Artificial Intelligence-based quantification of atherosclerotic plaque and stenosis from coronary computed tomography angiography using a novel method - Lin, Andrew; Manral, Nipun; McElhinney, Priscilla; Killekar, Aditya; Matsumoto, Hidenari; Kwiecinski, Jacek; Pieszko, Konrad; Razipour, Aryabod; Grodecki, Kajetan; Park, Caroline; Doris, Mhairi; Kwan, Alan; et al. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 2022)
Background: Coronary computed tomography angiography (CCTA) allows non-invasive assessment of luminal stenosis and coronary atherosclerotic plaque. We aimed to develop and externally validate an artificial intelligence-based deep learning (DL) network for CCTA-based measures of plaque volume and stenosis severity. Methods: This was an international multicenter study of 1,183 patients undergoing CCTA at 11 sites. A novel DL convolutional neural network was trained to segment coronary plaque in 921 patients (5,045 lesions). The DL architecture consisted of a novel hierarchical convolutional long short-term memory (ConvLSTM) Network. The training set was further split temporally into training (80%) and internal validation (20%) datasets. Each coronary lesion was assessed in a 3D slab about the vessel centrelines. Following training and internal validation, the model was applied to an independent test set of 262 patients (1,469 lesions), which included an external validation cohort of 162 patients Results: In the test set, there was excellent agreement between DL and clinician expert reader measurements of total plaque volume (intraclass correlation coefficient [ICC] 0.964) and percent diameter stenosis (ICC 0.879; both p<0.001, see tables and figure). The average per-patient DL plaque analysis time was 5.7 seconds versus 25-30 minutes taken by experts. There was significantly higher overlap measured by the Dice coefficient (DC) for ConvLSTM compared to UNet (DC for vessel 0.94 vs 0.83, p<0.0001; DC for lumen and plaque 0.90 vs 0.83, p<0.0001) or DeepLabv3 (DC for vessel both 0.94; DC for lumen and plaque 0.89 vs 0.84, p<0.0001). Conclusions: A novel externally validated artificial intelligence-based network provides rapid measurements of plaque volume and stenosis severity from CCTA which agree closely with clinician expert readers.
CRIS-Team Scopus Importer:2022-06-10
Keywords: artificial intelligence; atherosclerosis; coronary computed tomography angiography; deep learning

Automated quantification of epicardial adipose tissue from non-contrast CT on multi-center and multi-vendor data using deep learning - Commandeur, F.; Göller, Markus; Razipour, A.; Cadet, S.; Hell, Michaela; Kwiecinski, J.; Chen, X.; Chang, H. J.; Achenbach, Stephan; Berman, D. S.; Slomka, P. J.; Tamarappoo, B. K.; et al. (EUROPEAN HEART JOURNAL, 2019)
CRIS-Team WoS Importer:2020-02-04

Cardiac CT: Technological Advances in Hardware, Software, and Machine Learning Applications. - Commandeur, Frederic; Göller, Markus; Dey, Damini (Current Cardiovascular Imaging Reports, 2018)
Purpose of Review: Multidetector row computed tomography (CT) allows noninvasive imaging of the heart and coronary arteries. The purpose of this review is to briefly summarize recent advances in CT hardware and software technology, and machine learning applications for cardiovascular imaging. Recent Findings: In the last decades, there have been significant improvements in CT hardware focusing on faster gantry rotation resulting in improved temporal resolution. Concurrent hardware improvements include improved spatial resolution and higher coverage of the patient, enabling faster acquisition. Advances in cardiac CT software include methods for measurement of noninvasive FFR, coronary plaque characterization, and adipose tissue characteristics around the heart. Machine learning approaches using cardiac CT have been shown to improve both risk of prognosis and lesion-specific ischemia. Summary: Recent advances in CT hardware and software have expanded the clinical utility of CT for cardiovascular imaging. In the next decades, continued advances can be anticipated in these areas, and in machine learning applications in cardiac CT, as they are incorporated into clinical routine for image acquisition, image analysis, and prediction of patient outcomes.
EVALuna2:423072

Comparison of Coronary Atherosclerotic Plaque Burden and Composition as Assessed on Coronary Computed Tomography Angiography in East Asian and European-Origin Caucasians - Ihdayhid, Abdul Rahman; Göller, Markus; Dey, Damini; Nerlekar, Nitesh; Yap, Grace; Thakur, Udit; Adams, Daniel; Cameron, James; Seneviratne, Sujith; Achenbach, Stephan; Ko, Brian (American Journal of Cardiology, 2019)
Recent evidence suggests plaque morphology evaluated on coronary computed tomography angiography has prognostic implications. East Asians have a lower prevalence of myocardial infarction and cardiovascular mortality compared with European-origin Caucasians. We aimed to compare coronary atherosclerotic burden and plaque composition in a matched cohort of Caucasian and East Asians patients with stable chest pain who underwent computed tomography angiography. Two-hundred symptomatic patients (age 58.8 ± 7.9, male 51%) were matched for age, gender, body mass index, and diabetes (100 each ethnic group). A blinded core-laboratory quantified calcified and noncalcified plaque (NCP) volume and burden. Components of NCP were differentiated by plaque hounsfield unit (HU) thresholds which defined high-risk necrotic core (−30 to 30HU), fibrofatty plaque (31 to 130HU); and low-risk fibrous plaque (131 to 350HU). Composition of NCP components was derived as (NCP component volume/total NCP volume) × 100%. Segment Involvement Score, percent diameter and area stenosis were comparable in both groups. Similarly, there was no difference in the volume and burden of total, calcified and NCP. Compared with Caucasians, East Asians demonstrated lower composition of plaque attenuation corresponding to necrotic core (3.5 vs 5.1%; p = 0.004) and fibrofatty plaque (29.6 vs 37.3%; p = 0.005), and higher fibrous plaque (65.7 vs 57.6%; p = 0.004). On multivariable analysis East Asian ethnicity was independently associated with lower composition of high-risk plaque after adjustment for risk factors and scan parameters. These findings were consistent in a propensity-matched sensitivity-analysis. In conclusion, based on this matched cohort, East Asian ethnicity is associated with significantly less composition of high-risk NCP (necrotic core and fibrofatty plaque) and a higher composition of low-risk fibrous plaque compared with Caucasians; which may confer a lower risk of cardiovascular events.
CRIS-Team Scopus Importer:2019-09-03

Computed tomography–based pericoronary adipose tissue attenuation in patients undergoing TAVR: a novel method for risk assessment - Steyer, Alexandra; Mas-Peiro, Silvia; Leistner, David M.; Puntmann, Valentina O.; Nagel, Eike; Dey, Damini; Göller, Markus; Koch, Vitali; Booz, Christian; Vogl, Thomas J.; Martin, Simon S. (Frontiers in Cardiovascular Medicine, 2023)
Objectives: This study aims to assess the attenuation of pericoronary adipose tissue (PCAT) surrounding the proximal right coronary artery (RCA) in patients with aortic stenosis (AS) and undergoing transcatheter aortic valve replacement (TAVR). RCA PCAT attenuation is a novel computed tomography (CT)–based marker for evaluating coronary inflammation. Coronary artery disease (CAD) in TAVR patients is common and usually evaluated prior to intervention. The most sensible screening method and consequential treatment approach are unclear and remain a matter of ceaseless discussion. Thus, interest remains for safe and low-demand predictive markers to identify patients at risk for adverse outcomes postaortic valve replacement. Methods: This single-center retrospective study included patients receiving a standard planning CT scan prior to TAVR. Conventional CAD diagnostic tools, such as coronary artery calcium score and significant stenosis via invasive coronary angiography and coronary computed tomography angiography, were determined in addition to RCA PCAT attenuation using semiautomated software. These were assessed for their relationship with major adverse cardiovascular events (MACE) during a 24-month follow-up period. Results: From a total of 62 patients (mean age: 82 ± 6.7 years), 15 (24.2%) patients experienced an event within the observation period, 10 of which were attributed to cardiovascular death. The mean RCA PCAT attenuation was higher in patients enduring MACE than that in those without an endpoint (−69.8 ± 7.5 vs. −74.6 ± 6.2, P = 0.02). Using a predefined cutoff of >−70.5 HU, 20 patients (32.3%) with high RCA PCAT attenuation were identified, nine (45%) of which met the endpoint within 2 years after TAVR. In a multivariate Cox regression model including conventional CAD diagnostic tools, RCA PCAT attenuation prevailed as the only marker with significant association with MACE (P = 0.02). After dichotomization of patients into high- and low-RCA PCAT attenuation groups, high attenuation was related to greater risk of MACE (hazard ration: 3.82, P = 0.011). Conclusion: RCA PCAT attenuation appears to have predictive value also in a setting of concomitant AS in patients receiving TAVR. RCA PCAT attenuation was more reliable than conventional CAD diagnostic tools in identifying patients at risk for MACE.
CRIS-Team Scopus Importer:2023-06-16
Keywords: computed tomography angiography; coronary artery disease; major adverse cardiovascular events; pericoronary adipose tissue; risk stratification; transcatheter aortic valve replacements

