaque volume, positive remodeling and plaque burden) measured by semi-automated software correlated with qualitative assessment of high-risk plaque features. Show less
PurposeAutomatically extracted coronary artery trees (CATs) from coronary computed tomography angiography imagescould contain incorrect extractions which require manual corrections before they can... Show morePurposeAutomatically extracted coronary artery trees (CATs) from coronary computed tomography angiography imagescould contain incorrect extractions which require manual corrections before they can be used in clinical practice.A model-guided method for improving the extracted CAT is described to automatically detect potential incorrectextractions and improve them.MethodsThe proposed method is a coarse-to-fine approach. A coarse improvement is first applied on all vessels in theextracted CAT, and then a fine improvement is applied only on vessels with higher clinical significance. Basedupon a decision tree, the proposed method automatically and iteratively performs improvement operations for theentire extracted CAT until it meets the stop criteria. The improvement of the extraction quality obtained by theproposed method is measured using a scoring system. 18 datasets were used to determine optimal values for theparameters involved in the model-guided method and 122 datasets were used for evaluation.ResultsCompared to the initial automatic extractions, the proposed method improves the CATs for 122 datasets from anaverage quality score of 87±6 to 93±4. The developed method is able to run within 2 minutes on a typicalworkstation. The difference in extraction quality after automatic improvement is negatively correlated with theinitial extraction quality (R=-0.694, P<0.001).ConclusionWithout deteriorating the initially extracted CATs, the presented method automatically detects incorrectextractions and improves the CATs to an average quality score of 93 guided by anatomical statistical models. Show less
Cao, Q.; Broersen, A.; Graaf, M.A. de; Kitslaar, P.H.; Yang, G.Y.; Scholte, A.J.; ... ; Dijkstra, J. 2017
