On-Site Computed Tomography-Derived Fractional Flow Reserve to Guide Management of Patients With Stable Coronary Artery Disease: The TARGET Randomized Trial.

BACKGROUND: Computed tomography-derived fractional flow reserve (CT-FFR) using on-site machine learning enables identification of both the presence of coronary artery disease and vessel-specific ischemia. However, it is unclear whether on-site CT-FFR improves clinical or economic outcomes when compared with the standard of care in patients with stable coronary artery disease. METHODS: In total, 1216 patients with stable coronary artery disease and an intermediate stenosis of 30% to 90% on coronary computed tomographic angiography were randomized to an on-site CT-FFR care pathway using machine learning or to standard care in 6 Chinese medical centers. The primary end point was the proportion of patients undergoing invasive coronary angiography without obstructive coronary artery disease or with obstructive disease who did not undergo intervention within 90 days. Secondary end points included major adverse cardiovascular events, quality of life, symptoms of angina, and medical expenditure at 1 year. RESULTS: Baseline characteristics were similar in both groups, with 72.4% (881/1216) having either typical or atypical anginal symptoms. A total of 421 of 608 patients (69.2%) in the CT-FFR care group and 483 of 608 patients (79.4%) in the standard care group underwent invasive coronary angiography. Compared with standard care, the proportion of patients undergoing invasive coronary angiography without obstructive coronary artery disease or with obstructive disease not undergoing intervention was significantly reduced in the CT-FFR care group (28.3% [119/421] versus 46.2% [223/483]; P<0.001). Overall, more patients underwent revascularization in the CT-FFR care group than in the standard care group (49.7% [302/608] versus 42.8% [260/608]; P=0.02), but major adverse cardiovascular events at 1 year did not differ (hazard ratio, 0.88 [95% CI, 0.59-1.30]). Quality of life and symptoms improved similarly during follow-up in both groups, and there was a trend towards lower costs in the CT-FFR care group (difference, -¥4233 [95% CI, -¥8165 to ¥973]; P=0.07). CONCLUSIONS: On-site CT-FFR using machine learning reduced the proportion of patients with stable coronary artery disease undergoing invasive coronary angiography without obstructive disease or requiring intervention within 90 days, but increased revascularization overall without improving symptoms or quality of life, or reducing major adverse cardiovascular events. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03901326.

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.

Deep-Learning-Based Disease Classification in Patients Undergoing Cine Cardiac MRI.

BACKGROUND: Automated approaches may allow for fast, reproducible clinical assessment of cardiovascular diseases from MRI. PURPOSE: To develop an MRI-based deep learning (DL) disease classification algorithm to distinguish among normal subjects (NORM), patients with dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), and ischemic heart disease (IHD). STUDY TYPE: Retrospective. POPULATION: A total of 1337 subjects (55% female), comprising normal subjects (N = 568), and patients with DCM (N = 151), HCM (N = 177), and IHD (N = 441). FIELD STRENGTH/SEQUENCE: Balanced steady-state free precession cine sequence at 1.5/3.0 T. ASSESSMENT: Bi-ventricular morphological and functional features and global and segmental left ventricular strain features were automatically extracted from short- and long-axis cine images. Variational autoencoder models were trained on the extracted features and compared against consensus disease label provided by two expert readers (13 and 14 years of experience). Adding unlabeled, normal data to the training was explored to increase specificity of NORM class. STATISTICAL TESTS: Tenfold cross-validation for model development; mean, standard deviation (SD) for measurements; classification metrics: area under the curve (AUC), confusion matrix, accuracy, specificity, precision, recall; 95% confidence intervals; Mann-Whitney U test for significance. RESULTS: AUCs of 0.952 for NORM, 0.881 for DCM, 0.908 for HCM, and 0.856 for IHD and overall accuracy of 0.778 were obtained, with specificity of 0.908 for the NORM class using both SAX and LAX features. Longitudinal strain features slightly improved classification metrics by 0.001 to 0.03 points, except for HCM-AUC. Differences in accuracy, metrics for NORM class and HCM-AUC were statistically significant. Cotraining using unlabeled data increased the specificity for the NORM class to 0.961. DATA CONCLUSION: Cardiac function features automatically extracted from cine MRI have potential to be used for disease classification, especially for normal-abnormal classification. Feature analyses showed that strain features were important for disease labeling. Cotraining using unlabeled data may help to increase specificity for normal-abnormal classification. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 1.

Highly accelerated free-breathing real-time 2D flow imaging using compressed sensing and shared velocity encoding.

