Coronary Artery Disease Reporting And Data System Research Articles

Abstract 4119869: Automatic assignment of CAD-RADS categories in coronary CTA reports using large language model

Background: The effectiveness of different large language models (LLM) in extracting important information from CT angiography (CTA) radiology reports is unknown. Purpose: The Coronary Artery Disease-Reporting and Data System (CAD-RADS) is a standardized reporting system for CTA that categorizes the severity of coronary artery disease to aid in clinical decision-making. To evaluate the agreement between human readers and LLMs in assigning CAD-RADS categories based on CTA reports. Materials and Methods: This retrospective study analyzed reports from patients who underwent coronary CTA for screening or diagnosis at Johns Hopkins Hospital. Reports with CAD-RADS 0–5 findings were collected from Jan. 2020 to Oct. 2023. Initially, 6,212 CTA reports were retrieved. After excluding non-organized reports and retaining only those with CAD-RADS scores, 590 reports remained. Board-certified radiologists and three large language models (GPT-3.5, GPT-4, and Llama3) assigned CAD-RADS categories based on the original radiologists' findings. Two radiologists reviewed the CAD scores, with only one discrepancy in the 590 reports, indicating high inter-agreement. Agreement between human readers and LLMs for CAD-RADS categories was assessed using the Gwet agreement coefficient (AC1 value). Frequencies of changes in CAD-RADS category assignments that could potentially affect clinical management (CAD-RADS 0-2 vs. 3-5) were calculated and compared. Typically, CAD-RADS 0-2 indicates mild disease leading to conservative management, while CAD-RADS 3-5 denotes further testing or disease requiring aggressive intervention to prevent adverse cardiovascular events. Results: Among 590 reports, agreement between original and reviewing radiologists was almost perfect (AC1 = 0.985). Good agreement was also found between original radiologists and Llama3, GPT-3.5, and GPT-4 (AC1 = 0.861, 0.907, 0.941, respectively). Differences in CAD-RADS category upgrades/downgrades potentially affecting clinical management were observed: 0 of 590 (0%) for human readers, 56 of 590 (9.4%) for Llama3, 33 of 590 (5.5%) for GPT-3.5, and 23 of 590 (3.9%) for GPT-4 upgrading CAD-RADs; 8 of 590 (1.4%) for human readers, 19 of 590 (3.2%) for Llama3, 22 of 590 (3.7%) for GPT-3.5, and 12 of 590 (2.0%) for GPT-4 downgrading RAD-CADs. Conclusion: LLMs showed good agreement with human readers in assigning CAD-RADS categories on CTA reports. However, they were more likely to upgrade CAD-RADS category when compared to radiologists.

Plaque characterization and individualized risk assessment

Risk assessment and accurate plaque characterization are key to individual prognosis in coronary artery disease (CAD). The standard of care is cardiac computed tomography (CT), including calcium scoring and coronary CT angiography (CCTA). Diagnosis is based on the CAD-RADS (Coronary Artery Disease-Reporting and Data System) classification. New developments include CT-based fractional flow reserve (CT-FFR) and plaque quantification ("virtual histology"). Acalcium score of0 indicates an event risk of less than 1% over 10years [7, 17]. CAD-RADS classes1 to5 allow risk assessment compared to patients without coronary plaques [2]. CT-FFR has high accuracy (area under the curve [AUC] 0.90; 95% confidence interval 0.87-0.94) in assessing the hemodynamic significance of stenoses compared with invasive coronary angiography [25]. Plaque quantification has shown that anecrotic core greater than 4% is associated with an almost fivefold increase in 5‑year event risk [29]. The presence of obstructive CAD (stenosis > 50%) is astrong prognostic factor. The evaluation of the hemodynamic relevance of 40-90% stenoses by CT-FFR or other functional tests is already guideline-compliant in the USA, but not yet in Germany. Quantitative approaches to measure plaque volume and composition are gaining importance in research and are expected to become relevant in clinical practice. The CAD-RADS 2.0 classification, which also provides therapy recommendations, should be used to assess the extent of CAD.

