Incremental Prognostic Value of Coronary Artery Calcium Score for Predicting All-Cause Mortality after Transcatheter Aortic Valve Replacement

Photon-Counting Chest CT at Radiography-Comparable Dose Levels: Impact on Opportunistic Visual and Semiautomated Coronary Calcium Quantification

OBJECTIVES

The introduction of photon-counting detector computed tomography (PCCT) has allowed for significant dose reductions compared to energy-integrating-detector CT, making it particularly relevant for applications such as lung cancer screening. Coronary artery calcification is an important incidental finding in lung cancer screening, warranting attention in this context. This study aims to assess the impact of dose reduction to levels comparable to that of a chest radiography on opportunistic evaluation of coronary artery calcification on PCCTs of the chest.

MATERIALS AND METHODS

Sixty-eight out of 115 patients with age >45 years and body mass index ≤30 kg/m2 undergoing noncontrast low- and chest-radiography-comparable-dose PCCT in the same session were included. Scans were performed at 100 kVp with image quality settings 12 (low-dose) and 2 (radiography-comparable-dose). Visual calcium scoring was conducted by 2 readers using 2 scoring approaches (CAD-RADS 2.0 and Shemesh). Semiautomated quantitative analysis was performed using commercially available software. Image quality was evaluated using 5-point Likert scales.

RESULTS

Sixty-eight patients (65.9 ± 8.6 years; 49 men) were subjected to evaluation. CTDI was lower for radiography-dose scans (0.11 mGy vs 0.68 mGy; P < 0.001). Image quality was found to be inferior for radiography-dose scans (4.01 vs 2.03; P < 0.001). In both visual scoring approaches, coronary calcification was scored significantly lower in radiography-dose scans (P < 0.001 for both) with almost perfect reader agreement (CAD-RADS score Cohen's kappa =0.82; Shemesh score Cohen's kappa =0.81), most importantly reclassification from mild to absent occurred for CAD-RADS score in 31%/21% of cases and for Shemesh score in 23%/15% of cases (reader 1/reader 2). Semiautomated assessment showed no significant differences between low and radiography dose (P = 0.121). Strong correlation between scores (Pearson's r = 0.98, P < 0.001) with good agreement (Cohen's kappa =0.61) was found.

CONCLUSIONS

Coronary artery calcifications are underestimated on radiography-dose PCCT visually, whereas semiautomatic analysis provides more robust results. Visual underestimation of coronary artery calcification in low-dose imaging is further amplified with the additional dose reduction to radiography-comparable dose levels, indicating that while estimation of high cardiovascular risk is feasible, exclusion of such risk is not possible.

Effect of temporal resolution on calcium scoring: insights from photon-counting detector CT

To intra-individually investigate the variation of coronary artery calcium (CAC), aortic valve calcium (AVC), and mitral annular calcium (MAC) scores and the presence of blur artifacts as a function of temporal resolution in patients undergoing non-contrast cardiac CT on a dual-source photon counting detector (PCD) CT. This retrospective, IRB-approved study included 70 patients (30 women, 40 men, mean age 78 ± 9 years) who underwent ECG-gated cardiac non-contrast CT with PCD-CT (gantry rotation time 0.25 s) prior to transcatheter aortic valve replacement. Each scan was reconstructed at a temporal resolution of 66 ms using the dual-source information and at 125 ms using the single-source information. Average heart rate and heart rate variability were calculated from the recorded ECG. CAC, AVC, and MAC were quantified according to the Agatston method on images with both temporal resolutions. Two readers assessed blur artifacts using a 4-point visual grading scale. The influence of average heart rate and heart rate variability on calcium quantification and blur artifacts of the respective structures were analyzed by linear regression analysis. Mean heart rate and heart rate variability during data acquisition were 76 ± 17 beats per minute (bpm) and 4 ± 6 bpm, respectively. CAC scores were smaller on 66 ms (median, 511; interquartile range, 220-978) than on 125 ms reconstructions (538; 203-1050, p < 0.001). Median AVC scores [2809 (2009-3952) versus 3177 (2158-4273)] and median MAC scores [226 (0-1284) versus 251 (0-1574)] were also significantly smaller on 66ms than on 125ms reconstructions (p < 0.001). Reclassification of CAC and AVC risk categories occurred in 4% and 11% of cases, respectively, whereby the risk category was always overestimated on 125ms reconstructions. Image blur artifacts were significantly less on 66ms as opposed to 125 ms reconstructions (p < 0.001). Intra-individual analyses indicate that temporal resolution significantly impacts on calcium scoring with cardiac CT, with CAC, MAC, and AVC being overestimated at lower temporal resolution because of increased motion artifacts eventually leading to an overestimation of patient risk.