OBJECTIVES: 2D real-time (RT) phase-contrast (PC) MRI is a promising alternative to conventional PC MRI, which overcomes problems due to irregular heartbeats or poor respiratory control. This study aims to evaluate a prototype compressed sensing (CS)-accelerated 2D RT-PC MRI technique with shared velocity encoding (SVE) for accurate beat-to-beat flow measurements. METHODS: The CS RT-PC technique was implemented using a single-shot fast RF-spoiled gradient echo with SVE by symmetric velocity encoding, and acquired with a temporal resolution of 51-56.5 ms in 1-5 heartbeats. Both aortic dissection phantom (n = 8) and volunteer (n = 7) studies were conducted using the prototype CS RT (CS, R = 8), the conventional (GRAPPA, R = 2), and the fully sampled PC sequences on a 3T clinical system. Flow parameters including peak velocity, peak flow rate, net flow rate, and maximum velocity were calculated to compare the performance between different methods using linear regression, intraclass correlation (ICC), and Bland-Altman analyses. RESULTS: Comparisons of the flow measurements at all locations in the phantoms demonstrated an excellent correlation (all R2 ≥ 0.93) and agreement (all ICC ≥ 0.97) with negligible means of differences. In healthy volunteers, a similarly good correlation (all R2 ≥ 0.80) and agreement (all ICC ≥ 0.90) were observed; however, CS RT slightly underestimated the maximum velocities and flow rates (~ 12%). CONCLUSION: The highly accelerated CS RT-PC technique is feasible for the evaluation of flow patterns without requiring breath-holding, and it allows for rapid flow assessment in patients with arrhythmia or poor breath-hold capacity. CLINICAL RELEVANCE STATEMENT: The free-breathing real-time flow MRI technique offers improved spatial and temporal resolutions, as well as the ability to image individual cardiac cycles, resulting in superior image quality compared to the conventional PC technique when imaging patients with arrhythmias, especially those with atrial fibrillation. KEY POINTS: • The highly accelerated prototype CS RT-PC MRI technique with improved temporal resolution by the concept of SVE is feasible for beat-to-beat flow evaluation without requiring breath-holding. • The results of the phantom and in vivo quantitative flow evaluation show the ability of the prototype CS RT-PC technique to obtain reliable flow measurements similarly to the conventional PC MRI. • With less than 12% underestimation, excellent agreements between the two techniques were shown for the measurements of peak velocities and flow rates.

Prediction value of pericoronary fat attenuation index for coronary in-stent restenosis.

OBJECTIVES: As a novel imaging marker, pericoronary fat attenuation index (FAI) reflects the local coronary inflammation which is one of the major mechanisms for in-stent restenosis (ISR). We aimed to validate the ability of pericoronary FAI to predict ISR in patients undergoing percutaneous coronary intervention (PCI). MATERIALS AND METHODS: Patients who underwent coronary CT angiography (CCTA) before PCI within 1 week between January 2017 and December 2019 at our hospital and had follow-up invasive coronary angiography (ICA) or CCTA were enrolled. Pericoronary FAI was measured at the site where stents would be placed. ISR was defined as ≥ 50% diameter stenosis at follow-up ICA or CCTA in the in-stent area. Multivariable analysis using mixed effects logistic regression models was performed to test the association between pericoronary FAI and ISR at lesion level. RESULTS: A total of 126 patients with 180 target lesions were included in the study. During 22.5 months of mean interval time from index PCI to follow-up ICA or CCTA, ISR occurred in 40 (22.2%, 40/180) stents. Pericoronary FAI was associated with a higher risk of ISR (adjusted OR = 1.12, p = 0.028). The optimum cutoff was - 69.6 HU. Integrating the dichotomous pericoronary FAI into current state of the art prediction model for ISR improved the prediction ability of the model significantly (△area under the curve = + 0.064; p = 0.001). CONCLUSION: Pericoronary FAI around lesions with subsequent stent placement is independently associated with ISR and could improve the ability of current prediction model for ISR. CLINICAL RELEVANCE STATEMENT: Pericoronary fat attenuation index can be used to identify the lesions with high risk for in-stent restenosis. These lesions may benefit from extra anti-inflammation treatment to avoid in-stent restenosis. KEY POINTS: • Pericoronary fat attenuation index reflects the local coronary inflammation. • Pericoronary fat attenuation index around lesions with subsequent stents placement can predict in-stent restenosis. • Pericoronary fat attenuation index can be used as a marker for future in-stent restenosis.

Photon-Counting Detector CT Virtual Monoenergetic Images for Coronary Artery Stenosis Quantification: Phantom and In Vivo Evaluation.