Correlation of Sarcopenia with Coronary Artery Disease Severity and Pericoronary Adipose Tissue Attenuation: A Coronary CT Study

Objective: To investigate the association between sarcopenia, as appraised with CT-derived muscle metrics, and cardiovascular status, as assessed via coronary CT angiography (CCTA) using the Coronary Artery Disease-Reporting and Data System (CAD-RADS) and with pericoronary adipose tissue (pCAT) metrics. Methods: A retrospective observational study conducted on patients who underwent CCTA. The cross-sectional area (CSA) and attenuation values of the paravertebral muscles at the T8 level and the pectoralis major muscles at the T6 level were measured. The patient height was employed for the normalization of the skeletal muscle CSA. The pCAT attenuation around the coronary arteries was assessed, and the CAD severity was graded using the CAD-RADS reporting system. Regression analyses were performed to assess the impact of demographics, clinical factors, and CT variables on the CAD-RADS and pCAT. Results: A total of 220 patients were included (132 males, median age 65 years). Regression analyses showed the associations of CAD with age and sex (p < 0.001). Familiarity with CAD was related to the left anterior descending artery pCAT (p = 0.002) and circumflex artery pCAT (p = 0.018), whereas age was related to the left anterior descending artery pCAT (p = 0.032). Weak positive correlations were found between the lower muscle density and lower pCAT attenuation (ρ = 0.144–0.240, p < 0.039). Conclusions: This study demonstrated weak associations between the sarcopenia indicators and the cardiovascular risk, as assessed by the CAD severity and pCAT inflammation. However, these correlations were not strong predictors of CAD severity, as age and traditional cardiovascular risk factors overshadowed the impact of sarcopenia in the cardiovascular risk assessment.

Prevalence of high-risk plaque features on cardiac computed tomography scans in patients with a coronary artery calcium score of zero

Abstract Introduction Coronary artery calcium (CAC) score of zero (so-called "power of zero") is associated with a very low rate of major adverse cardiac events (MACE), especially during short and midterm follow-up. However, a CAC score of zero does not definitively exclude the presence of atherosclerotic plaques or obstructive coronary artery disease (CAD). The composition of atherosclerotic plaques and the frequency of high-risk plaque features in this population are not well described. Purpose We sought to characterize the composition of atherosclerotic plaques and assess the frequency of high-risk plaque features on contrast-enhanced computed tomography (CT) images in patients with a zero CAC score. Methods The study enrolled patients with stable chest pain suspected of CAD referred for coronary CT imaging and having a CAC score of zero. Coronary CT angiography images were assessed by an expert reader to identify atherosclerotic plaques and high-risk plaque features in all coronary arteries with a diameter ≥1.5mm. The coronary artery lumen and plaques were manually segmented, and the degree of stenosis was evaluated following the Coronary Artery Disease Reporting and Data System (CAD-RADS) criteria. The presence of four high-risk plaque features was identified: positive remodeling, spotty calcification, low-attenuation plaque, and napkin ring sign. Total plaque volume, percent atheroma volume, and plaque composition were quantified using dedicated software (Figure 1). Results A total of 145 patients (mean age 54.2±12.1 years, 35.9% males) were included in the analysis. At least one coronary artery plaque was identified in 30 individuals (20.7%). 22 (15.2%), 7 (4.8%), and 1 (0.7%) patients were categorized into CAD-RADS 1, CAD-RADS 2, and CAD-RADS 3 categories, respectively. Among 30 patients with any coronary artery plaque, at least one high-risk feature was found in 10 individuals (33.3%), while 3 individuals (10.0%) had two features. Positive remodeling was found in 7 (23.3%), spotty calcification in 3 (10.0%), low-attenuation plaque in 3 (10.0%), and napkin ring sign in 0 patients, respectively (Figure 1). The mean total plaque volume was 48.2±54.3mm³, and the mean percent atheroma volume was 1.2±0.8%. Total plaque volume comprised low-attenuation (0.4%), fibro-fatty (58.9%), fibrous (39.4%), and calcified (1.3%) plaque volumes. Notably, in 3 (10.0%) individuals, the presence of calcified plaque was identified, which on non-contrast CT images did not meet the Agatston criteria for the CAC score. Conclusions Our study demonstrates a significant prevalence of atherosclerotic plaques and high-risk plaque features in patients with a CAC score of zero. Specifically, one in every five study participants had identifiable atherosclerotic plaque, with one in every three of those exhibiting one or more high-risk plaque features. The prognostic significance of these findings warrants further evaluation in studies with longitudinal follow-up.

Lack of incremental prognostic value of triglyceride glucose index beyond coronary computed tomography angiography features for major events

This study was aim to determine the prognostic value of triglyceride-glucose (TyG) index and coronary computed tomography angiography (CTA) features for major adverse cardiovascular events (MACE). In addition, we investigate the incremental prognostic value of TyG index beyond coronary CTA features in patients with suspected or known coronary artery disease (CAD). The present study ultimately includes 3528 patients who met the enrollment criteria. The TyG index was calculated based on measured levels of triglycerides and fasting blood glucose. Primary combined endpoint consisted of MACE, which defined as myocardial infraction (MI), all-cause mortality and stroke. Three multivariate Cox proportional hazard regression models were performed to assess the association between TyG index and MACE. C-statistic was performed to assess the discriminatory value of models. 212 (6.0%) patients developed MACE during a median follow-up of 50.4 months (IQR, 39.4–55.1). TyG index remained to be a significantly and independent risk factors for predicting MACE after adjusting by different models (clinical variables alone or plus coronary CTA features) in multivariable analysis. Both the addition of TyG index to clinical model plus Coronary Artery Disease Reporting and Data System (CAD-RADS) and to clinical model plus CAD-RADS 2.0 slightly but not significantly increased the C-statistic index (0.725 vs. 0.721, p = 0.223; 0.733 vs. 0.731, p = 0.505). TyG index was associated with an increased risk of MACE. However, no incremental prognostic benefit of TyG index over CAD-RADS or CAD-RADS 2.0 was detected for MACE in patients with suspected or known CAD.