Computed tomography-derived characterisation of pericoronary,epicardial and paracardial adipose tissue and its association with myocardial ischemia as assessed by computed and invasive fractional flow - Göller, Markus; Duncker, Hendrik; Moshage, Maximilian; Dey, D.; Bittner, Daniel; Ammon, Fabian; Achenbach, Stephan; Marwan, Mohamed (EUROPEAN HEART JOURNAL, 2021)
CRIS-Team WoS Importer:2021-12-10

Coronary atherosclerotic plaque burden and composition as assessed on CT angiography in East Asian and Caucasian populations - Ihdayhid, A. R.; Göller, Markus; Dey, D.; Adams, D.; Nerlekar, N.; Yap, G.; Thakur, U.; Cameron, J.; Seneviratne, S. K.; Achenbach, Stephan; Ko, B. (EUROPEAN HEART JOURNAL, 2018)
CRIS-Team WoS Importer:2019-03-15

Deep learning-based stenosis quantification from coronary CT angiography - Hong, Youngtaek; Commandeur, Frederic; Cadet, Sebastien; Göller, Markus; Doris, Mhairi K.; Chen, Xi; Kwiecinski, Jacek; Berman, Daniel S.; Slomka, Piotr J.; Chang, Hyuk Jae; Dey, Damini (Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 2019)
Coronary computed tomography angiography (CTA) allows quantification of stenosis. However, such quantitative analysis is not part of clinical routine. We evaluated the feasibility of utilizing deep learning for quantifying coronary artery disease from CTA. Methods: A total of 716 diseased segments in 156 patients (66 ± 10 years) who underwent CTA were analyzed. Minimal luminal area (MLA), percent diameter stenosis (DS), and percent contrast density difference (CDD) were measured using semi-automated software (Autoplaque) by an expert reader. Using the expert annotations, deep learning was performed with convolutional neural networks using 10-fold cross-validation to segment CTA lumen and calcified plaque. MLA, DS and CDD computed using deep-learning-based approach was compared to expert reader measurements. Results: There was excellent correlation between the expert reader and deep learning for all quantitative measures (r=0.984 for MLA; r=0.957 for DS; and r=0.975 for CDD, p<0.001 for all). The expert reader and deep learning method was not significantly different for MLA (median 4.3 mm2 for both, p=0.68) and CDD (11.6 vs 11.1%, p=0.30), and was significantly different for DS (26.0 vs 26.6%, p<0.05); however, the ranges of all the quantitative measures were within inter-observer variability between 2 expert readers. Conclusions: Our deep learning-based method allows quantitative measurement of coronary artery disease segments accurately from CTA and may enhance clinical reporting.
CRIS-Team Scopus Importer:2019-07-12
Keywords: contrast density difference; coronary CT Angiography; deep learning; minimum luminal area; quantitative CT.; stenosis

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study - Lin, Andrew; Manral, Nipun; McElhinney, Priscilla; Killekar, Aditya; Matsumoto, Hidenari; Kwiecinski, Jacek; Pieszko, Konrad; Razipour, Aryabod; Grodecki, Kajetan; Park, Caroline; Otaki, Yuka; Doris, Mhairi; et al. (The Lancet Digital Health, 2022)
BACKGROUND: Atherosclerotic plaque quantification from coronary CT angiography (CCTA) enables accurate assessment of coronary artery disease burden and prognosis. We sought to develop and validate a deep learning system for CCTA-derived measures of plaque volume and stenosis severity. METHODS: This international, multicentre study included nine cohorts of patients undergoing CCTA at 11 sites, who were assigned into training and test sets. Data were retrospectively collected on patients with a wide range of clinical presentations of coronary artery disease who underwent CCTA between Nov 18, 2010, and Jan 25, 2019. A novel deep learning convolutional neural network was trained to segment coronary plaque in 921 patients (5045 lesions). The deep learning network was then applied to an independent test set, which included an external validation cohort of 175 patients (1081 lesions) and 50 patients (84 lesions) assessed by intravascular ultrasound within 1 month of CCTA. We evaluated the prognostic value of deep learning-based plaque measurements for fatal or non-fatal myocardial infarction (our primary outcome) in 1611 patients from the prospective SCOT-HEART trial, assessed as dichotomous variables using multivariable Cox regression analysis, with adjustment for the ASSIGN clinical risk score. FINDINGS: In the overall test set, there was excellent or good agreement, respectively, between deep learning and expert reader measurements of total plaque volume (intraclass correlation coefficient [ICC] 0·964) and percent diameter stenosis (ICC 0·879; both p<0·0001). When compared with intravascular ultrasound, there was excellent agreement for deep learning total plaque volume (ICC 0·949) and minimal luminal area (ICC 0·904). The mean per-patient deep learning plaque analysis time was 5·65 s (SD 1·87) versus 25·66 min (6·79) taken by experts. Over a median follow-up of 4·7 years (IQR 4·0-5·7), myocardial infarction occurred in 41 (2·5%) of 1611 patients from the SCOT-HEART trial. A deep learning-based total plaque volume of 238·5 mm3 or higher was associated with an increased risk of myocardial infarction (hazard ratio [HR] 5·36, 95% CI 1·70-16·86; p=0·0042) after adjustment for the presence of deep learning-based obstructive stenosis (HR 2·49, 1·07-5·50; p=0·0089) and the ASSIGN clinical risk score (HR 1·01, 0·99-1·04; p=0·35). INTERPRETATION: Our novel, externally validated deep learning system provides rapid measurements of plaque volume and stenosis severity from CCTA that agree closely with expert readers and intravascular ultrasound, and could have prognostic value for future myocardial infarction. FUNDING: National Heart, Lung, and Blood Institute and the Miriam & Sheldon G Adelson Medical Research Foundation.
CRIS-Team Scopus Importer:2022-04-08