Pre-interventional renal artery calcification and survival after transcatheter aortic valve implantation

The prognostic significance of renal artery calcification (RAC) is unknown in patients with severe aortic stenosis (AS) eligible for transcatheter aortic valve implantation (TAVI). RAC can be assessed by computed tomography (CT) performed during pre-interventional planning for TAVI. This study aimed at investigating the utility of RAC for predicting survival after TAVI. In this longitudinal cohort study, RAC volume was measured by CT in 268 consecutive patients with severe AS undergoing TAVI. Association of RAC with mortality was assessed using Cox regression analysis. RAC was evaluated as a binary parameter and in a supplementary analysis as a logarithmically transformed continuous variable. Over a median follow-up time of 9.6 years, 237 (88.4%) patients died, with 174 (73.4%) deaths attributable to a cardiovascular cause. RAC was highly prevalent (N = 150 (86.2%)) among patients suffering cardiovascular death. Competing risk cumulative incidence curves revealed a higher occurrence of cardiovascular death in patients with RAC (P-value = 0.008), while this was not the case for non-cardiovascular death (P-value = 0.71). RAC was independently associated with cardiovascular death (HR 1.61 [95% CI: 1.01-2.57]; P = 0.047) after adjustment for age, sex, cardiovascular risk factors, impaired renal function, and aortic valve calcification. The presence or absence of RAC rather than its volume was important in all the analyses. RAC is a strong and independent predictor of cardiovascular death in patients with severe AS undergoing TAVI. Given its favourable properties for event prediction, RAC may be considered valuable for prognostic assessment of TAVI patients.

The Current Landscape of Artificial Intelligence in Imaging for Transcatheter Aortic Valve Replacement

Purpose

This review explores the current landscape of AI applications in imaging for TAVR, emphasizing the potential and limitations of these tools for (1) automating the image analysis and reporting process, (2) improving procedural planning, and (3) offering additional insight into post-TAVR outcomes. Finally, the direction of future research necessary to bridge these tools towards clinical integration is discussed.

Recent Findings

Transcatheter aortic valve replacement (TAVR) has become a pivotal treatment option for select patients with severe aortic stenosis, and its indication for use continues to broaden. Noninvasive imaging techniques such as CTA and MRA have become routine for patient selection, preprocedural planning, and predicting the risk of complications. As the current methods for pre-TAVR image analysis are labor-intensive and have significant inter-operator variability, experts are looking towards artificial intelligence (AI) as a potential solution.

Summary

AI has the potential to significantly enhance the planning, execution, and post-procedural follow up of TAVR. While AI tools are promising, the irreplaceable value of nuanced clinical judgment by skilled physician teams must not be overlooked. With continued research, collaboration, and careful implementation, AI can become an integral part in imaging for TAVR, ultimately improving patient care and outcomes.