Moving towards auniform diagnosis of coronary artery disease on coronary CTA : Coronary Artery Disease-Reporting and Data System2.0.

The Coronary Artery Disease-Reporting and Data System (CAD-RADS) is astandardised reporting method which was created in order to improve communication with referring physicians as well as for management considerations. The CAD-RADS score denotes the absence or presence of stenosis, while plaque burden and potential modifiers provide insight into plaque extent and characteristics. The modifier ischaemia enables the incorporation of fractional flow reserve CT and CT perfusion, while the modifier exception is used to denote potential coronary abnormalities. Higher CAD-RADS categories demonstrate incremental prognostic value, with further improvement when taking plaque burden into account. CAD-RADS improves communication with the referring clinician as well as guiding therapeutic management and as such is relevant to uniform patient care in the Netherlands.

Intraindividual Comparison of Ultrahigh-Spatial-Resolution Photon-Counting Detector CT and Energy-Integrating Detector CT for Coronary Stenosis Measurement.

A recent simulation study proposed that stenosis measurements on coronary computed tomography (CT) angiography are influenced by the improved spatial resolution of photon-counting detector (PCD)-CT. The aim of the current study was to evaluate the impact of ultrahigh-spatial-resolution (UHR) on coronary stenosis measurements and Coronary Artery Disease Reporting and Data System (CAD-RADS) reclassification rates in patients undergoing coronary CT angiography on both PCD-CT and energy-integrating detector (EID)-CT and to compare measurements against quantitative coronary angiography. Patients with coronary calcification on EID-CT (collimation, 192×0.6 mm) were prospectively enrolled for a research coronary CT angiography with UHR PCD-CT (collimation, 120×0.2 mm) within 30 days (between April 1, 2023 and January 31, 2024). PCD-CT was acquired with the same or lower CT dose index and equivalent contrast media volume as EID-CT. Percentage diameter stenosis (PDS) for calcified, partially calcified, and noncalcified lesions were compared between scanners. Patient-level reclassification rates for CAD-RADS were evaluated. The accuracy of PDS measurements was validated against quantitative coronary angiography in patients who underwent invasive coronary angiography. In total, PDS of 278 plaques were quantified in 49 patients (calcified, 202; partially calcified, 51; noncalcified, 25). PCD-CT-based PDS values were lower than EID-CT measurements for calcified (45.1±20.7 versus 54.6±19.2%; P<0.001) and partially calcified plaques (44.3±19.6 versus 54.9±20.0%; P<0.001), without significant differences for noncalcified lesions (39.1±15.2 versus 39.0±16.0%; P=0.98). The reduction in stenosis degrees led to a 49.0% (24/49) reclassification rate to a lower CAD-RADS with PCD-CT. In a subset of 12 patients with 56 lesions, UHR-based PDS values showed higher agreement with quantitative coronary angiography (mean difference, 7.3%; limits of agreement, -10.7%/25.2%) than EID-CT measurements (mean difference, 17.4%; limits of agreement, -6.9%/41.7%). Compared with conventional EID-CT, UHR PCD-CT results in lower PDS values and more accurate stenosis measurements in coronary plaques with calcified components and leads to a substantial Coronary Artery Disease Reporting and Data System reclassification rate in 49.0% of patients.

Clinical Validation of a Deep Learning Algorithm for Automated Coronary Artery Disease Detection and Classification Using a Heterogeneous Multivendor Coronary Computed Tomography Angiography Data Set.