Diagnostic accuracy of low and high tube voltage coronary CT angiography using an X-ray tube potential-tailored contrast medium injection protocol - Albrecht, Moritz H.; Nance, John W.; Schoepf, U. Joseph; Jacobs, Brian E.; Bayer, Richard R.; Litwin, Sheldon E.; Reynolds, Michael A.; Otani, Katharina; Mangold, Stefanie; Varga-Szemes, Akos; De Santis, Domenico; Eid, Marwen; et al. (European Radiology, 2018)
OBJECTIVES: To compare the diagnostic accuracy between low-kilovolt peak (kVp) (≤ 100) and high-kVp (> 100) third-generation dual-source coronary CT angiography (CCTA) using a kVp-tailored contrast media injection protocol. METHODS: One hundred twenty patients (mean age = 62.6 years, BMI = 29.0 kg/m2) who underwent catheter angiography and CCTA with automated kVp selection were separated into two cohorts (each n = 60, mean kVp = 84 and 117). Contrast media dose was tailored to the kVp level: 70 = 40 ml, 80 = 50 ml, 90 = 60 ml, 100 = 70 ml, 110 = 80 ml, and 120 = 90 ml. Contrast-to-noise ratio (CNR) was measured. Two observers evaluated image quality and the presence of significant coronary stenosis (> 50% luminal narrowing). RESULTS: Diagnostic accuracy (sensitivity/specificity) with ≤ 100 vs. > 100 kVp CCTA was comparable: per patient = 93.9/92.6% vs. 90.9/92.6%, per vessel = 91.5/97.8% vs. 94.0/96.8%, and per segment = 90.0/96.7% vs. 90.7/95.2% (all P > 0.64). CNR was similar (P > 0.18) in the low-kVp vs. high-kVp group (12.0 vs. 11.1), as ws subjective image quality (P = 0.38). Contrast media requirements were reduced by 38.1% in the low- vs. high-kVp cohort (53.6 vs. 86.6 ml, P < 0.001) and radiation dose by 59.6% (4.3 vs. 10.6 mSv, P < 0.001). CONCLUSIONS: Automated tube voltage selection with a tailored contrast media injection protocol allows CCTA to be performed at ≤ 100 kVp with substantial dose reductions and equivalent diagnostic accuracy for coronary stenosis detection compared to acquisitions at > 100 kVp. KEY POINTS: • Low-kVp coronary CT angiography (CCTA) enables reduced contrast and radiation dose. • Diagnostic accuracy is comparable between ≤ 100 and > 100 kVp CCTA. • Image quality is similar for low- and high-kVp CCTA. • Low-kVp image acquisition is facilitated by automated tube voltage selection. • Tailoring contrast injection protocols to the automatically selected kVp-level is feasible.
EVALuna2:35999

Differences of inflammatory cytokine profile in patients with vulnerable plaque: A coronary CTA study - Roesner, Caroline; Göller, Markus; Raaz-Schrauder, Dorette; Dey, Damini; Kilian, Tobias; Achenbach, Stephan; Marwan, Mohamed; Bittner, Daniel O. (Atherosclerosis, 2022)
Background and aims: Various pro-and anti-inflammatory biomarkers are involved in the process of atherosclerosis. We analyzed the association of different biomarkers with coronary plaque volume and vulnerable plaque subcomponents. Methods: In 301 patients undergoing coronary CT angiography (CTA), total coronary plaque volume (TPV) and subcomponents including non-calcified plaque volume (NCPV) and vulnerable plaque burden were quantified using semi-automated software. Serum was analyzed for various cytokines. Results: Out of 301 patients, 207 (69%) were male. The mean age was 59 +/- 10 years. Patients were divided using the median of TPV, NCPV and vulnerable plaque burden. In univariable analysis, patients with high TPV, high NCPV and high vulnerable plaque burden showed significant higher serum levels for IFN?, IL-1a,-2,-4,-10 and-17 and significant lower levels for IL-8 and MCP-1 (all p < 0.05). Multivariable analysis showed positive associations between high vulnerable plaque burden, IL-1a (OR 2.60, p = 0.001) and Eotaxin (OR 1.89, p = 0.020), and inverse association to MCP-1 (OR 0.33, p < 0.001), independent of age, gender and CVRF. In exploratory subanalyses, patients with presence of atherosclerosis (n = 247; 82%) showed significantly higher levels of IL-17 in all subgroups with high vulnerable plaque burden, irrespective of overall plaque volume (all p < 0.001). Conclusions: The cytokine profile significantly differs between patients with high and low coronary plaque volume. IL-1a and IL-17 seem to play a major proatherogenic role in vulnerable plaque formation, whereas MCP-1 paradoxically portends protective effects. Longitudinal studies with serial cytokine testing are needed to identify potential targets for therapeutic interventions.
CRIS-Team WoS Importer:2022-06-24
Keywords: Inflammatory biomarkers; Interleukin; Atherosclerosis; Coronary CT-angiography; Plaque volume; Vulnerable plaque

Direct head-to-head comparison of convolutional long short-term memory and transformer networks for artificial Intelligence-based quantification of atherosclerotic plaque and stenosis from coronary CT angiography - Manral, Nipun; Lin, Andrew; Park, Caroline; McElhinney, Priscilla; Killekar, Aditya; Matsumoto, Hidenari; Kwiecinski, Jacek; Pieszko, Konrad; Razipour, Aryabod; Grodecki, Kajetan; Doris, Mhairi; Kwan, Alan C.; et al. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 2023)
Background: Coronary computed tomography angiography (CCTA) enables non-invasive assessment of luminal stenosis and coronary atherosclerotic plaque. We aimed to directly compare the performance of 2 novel deep learning networks—convolutional long short-term memory and transformer network—for artificial intelligence-based quantification of plaque volume and stenosis severity from CCTA. Methods: This was an international multicenter study of patients undergoing CCTA at 11 sites. The deep learning (DL) convolutional neural networks were trained to segment coronary plaque in 921 patients (5,045 lesions). The training dataset was further split temporally into training (80%) and internal validation (20%) datasets. The primary DL architecture was a hierarchical convolutional long short- term memory (ConvLSTM) network. This was compared against a TransUNet network, which combines the abilities of Vision Transformer with U-Net, enabling the capture of in-depth localization information while modeling long-range dependencies. Following training and internal validation, the both DL networks were applied to an external validation cohort of 162 patients (1,468 lesions) from the SCOT-HEART trial. Results: In the external validation cohort, agreement between DL and expert reader measurements was stronger when using the ConvLSTM network than with TransUNet, for both per-lesion total plaque volume (ICC 0·953 vs 0.830) and percent diameter stenosis (ICC 0·882 vs 0.735; both p<0.001). The ConvLSTM network showed higher per-cross-section overlap with expert reader segmentations (as measured by the Dice coefficient) compared to TransUnet, for vessel wall (0.947 vs 0.946), lumen (0.93 vs 0.92), and calcified plaque (0.87 vs 0.86; p<0.0001 for all), with similar execution times. Conclusions: In a direct comparison with external validation, the ConvLSTM network yielded higher agreement with expert readers for quantification of total plaque volume and stenosis severity compared to TransUnet, with faster execution times.
CRIS-Team Scopus Importer:2023-06-02
Keywords: artificial intelligence; atherosclerosis; convolutional long short-term memory network; coronary computed tomography angiography; deep learning; transformers

Early-onset coronary atherosclerosis in patients with low levels of omega-3 fatty acids - Bittner, D. O.; Göller, Markus; Zopf, Yurdagül; Achenbach, Stephan; Marwan, Mohamed (European Journal of Clinical Nutrition, 2020)
Objectives: Coronary artery calcification (CAC) can reliably predict cardiovascular events. Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are thought to inhibit vascular calcification on a cellular level and in animal models, however, the correlation in humans is controversial. Methods: In symptomatic patients, CAC was quantified according to Agatstons’ method using non-contrast coronary CT. We assessed the association of EPA and DHA with early-onset coronary atherosclerosis, defined as presence of CAC above the 75th Agatston-Score (AS) percentile in sex adjusted age categories. Erythrocyte fatty acid composition was analyzed with a standardized methodology. The percentage of EPA and DHA in relation to all fatty acids present in the erythrocyte membrane is regarded the Omega-3 Index®. Results: Among 71 patients, 51 were below and 20 were above the 75th AS-percentile. No differences were seen in age, gender, cardiovascular risk factors, and relevant medication. In univariable analysis, significantly lower values for EPA (0.77%[0.63; 0.97] vs. 0.93%[0.72; 1.21]; p = 0.045), DHA (4.90%[4.12; 5.57] vs. 5.50%[4.58; 6.52]; p = 0.038) and the Omega-3 Index (5.73%[4.75; 6.35] vs. 6.22%[5.46; 7.71]; p = 0.034) were seen in patients above the 75th AS-percentile. All other fatty acids showed no significant differences. In multivariable analysis, the Omega-3 Index showed a significant inverse association with early onset of CAC (OR: 0.533 (95%CI: 0.303–0.938; p = 0.029)), independent of age, gender, statin use, and creatinine level (all p > 0.05). Conclusions: Low levels of EPA and DHA (Omega-3 Index) are associated with early-onset coronary atherosclerosis. This finding needs to be validated in larger cohorts and might help understand the beneficial cardiovascular effects of omega-3 fatty acids.
CRIS-Team Scopus Importer:2020-01-21

