Complex dual cardiac and respiratory movement is a challenge for PET/CT imaging of coronary plaques. When using dual-gating, respiratory motion correction (RMC) is essential to reduce blurring, but this is not yet available in vendor software. Moreover, existing vendor methods for RMC either ignore attenuation mismatch or require external devices to obtain matched PET and CT. This study investigates a method for cardiac PET/CT motion estimation and motion correction that uses gated PET in combination with cine-CT obtained without external monitoring. This methodology will be incorporated into an open-source software platform. 68GaDOTATATE PET/CINE-CT were acquired for 24 patients with identified coronary plaques. A respiratory motion model was derived from the cine-CT data after sorting via intensity analysis. Motion parameters were derived from respiratory gated non-attenuation corrected PET images. The resulting deformations were then applied to the CT data, which were used to obtain respiratory motion and attenuation corrected PET images. The effectiveness of our method was verified by comparing key metrics Root Mean Squared Error and Foot-to-head profiles in liver dome before and after the application of the motion model.

Purpose:This study aims to investigate the correlation between myocardial area at risk at coronary computed tomography angiography (CCTA) and the ischemic burden derived from myocardial computed tomography perfusion (CTP) by using the 17-segment model.Methods:Forty-two patients with chest pain complaints who underwent a combined CCTA and CTP protocol were identified. Patients with reversible ischemia at CTP and at least one stenosis of ≥ 50% at CCTA were selected. Myocardial area at risk was calculated using a Voronoi-based segmentation algorithm at CCTA and was defined as the sum of all territories related to a ≥ 50% stenosis as a percentage of the total left ventricular (LV) mass. The latter was calculated using LV contours which were automatically drawn using a machine learning algorithm. Subsequently, the ischemic burden was defined as the number of segments demonstrating relative hypoperfusion as a percentage of the total amount of segments (=17). Finally, correlations were tested between the myocardial area at risk and the ischemic burden using Pearson's correlation coefficient.Results:A total of 77 coronary lesions were assessed. Average myocardial area at risk and ischemic burden for all lesions was 59% and 23%, respectively. Correlations for ≥ 50% and ≥ 70% stenosis based myocardial area at risk compared to ischemic burden were moderate (r = 0.564; p < 0.01) and good (r = 0.708; p < 0.01), respectively.Conclusion:The relation between myocardial area at risk as calculated by using a Voronoi-based algorithm at CCTA and ischemic burden as assessed by CTP is dependent on stenosis severity.

To present an overview of studies using serial coronary computed tomography angiography (CCTA) as a tool for finding both quantitative (changes) and qualitative plaque characteristics as well as epicardial adipose tissue (EAT) volume changes as predictors of plaque progression and/or major adverse cardiac events (MACE) and outline the challenges and advantages of using a serial non-invasive imaging approach for assessing cardiovascular prognosis. A literature search was performed in PubMed, Embase, Web of Science, Cochrane Library and Emcare. All observational cohort studies were assessed for quality using the Newcastle–Ottawa Scale (NOS). The NOS score was then converted into Agency for Healthcare Research and Quality (AHRQ) standards: good, fair and poor. A total of 36 articles were analyzed for this review, 3 of which were meta-analyses and one was a technical paper. Quantitative baseline plaque features seem to be more predictive of MACE and/or plaque progression as compared to qualitative plaque features. A critical review of the literature focusing on studies utilizing serial CCTA revealed that mainly quantitative baseline plaque features and quantitative plaque changes are predictive of MACE and/or plaque progression contrary to qualitative plaque features. Significant questions regarding the clinical implications of these specific quantitative and qualitative plaque features as well as the challenges of using serial CCTA have yet to be resolved in studies using this imaging technique. • Use of (serial) CCTA can identify plaque characteristics and plaque changes as well as changes in EAT volume that are predictive of plaque progression and/or major adverse events (MACE) at follow-up. • Studies utilizing serial CCTA revealed that mainly quantitative baseline plaque features and quantitative plaque changes are predictive of MACE and/or plaque progression contrary to qualitative plaque features. • Ultimately, serial CCTA is a promising technique for the evaluation of cardiovascular prognosis, yet technical details remain to be refined.