BACKGROUND. Calcium blooming causes stenosis overestimation on coronary CTA. OBJECTIVE. The purpose of this article was to evaluate the impact of virtual monoenergetic imaging (VMI) reconstruction level on coronary artery stenosis quantification using photon-counting detector (PCD) CT. METHODS. A phantom containing two custom-made vessels (representing 25% and 50% stenosis) underwent PCD CT acquisitions without and with simulated cardiac motion. A retrospective analysis was performed of 33 patients (seven women, 26 men; mean age, 71.3 ± 9.0 [SD] years; 64 coronary artery stenoses) who underwent coronary CTA by PCD CT followed by invasive coronary angiography (ICA). Scans were reconstructed at nine VMI energy levels (40-140 keV). Percentage diameter stenosis (PDS) was measured, and bias was determined from the ground-truth stenosis percentage in the phantom and ICA-derived quantitative coronary angiography measurements in patients. Extent of blooming artifact was measured in the phantom and in calcified and mixed plaques in patients. RESULTS. In the phantom, PDS decreased for 25% stenosis from 59.9% (40 keV) to 13.4% (140 keV) and for 50% stenosis from 81.6% (40 keV) to 42.3% (140 keV). PDS showed lowest bias for 25% stenosis at 90 keV (bias, 1.4%) and for 50% stenosis at 100 keV (bias, -0.4%). Blooming artifacts decreased for 25% stenosis from 61.5% (40 keV) to 35.4% (140 keV) and for 50% stenosis from 82.7% (40 keV) to 52.1% (140 keV). In patients, PDS for calcified plaque decreased from 70.8% (40 keV) to 57.3% (140 keV), for mixed plaque decreased from 69.8% (40 keV) to 56.3% (140 keV), and for noncalcified plaque was 46.6% at 40 keV and 54.6% at 140 keV. PDS showed lowest bias for calcified plaque at 100 keV (bias, 17.2%), for mixed plaque at 140 keV (bias, 5.0%), and for noncalcified plaque at 40 keV (bias, -0.5%). Blooming artifacts decreased for calcified plaque from 78.4% (40 keV) to 48.6% (140 keV) and for mixed plaque from 73.1% (40 keV) to 44.7% (140 keV). CONCLUSION. For calcified and mixed plaque, stenosis severity measurements and blooming artifacts decreased at increasing VMI reconstruction levels. CLINICAL IMPACT. PCD CT with VMI reconstruction helps overcome current limitations in stenosis quantification on coronary CTA.

Enhancing diagnostic precision for acute chest syndrome in sickle cell disease: insights from dual-energy CT lung perfusion mapping.

PURPOSE: Acute chest syndrome (ACS) is secondary to occlusion of the pulmonary vasculature and a potentially life-threatening complication of sickle cell disease (SCD). Dual-energy CT (DECT) iodine perfusion map reconstructions can provide a method to visualize and quantify the extent of pulmonary microthrombi. METHODS: A total of 102 patients with sickle cell disease who underwent DECT CTPA with perfusion were retrospectively identified. The presence or absence of airspace opacities, segmental perfusion defects, and acute or chronic pulmonary emboli was noted. The number of segmental perfusion defects between patients with and without acute chest syndrome was compared. Sub-analyses were performed to investigate robustness. RESULTS: Of the 102 patients, 68 were clinically determined to not have ACS and 34 were determined to have ACS by clinical criteria. Of the patients with ACS, 82.4% were found to have perfusion defects with a median of 2 perfusion defects per patient. The presence of any or new perfusion defects was significantly associated with the diagnosis of ACS (P = 0.005 and < 0.001, respectively). Excluding patients with pulmonary embolism, 79% of patients with ACS had old or new perfusion defects, and the specificity for new perfusion defects was 87%, higher than consolidation/ground glass opacities (80%). CONCLUSION: DECT iodine map has the capability to depict microthrombi as perfusion defects. The presence of segmental perfusion defects on dual-energy CT maps was found to be associated with ACS with potential for improved specificity and reclassification.

Optimisation of virtual monoenergetic reconstructions for the diagnosis of pulmonary embolism using photon-counting detector computed tomography angiography.

Purpose: Computed tomography (CT) pulmonary angiography is considered the gold standard for pulmonary embolism (PE) diagnosis, relying on the discrimination between contrast and embolus. Photon-counting detector CT (PCD-CT) generates monoenergetic reconstructions through energy-resolved detection. Virtual monoenergetic images (VMI) at low keV can be used to improve pulmonary artery opacification. While studies have assessed VMI for PE diagnosis on dual-energy CT (DECT), there is a lack of literature on optimal settings for PCD-CT-PE reconstructions, warranting further investigation. Material and methods: Twenty-five sequential patients who underwent PCD-CT pulmonary angiography for suspicion of acute PE were retrospectively included in this study. Quantitative metrics including signal-to-noise ratio (SNR) and contrast-to-noise (CNR) ratio were calculated for 4 VMI values (40, 60, 80, and 100 keV). Qualitative measures of diagnostic quality were obtained for proximal to distal pulmonary artery branches by 2 cardiothoracic radiologists using a 5-point modified Likert scale. Results: SNR and CNR were highest for the 40 keV VMI (49.3 ± 22.2 and 48.2 ± 22.1, respectively) and were inversely related to monoenergetic keV. Qualitatively, 40 and 60 keV both exhibited excellent diagnostic quality (mean main pulmonary artery: 5.0 ± 0 and 5.0 ± 0; subsegmental pulmonary arteries 4.9 ± 0.1 and 4.9 ± 0.1, respectively) while distal segments at high (80-100) keVs had worse quality. Conclusions: 40 keV was the best individual VMI for the detection of pulmonary embolism by quantitative metrics. Qualitatively, 40-60 keV reconstructions may be used without a significant decrease in subjective quality. VMIs at higher keV lead to reduced opacification of the distal pulmonary arteries, resulting in decreased image quality.

Myocardial Characterization with Extracellular Volume Mapping with a First-Generation Photon-counting Detector CT with MRI Reference.