Ethnic differences in coronary anatomy, left ventricular mass and CT-derived fractional flow reserve - Ihdayhid, Abdul Rahman; Thakur, Udit; Yap, Grace; Göller, Markus; Nerlekar, Nitesh; Adams, Daniel; Isa, Mourushi; Joshi, Mitwa; Cameron, James; Seneviratne, Sujith; Dey, Damini; Achenbach, Stephan; et al. (Journal of Cardiovascular Computed Tomography, 2020)
Background: Studies have observed higher incidence of cardiovascular mortality in South Asians (SA), and lower prevalence in East Asians (EA), compared with Caucasians. These observations are not entirely explained by ethnic differences in cardiovascular risk factors and mechanistic factors such as variations in cardiac anatomy and physiology may play a role. This study compared ethnic differences in CT-assessed left ventricular (LV) mass, coronary anatomy and non-invasive fractional flow reserve (FFRCT). Methods: Three-hundred symptomatic patients (age 59 ± 7.9, male 51%) underwent clinically-mandated CT-coronary-angiography (CTA) were matched for age, gender, BMI and diabetes (100 each ethnicity). Assessment of coronary stenosis, luminal dimensions and vessel dominance was performed by independent observers. LV mass, coronary luminal volume and FFRCT were quantified by blinded core-laboratory. A sub-analysis was performed on patients (n = 187) with normal/minimal disease (0–25% stenosis). Results: Stenosis severity was comparable across ethnic groups. EA demonstrated less left-dominant circulation (2%) compared with SA (8.2%) and Caucasians (10.1%). SA compared with EA and Caucasians demonstrated smallest indexed LV mass, coronary luminal volumes and dimensions. EA compared with Caucasians had comparable indexed LV mass, coronary luminal dimensions and highest luminal volumes. The latter was driven by higher prevalence of right-dominance including larger and longer right posterior left ventricular artery. FFRCT in the left anterior descending artery (LAD) was lowest in SA (0.87) compared with EA (0.89; P = 0.009) and Caucasians (0.89; P < 0.001), with no difference in other vessels. All observed differences were consistent in patients with minimal disease. Conclusion: This single-centre study identified significant ethnic differences in CT-assessed LV mass, coronary anatomy and LAD FFRCT. These hypotheses generating results may provide a mechanistic explanation for ethnic differences in cardiovascular outcomes and require validation in larger cohorts.
CRIS-Team Scopus Importer:2020-10-16
Keywords: Computerized tomography (CT); Coronary artery dominance; Fractional flow reserve; Left ventricular mass; Race and ethnicity

Ethnic differences in coronary luminal volume, left ventricular mass and CT-derived fractional flow reserve - Ihdayhid, Abdul Rahman; Adams, Daniel; Göller, Markus; Dey, Damini; Thakur, Udit; Yap, Grace; Lim, Ren Yik; Isa, Mourushi; Michail, Michael; Cameron, James; Seneviratne, Sujith; Ko, Brian (2018)
EVALuna2:35967

Fully automated CT quantification of Epicardial adipose tissue by deep learning: A multicenter study - Commandeur, Frederic; Göller, Markus; Razipour, Aryabod; Cadet, Sebastien; Hell, Michaela; Kwiecinski, Jacek; Chen, Xi; Chang, Hyuk-Jae; Marwan, Mohamed; Achenbach, Stephan; Berman, Daniel S.; Slomka, Piotr J.; et al. (Radiology: Artificial Intelligence, 2019)
Purpose: To evaluate the performance of deep learning for robust and fully automated quantification of epicardial adipose tissue (EAT) from multicenter cardiac CT data. Materials and Methods: In this multicenter study, a convolutional neural network approach was trained to quantify EAT on non-contrast material-enhanced calcium-scoring CT scans from multiple cohorts, scanners, and protocols (n = 850). Deep learning performance was compared with the performance of three expert readers and with interobserver variability in a subset of 141 scans. The deep learning algorithm was incorporated into research software. Automated EAT progression was compared with expert measurements for 70 patients with baseline and follow-up scans. Results: Automated quantification was performed in a mean (6 standard deviation) time of 1.57 seconds 6 0.49, compared with 15 minutes for experts. Deep learning provided high agreement with expert manual quantification for all scans (R = 0.974; P, 001), with no significant bias (0.53 cm3; P =. 13). Manual EAT volumes measured by two experienced readers were highly correlated (R = 0.984; P, 001) but with a bias of 4.35 cm3 (P, 001). Deep learning quantifications were highly correlated with the measurements of both experts (R = 0.973 and R = 0.979; P, 001), with significant bias for reader 1 (5.11 cm3; P, 001) but not for reader 2 (0.88 cm3; P =. 26). EAT progression by deep learning correlated strongly with manual EAT progression (R = 0.905; P, 001) in 70 patients, with no significant bias (0.64 cm3; P =. 43), and was related to an increased noncalcified plaque burden quantified from coronary CT angiography (5.7% vs 1.8%; P =. 026). Conclusion: Deep learning allows rapid, robust, and fully automated quantification of EAT from calcium scoring CT. It performs as well as an expert reader and can be implemented for routine cardiovascular risk assessment.
CRIS-Team Scopus Importer:2023-03-08

Fully automated epicardial adipose tissue volume and density measured from non-contrast CT predict major adverse cardiovascular events in asymptomatic subjects - Mcelhinney, P.; Eisenberg, E.; Commandeur, F.; Chen, X.; Cadet, S.; Göller, Markus; Cantu, S.; Miller, R.; Slomka, P.; Wong, N.; Rozanski, A.; Achenbach, Stephan; et al. (EUROPEAN HEART JOURNAL, 2019)
CRIS-Team WoS Importer:2020-02-04

High level of EPA is associated with lower perivascular coronary attenuation as measured by coronary CTA - Bittner, D. O.; Göller, Markus; Zopf, Yurdagül; Achenbach, Stephan; Marwan, Mohamed (EUROPEAN HEART JOURNAL, 2019)
CRIS-Team WoS Importer:2020-02-04

High levels of eicosapentaenoic acid are associated with lower pericoronary adipose tissue attenuation as measured by coronary CTA - Bittner, Daniel O.; Göller, Markus; Dey, Damini; Zopf, Yurdagül; Achenbach, Stephan; Marwan, Mohamed (Atherosclerosis, 2020)
Background and aims: Higher pericoronary adipose tissue (PCAT) attenuation, a novel marker of inflammation in coronary CT angiography (CTA), has been shown to indicate increased cardiac mortality. Supplementation of eicosapentaenoic acid (EPA) has been shown to decrease cardiovascular death. Whether blood levels of n-3 fatty acids are associated with differences in PCAT attenuation is unknown. Methods: This is a cross-sectional analysis including 64 symptomatic patients who underwent coronary CTA. PCAT attenuation was measured in Hounsfield Units (HU) around the proximal 40 mm of the right coronary artery using semi-automated software. Erythrocyte membrane fatty acid composition was analyzed using gas chromatography. Individual fatty acids were expressed as a percentage of total identified fatty acids. Results: The patient cohort was divided into two groups using the median PCAT attenuation of −78.1 HU (each n = 32). No differences were seen in age, sex, BMI or traditional cardiovascular risk factors (CVRF) between groups (all p > 0.05). In univariable analysis, significantly higher values of EPA (1.00% [0.78; 1.26] vs. 0.78% [0.63; 0.99]; p = 0.02) were seen in patients with lower PCAT attenuation. All other fatty acids showed no differences (all p > 0.05). Moreover, a significant negative correlation was seen between PCAT attenuation and EPA (CC: 0.38; p = 0.002). In multivariable analysis, an inverse association of EPA with PCAT attenuation existed (ß = −0.31, p = 0.017), independent of age, gender, BMI and number of CVRF (all p > 0.1). Conclusions: High levels of EPA are associated with lower PCAT attenuation on coronary CTA. This may indicate a different composition of pericoronary adipose tissue, potentially caused by a lower degree of coronary inflammation.
CRIS-Team Scopus Importer:2020-11-06
Keywords: Coronary CT-Angiography; Eicosapentaenoic acid; Omega-3 fatty acids; Perivascular coronary inflammation