We sought to clinically validate a fully automated deep learning (DL) algorithm for coronary artery disease (CAD) detection and classification in a heterogeneous multivendor cardiac computed tomography angiography data set. In this single-centre retrospective study, we included patients who underwent cardiac computed tomography angiography scans between 2010 and 2020 with scanners from 4 vendors (Siemens Healthineers, Philips, General Electrics, and Canon). Coronary Artery Disease-Reporting and Data System (CAD-RADS) classification was performed by a DL algorithm and by an expert reader (reader 1, R1), the gold standard. Variability analysis was performed with a second reader (reader 2, R2) and the radiologic reports on a subset of cases. Statistical analysis was performed stratifying patients according to the presence of CAD (CAD-RADS >0) and obstructive CAD (CAD-RADS ≥3). Two hundred ninety-six patients (average age: 53.66 ± 13.65, 169 males) were enrolled. For the detection of CAD only, the DL algorithm showed sensitivity, specificity, accuracy, and area under the curve of 95.3%, 79.7%, 87.5%, and 87.5%, respectively. For the detection of obstructive CAD, the DL algorithm showed sensitivity, specificity, accuracy, and area under the curve of 89.4%, 92.8%, 92.2%, and 91.1%, respectively. The variability analysis for the detection of obstructive CAD showed an accuracy of 92.5% comparing the DL algorithm with R1, and 96.2% comparing R1 with R2 and radiology reports. The time of analysis was lower using the DL algorithm compared with R1 (P < 0.001). The DL algorithm demonstrated robust performance and excellent agreement with the expert readers' analysis for the evaluation of CAD, which also corresponded with significantly reduced image analysis time.

Computed tomography angiography and coronary artery disease-reporting and data system and a 5-year prognostic major adverse cardiovascular and cerebral event outcome study in a symptomatic Southeast Asian population.

This study investigated the relationship between coronary artery disease-reporting and data system (CAD-RADS) for coronary computed tomography angiogram (CCTA) and major adverse cardiovascular and cerebral event (MACE) in a symptomatic Southeast Asian, Thai population over a 5-year period. A retrospective cohort study of Thai patients without known CAD who underwent CCTA for CAD symptoms. CCTA images and 5-year health data were reviewed for CAD-RADS and MACE. MACE consists of all-cause mortality, cardiovascular death, acute coronary syndrome, heart failure hospitalization, and stroke. In total 336 patients were evaluated. The median follow-up period was 6.4 years. The overall MACE incidence was 63 cases (18.8%). The MACE event rate was progressively increased with higher CAD-RADS categories; CAD-RADS 3 [hazard ratio (HR), 3.62; P = 0.015], CAD-RADS 4a (HR, 3.50; P = 0.024), CAD-RADS 4b & 5 (HR, 7.56; P = 0.001). The risk of MACE increased significantly in the moderate to severe CAD burden group (HR, 5.58; P = 0.01). Kaplan-Meier curve showed a significant rise in MACE with higher CAD-RADS categories ( P = 0.01). CAD-RADS classification has a significant prognostic value in Southeast Asian, Thai population with cardiac symptoms.

The Plaque Analysis Classifies the Coronary Artery Disease-Reporting and Data System (CAD-RADS) Stenosis and Plaque Burden Categories: Association of the Plaque Features, Fat Attenuation Index, Coronary Computed Tomography Fractional Flow Reserve, and the Combination of Stenosis and Calcification.

The coronary artery disease-reporting and data system (CAD-RADS) 2.0 is used to standardize the reporting of coronary computed tomography angiography (CCTA) results. Artificial intelligence software can quantify the plaque composition, fat attenuation index, and fractional flow reserve. To analyze plaque features of varying severity in patients with a combination of CAD-RADS stenosis and plaque burden categorization and establish a random forest classification model. The data of 100 patients treated between April 2021 and February 2022 were retrospectively collected. The most severe plaque observed in each patient was the target lesion. Patients were categorized into three groups according to CAD-RADS: CAD-RADS 1-2 + P0-2, CAD-RADS 3-4B + P0-2, and CAD-RADS 3-4B + P3-4. Differences and correlations between variables were assessed between groups. AUC, accuracy, precision, recall, and F1 score were used to evaluate the diagnostic performance. A total of 100 patients and 178 arteries were included. The differences of computed tomography fractional flow reserve (CT-FFR) (H = 23.921, p < 0.001),the volume of lipid component (H = 12.996, p = 0.002),the volume of fibro-lipid component (H = 8.692, p = 0.013),the proportion of lipid component volume (H = 22.038, p < 0.001),the proportion of fibro-lipid component volume (H = 11.731, p = 0.003),the proportion of calcification component volume (H = 11.049, p = 0.004), and plaque type (χ2 = 18.110, p = 0.001) was statistically significant. CT-FFR, volume and proportion of lipid and fibro-lipid components of plaques, the proportion of calcified components, and plaque type were valuable for CAD-RADS stenosis + plaque burden classification, especially CT-FFR, volume, and proportion of lipid and fibro-lipid components. The model built using the random forest was better than the clinical model (AUC: 0.874 vs. 0.647).