Background Photon-counting detector (PCD) CT provides comprehensive spectral data with every acquisition, but studies evaluating myocardial extracellular volume (ECV) quantification with use of PCD CT compared with an MRI reference remain lacking. Purpose To compare ECV quantification for myocardial tissue characterization between a first-generation PCD CT system and cardiac MRI. Materials and Methods In this single-center prospective study, adults without contraindication to iodine-based contrast media underwent same-day cardiac PCD CT and MRI with native and postcontrast T1 mapping and late gadolinium enhancement for various clinical indications for cardiac MRI (the reference standard) between July 2021 and January 2022. Global and midventricular ECV were assessed with use of three methods: single-energy PCD CT, dual-energy PCD CT, and MRI T1 mapping. Quantitative comparisons among all techniques were performed. Correlation and reliability between different methods of ECV quantification were assessed with use of the Pearson correlation coefficient (r) and the intraclass correlation coefficient. Results The final sample included 29 study participants (mean age ± SD, 54 years ± 17; 15 men). There was a strong correlation of ECV between dual- and single-energy PCD CT (r = 0.91, P < .001). Radiation dose was 40% lower with dual-energy versus single-energy PCD CT (volume CT dose index, 10.1 mGy vs 16.8 mGy, respectively; P < .001). In comparison with MRI, dual-energy PCD CT showed strong correlation (r = 0.82 and 0.91, both P < .001) and good to excellent reliability (intraclass correlation coefficients, 0.81 and 0.90) for midventricular and global ECV quantification, but it overestimated ECV by approximately 2%. Single-energy PCD CT showed similar relationship with MRI but underestimated ECV by 3%. Conclusion Myocardial tissue characterization with photon-counting detector CT-based quantitative extracellular volume analysis showed a strong correlation to MRI. © RSNA, 2023 Supplemental material is available for this article.

Residual Risk in Non-ST-Segment Elevation Acute Coronary Syndrome: Quantitative Plaque Analysis at Coronary CT Angiography.

Background Lipid-rich plaques detected with intravascular imaging are associated with adverse cardiovascular events in patients with non-ST-segment elevation (NSTE) acute coronary syndrome (ACS). But evidence about the prognostic implication of coronary CT angiography (CCTA) in NSTE ACS is limited. Purpose To assess whether quantitative variables at CCTA that reflect lipid content in nonrevascularized plaques in individuals with NSTE ACS might be predictors of subsequent nonrevascularized plaque-related major adverse cardiovascular events (MACEs). Materials and Methods In this multicenter prospective cohort study, from November 2017 to January 2019, individuals diagnosed with NSTE ACS (excluding those at very high risk) were enrolled and underwent CCTA before invasive coronary angiography (ICA) within 1 day. Lipid core was defined as areas with attenuation less than 30 HU in plaques. MACEs were defined as cardiac death, myocardial infarction, hospitalization for unstable angina, and revascularization. Participants were followed up at 6 months, 12 months, and annually thereafter for at least 3 years (ending by July 2022). Multivariable analysis using Cox proportional hazards regression models was performed to determine the association between lipid core burden, lipid core volume, and future nonrevascularized plaque-related MACEs at both the participant and plaque levels. Results A total of 342 participants (mean age, 57.9 years ± 11.1 [SD]; 263 male) were included for analysis with a median follow-up period of 4.0 years (IQR, 3.6-4.4 years). The 4-year nonrevascularized plaque-related MACE rate was 23.9% (95% CI: 19.1, 28.5). Lipid core burden (hazard ratio [HR], 12.6; 95% CI: 4.6, 34.3) was an independent predictor at the participant level, with an optimum threshold of 2.8%. Lipid core burden (HR, 12.1; 95% CI: 6.6, 22.3) and volume (HR, 11.0; 95% CI: 6.5, 18.4) were independent predictors at the plaque level, with an optimum threshold of 7.2% and 10.1 mm3, respectively. Conclusion In NSTE ACS, quantitative analysis of plaque lipid content at CCTA independently predicted participants and plaques at higher risk for future nonrevascularized plaque-related MACEs. Chinese Clinical Trial Registry no. ChiCTR1800018661 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Tavakoli and Duman in this issue.

A Coronary CT Angiography Radiomics Model to Identify Vulnerable Plaque and Predict Cardiovascular Events.

Background A noninvasive coronary CT angiography (CCTA)-based radiomics technique may facilitate the identification of vulnerable plaques and patients at risk for future adverse events. Purpose To assess whether a CCTA-based radiomic signature (RS) of vulnerable plaques defined with intravascular US was associated with increased risk for future major adverse cardiac events (MACE). Materials and Methods In a retrospective study, an RS of vulnerable plaques was developed and validated using intravascular US as the reference standard. The RS development data set included patients first undergoing CCTA and then intravascular US within 3 months between June 2013 and December 2020 at one tertiary hospital. The development set was randomly assigned to training and validation sets at a 7:3 ratio. Diagnostic performance was assessed internally and externally from three tertiary hospitals using the area under the curve (AUC). The prognostic value of the RS for predicting MACE was evaluated in a prospective cohort with suspected coronary artery disease between April 2018 and March 2019. Multivariable Cox regression analysis was used to evaluate the RS and conventional anatomic plaque features (eg, segment involvement score) for predicting MACE. Results The RS development data set included 419 lesions from 225 patients (mean age, 64 years ± 10 [SD]; 68 men), while the prognostic cohort included 1020 lesions from 708 patients (mean age, 62 years ± 11; 498 men). Sixteen radiomic features, including two shape features and 14 textural features, were selected to build the RS. The RS yielded a moderate to good AUC in the training, validation, internal, and external test sets (AUC = 0.81, 0.75, 0.80, and 0.77, respectively). A high RS (≥1.07) was independently associated with MACE over a median 3-year follow-up (hazard ratio, 2.01; P = .005). Conclusion A coronary CT angiography-derived radiomic signature of coronary plaque enabled the detection of vulnerable plaques that were associated with increased risk for future adverse cardiac outcomes. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by De Cecco and van Assen in this issue.