Imaging of the Pericoronary Adipose Tissue (PCAT) Using Cardiac Computed Tomography: Modern Clinical Implications - Göller, Markus; Achenbach, Stephan; Duncker, Hendrik; Dey, Damini; Marwan, Mohamed (Journal of Thoracic Imaging, 2021)
Modern coronary computed tomography angiography (CTA) is the gold standard to visualize the epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT). The EAT is a metabolic active fat depot enclosed by the visceral pericardium and surrounds the coronary arteries. In disease states with increased EAT volume and dysfunctional adipocytes, EAT secretes an increased amount of adipocytokines and the resulting imbalance of proinflammatory and anti-inflammatory mediators potentially causes atherogenic effects on the coronary vessel wall in a paracrine way ("outside-to-inside" signaling). These EAT-induced atherogenic effects are reported to increase the risk for the development of coronary artery disease, myocardial ischemia, high-risk plaque features, and future major adverse cardiac events. Coronary inflammation plays a key role in the development and progression of coronary artery disease; however, its noninvasive detection remains challenging. In future, this clinical dilemma might be changed by the CTA-derived analysis of the PCAT. On the basis of the concept of an "inside-to-outside" signaling between the inflamed coronary vessel wall and the surrounding PCAT recent evidence demonstrates that PCAT computed tomography attenuation especially around the right coronary artery derived from routine CTA is a promising imaging biomarker and "sensor" to noninvasively detect coronary inflammation. This review summarizes the biological and technical principles of CTA-derived PCAT analysis and highlights its clinical implications to improve modern cardiovascular prevention strategies.
CRIS-Team Scopus Importer:2021-05-21
Keywords: atherosclerosis; computed tomography attenuation; computed tomography imaging; inflammation; pericoronary adipose tissue

Independent predictors of major cardiovascular events as quantitatively assessed by coronary CT-angiography: a long-term follow-up analysis - Bittner, Daniel O.; Roesner, C.; Kilian, Tobias; Göller, Markus; Dey, D.; Raaz-Schrauder, Dorette; Achenbach, Stephan; Marwan, Mohamed (EUROPEAN HEART JOURNAL, 2021)
CRIS-Team WoS Importer:2021-12-10

Influence of gender on coronary atherosclerosis and inflammatory biomarker profile: a CT angiographic study - Bittner, Daniel O.; Rösner, Caroline; Göller, Markus; Raaz-Schrauder, Dorette; Dey, D.; Kilian, Tobias; Achenbach, Susanne; Marwan, Mohamed (EUROPEAN HEART JOURNAL, 2022)
CRIS-Team WoS Importer:2023-03-03

Influence of lesion location on the accuracy of CT derived FFR: head-to-head comparison with invasive FFR - Moshage, Maximilian; Smolka, S.; Achenbach, Stephan; Ammon, Fabian; Ferstl, Paul; Göller, Markus; Bittner, Daniel O.; Uehlein, Sabrina; Bal, Zeynep; Marwan, Mohamed (EUROPEAN HEART JOURNAL, 2020)
CRIS-Team WoS Importer:2021-02-12

Influence of reconstruction kernels on the accuracy of CT-derived fractional flow reserve - Ammon, Fabian; Moshage, Maximilian; Smolka, Silvia; Göller, Markus; Bittner, Daniel O.; Achenbach, Stephan; Marwan, Mohamed (European Radiology, 2021)
Objectives: We evaluated the influence of image reconstruction kernels on the diagnostic accuracy of CT-derived fractional flow reserve (FFRCT) compared to invasive FFR in patients with coronary artery disease. Methods: Sixty-nine patients, in whom coronary CT angiography was performed and who were further referred for invasive coronary angiography with FFR measurement via pressure wire, were retrospectively included. CT data sets were acquired using a third-generation dual-source CT system and rendered with medium smooth (Bv40) and sharp (Bv49) reconstruction kernels. FFRCT was calculated on-site using prototype software. Coronary stenoses with invasive FFR ≤ 0.80 were classified as significant. Agreement between FFRCT and invasive FFR was determined for both reconstruction kernels. Results: One hundred analyzed vessels in 69 patients were included. Twenty-five vessels were significantly stenosed according to invasive FFR. Using a sharp reconstruction kernel for FFRCT resulted in a significantly higher correlation with invasive FFR (r = 0.74, p < 0.01 vs. r = 0.58, p < 0.01; p = 0.04) and a higher AUC in ROC curve analysis to correctly identify/exclude significant stenosis (AUC = 0.92 vs. AUC = 0.82 for sharp vs. medium smooth kernel, respectively, p = 0.02). A FFRCT value of ≤ 0.8 using a sharp reconstruction kernel showed a sensitivity of 88% and a specificity of 92% for detecting ischemia-causing lesions, resulting in a diagnostic accuracy of 91%. The medium smooth reconstruction kernel performed worse (sensitivity 60%, specificity 89%, accuracy 82%). Conclusion: Compared to invasively measured FFR, FFRCT using a sharp image reconstruction kernel shows higher diagnostic accuracy for detecting lesions causing ischemia, potentially altering decision-making in a clinical setting. Key Points: • Image reconstruction parameters influence the diagnostic accuracy of simulated fractional flow reserve derived from coronary computed tomography angiography. • Using a sharp kernel image reconstruction algorithm delivers higher diagnostic accuracy compared to medium smooth kernel image reconstruction (gold standard invasive fractional flow reserve).
CRIS-Team Scopus Importer:2021-11-12
Keywords: Computed tomography angiography; Coronary artery disease; Fractional flow reserve; myocardial; Image processing; computer-assisted

Is PCAT CT Attenuation the ‘Game Changer’ in the Prediction of Death and Myocardial Infarction? - Göller, Markus; Marwan, Mohamed (Journal of the American College of Cardiology : Cardiovascular imaging, 2021)
CRIS-Team Scopus Importer:2021-07-30
Keywords: coronary CT angiography; CT attenuation; myocardial infarction; pericoronary adipose tissue