Association between severity of nonalcoholic fatty liver disease and major adverse cardiovascular events in patients assessed by coronary computed tomography angiography

BackgroundThe effect of nonalcoholic fatty liver disease (NAFLD) on major adverse cardiovascular events (MACEs) can be influenced by the degree of coronary artery stenosis. However, the association between the severity of NAFLD and MACEs in patients who underwent coronary computed tomography angiography (CCTA) is unclear.MethodsA total of 341 NAFLD patients who underwent CCTA were enrolled. The severity of NAFLD was divided into mild NAFLD and moderate-severe NAFLD by abdominal CT results. The degree of coronary artery stenosis was evaluated by using Coronary Artery Disease Reporting and Data System (CAD-RADS) category. Cox regression analysis and Kaplan–Meier analysis were used to assess poor prognosis.ResultsDuring the follow-up period, 45 of 341 NAFLD patients (13.20%) who underwent CCTA occurred MACEs. The severity of NAFLD (hazard ratio [HR] = 2.95[1.54–5.66]; p = 0.001) and CAD-RADS categories 3–5 (HR = 16.31[6.34–41.92]; p < 0.001) were independent risk factors for MACEs. The Kaplan–Meier analysis showed that moderate to severe NAFLD patients had a worsen prognosis than mild NAFLD patients (log-rank p < 0.001). Moreover, the combined receiver operating characteristic curve of the severity of NAFLD and CAD-RADS category showed a good predicting performance for the risk of MACEs, with an area under the curve of 0.849 (95% CI = 0.786–0.911).ConclusionThe severity of NAFLD was independent risk factor for MACEs in patients with obstructive CAD, having CAD-RADS 3–5 categories on CCTA.

Prognostic significance of CAD-RADS for patients with suspected coronary artery disease: A systematic review and meta-analysis

Abstract Background Coronary Artery Disease-Reporting and Data System (CAD-RADS) is a standardized reporting system that offers a structured method for interpreting and reporting results obtained through coronary computed tomography angiography. It has been deemed useful in the prognostication of patients with suspected coronary artery disease (CAD). Purpose The present meta-analysis sought to assess the prognostic value of CAD-RADS in individuals with suspected CAD. Materials and Methods We conducted a systematic search of the electronic databases of PubMed, Web of Science Core Collection, Cochrane advanced search, and EMBASE. A random-effects model was implemented to evaluate the pooled hazard ratio (HR) for each CAD-RADS category and area under the receiver operating characteristics curve for predicting major adverse cardiovascular events. Results Data from 37 596 coronary computed tomography angiography examinations from 13 studies were analyzed. During follow-up, 2,536 (6.7%) adverse events were observed. Pooled HRs for prediction of adverse events were significant for all CAD-RADS categories, with incremental increase in HRs with progressively higher categories. For prediction of all-cause mortality, all categories except CAD-RADS 1 showed significant HR compared with CAD-RADS 0. Combination of CAD-RADS to conventional clinical risk factors and CAC resulted in a high predictive capacity for adverse events (pooled area under the receiver operating characteristics curve: 0.82 ([95% confidence interval, 0.73-0.91]). Conclusion The CAD-RADS category imparts information on the CAD severity and shows incremental increase in HR for adverse events with progressively higher categories, especially beyond CAD-RADS4b.

Diagnostic performance of 3.0 T unenhanced Dixon water-fat separation coronary MR angiography in patients with low-to-intermediate risk of coronary artery disease

PurposeTo evaluate the diagnostic performance of 3.0 T unenhanced compressed-sensing sensitivity encoding (CS-SENSE) Dixon water-fat separation coronary MR angiography (CMRA) in patients with low-to-intermediate risk of coronary artery disease (CAD) and its ability to grade the severity of CAD based on Coronary Artery Disease Reporting and Data System (CAD-RADS). MethodsA total of 55 patients who was clinically evaluated as low-to-intermediate risk of CAD were finally included to undergo both 3.0 T CS-SENSE water-fat separation CMRA and coronary computed tomography angiography (CCTA), and 11 of them also underwent X-ray coronary angiography (CAG). The severity of coronary artery disease was graded in patients who had completed both CCTA and CMRA examinations by the use of CAD-RADS reports for the patients with stable chest pain, and the diagnostic consistency between the two approaches was evaluated. Diagnostic performance of CMRA was assessed using the combination of CCTA and CAG as the reference standard for excluding or confirming CAD respectively. ResultsThe sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy of 3.0 T unenhanced water-fat separation coronary MRA were 90.0%, 95.0%, 81.8%, 97.4% and 94.0% for a patient-based analysis respectively. In comparison with CCTA, 3.0 T Dixon water-fat separation CMRA demonstrated excellent consistency in grading the severity of coronary heart disease according to CAD-RADS (0.77 for kappa value). ConclusionIn the group of low-to-intermediate probability for CAD, 3.0 T unenhanced CS-SENSE Dixon water-fat separation CMRA can present satisfactory diagnostic performance for the exclusion of CAD with high sensitivity and negative predictive value as well as the evaluation of grading the severity of coronary artery disease.