Predicting mortality after transcatheter aortic valve replacement using preprocedural CT

Transcatheter aortic valve replacement (TAVR) is a widely used intervention for patients with severe aortic stenosis. Identifying high-risk patients is crucial due to potential postprocedural complications. Currently, this involves manual clinical assessment and time-consuming radiological assessment of preprocedural computed tomography (CT) images by an expert radiologist. In this study, we introduce a probabilistic model that predicts post-TAVR mortality automatically using unprocessed, preprocedural CT and 25 baseline patient characteristics. The model utilizes CT volumes by automatically localizing and extracting a region of interest around the aortic root and ascending aorta. It then extracts task-specific features with a 3D deep neural network and integrates them with patient characteristics to perform outcome prediction. As missing measurements or even missing CT images are common in TAVR planning, the proposed model is designed with a probabilistic structure to allow for marginalization over such missing information. Our model demonstrates an AUROC of 0.725 for predicting all-cause mortality during postprocedure follow-up on a cohort of 1449 TAVR patients. This performance is on par with what can be achieved with lengthy radiological assessments performed by experts. Thus, these findings underscore the potential of the proposed model in automatically analyzing CT volumes and integrating them with patient characteristics for predicting mortality after TAVR.

Coronary Artery Disease Assessment via On-Site CT Fractional Flow Reserve in Patients Undergoing Transcatheter Aortic Valve Replacement

Purpose To examine the clinical feasibility of workstation-based CT fractional flow reserve (CT-FFR) for coronary artery disease (CAD) evaluation during preprocedural planning in patients undergoing transcatheter aortic valve replacement (TAVR). Materials and Methods In this retrospective single-center study, 434 patients scheduled for TAVR between 2018 and 2020 were screened for study inclusion; a relevant proportion of patients (35.0% [152 of 434]) was not suitable for evaluation due to insufficient imaging properties. A total of 112 patients (mean age, 82.1 years ± 6.7 [SD]; 58 [52%] men) were included in the study. Invasive angiography findings, coronary CT angiography results, and Agatston score were acquired and compared with on-site CT-FFR computation for evaluation of CAD and prediction of major adverse cardiovascular events (MACE) within a 24-month follow-up. Results Hemodynamic relevant CAD, as suggested by CT-FFR of 0.80 or less, was found in 41 of 70 (59%) patients with stenosis of 50% or more. MACE occurred in 23 of 112 (20.5%) patients, from which 14 of 23 had stenoses with CT-FFR of 0.80 or less (hazard ratio [HR], 3.33; 95% CI: 1.56, 7.10; P = .002). CT-FFR remained a significant predictor of MACE after inclusion in a multivariable model with relevant covariables (HR, 2.89; 95% CI: 1.22, 6.86; P = .02). An Agatston score of 1000 Agatston units or more (HR, 2.25; 95% CI: 0.98, 5.21; P = .06) and stenoses of 50% or more determined via invasive angiography (HR, 0.94; 95% CI: 0.41, 2.17; P = .88) were not significant predictors of MACE. Conclusion Compared with conventional CAD markers, CT-FFR better predicted adverse outcomes after TAVR. A relevant portion of the screened cohort, however, was not suitable for CT-based CAD evaluation. Keywords: CT, Transcatheter Aortic Valve Implantation/Replacement (TAVI/TAVR), Cardiac, Coronary Arteries, Outcomes Analysis © RSNA, 2024 See also the commentary by Weir-McCall and Pugliese in this issue.

Coronary Artery Calcium Score Predicts Major Adverse Cardiovascular Events in Stable Chest Pain

Background Coronary artery calcium (CAC) has prognostic value for major adverse cardiovascular events (MACE) in asymptomatic individuals, whereas its role in symptomatic patients is less clear. Purpose To assess the prognostic value of CAC scoring for MACE in participants with stable chest pain initially referred for invasive coronary angiography (ICA). Materials and Methods This prespecified subgroup analysis from the Diagnostic Imaging Strategies for Patients With Stable Chest Pain and Intermediate Risk of Coronary Artery Disease (DISCHARGE) trial, conducted between October 2015 and April 2019 across 26 centers in 16 countries, focused on adult patients with stable chest pain referred for ICA. Participants were randomly assigned to undergo either ICA or coronary CT. CAC scores from noncontrast CT scans were categorized into low, intermediate, and high groups based on scores of 0, 1-399, and 400 or higher, respectively. The end point of the study was the occurrence of MACE (myocardial infarction, stroke, and cardiovascular death) over a median 3.5-year follow-up, analyzed using Cox proportional hazard regression tests. Results The study involved 1749 participants (mean age, 60 years ± 10 [SD]; 992 female). The prevalence of obstructive coronary artery disease (CAD) at CT angiography rose from 4.1% (95% CI: 2.8, 5.8) in the CAC score 0 group to 76.1% (95% CI: 70.3, 81.2) in the CAC score 400 or higher group. Revascularization rates increased from 1.7% to 46.2% across the same groups (P < .001). The CAC score 0 group had a lower MACE risk (0.5%; HR, 0.08 [95% CI: 0.02, 0.30]; P < .001), as did the 1-399 CAC score group (1.9%; HR, 0.27 [95% CI: 0.13, 0.59]; P = .001), compared with the 400 or higher CAC score group (6.8%). No significant difference in MACE between sexes was observed (P = .68). Conclusion In participants with stable chest pain initially referred for ICA, a CAC score of 0 showed very low risk of MACE, and higher CAC scores showed increasing risk of obstructive CAD, revascularization, and MACE at follow-up. Clinical trial registration no. NCT02400229 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Hanneman and Gulsin in this issue.