AI Cardiac MRI Scar Analysis Aids Prediction of Major Arrhythmic Events in the Multicenter DERIVATE Registry.

Background Scar burden with late gadolinium enhancement (LGE) cardiac MRI (CMR) predicts arrhythmic events in patients with postinfarction in single-center studies. However, LGE analysis requires experienced human observers, is time consuming, and introduces variability. Purpose To test whether postinfarct scar with LGE CMR can be quantified fully automatically by machines and to compare the ability of LGE CMR scar analyzed by humans and machines to predict arrhythmic events. Materials and Methods This study is a retrospective analysis of the multicenter, multivendor CarDiac MagnEtic Resonance for Primary Prevention Implantable CardioVerter DebrillAtor ThErapy (DERIVATE) registry. Patients with chronic heart failure, echocardiographic left ventricular ejection fraction (LVEF) of less than 50%, and LGE CMR were recruited (from January 2015 through December 2020). In the current study, only patients with ischemic cardiomyopathy were included. Quantification of total, dense, and nondense scars was carried out by two experienced readers or a Ternaus network, trained and tested with LGE images of 515 and 246 patients, respectively. Univariable and multivariable Cox analyses were used to assess patient and cardiac characteristics associated with a major adverse cardiac event (MACE). Area under the receiver operating characteristic curve (AUC) was used to compare model performances. Results In 761 patients (mean age, 65 years ± 11, 671 men), 83 MACEs occurred. With use of the testing group, univariable Cox-analysis found New York Heart Association class, left ventricle volume and/or function parameters (by echocardiography or CMR), guideline criterion (LVEF of ≤35% and New York Heart Association class II or III), and LGE scar analyzed by humans or the machine-learning algorithm as predictors of MACE. Machine-based dense or total scar conferred incremental value over the guideline criterion for the association with MACE (AUC: 0.68 vs 0.63, P = .02 and AUC: 0.67 vs 0.63, P = .01, respectively). Modeling with competing risks yielded for dense and total scar (AUC: 0.67 vs 0.61, P = .01 and AUC: 0.66 vs 0.61, P = .005, respectively). Conclusion In this analysis of the multicenter CarDiac MagnEtic Resonance for Primary Prevention Implantable CardioVerter DebrillAtor ThErapy (DERIVATE) registry, fully automatic machine learning-based late gadolinium enhancement analysis reliably quantifies myocardial scar mass and improves the current prediction model that uses guideline-based risk criteria for implantable cardioverter defibrillator implantation. ClinicalTrials.gov registration no.: NCT03352648 Published under a CC BY 4.0 license. Supplemental material is available for this article.

Highly Accelerated Compressed-Sensing 4D Flow for Intracardiac Flow Assessment.

BACKGROUND: Four-dimensional (4D) flow MRI allows for the quantification of complex flow patterns; however, its clinical use is limited by its inherently long acquisition time. Compressed sensing (CS) is an acceleration technique that provides substantial reduction in acquisition time. PURPOSE: To compare intracardiac flow measurements between conventional and CS-based highly accelerated 4D flow acquisitions. STUDY TYPE: Prospective. SUBJECTS: Fifty healthy volunteers (28.0 ± 7.1 years, 24 males). FIELD STRENGTH/SEQUENCE: Whole heart time-resolved 3D gradient echo with three-directional velocity encoding (4D flow) with conventional parallel imaging (factor 3) as well as CS (factor 7.7) acceleration at 3 T. ASSESSMENT: 4D flow MRI data were postprocessed by applying a valve tracking algorithm. Acquisition times, flow volumes (mL/cycle) and diastolic function parameters (ratio of early to late diastolic left ventricular peak velocities [E/A] and ratio of early mitral inflow velocity to mitral annular early diastolic velocity [E/e']) were quantified by two readers. STATISTICAL TESTS: Paired-samples t-test and Wilcoxon rank sum test to compare measurements. Pearson correlation coefficient (r), Bland-Altman-analysis (BA) and intraclass correlation coefficient (ICC) to evaluate agreement between techniques and readers. A P value < 0.05 was considered statistically significant. RESULTS: A significant improvement in acquisition time was observed using CS vs. conventional accelerated acquisition (6.7 ± 1.3 vs. 12.0 ± 1.3 min). Net forward flow measurements for all valves showed good correlation (r > 0.81) and agreement (ICCs > 0.89) between conventional and CS acceleration, with 3.3%-8.3% underestimation by the CS technique. Evaluation of diastolic function showed 3.2%-17.6% error: E/A 2.2 [1.9-2.4] (conventional) vs. 2.3 [2.0-2.6] (CS), BA bias 0.08 [-0.81-0.96], ICC 0.82; and E/e' 4.6 [3.9-5.4] (conventional) vs. 3.8 [3.4-4.3] (CS), BA bias -0.90 [-2.31-0.50], ICC 0.89. DATA CONCLUSION: Analysis of intracardiac flow patterns and evaluation of diastolic function using a highly accelerated 4D flow sequence prototype is feasible, but it shows underestimation of flow measurements by approximately 10%. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Left atrial strain correlates with severity of cardiac involvement in Anderson-Fabry disease.