Ultrahigh-Spatial-Resolution Photon-counting Detector CT Angiography of Coronary Artery Disease for Stenosis Assessment.

Background Coronary CT angiography is a first-line test in coronary artery disease but is limited by severe calcifications. Photon-counting-detector (PCD) CT improves spatial resolution. Purpose To investigate the effect of improved spatial resolution on coronary stenosis assessment and reclassification. Materials and Methods Coronary stenoses were evaluated prospectively in a vessel phantom (in vitro) containing two stenoses (25%, 50%), and retrospectively in patients (in vivo) who underwent ultrahigh-spatial-resolution cardiac PCD CT (from July 2022 to April 2023). Images were reconstructed at standard resolution (section thickness, 0.6 mm; increment, 0.4 mm; Bv44 kernel), high spatial resolution (section thickness, 0.4 mm; increment, 0.2 mm; Bv44 kernel), and ultrahigh spatial resolution (section thickness, 0.2; increment, 0.1 mm; Bv64 kernel). Percentages of diameter stenosis (DS) were compared between reconstructions. In vitro values were compared with the manufacturer specifications of the phantom and patient results were assessed regarding effects on Coronary Artery Disease Reporting and Data System (CAD-RADS) reclassification. Results The in vivo sample included 114 patients (mean age, 68 years ± 9 [SD]; 71 male patients). In vitro percentage DS measurements were more accurate with increasing spatial resolution for both 25% and 50% stenoses (mean bias for standard resolution, high spatial resolution, and ultrahigh spatial resolution, respectively: 10.1%, 8.0%, and 2.3%; P < .001). In vivo results confirmed decreasing median percentage DS with increasing spatial resolution for calcified stenoses (n = 161) (standard resolution, high spatial resolution, and ultrahigh spatial resolution, respectively: 41.5% [IQR, 27.3%-58.2%], 34.8% [IQR, 23.7%-55.1%], and 26.7% [IQR, 18.6%-44.3%]; P < .001), whereas noncalcified (n = 13) and mixed plaques (n = 19) did not show evidence of a difference (P ≥ .88). Ultrahigh-spatial-resolution reconstructions led to reclassification of 62 of 114 (54.4%) patients to lower CAD-RADS category than that assigned using standard resolution. Conclusion In vivo and in vitro coronary stenosis assessment improved for calcified stenoses by using ultrahigh-spatial-resolution PCD CT reconstructions, leading to lower percentage DS compared with standard resolution and clinically relevant rates of reclassification. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by McCollough in this issue.

Impact of atherosclerosis imaging-quantitative computed tomography on diagnostic certainty, downstream testing, coronary revascularization, and medical therapy: the CERTAIN study.

The incremental impact of atherosclerosis imaging-quantitative computed tomography (AI-QCT) on diagnostic certainty and downstream patient management is not yet known. The aim of this study was to compare the clinical utility of the routine implementation of AI-QCT versus conventional visual coronary CT angiography (CCTA) interpretation. In this multi-centre cross-over study in 5 expert CCTA sites, 750 consecutive adult patients referred for CCTA were prospectively recruited. Blinded to the AI-QCT analysis, site physicians established patient diagnoses and plans for downstream non-invasive testing, coronary intervention, and medication management based on the conventional site assessment. Next, physicians were asked to repeat their assessments based upon AI-QCT results. The included patients had an age of 63.8 ± 12.2 years; 433 (57.7%) were male. Compared with the conventional site CCTA evaluation, AI-QCT analysis improved physician's confidence two- to five-fold at every step of the care pathway and was associated with change in diagnosis or management in the majority of patients (428; 57.1%; P < 0.001), including for measures such as Coronary Artery Disease-Reporting and Data System (CAD-RADS) (295; 39.3%; P < 0.001) and plaque burden (197; 26.3%; P < 0.001). After AI-QCT including ischaemia assessment, the need for downstream non-invasive and invasive testing was reduced by 37.1% (P < 0.001), compared with the conventional site CCTA evaluation. Incremental to the site CCTA evaluation alone, AI-QCT resulted in statin initiation/increase an aspirin initiation in an additional 28.1% (P < 0.001) and 23.0% (P < 0.001) of patients, respectively. The use of AI-QCT improves diagnostic certainty and may result in reduced downstream need for non-invasive testing and increased rates of preventive medical therapy.