Cardiac Virtual Noncontrast Images for Calcium Quantification with Photon-counting Detector CT

Purpose

To assess the accuracy of aortic valve calcium (AVC), mitral annular calcium (MAC), and coronary artery calcium (CAC) quantification and risk stratification using virtual noncontrast (VNC) images from late enhancement photon-counting detector CT as compared with true noncontrast images.

Materials and Methods

This retrospective, institutional review board-approved study evaluated patients undergoing photon-counting detector CT between January and September 2022. VNC images were reconstructed from late enhancement cardiac scans at 60, 70, 80, and 90 keV using quantum iterative reconstruction (QIR) strengths of 2-4. AVC, MAC, and CAC were quantified on VNC images and compared with quantification of AVC, MAC, and CAC on true noncontrast images using Bland-Altman analyses, regression models, intraclass correlation coefficients (ICC), and Wilcoxon tests. Agreement between severe aortic stenosis likelihood categories and CAC risk categories determined from VNC and true noncontrast images was assessed by weighted κ analysis.

Results

Ninety patients were included (mean age, 80 years ± 8 [SD]; 49 male patients). Scores were similar on true noncontrast images and VNC images at 80 keV for AVC and MAC, regardless of QIR strengths, and VNC images at 70 keV with QIR 4 for CAC (all P > .05). The best results were achieved using VNC images at 80 keV with QIR 4 for AVC (mean difference, 3; ICC = 0.992; r = 0.98) and MAC (mean difference, 6; ICC = 0.998; r = 0.99), and VNC images at 70 keV with QIR 4 for CAC (mean difference, 28; ICC = 0.996; r = 0.99). Agreement between calcification categories was excellent on VNC images at 80 keV for AVC (κ = 0.974) and on VNC images at 70 keV for CAC (κ = 0.967).

Conclusion

VNC images from cardiac photon-counting detector CT enables patient risk stratification and accurate quantification of AVC, MAC, and CAC.Keywords: Coronary Arteries, Aortic Valve, Mitral Valve, Aortic Stenosis, Calcifications, Photon-counting Detector CT Supplemental material is available for this article © RSNA, 2023.

Computed tomography-based pericoronary adipose tissue attenuation in patients undergoing TAVR: a novel method for risk assessment

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 .

First in-human quantitative plaque characterization with ultra-high resolution coronary photon-counting CT angiography

Purpose

To assess the effect of ultra-high-resolution coronary CT angiography (CCTA) with photon-counting detector (PCD) CT on quantitative coronary plaque characterization.

Materials and methods

In this IRB-approved study, 22 plaques of 20 patients (7 women; mean age 77 ± 8 years, mean body mass index 26.1 ± 3.6 kg/m2) undergoing electrocardiography (ECG)-gated ultra-high-resolution CCTA with PCD-CT were included. Images were reconstructed with a smooth (Bv40) and a sharp (Bv64) vascular kernel, with quantum iterative reconstruction (strength level 4), and using a slice thickness of 0.6, 0.4, and 0.2 mm, respectively (field-of-view 200 mm × 200 mm, matrix size 512 × 512 pixels). Reconstructions with the Bv40 kernel and slice thickness of 0.6 mm served as the reference standard. After identification of a plaque in coronary arteries with a vessel diameter ≥2 mm, plaque composition was determined using a dedicated, semi-automated plaque quantification software. Total plaque, calcified, fibrotic, and lipid-rich plaque components were quantified in all datasets.