OBJECTIVES: Cardiac involvement in Anderson-Fabry disease (AFD) results in myocardial lipid depositions. An early diagnosis can maximize therapeutic benefit. Thus, this study aims to investigate the potential of cardiac MRI (CMR) based parameters of left atrial (LA) function and strain to detect early stages of AFD. METHODS: Patients (n = 58, age 40 (29-51) years, 31 female) with genetically proven AFD had undergone CMR including left ventricular (LV) volumetry, mass index (LVMi), T1, and late gadolinium enhancement, complemented by LA and LV strain measurements and atrial emptying fractions. Patients were stratified into three disease phases and compared to age and sex-matched healthy controls (HC, n = 58, age 41 [26-56] years, 31 female). RESULTS: A total of 19 early-, 20 intermediate-, and 19 advanced-phase patients were included. LV and LA reservoir strain was significantly impaired in all AFD phases, including early disease (both p < 0.001). In contrast, LA volumetry, T1, and LVMi showed no significant differences between the early phase and HC (p > 0.05). In the intermediate phase, LVMi and T1 demonstrated significant differences. In advanced phase, all parameters except active emptying fractions differed significantly from HC. ROC curve analyses of early disease phases revealed superior diagnostic confidence for the LA reservoir strain (AUC 0.88, sensitivity 89%, specificity 75%) over the LV strain (AUC 0.82). CONCLUSIONS: LA reservoir strain showed impairment in early AFD and significantly correlated with disease severity. The novel approach performed better in identifying early disease than the established approach using LVMi and T1. Further studies are needed to evaluate whether these results justify earlier initiation of therapy and help minimize cardiac complications. KEY POINTS: • Parameters of left atrial function and deformation showed impairments in the early stages of Anderson-Fabry disease and correlated significantly with the severity of Anderson-Fabry disease. • Left atrial reservoir strain performed superior to ventricular strain in detecting early myocardial involvement in Anderson-Fabry disease and improved diagnostic accuracies of approaches already using ventricular strain. • Further studies are needed to evaluate whether earlier initiation of enzyme replacement therapy based on these results can help minimize cardiac complications from Anderson-Fabry disease.

Stent imaging on a clinical dual-source photon-counting detector CT system-impact of luminal attenuation and sharp kernels on lumen visibility.

OBJECTIVES: To assess the impact of scan modes and reconstruction kernels using a novel dual-source photon-counting detector CT (PCD-CT) on lumen visibility and sharpness of different stent sizes. METHODS: A phantom containing six balloon-expandable stents (2.5 to 9 mm diameter) in silicone tubing was scanned on a PCD-CT with standard (0.6 mm and 0.4 mm thicknesses) and ultra-high-resolution (0.2 mm thickness) modes. With the use of increasing contrast medium concentrations, densities of 0, 200, 400, and 600 HU were achieved. Standard-resolution scans were reconstructed using increasing sharpness kernels, using both polyenergetic quantitative soft tissue "conventional" ((Qr40c(0.6 mm), Qr40c(0.4 mm), Qr72c(0.2 mm)) and vascular (Bv) virtual monoenergetic reconstructions (Bv44m(0.4 mm), Bv60m(0.4 mm)) at 70 keV. In-stent lumen visibility, sharpness (max. ΔHU of the stent measured in profile plots), and in-stent noise (standard deviation of HU) were measured. RESULTS: In-stent lumen visibility was highest for Qr72c(0.2 mm) (86.5 ± 2.8% to 88.3 ± 2.6%) and in Bv60m(0.4 mm) reconstructions (77.3 ± 2.9 to 82.7 ± 2.5%). Lumen visibility was lowest in the smallest stent (2.5 mm) ranging from 54.1% in Qr40c(0.6 mm) to 74.1% in Qr72c(0.2 mm) and highest in the largest stent (9 mm) ranging from 93.8% in Qr40c(0.6 mm) to 99.1% in the Qr72c(0.2 mm) series. Lumen visibility decreased by 2.1% for every 200-HU increase in lumen attenuation. Max. ΔHU between stents and stent lumen was highest in Qr72c(0.2 mm) (ΔHU 892 ± 504 to 1526 ± 517) and Bv60m(0.4 mm) series (ΔHU 480 ± 357 to 1030 ± 344). Improvement of lumen visibility and sharpness in UHR and Bv60m(0.4 mm) series was strongest in smaller stent sizes. CONCLUSION: UHR acquisition mode and sharp reconstruction kernels on a novel PCD-CT system significantly improve in-stent lumen visibility and sharpness-especially for smaller stent sizes. KEY POINTS: • In-stent lumen visibility and sharpness of stents significantly improve using sharp reconstruction kernels (Bv60) and ultra-high-resolution mode in photon-counting detector computed tomography. • The observed improvement of stent-lumen visibility was highest in smaller stent sizes.