Prognostic value of mitral annular calcification in coronary atherosclerotic disease assessed by coronary computed tomographic angiography

Abstract Background: There is a lack of evidence on the link between mitral annular calcification (MAC) and coronary atherosclerotic diseases. The present investigation was undertaken to detect the clinical and prognostic value of MAC in coronary atherosclerotic diseases in patients who underwent coronary computed tomographic (CT) angiography. Materials and Methods: Two hundred and five individuals with MAC and without it (n = 85 and 120, respectively) were included in the present cross-sectional study. Coronary artery disease-reporting and data system (CAD-RADS) at coronary CT angiography was used to define the severity of coronary atherosclerotic diseases. Patients were classified into no or non-significant CAD (CAD-RADS 0–2) and significant CAD (CAD-RADS 3–5) according to the severity of coronary atherosclerotic diseases. The association of MAC with two mentioned groups (no or non-significant CAD and significant CAD) was assessed using the Chi-squared test and logistic regression in crude and adjusted models. Results: Patients with MAC were significantly older (69.34 ± 8.20 vs. 60.64 ± 11.42, P &lt; 0.001), had lower glomerular infiltration rate (69.67 ± 20.92 vs. 78.00 ± 20.23, P = 0.005), and higher coronary artery calcification score (352.87 ± 495.85 vs. 200.55 ± 426.13, P = 0.05) in comparison to those without MAC. However, the significant difference between the two groups regarding coronary artery calcification score disappeared after adjustment for confounders (P = 0.14). In addition, a statistically significant positive link between MAC and significant CAD was observed (odds ratio [OR] [95% confidence interval (CI)]: 1.96 [1.04–3.71], P = 0.04). Nevertheless, the association became statistically insignificant after adjustment for confounders (OR [95% CI]: 1.60 [0.78–3.28], P = 0.2). Conclusion: The findings of the study revealed that MAC has no independent prognostic value in coronary atherosclerotic diseases evaluated by coronary CT angiography.

The prevalence of coronary artery disease in patients presenting with 'non-anginal chest pain'.

The National Institute for Health and Care Excellence (NICE) advise against routine testing for coronary artery disease (CAD) in patients with non-anginal chest pain (NACP). This clinical audit sought to establish the prevalence of significant CAD in this cohort using computed tomography angiography (CTCA) and evaluate differences in the prevalence of cardiovascular risk factors between those with and without obstructive coronary disease. Over 23 months, 866 patients with NACP underwent CTCA. Patients were separated into three groups for analysis depending on the degree of CAD on CTCA using the CAD-RADS (Coronary Artery Disease Reporting and Data System) scoring system; no evidence of CAD (group 1), a degree of CAD requiring medical therapy only (group 2), significant CAD defined as a CAD-RADS score 4A/B or 5 (group 3). Cardiovascular risk factors were compared between the groups. We found 11.5% had significant CAD (group 3), 58.3% required medical therapy (group 2) and 30.1% had no CAD (group 1). There were 32 patients who required coronary revascularisation. Patients in group 2 and 3 were more likely to be male (p<0.001) and older (p<0.001) when compared to patients in group 1. Patients in group 3 were more likely to be hypertensive (p=0.008) and have higher Qrisk2 scores (p<0.001) when compared with those in group 1. In conclusion, NICE guidelines for NACP may result in a significant proportion of patients with CAD being underdiagnosed, including some with severe disease requiring revascularisation. This analysis suggests age, male gender, Qrisk2 score and hypertension are predictors of CAD in this cohort.

Epicardial fat volume and its association with cardiac arrhythmias in CT coronary angiography.

This retrospective study aimed to investigate the epicardial fat volume in cardiac computed tomography (CT), its relationship with cardiac arrhythmias, and its correlation with the coronary artery disease reporting and data system (CAD-RADS) score. Ninety-six patients who underwent CT coronary angiography (CTCA) were included in this study. Patient data, including demographic information, clinical history, and imaging data were collected retrospectively. Epicardial fat volume was quantified using a standardised algorithm, the CAD-RADS scoring system was applied to assess the extent of coronary artery disease (CAD). Descriptive statistics, correlation analyses, and receiver operating characteristics methods were used. The study found a significant correlation between epicardial fat volume and CAD-RADS score (r2 = 0.31; p < 0.001), indicating the known influence of epicardial fat on CAD risk. Moreover, patients with higher epicardial fat volumes were more likely to experience cardiac tachyarrhythmia (p < 0.001). Receiver operating characteristic analysis established a threshold value of 123 cm3 for epicardial fat volume to predict tachyarrhythmia with 80% sensitivity (AUC = 0.69). In this study a volume of at least 123 cm3 epicardial fat in native coronary calcium scans is associated with cardiac tachyarrhythmia. In these patients, careful selection of suitable imaging protocols is advised.