Abstract Background Computed Tomography Coronary Angiography (CTCA) is an effective non-invasive imaging modality for anatomo-functional assessment of coronary artery disease (CAD). Radiomics features have been used for diagnosis or outcome prediction, however, their potential value for characterizing flow limiting coronary lesions has not been explored. Purpose To assess whether application of novel radiomics and machine learning (ML) techniques on CTCA derived datasets improves characterization of functionally significant coronary lesions. Methods Consecutive patients with stable chest pain and intermediate pre-test likelihood for CAD, who underwent CTCA and PET-or SPECT-Myocardial Perfusion Imaging (MPI) respectively, were prospectively evaluated and included in the analysis. PET-MPI was considered abnormal when >1 contiguous segments showed both stress Myocardial Blood Flow ≤2.3mL/g/min and Myocardial Flow Reserve (MFR) ≤2.5 for 15O-water or <1.79 mL/g/min and ≤2.0 for 13N-ammonia respectively. Defect reversibility (DR) was defined as a summed difference score (SDS) between stress and rest images ≥2. CTCA and functional images were fused to assign each myocardial segment to the pertinent coronary territory. Stenosis severity, plaque characteristics and radiomic plaque features were assessed in the total length of the 3 main coronary vessels. In total, 1765 features were extracted from each vessel and a feature reduction and model creation pipeline was constructed [Figure 1]. Two separate datasets: a) coronary stenosis (≥50%) + plaque characteristics and b) coronary stenosis (≥50%) + plaque characteristics + radiomics were formulated and compared in terms of AUCs accordingly. Results A total of 292 coronary vessels (140 with corresponding PET-MPI data and 152 with SPECT MPI data) were analysed. Plaque burden and stenosis severity were the only independent predictors of impaired myocardial perfusion on PET-MPI, with an AUC = 0.749, (95% CI: 0.658–0.826). Stenosis severity, kurtosis, contrast, interquartile range and entropy were predictors of an abnormal PET-MPI result and their combination resulted in an AUC = 0.854, (95% CI: 0.775–0.914). The difference between the 2 models was statistically significant (p-diff: 0.02, 95% CI: 0.0165–0.194). Stenosis severity was the only predictor of a DR on SPECT-MPI, AUC = 0.624 (95% CI: 0.542–0.702). Small Dependence High Gray Level Emphasis, Cluster Prominence, Region Length, wavelet Median and square Median were predictors of a positive SPECT result, with AUC = 0.816, (95% CI: 0.745–0.875). The difference between the two models was statistically significant (p-diff: 0.006, 95% CI: 0.152–0.329) Conclusion Radiomic futures can be combined with anatomical and morphological characteristics of coronary lesions in CTCA imaging and provide valuable complementary information for characterizing functionally significant coronary lesions. Funding Acknowledgement Type of funding sources: Public grant(s) – EU funding. Main funding source(s): This work was supported from European Regional Development Fund, Operational Programme “Competitiveness, Entrepreneurship and Innovation 2014-2022 (EPAnEK)”, titled: The Greek Research Infrastructure for Personalized Medicine (pMED-GR)

Introduction: Combination of computed tomography angiography (CTA) and adenosine stress CT myocardial perfusion (CTP) allows for coronary artery lesion assessment as well as myocardial ischemia. Nowadays, ischemia on CTP is assessed semi-quantitatively by visual analysis. The aim of this study was to fully quantify myocardial ischemia and the subtended myocardial mass on CTP. Methods: We included 33 patients referred for a combined CTA and adenosine stress CTP with good or excellent imaging quality on CTP. Firstly, the coronary artery tree was automatically extracted from CTA and the relevant coronary artery lesions (≥ 50%) were manually defined (fig 1A). Secondly, epi- and endocardial contours along with CTP deficits were manually defined in short-axis images (fig 1D, 1E). Thirdly, a Voronoi-based algorithm was used to quantify the subtended myocardial mass (fig 1B). Fourthly, the perfusion defect and subtended myocardial mass were spatially registered to the CTA and measured in grams (fig 1F, 1C). Finally, this can be used to quantitatively correlate the perfusion defect to the subtended myocardial mass. To assess reproducibility, left ventricular epicardial and endocardial contours along with perfusion defects were re-drawn. Results: Voronoi-based segmentation was successful in all cases. We assessed a total of 64 relevant coronary artery lesions. Average values for left ventricular mass, total subtended mass and perfusion defect mass were 118, 69 and 7 grams respectively. In 19/33 patients (58%) the total perfusion defect mass could be distributed over the relevant coronary artery lesion(s). Results were highly reproducible (r≥0.822, p<0.01). Conclusions: Quantification of myocardial ischemia and subtended myocardial mass using a Voronoi-based segmentation algorithm seem feasible at adenosine stress CTP and allows for quantitative correlation of coronary artery lesions to corresponding areas of myocardial hypoperfusion.