Multiparametric cardiac magnetic resonance reveals persistent myocardial inflammation in patients with exertional heat illness.

OBJECTIVES: To explore the clinical potential of multiparametric cardiac magnetic resonance (CMR) in evaluating myocardial inflammation in patients with exertional heat illness (EHI). METHODS: This prospective study enrolled 28 males with EHI (18 patients with exertional heat exhaustion (EHE) and 10 with exertional heat stroke (EHS)) and 18 age-matched male healthy controls (HC). All subjects underwent multiparametric CMR, and 9 patients had follow-up CMR measurements 3 months after recovery from EHI. CMR-derived left ventricular geometry, function, strain, native T1, extracellular volume (ECV), T2, T2*, and late gadolinium enhancement (LGE) were obtained and compared among different groups. RESULTS: Compared with HC, EHI patients showed increased global ECV, T2, and T2* values (22.6% ± 4.1 vs. 19.7% ± 1.7; 46.8 ms ± 3.4 vs. 45.1 ms ± 1.2; 25.5 ms ± 2.2 vs. 23.8 ms ± 1.7; all p < 0.05). Subgroup analysis showed that ECV was higher in the EHS patients than those in EHE and HC groups (24.7% ± 4.9 vs. 21.4% ± 3.2, 24.7% ± 4.9 vs. 19.7% ± 1.7; both p < 0.05). Repeated CMR measurements at 3 months after baseline CMR showed persistently higher ECV than HC (p = 0.042). CONCLUSIONS: With multiparametric CMR, EHI patients demonstrated increased global ECV, T2, and persistent myocardial inflammation at 3-month follow-up after EHI episode. Therefore, multiparametric CMR might be an effective method in evaluating myocardial inflammation in patients with EHI. CLINICAL RELEVANCE STATEMENT: This study showed persistent myocardial inflammation after an exertional heat illness (EHI) episode demonstrated by multiparametric CMR, which is a potential promising method to evaluate the severity of myocardial inflammation and guide return to work, play, or duty in EHI patients. KEY POINTS: • EHI patients showed an increased global extracellular volume (ECV), late gadolinium enhancement, and T2 value, indicating myocardial edema and fibrosis. • ECV was higher in the exertional heat stroke patients than exertional heat exhaustion and healthy control groups (24.7% ± 4.9 vs. 21.4% ± 3.2, 24.7% ± 4.9 vs. 19.7% ± 1.7; both p < 0.05). • EHI patients showed persistent myocardial inflammation with higher ECV than healthy controls 3 months after index CMR (22.3% ± 2.4 vs. 19.7% ± 1.7, p = 0.042).

Calcium Scoring at Coronary CT Angiography Using Deep Learning.

Background Separate noncontrast CT to quantify the coronary artery calcium (CAC) score often precedes coronary CT angiography (CTA). Quantifying CAC scores directly at CTA would eliminate the additional radiation produced at CT but remains challenging. Purpose To quantify CAC scores automatically from a single CTA scan. Materials and Methods In this retrospective study, a deep learning method to quantify CAC scores automatically from a single CTA scan was developed on training and validation sets of 292 patients and 73 patients collected from March 2019 to July 2020. Virtual noncontrast scans obtained with a spectral CT scanner were used to develop the algorithm to alleviate tedious manual annotation of calcium regions. The proposed method was validated on an independent test set of 240 CTA scans collected from three different CT scanners from August 2020 to November 2020 using the Pearson correlation coefficient, the coefficient of determination, or r2, and the Bland-Altman plot against the semiautomatic Agatston score at noncontrast CT. The cardiovascular risk categorization performance was evaluated using weighted κ based on the Agatston score (CAC score risk categories: 0-10, 11-100, 101-400, and >400). Results Two hundred forty patients (mean age, 60 years ± 11 [standard deviation]; 146 men) were evaluated. The positive correlation between the automatic deep learning CTA and semiautomatic noncontrast CT CAC score was excellent (Pearson correlation = 0.96; r2 = 0.92). The risk categorization agreement based on deep learning CTA and noncontrast CT CAC scores was excellent (weighted κ = 0.94 [95% CI: 0.91, 0.97]), with 223 of 240 scans (93%) categorized correctly. All patients who were miscategorized were in the direct neighboring risk groups. The proposed method's differences from the noncontrast CT CAC score were not statistically significant with regard to scanner (P = .15), sex (P = .051), and section thickness (P = .67). Conclusion A deep learning automatic calcium scoring method accurately quantified coronary artery calcium from CT angiography images and categorized risk. © RSNA, 2021 See also the editorial by Goldfarb and Cao et al in this issue.

CT in Transcatheter-delivered Treatment of Valvular Heart Disease.