Leaflet thrombosis following transcatheter aortic valve implantation - Mekkhala, N.; Göller, Markus; Röther, Jens; Bittner, D.; Schuhbaeck, A.; Hell, M.; Muschiol, G.; Kolwelter, Julie; Feyrer, R.; Schlundt, Christian; Achenbach, Stephan; Arnold, M.; et al. (Journal of Cardiovascular Computed Tomography, 2018)
BACKGROUND: Transcatheter aortic valve implantation (TAVI) is increasingly being offered to high-risk patients with symptomatic aortic valve stenosis. Recent reports have suggested a high incidence of subclinical leaflet thrombosis following bioprosthestic aortic valve replacement. We report the frequency and clinical presentation of leaflet thrombosis identified by cardiac CT in patients referred for follow-up contrast enhanced CT angiography following TAVI. METHODS: 91 consecutive patients referred for follow-up contrast-enhanced CT angiography following TAVI were screened for inclusion in this analysis. Out of these, 13 patients were excluded. All CT examinations were performed using a 2nd or a 3rd generation dual-source system (Somatom Definition Flash/Force, Forchheim, Germany). In all patients, retrospectively ECG-gated spiral acquisition with tube modulation was performed to allow for assessment of leaflet motion. All prostheses were analyzed for presence of leaflet thrombosis defined as hypo-attenuated leaflet thickening with or without leaflet restriction. Post-procedural antithrombotic regimen as well as symptom status was documented in all patients. RESULTS: 78 consecutive patients (35 males, 81 ± 4 years) were analyzed. TAVI had been performed in all patients (76 transfemoral access, 2 transapical access) with either balloon-expandable prostheses (4 Sapien XT, 64 Sapien 3) or self-expandable prostheses (5 SJM Portico, 5 Symetis Acurate). Follow-up CT angiography was performed at a median of 4 months following index procedure (Interquartile range 1 month). Leaflet thrombosis was detected in 18 patients (23%, 14 Sapien 3, 1 Sapien XT, 2 SJM Portico, 1 Symetis Acurate). In patients with leaflet thickening on CT, only 11% were on either oral anticoagulation or new oral anticoagulants versus 50% for patients with no leaflet thickening (p 0.002). In patients with leaflet thrombosis, 3 leaflets were affected in 5 patients, 2 leaflets in 5 patients and in 8 patient only 1 leaflet was affected. Clinical symptoms (angina, dyspnea or both) were reported in 2/18 patients with leaflet thrombosis (11%) and in both patients a significant increase of the mean echocardiographic gradient over the prosthesis was documented. The peak and mean echocardiographic gradients obtained at the day of CT examination was significantly higher in symptomatic patients versus asymptomatic patients (peak 46 ± 7 vs. 23 ± 11 mmHg, mean 29 ± 7 vs. 12 ± 6 mmHg, p = 0.01 and 0.002, respectively). Follow-up CT was available for 4 patients with complete resolution of the hypo-attenuated leaflet thickening following treatment. CONCLUSION: Leaflet thrombosis following TAVI is a relatively frequent finding in patients referred for contrast enhanced CT angiography following TAVI. In the majority of patients it follows a subclinical course and is substantially more frequent in individuals who are not on oral anticoagulation. However, in patients with relevant increase in prosthetic gradients, symptomatic presentations are possible.
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Leaflet thrombosis following transcatheter aortic valve implantation: insights from a single center experience - Achenbach, Stephan; Göller, Markus; Loders, Sabrina; Schuhbaeck, A.; Hell, M.; Marwan, Mohamed; Arnold, Martin (2016)
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Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium and epicardial adipose tissue: a prospective study - Commandeur, F. C.; Slomka, P. J.; Göller, Markus; Chen, X.; Cadet, S.; Razipour, A.; Gransar, H.; Cantu, S.; Miller, R.; Rozanski, A.; Achenbach, Stephan; Tamarappoo, B.; et al. (EUROPEAN HEART JOURNAL, 2019)
CRIS-Team WoS Importer:2020-02-04

Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium, and epicardial adipose tissue: a prospective study - Commandeur, Frederic; Slomka, Piotr J.; Göller, Markus; Chen, Xi; Cadet, Sebastien; Razipour, Aryabod; McElhinney, Priscilla; Gransar, Heidi; Cantu, Stephanie; Miller, Robert J.H.; Rozanski, Alan; Achenbach, Stephan; et al. (Cardiovascular Research, 2020)
AIMS: Our aim was to evaluate the performance of machine learning (ML), integrating clinical parameters with coronary artery calcium (CAC), and automated epicardial adipose tissue (EAT) quantification, for the prediction of long-term risk of myocardial infarction (MI) and cardiac death in asymptomatic subjects. METHODS AND RESULTS: Our study included 1912 asymptomatic subjects [1117 (58.4%) male, age: 55.8 ± 9.1 years] from the prospective EISNER trial with long-term follow-up after CAC scoring. EAT volume and density were quantified using a fully automated deep learning method. ML extreme gradient boosting was trained using clinical co-variates, plasma lipid panel measurements, risk factors, CAC, aortic calcium, and automated EAT measures, and validated using repeated 10-fold cross validation. During mean follow-up of 14.5 ± 2 years, 76 events of MI and/or cardiac death occurred. ML obtained a significantly higher AUC than atherosclerotic cardiovascular disease (ASCVD) risk and CAC score for predicting events (ML: 0.82; ASCVD: 0.77; CAC: 0.77, P < 0.05 for all). Subjects with a higher ML score (by Youden's index) had high hazard of suffering events (HR: 10.38, P < 0.001); the relationships persisted in multivariable analysis including ASCVD-risk and CAC measures (HR: 2.94, P = 0.005). Age, ASCVD-risk, and CAC were prognostically important for both genders. Systolic blood pressure was more important than cholesterol in women, and the opposite in men. CONCLUSIONS: In this prospective study, machine learning used to integrate clinical and quantitative imaging-based variables significantly improves prediction of MI and cardiac death compared with standard clinical risk assessment. Following further validation, such a personalized paradigm could potentially be used to improve cardiovascular risk assessment.
CRIS-Team Scopus Importer:2020-12-11
Keywords: Coronary calcium scoring; Epicardial adipose tissue; Machine learning; Myocardial infarction and cardiac death

Patient-Specific Myocardial Infarction Risk Thresholds from AI-Enabled Coronary Plaque Analysis - Miller, Robert J.H.; Manral, Nipun; Lin, Andrew; Shanbhag, Aakash; Park, Caroline; Kwiecinski, Jacek; Killekar, Aditya; McElhinney, Priscilla; Matsumoto, Hidenari; Razipour, Aryabod; Grodecki, Kajetan; Kwan, Alan C.; et al. (Circulation: Cardiovascular Imaging, 2024)
BACKGROUND: Plaque quantification from coronary computed tomography angiography has emerged as a valuable predictor of cardiovascular risk. Deep learning can provide automated quantification of coronary plaque from computed tomography angiography. We determined per-patient age- and sex-specific distributions of deep learning-based plaque measurements and further evaluated their risk prediction for myocardial infarction in external samples. METHODS: In this international, multicenter study of 2803 patients, a previously validated deep learning system was used to quantify coronary plaque from computed tomography angiography. Age- and sex-specific distributions of coronary plaque volume were determined from 956 patients undergoing computed tomography angiography for stable coronary artery disease from 5 cohorts. Multicenter external samples were used to evaluate associations between coronary plaque percentiles and myocardial infarction. RESULTS: Quantitative deep learning plaque volumes increased with age and were higher in male patients. In the combined external sample (n=1847), patients in the ≥75th percentile of total plaque volume (unadjusted hazard ratio, 2.65 [95% CI, 1.47-4.78]; P=0.001) were at increased risk of myocardial infarction compared with patients below the 50th percentile. Similar relationships were seen for most plaque volumes and persisted in multivariable analyses adjusting for clinical characteristics, coronary artery calcium, stenosis, and plaque volume, with adjusted hazard ratios ranging from 2.38 to 2.50 for patients in the ≥75th percentile of total plaque volume. CONCLUSIONS: Per-patient age- and sex-specific distributions for deep learning-based coronary plaque volumes are strongly predictive of myocardial infarction, with the highest risk seen in patients with coronary plaque volumes in the ≥75th percentile. 2024 American Heart Association, Inc.
CRIS-Team Scopus Importer:2024-10-25
Keywords: cardiac imaging techniques; coronary artery disease; deep learning; myocardial infarction; plaque; atherosclerotic