Background: The various plaque components have been associated with ischemia and outcomes in patients with coronary artery disease (CAD). The main goal of this analysis was to test the hypothesis that, at patient level, the fraction of non-calcified plaque volume (PV) of total PV is associated with ischemia and outcomes in patients with CAD. This ratio could be a simple and clinically useful parameter, if predicting outcomes. Methods: Consecutive patients with suspected CAD undergoing coronary computed tomography angiography with selective positron emission tomography perfusion imaging were selected. Plaque components were quantitatively analyzed at patient level. The fraction of various plaque components were expressed as percentage of total PV and examined among patients with non-obstructive CAD, suspected stenosis with normal perfusion, and those with reduced myocardial perfusion. Clinical outcomes included all-cause mortality and myocardial infarction. Results: In total, 494 patients (age 63 & PLUSMN; 9 years, 55% male) were included. Total PV and all plaque components were significantly larger in patients with reduced myocardial perfusion compared to patients with normal perfusion and those with non-obstructive CAD. During follow-up 35 events occurred. Patients with any plaque component & GE; median showed worse outcomes (log-rank p < 0.001 for all). In addition, low-attenuation plaque & GE; median was associated with worse outcomes independent of total PV (adjusted HR: 2.754, 95% CI: 1.022-7.0419, p = 0.045). The fractions of the various plaque components were not associated with outcomes. Conclusion: Larger total PV or any plaque component at patient level are associated with abnormal myocardial perfusion and adverse events. The various plaque components as fraction of total PV lack additional prognostic value.

Background and aim To investigate sex differences with respect to presence and location of atherosclerosis in acute ischemic stroke patients. Methods Participants with acute ischemic stroke were included from the Dutch acute stroke trial, a large prospective multicenter cohort study performed between May 2009 and August 2013. All patients received computed tomography/computed tomography-angiography within 9 h of stroke onset. We assessed presence of atherosclerosis in the intra- and extracranial internal carotid and vertebrobasilar arteries. In addition, we determined the burden of intracranial atherosclerosis by quantifying internal carotid and vertebrobasilar artery calcifications, resulting in calcium volumes. Prevalence ratios between women and men were calculated with Poisson regression analysis and adjusted prevalence ratio for potential confounders (age, hypertension, hyperlipidemia, diabetes, smoking, and alcohol use). Results We included 1397 patients with a mean age of 67 years, of whom 600 (43%) were women. Presence of atherosclerosis in intracranial vessel segments was found as frequently in women as in men (71% versus 72%, adjusted prevalence ratio 0.95; 95% CI 0.89-1.01). In addition, intracranial calcification volume did not differ between women and men in both intracranial internal carotid (large burden 35% versus 33%, adjusted prevalence ratio 0.93; 95% CI 0.73-1.19) and vertebrobasilar arteries (large burden 26% versus 40%, adjusted prevalence ratio 0.69; 95% CI 0.41-1.12). Extracranial atherosclerosis was less common in women than in men (74% versus 81%, adjusted prevalence ratio 0.86; 95% CI 0.81-0.92). Conclusions In patients with acute ischemic stroke the prevalence of intracranial atherosclerosis does not differ between women and men, while extracranial atherosclerosis is less often present in women compared with men.