Minimally invasive strategies to treat valvular heart disease have emerged over the past 2 decades. The use of transcatheter aortic valve replacement in the treatment of severe aortic stenosis, for example, has recently expanded from high- to low-risk patients and became an alternative treatment for those with prohibitive surgical risk. With the increase in transcatheter strategies, multimodality imaging, including echocardiography, CT, fluoroscopy, and cardiac MRI, are used. Strategies for preprocedural imaging strategies vary depending on the targeted valve. Herein, an overview of preprocedural imaging strategies and their postprocessing approaches is provided, with a focus on CT. Transcatheter aortic valve replacement is reviewed, as well as less established minimally invasive treatments of the mitral and tricuspid valves. In addition, device-specific details and the goals of CT imaging are discussed. Future imaging developments, such as peri-procedural fusion imaging, machine learning for image processing, and mixed reality applications, are presented.

Coronary CT Fractional Flow Reserve before Transcatheter Aortic Valve Replacement: Clinical Outcomes.

Background The role of CT angiography-derived fractional flow reserve (CT-FFR) in pre-transcatheter aortic valve replacement (TAVR) assessment is uncertain. Purpose To evaluate the predictive value of on-site machine learning-based CT-FFR for adverse clinical outcomes in candidates for TAVR. Materials and Methods This observational retrospective study included patients with severe aortic stenosis referred to TAVR after coronary CT angiography (CCTA) between September 2014 and December 2019. Clinical end points comprised major adverse cardiac events (MACE) (nonfatal myocardial infarction, unstable angina, cardiac death, or heart failure admission) and all-cause mortality. CT-FFR was obtained semiautomatically using an on-site machine learning algorithm. The ability of CT-FFR (abnormal if ≤0.75) to predict outcomes and improve the predictive value of the current noninvasive work-up was assessed. Survival analysis was performed, and the C-index was used to assess the performance of each predictive model. To compare nested models, the likelihood ratio χ2 test was performed. Results A total of 196 patients (mean age ± standard deviation, 75 years ± 11; 110 women [56%]) were included; the median time of follow-up was 18 months. MACE occurred in 16% (31 of 196 patients) and all-cause mortality in 19% (38 of 196 patients). Univariable analysis revealed CT-FFR was predictive of MACE (hazard ratio [HR], 4.1; 95% CI: 1.6, 10.8; P = .01) but not all-cause mortality (HR, 1.2; 95% CI: 0.6, 2.2; P = .63). CT-FFR was independently associated with MACE (HR, 4.0; 95% CI: 1.5, 10.5; P = .01) when adjusting for potential confounders. Adding CT-FFR as a predictor to models that include CCTA and clinical data improved their predictive value for MACE (P = .002) but not all-cause mortality (P = .67), and it showed good discriminative ability for MACE (C-index, 0.71). Conclusion CT angiography-derived fractional flow reserve was associated with major adverse cardiac events in candidates for transcatheter aortic valve replacement and improved the predictive value of coronary CT angiography assessment. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Choe in this issue.

Quiescent-Interval Slice-Selective MRA Accurately Estimates Intravascular Stent Dimensions Prior to Intervention in Patients With Peripheral Artery Disease.

BACKGROUND: Quiescent-interval slice-selective (QISS) magnetic resonance angiography (MRA) is a non-contrast alternative for the pre-procedural assessment of patients with peripheral artery disease (PAD). However, the feasibility of pre-procedural stent size estimation using QISS MRA would merit investigation. PURPOSE: To evaluate the feasibility of QISS MRA for pre-procedural stent size estimation in PAD patients compared to computed tomography angiography (CTA). STUDY TYPE: Retrospective. SUBJECTS: Thirty-three PAD patients (68 ± 9 years, 18 men, 15 women). FIELD STRENGTH/SEQUENCE: Two-dimensional balanced steady-state free precession QISS MRA at 1.5 T and 3 T. ASSESSMENT: All patients received QISS MRA and CTA of the lower extremity run-off followed by interventional digital subtraction angiography (DSA). Stenotic lesion length and diameter were quantified (AMF and AVS with 3 and 13 years of experience in cardiovascular imaging, respectively) to estimate the dimensions of the stent necessary to restore blood flow in the treated arteries. Measured dimensions were adjusted to the closest stent size available. STATISTICAL TESTS: The Friedman test with subsequent pairwise Wilcoxon signed-rank test was used to compare the estimated stent dimensions between QISS MRA, CTA, and the physical stent size used for intervention. Intra-class correlation (ICC) analysis was performed to assess inter-reader agreement. Significant differences were considered at P < 0.05. RESULTS: No significant difference was observed between estimated stent diameter by QISS MRA or CTA compared to physical stent diameter (8.9 ± 2.9 mm, 8.8 ± 3.0 mm, and 8.8 ± 3.8 mm, respectively; χ2  = 1.45, P = 0.483). There was a significant underestimation of stent length for both QISS MRA and CTA, compared to physical stent length (45.8 ± 27.8 mm, 46.4 ± 29.3 mm, and 50.4 ± 34.0 mm, respectively; χ2  = 11.96) which could be corrected when measurements were adjusted to the next available stent length (χ2  = 2.38, P = 0.303). Inter-reader assessment showed good to excellent agreement between the readers (all ICC ≥0.81). DATA CONCLUSION: QISS MRA represents a reliable method for pre-procedural lesion assessment and stent diameter and length estimation in PAD patients. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.