Pericoronary adipose tissue and quantitative global non-calcified plaque characteristics from CT angiography do not differ in matched South Asian, East Asian and European-origin Caucasian patients with stable chest pain - Göller, Markus; Rahman Ihdayhid, Abdul; Cadet, Sebastien; Lin, Andrew; Adams, Daniel; Thakur, Udit; Yap, Grace; Achenbach, Stephan; Dey, Damini; Ko, Brian; Marwan, Mohamed (European Journal of Radiology, 2020)
Purpose: South Asian (SA) have been observed to have higher cardiovascular mortality rates compared to East Asians (EA) and Caucasians. Pericoronary adipose tissue (PCAT) attenuation around the right coronary artery (RCA) from coronary CT angiography (CTA) has been associated with coronary inflammation and cardiac death. We aimed to investigate i) the relationship between plaque characteristics and PCAT attenuation and ii) to assess gender and ethnic differences in PCAT attenuation using a matched cohort of SA, EA and Caucasians. Method: Three-hundred symptomatic patients who underwent CTA were matched for age, gender, BMI and diabetes (100 in each ethnic group). Semi-automated software was used to quantify the total volumes and burden of non-calcified plaque (NCP), low-density non-calcified plaque (LD-NCP) and calcified plaque (CP) in blinded core-lab analysis. PCAT CT attenuation was measured around the RCA (10–50 mm from RCA ostium), the most standardized model for PCAT analysis. Results: The total volumes and burden of NCP, LD-NCP and CP were comparable in the ethnic groups (each p > 0.05). PCAT attenuation was higher in patients with coronary plaque. PCAT attenuation correlated with the total volumes and burden of NCP, LD-NCP and CP (r>0.17; p < 0.003). Within the RCA this correlation persisted only for NCP features (r>0.39;p < 0.001). Males showed higher PCAT attenuation (p < 0.001). PCAT attenuation was similar between Caucasian, EA and SA (p = 0.32). Conclusions: PCAT CT attenuation correlated most with its surrounded NCP features further highlighting its role as surrogate measure of coronary inflammation. As coronary plaque burden and RCA PCAT attenuation did not differ between ethnic groups, causes of increased cardiac mortality in South Asians needs further investigations.
CRIS-Team Scopus Importer:2020-02-28
Keywords: Atherosclerosis; Computerized tomography (CT); Pericoronary adipose tissue; Race and ethnicity

Pericoronary adipose tissue CT attenuation and its association with serum levels of atherosclerosis-relevant inflammatory mediators, coronary calcification and major adverse cardiac events - Göller, Markus; Achenbach, Stephan; Herrmann, Nicolai; Bittner, Daniel O.; Kilian, Tobias; Dey, Damini; Raaz-Schrauder, Dorette; Marwan, Mohamed (Journal of Cardiovascular Computed Tomography, 2021)
Background: Increased attenuation of pericoronary adipose tissue (PCAT) around the right coronary artery (RCA) derived from coronary CTA might detect coronary inflammation. We investigated a potential association between RCA PCAT attenuation and serum levels of atherosclerosis-relevant cytokines and MACE (coronary revascularization, myocardial infarction and/or cardiac death). Methods: Blood samples of 293 clinically stable individuals (59.0 ​± ​9.8 years, 69% males) were analyzed for atherosclerosis-relevant cytokines including interleukin (IL)-2, IL- 4, IL-6, IL-7, IL-8, IL-10, IL-13, IL-15, IL-17, TNF-a, IP-10, CRP, MCP-1, MIP-1a, Eotaxin and GM-CSF. Subjects also underwent coronary calcium scoring (CCS) followed by CTA. PCAT CT attenuation was measured around the RCA using semi-automated software. Increased RCA PCAT attenuation was defined as PCAT attenuation above the 75th percentile (>−73.5 HU). To assess MACE, 232 individuals were followed for a mean duration of 9.6 ​± ​2.1 years. Results: In patients with increased RCA PCAT attenuation the serum levels of MCP-1 were increased (p ​< ​0.01), whereas levels of anti-inflammatory mediators IL-4 and -13 were significantly reduced (each p ​< ​0.05). Adipocytokine MCP-1 (r ​= ​0.23, p ​< ​0.01) and pro-inflammatory mediator IL-7 (r ​= ​0.12, p ​= ​0.04) showed a mild positive correlation with RCA PCAT attenuation, whereas anti-inflammatory mediators Il-4, -10 and -13 correlated inversely (each r < −0.12, each p ​< ​0.05). 40/232 patients experienced MACE during follow-up. In multivariable Cox regression analysis increased RCA PCAT attenuation was shown to be an independent predictor of MACE (HR 2.01, p ​= ​0.044). Conclusions: Increased RCA PCAT CT attenuation shows a weak association with serum levels of selected atherosclerosis-relevant inflammatory biomarkers. Increased RCA PCAT attenuation is an independent predictor of MACE and may potentially guide future prevention strategies in stable patients.
CRIS-Team Scopus Importer:2021-04-30
Keywords: Atherosclerosis-relevant inflammatory biomarkers; Coronary calcium score; CT attenuation; Inflammation; MACE; Pericoronary adipose tissue

Quantification of epicardial adipose tissue by cardiac CT: Influence of acquisition parameters and contrast enhancement - Koenig, Susanna; Schreiber, Kirsten; Ammon, Fabian; Göller, Markus; Bittner, Daniel; Achenbach, Stephan; Hell, Michaela; Marwan, Mohamed (European Journal of Radiology, 2019)
Purpose: While computed tomography (CT) is frequently used to quantify epicardial adipose tissue (EAT), the effect of different acquisition parameters on EAT volume has not been systematically reported. We assessed the influence of low-voltage acquisition and contrast enhancement on EAT quantification. Method: Two independent cohorts (100 and 127 patients) referred for routine coronary CT were included. One cohort received a low-voltage and a standard voltage non-contrast acquisition (120 and 100 kV), the other cohort underwent non-contrast and contrast-enhanced CT. EAT volume was quantified using a semi-automated analysis software. Whereas the lower EAT threshold was consistently set at -190 Hounsfield Units (HU), different upper thresholds for EAT were analyzed. Bland-Altman analysis was used to analyze the agreement of EAT volume between scans with different acquisition parameters. We referred to a non-enhanced 120 kV acquisition with an upper threshold of -30 HU. Results: Mean EAT volume was 159 ± 76 ml as measured in 120 kV non-contrast data sets with an upper threshold of -30 HU. For 100 kV data sets, an upper threshold of -40 HU showed the best correlation (r = 0.961, p < 0.05). Significant overestimation was found for upper thresholds of -20 and -30 HU and significant underestimation for -50 HU. In non-contrast vs. contrast-enhanced acquisitions, there was a significant underestimation of EAT volume for contrast-enhanced scans (mean difference 31 ml, 95% limits of agreement 27 to −89 ml). Conclusions: CT-based EAT volume quantification in low-voltage and contrast-enhanced images is feasible. However, adjustment of the upper threshold for detection of fat is mandatory.
CRIS-Team Scopus Importer:2019-11-12
Keywords: Cardiac computed tomography; Contrast-enhanced imaging; Epicardial adipose tissue; Low-dose acquisition