Intra-individual comparison of coronary artery stenosis measurements between energy-integrating detector CT and photon-counting detector CT

AbstractPurposeTo compare intra-individual percentage diameter stenosis (PDS) measurements of coronary artery stenoses between energy-integrating detector computed tomography (EID-CT) and a clinical photon-counting detector computed tomography (PCD-CT) systems using similar acquisition and reconstruction settings.MethodsPatients (n = 23, mean age of 65 ± 12.1 years, out of these 16 (69.6%) male) were imaged on a conventional EID- and a clinical PCD-CT system with a median of 5.5 (3.0–12.5) days apart. Sequential CCTA scans were acquired and reconstructed using similar settings, including a vascular Bv36 kernel, a tube voltage of 110 kVp for EID-CT vs 120 kVp for PCD-CT, a slice thickness of 0.5 for EID-CT vs 0.6 for PCD-CT, and an iterative reconstruction strength of 3 on EID-CT vs a virtual monoenergetic reconstruction at 55 keV and quantum iterative reconstruction level of 3 on PCD-CT. Radiation dose, contrast volume, and injection parameters were matched as similarly as possible between the systems. PDS measurements were performed according to the coronary artery disease reporting and data system (CAD-RADS) by two trained readers and compared between the different modalities using the Wilcoxon rank sum test, Spearman correlation, and Bland-Altman analysis.ResultsPCD-CT measured significantly lower PDS values than EID-CT [PDSEID-CT: 45.1% (35.1%–64.0%) vs. PDSPCD-CT 44.2% (32.4%–61.0%), P &lt; 0.0001]. This difference led to a mean bias of 1.8 (LoA −3.0/6.5) with an excellent ICC (0.99) value among EID- and PCD-CT. The mean intra-individual deviation between the examinations was 1.8% between the scanners. This led to CAD-RADS re-classification in 3/23 cases (13.0%, new-lower class) for the first reader, and in 4/23 cases (13.0%, new-lower and 4.4%, new-higher class) for the second reader. Inter-reader agreement between the two readers for each stenosis was very strong (ICC = 0.98).ConclusionsCoronary artery stenosis measurements from PCD-CT correlate strongly to EID-CT-based measurements, despite the tendency of the measurement from PCD-CT being lower. This difference led to a change in CAD-RADS classification in 17.4% of patients. The effects on clinical decision-making, downstream testing, and prognosis have to be evaluated in future studies.

The differences between patients with nonalcoholic fatty liver disease (NAFLD) and those without NAFLD, as well as predictors of functional coronary artery ischemia in patients with NAFLD.

Nonalcoholic fatty liver disease (NAFLD) is a chronic liver disease associated with metabolic syndrome. It is the most common cause of cryptogenic cirrhosis. The disease is also involved in the occurrence and development of type 2 diabetes and atherosclerosis and can directly affect the outcome of patients with coronary heart disease. Therefore, the focus of treatment of nonalcoholic fatty liver disease has also begun to focus on the treatment of risk factors for atherosclerotic heart disease. In this study, we investigated the difference between patients with coronary artery stenosis combined with NAFLD and those without NAFLD and evaluated the predictive factors and value of functional coronary artery ischemia in patients with NAFLD. Many clinical factors (such as age, BMI, hyperglycemia) and imaging parameters (such as CACS grade) in the NAFLD group were different from those in the non-NAFLD group. The predictive model combined with multiple influencing factors has a good value in predicting coronary artery ischemia in patients with NAFLD. We collected the clinical and imaging data of patients who underwent coronary computed tomography angiographyand coronary artery calcification score (CACS) scans between January and June 2023. A total of 392 patients were included and divided into the NAFLD group and the non-NAFLD group. Based on CT fractional flow reserve (CT-FFR), patients with NAFLD were divided into CT-FFR ≤ 0.08 group and CT-FFR > 0.08 group. Significant differences were observed between the non-NAFLD and NAFLD groups in terms of age, body mass index, hyperglycemia, hyperlipidemia, triglyceride, high-density lipoprotein, coronary artery disease-reporting and data system (CAD-RADS) classification, CACS classification, number of diseased coronary arteries, and CT-FFR ≤ 0.80 ratio (p < .05). The CAD-RADS and CACS classifications can independently predict functional coronary artery ischemia in NAFLD patients. The combined use of CAD-RADS and CACS classifications resulted in an area under the curve of 0.819 (95% confidence interval: 0.761-0.876) for predicting coronary artery ischemia in NAFLD patients, which was higher than the individual classification methods (CAD-RADS: 0.762, CACS: 0.742) (p = .000). There are differences between patients with coronary artery stenosis and NAFLD and those without NAFLD. The CAD-RADS classification and CACS classification can economically and efficiently predict functional coronary artery ischemia in patients with NAFLD, which has crucial value in clinical diagnosis and treatment.