Automated plaque quantification derived from coronary CT angiogragphy datasets provides exact and reliable assessment of coronary atherosclerosis burden. To investigate the potential for category based reclassification of patients based upon quantified coronary plaque volume in patients with 10 years of follow-up. Coronary PV was quantified with dedicated software in 1577 patients with suspected coronary artery disease. Cardiac death and acute coronary syndrome were defined as endpoint. Patients were initially classified as low, intermediate or high risk based upon the Morise score. Quantified PV was used to reclassify patients as shown in Figure 1 Panel A. The applied cutoffs (PV=0, PV0–110.5 mm3 and PV>110.5mm3) were established by previous work of our group. Categorical net reclassification improvement was used to compare the initial and updated patient stratification. Patients were followed for 10.4 years. The combined endpoint occurred in 59 patients, of whom 36 suffered from cardiac death, 18 had non-fatal myocardial infarction and 5 presented with unstable angina requiring recascularisation. The Morise score classified the majority of patients as intermediate risk patients (71%) and smaller proportions as low risk (21.9%) or high risk (7.1%). Quantified PV based reclassification resulted in reclassification of 800 (51%) patients. Of those, the majority was classified into a lower risk category (n=502). Calculation of the categorical NRI proved a significantly superior risk stratification when compared to the initial risk groups (0.48 with 95% CI 0.13 and 0.68, p<0.001). The reclassification matrix is shown in Figure 1 Panel B. After reclassification, the estimated 10-year event rates for low, intermediate and high risk patients were 0.6% (95% CI 0 and 1.3%), 4.8% (95% CI 2.4 and 7.2%) and 11.3% (95% CI 6.6 and 13.9%) respectively. Quantified coronary PV permits an effective and useful approach to reclassify patients with suspected coronary artery disease into superior risk categories. Type of funding source: None

Purpose: The rationale of this study was to identify patients with fast progression of coronary plaque volume PV and characterize changes in PV and plaque components over time. Method: Total PV (TPV) was measured in 350 patients undergoing serial coronary computed tomography angiography (median scan interval 3.6 years) using semi-automated software. Plaque morphology was assessed based on attenuation values and stratified into calcified, fibrous, fibrous-fatty and low-attenuation PV for volumetric measurements. Every plaque was additionally classified as either calcified, partially calcified or non-calcified. Results: In total, 812 and 955 plaques were detected in the first and second scan. Mean TPV increase was 20 % on a per-patient base (51.3 mm(3) [interquartile range (IQR): 14.4, 126.7] vs. 61.6 mm(3) [IQR: 16.7, 170.0]). TPV increase was driven by calcified PV (first scan: 7.6 mm(3) [IQR: 0.2, 33.6] vs. second scan: 16.6 mm(3) [IQR: 1.8, 62.1], p < 0.01). Forty-two patients showed fast progression of TPV, defined as > 1.3 mm(3) increase of TPV per month. Male sex (odds ratio 3.1, p = 0.02) and typical angina (odds ratio 3.95, p = 0.03) were identified as risk factors for fast TPV progression, while high-density lipoprotein cholesterol had a protective effect (odds ratio per 10 mg/dl increase of HDL cholesterol: 0.72, p < 0.01). Progression to > 50 % stenosis at follow-up was observed in 34 of 327 (10.4 %) calcified plaques, in 13 of 401 (3.2 %) partially calcified plaques and 2 of 221 (0.9 %) non-calcified plaques (p < 0.01). Conclusion: Fast plaque progression was observed in male patients and patients with typical angina. High HDL cholesterol showed a protective effect.

Abstract Background Automated plaque quantification derived from coronary CT angiogragphy (CCTA) datasets provides exact and reliable assessment of coronary atherosclerosis burden. Purpose To investigate the long-term predictive value of quantified coronary plaque volume (PV) in comparison to Calcium Score (CACS). Methods Dedicated software was used to quantify PV in 1577 patients. A combination of cardiac death and acute coronary syndrome was used as endpoint. Incremental prognostic value was tested with c-statistics and continuous net reclassification improvement (NRI). The Morise Score was used to summarize patients clinical risk profile. Results Patients were followed for 10.4 years. The combined endpoint occurred in 59 patients, of whom 36 suffered from cardiac death, 18 had non-fatal myocardial infarction and 5 presented with unstable angina requiring revascularisation. The additive predictive value of PV and CACS was tested against a baseline model (c-index 0.741) including clinical risk and the number of diseased coronary segments (segment-Involvement score). While PV provided additive prognostic value (rise in c-index to 0.763, p=0.01 and NRI 0.247, p=0.03), CACS did not (c-index 0.749, p=0.2 and NRI 0.162, p=0.12). A threshold of 110.5 mm3, which was established by a previous analysis of our group, provided excellent separation of patients into low (no PV), intermediate (PV <110.5 mm3) and high (PV >110.5 mm3) risk categories based upon quantified PV (see attached Figure). Conclusion Quantification of PV from CCTA datasets provides excellent prognostic information on long-term follow-up.