Radiomics-Based Precision Phenotyping Identifies Unstable Coronary Plaques From Computed Tomography Angiography - Lin, Andrew; Kolossváry, Márton; Cadet, Sebastien; McElhinney, Priscilla; Göller, Markus; Han, Donghee; Yuvaraj, Jeremy; Nerlekar, Nitesh; Slomka, Piotr J.; Marwan, Mohamed; Nicholls, Stephen J.; Achenbach, Stephan; et al. (Journal of the American College of Cardiology : Cardiovascular imaging, 2022)
Objectives: The aim of this study was to precisely phenotype culprit and nonculprit lesions in myocardial infarction (MI) and lesions in stable coronary artery disease (CAD) using coronary computed tomography angiography (CTA)-based radiomic analysis. Background: It remains debated whether any single coronary atherosclerotic plaque within the vulnerable patient exhibits unique morphology conferring an increased risk of clinical events. Methods: A total of 60 patients with acute MI prospectively underwent coronary CTA before invasive angiography and were matched to 60 patients with stable CAD. For all coronary lesions, high-risk plaque (HRP) characteristics were qualitatively assessed, followed by semiautomated plaque quantification and extraction of 1,103 radiomic features. Machine learning models were built to examine the additive value of radiomic features for discriminating culprit lesions over and above HRP and plaque volumes. Results: Culprit lesions had higher mean volumes of noncalcified plaque (NCP) and low-density noncalcified plaque (LDNCP) compared with the highest-grade stenosis nonculprits and highest-grade stenosis stable CAD lesions (NCP: 138.1 mm3 vs 110.7 mm3 vs 102.7 mm3; LDNCP: 14.2 mm3 vs 9.8 mm3 vs 8.4 mm3; both Ptrend < 0.01). In multivariable linear regression adjusted for NCP and LDNCP volumes, 14.9% (164 of 1,103) of radiomic features were associated with culprits and 9.7% (107 of 1,103) were associated with the highest-grade stenosis nonculprits (critical P < 0.0007) when compared with highest-grade stenosis stable CAD lesions as reference. Hierarchical clustering of significant radiomic features identified 9 unique data clusters (latent phenotypes): 5 contained radiomic features specific to culprits, 1 contained features specific to highest-grade stenosis nonculprits, and 3 contained features associated with either lesion type. Radiomic features provided incremental value for discriminating culprit lesions when added to a machine learning model containing HRP and plaque volumes (area under the receiver-operating characteristic curve 0.86 vs 0.76; P = 0.004). Conclusions: Culprit lesions and highest-grade stenosis nonculprit lesions in MI have distinct radiomic signatures compared with lesions in stable CAD. Within the vulnerable patient may exist individual vulnerable plaques identifiable by coronary CTA-based precision phenotyping.
CRIS-Team Scopus Importer:2022-05-06
Keywords: coronary computed tomography angiography; coronary plaque; machine learning; myocardial infarction; radiomics

Resolution of leaflet thrombosis under anticoagulant therapy in patients after transcatheter aortic valve implantation: influence of prosthesis type and size - Ferstl, Paul; Arnold, Martin; Göller, Markus; Ammon, Fabian; Smolka, S.; Moshage, Maximilian; Uehlein, Sabrina; Achenbach, Stephan; Bittner, Daniel O.; Marwan, Mohamed (EUROPEAN HEART JOURNAL, 2020)
CRIS-Team WoS Importer:2021-02-12

Software-based automated CT analysis for planning TAVI-Procedures: Systematic validation against expert and novice human interpretation - Weber, J.; Göller, Markus; Smolka, S.; Bittner, D. O.; Gaede, L.; Tröbs, Monique; Achenbach, Stephan; Marwan, Mohamed; Arnold, Martin (EUROPEAN HEART JOURNAL, 2019)
CRIS-Team WoS Importer:2020-02-04

The association of pericoronary adipose tissue attenuation with major adverse cardiac events (MACE) and atherosclerosis-relevant inflammatory mediators - Göller, Markus; Achenbach, Stephan; Herrmann, N.; Bittner, Daniel O.; Ammon, Fabian; Kilian, Tobias; Smolka, S.; Uehlein, Sabrina; Moshage, Maximilian; Raaz-Schrauder, Dorette; Dey, D.; Marwan, Mohamed (EUROPEAN HEART JOURNAL, 2020)
CRIS-Team WoS Importer:2021-02-12

The Munich-Transarterial Chemoembolisation Score Holds Superior Prognostic Capacities Compared to TACE-Tailored Modifications of 9 Established Staging Systems for Hepatocellular Carcinoma - Op Den Winkel, Mark; Nagel, Dorothea; Op Den Winkel, Philip; Paprottka, Philipp M.; Schmidt, Laura; Bourhis, Helene; Trojan, Joerg; Göller, Markus; Reiter, Florian P.; Stecher, Stephanie-Susanne; De Toni, Enrico N.; Gerbes, Alexander L.; et al. (Digestion, 2019)
Background/Aims: The recently proposed Munich-transarterial chemoembolisation-score (M-TACE) was tailored to suit hepatocellular Carcinoma (HCC) patients evaluated for TACE. M-TACE outperformed the established HCC-staging-systems and successfully passed external validation. Modifications of staging-systems through the rearrangement of stages or by adding prognostic factors are methods of improving prognostic power. M-TACEs performance compared to scores modified this way should be tested. Methods: Seven well-known HCC staging-systems (including Cancer of the Liver Italian Program-score [CLIP] and Barcelona Clinic liver cancer [BCLC]) and 2 TACE-specific scores (Selection for Transarterial Chemoembolisation Treatment [STATE] and Hepatoma Arterial embolisation Prognostic [HAP]) were rearranged in a cohort of 186 TACE-patients through score-point-analysis and subsequent linking of non-significant adjacent score-points. Additionally, a new score was constructed by combining the top established staging-system in TACE patients (CLIP-TACE) and the prognostic parameter with the highest hazard ratio for death in the TACE-cohort [C-reactive protein (CRP)]. Additionally, the TACE-tailored-scores were applied to an external TACE-cohort (n = 71). Results: Rearrangement resulted in optimal stratification and monotonicity. CLIP-TACE demonstrated the best prognostic capability of all rearranged scores (c-index 0.668, AIC 1294) and the addition of CRP yielded further prognostic improvement (c-index 0.680, AIC 1289). However, superiority over M-TACE could not be achieved by any of the new scores in the internal and external cohort. Conclusion: M-TACE outperforms TACE-tailored modifications of all relevant HCC-staging-systems. Prospective validation of M-TACE to promote its role as the preferred staging-system for TACE-patients is therefore justified.
CRIS-Team WoS Importer:2019-07-19

Transarterial chemoembolization for hepatocellular carcinoma: development and external validation of the Munich-TACE score - Op Den Winkel, Mark; Nagel, Dorothea; Op Den Winkel, Philip; Trojan, Joerg; Paprottka, Philipp M.; Steib, Christian J.; Schmidt, Laura; Göller, Markus; Stieber, Petra; Goehring, Peter; Herbst, Andreas; Rentsch, Markus; et al. (European Journal of Gastroenterology & Hepatology, 2018)
BACKGROUND: Allocation of patients with hepatocellular carcinoma (HCC) to the adequate therapy is determined by both tumor burden and liver function. The Barcelona Clinic Liver Cancer (BCLC) staging system and therapeutic algorithm recommends transarterial chemoembolization (TACE) based on the best evidence available to patients with intermediate-stage HCC (BCLC-B). However, many centers also treat subgroups of patients outside these recommendations and with more advanced disease by TACE. The purpose of this study was to identify prognostic factors in a TACE cohort, including BCLC-B patients, as well as patients treated outside of BCLC-B, to test the prognostic capabilities of published staging systems and to optimize prognostication for TACE patients. PATIENTS AND METHODS: A cohort of 186 first-line TACE patients was analyzed. Independent prognostic factors were identified and used to construct the Munich-TACE score (M-TACE). M-TACE was tested against established staging systems (including BCLC and two recently published TACE-specific scores) and a ranking using concordance index and Akaike Information Criterion was performed. Finally, an external validation in an independent TACE cohort (n=71) was conducted. RESULTS: Bilirubin, Quick/international normalized ratio, C-reactive protein, creatinine, α-feto protein, and tumor extension were identified as independent prognostic factors and used to construct M-TACE. M-TACE identifies three distinct subgroups (P<0.0001) with median survival times of 35.2, 16.9, and 8.6 months, respectively. Compared with established staging systems, M-TACE showed the best prognostic capabilities in both cohorts of patients (cohort 1: c-index, 0.71; Akaike Information Criterion: 1276; cohort 2: c-index, 0.754). CONCLUSION: We identified independent risk factors for patients treated with TACE. The newly constructed M-TACE score is superior to established staging systems and might prove helpful to identify patients who are most suitable for TACE.
EVALuna2:36012