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 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.

1228 Coronary CTA: plaque imaging Results: Patients were followed for 5.6 years and the combined endpoint occured in 18 (16.7%)diabetic and 28 (8.6%) non-diabetic patients (odds Ratio 2.1, p=0.03).There were no significant differences regarding the baseline characteristics of diabetic and non-diabetic patients including age, sex, BMI, hypertension, smoking habits, LDL and HDL cholesterol, family history for CAD as well as ASS and Statin medication.Diabetic patients had significantly higher total PV than non-diabetic patients (55.1 [IQR 6.2 and 220.4] vs. 24.9[IQR 0 and 166.7] mm 3 , p=0.02).Findings were consistent for calcifíed and non-calcified PV (both p<0.05).Quantification of coronary PV provided good separation of diabetic and non-diabetic patients at higher and lower risk for adverse events (see Figure 1) using a threshold of 110.5 mm 3 PV per patients (log-rank p<0.01 and 0.02, respectively).Noteworthy, diabetic and non-diabetic patients with a PV<110.5 mm 3 had a comparable outcome (hazard 1.3, p=0.59), while diabetic patients with PV>110.5 mm 3 had significantly worse outcome (hazard Ratio 2.3, p=0.03) compared to non-diabetic patients with PV>110.5 mm 3 .

Purpose: Investigate the influence of adaptive statistical iterative reconstruction (ASIR) and the model-based IR (Veo) reconstruction algorithm in coronary computed tomography angiography (CCTA) images on quantitative measurements in coronary arteries for plaque volumes and intensities.Methods: Three patients had three independent dose reduced CCTA performed and reconstructed with 30% ASIR (CTDIvol at 6.7 mGy), 60% ASIR (CTDIvol 4.3 mGy) and Veo (CTDIvol at 1.9 mGy). Coronary plaque analysis was performed for each measured CCTA volumes, plaque burden and intensities.Results: Plaque volume and plaque burden show a decreasing tendency from ASIR to Veo as median volume for ASIR is 314 mm(3) and 337 mm(3)-252 mm(3) for Veo and plaque burden is 42% and 44% for ASIR to 39% for Veo. The lumen and vessel volume decrease slightly from 30% ASIR to 60% ASIR with 498 mm(3)-391 mm(3) for lumen volume and vessel volume from 939 mm(3) to 830 mm(3). The intensities did not change overall between the different reconstructions for either lumen or plaque.Conclusion: We found a tendency of decreasing plaque volumes and plaque burden but no change in intensities with the use of low dose Veo CCTA (1.9 mGy) compared to dose reduced ASIR CCTA (6.7 mGy & 4.3 mGy), although more studies are warranted. (C) 2016 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

Background— High-risk plaque features (HRP) as detected by coronary CT 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 to definitions from intravascular ultrasound (IVUS). Methods and Results— In patients with suspected ACS, randomized to coronary CTA in the ROMICAT II trial, we retrospectively performed semi-automated quantitative analysis of HRP (including remodeling index, plaque burden as derived by plaque area, low CT attenuation plaque volume) and degree of luminal stenosis and analyzed the performance of traditional IVUS thresholds to detect ACS. Further, we derived CTA-specific thresholds in ACS patients to detect culprit lesions, and applied those to all patients to calculate the discriminatory ability to detect ACS in comparison to IVUS thresholds. Out 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 non-culprit 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 (OR: 6.82; p=0.014) and plaque burden (OR: 5.71, p=0.008) were independently associated with ACS, but not remodeling index (OR: 0.78; p=0.673). Optimized CTA-specific thresholds for plaque burden (AUC: 0.832 vs. 0.676) and degree of stenosis (AUC: 0.826 vs. 0.721) showed significantly higher diagnostic performance for ACS as compared to IVUS based thresholds (all p<0.05) with borderline significance for minimal luminal area (AUC: 0.817 vs. 0.742; p=0.066). Conclusions— CTA-specific definitions of high-risk plaque features may improve the discrimination of patients with ACS as compared to IVUS based definitions.