Results

Median plaque volume was highest (23.5 mm3, interquartiles 17.9-34.3 mm3) for reconstructions with the reference standard and lowest for ultra-high-resolution reconstructions with a slice thickness of 0.2 mm and the Bv64 kernel (18.1 mm3, interquartiles 14.1-25.8 mm3, p < 0.001). Reconstructions with the reference standard showed largest calcified (85.1%, interquartiles 76.4-91.1%) and smallest lipid-rich plaque components (0.5%, interquartiles 0.0-1.5%). Smallest calcified plaque components (75.2%, interquartiles 69.9-80.8%) and largest lipid-rich components (6.7%, interquartiles 5.1-8.4%) were found for ultra-high-resolution reconstructions with a slice thickness of 0.2 mm and the Bv64 kernel. At an identical slice thickness, volume of calcified components was always lower, and volume of lipid-rich components was always higher for reconstructions with the Bv64 kernel compared with reconstructions with the Bv40 kernel (all, p < 0.001).

Conclusion

This patient study indicates significant differences of ultra-high-resolution scanning with PCD-CT on quantitative coronary plaque characterization. Reduced blooming artifacts may allow improved visualization of fibrotic and lipid-rich plaque components with the ultra-high-resolution mode of PCD-CT.

The Role of Cardiac Computed Tomography in Heart Failure

PURPOSE OF REVIEW

Cardiac computed tomography (CT) is becoming a more widely applied tool in the diagnosis and management of a variety of cardiovascular conditions, including heart failure. The aim of this narrative review is to examine the role of cardiac CT in patients with heart failure.

RECENT FINDINGS

Coronary computed tomographic angiography has robust diagnostic accuracy for ruling out coronary artery disease. These data are reflected in updated guidelines from major cardiology organizations. New roles for cardiac CT in myocardial imaging, perfusion scanning, and periprocedural planning, execution, and monitoring are being implemented. Cardiac CT is useful in ruling out coronary artery disease its diagnostic accuracy, accessibility, and safety. It is also intricately linked to invasive cardiac procedures that patients with heart failure routinely undergo.

Tube voltage-independent coronary calcium scoring on a first-generation dual-source photon-counting CT-a proof-of-principle phantom study

To evaluate the accuracy of coronary artery calcium (CAC) scoring at various tube voltages and different monoenergetic image reconstructions on a first-generation dual-source photon-counting detector CT (PCD-CT). A commercially available anthropomorphic chest phantom with calcium inserts was scanned at different tube voltages (90 kV, Sn100kV, 120 kV, and Sn140kV) on a first-generation dual-source PCD-CT system with quantum technology using automatic exposure control with an image quality (IQ) level of 20. The same phantom was also scanned on a conventional energy-integrating detector CT (120 kV; weighted filtered back projection) for reference. Extension rings were used to emulate different patient sizes. Virtual monoenergetic images at 65 keV and 70 keV applying different levels of quantum iterative reconstruction (QIR) were reconstructed from the PCD-CT data sets. CAC scores were determined and compared to the reference. Radiation doses were noted. At an IQ level of 20, radiation doses ranged between 1.18 mGy and 4.64 mGy, depending on the tube voltage and phantom size. Imaging at 90 kV or Sn100kV was associated with a size-dependent radiation dose reduction between 23% and 48% compared to 120 kV. Tube voltage adapted image reconstructions with 65 keV and QIR 3 at 90 kV and with 70 keV and QIR 1 at Sn100kV allowed to calculate CAC scores comparable to conventional EID-CT scans with a percentage deviation of ≤ 5% for all phantom sizes. Our phantom study indicates that CAC scoring with dual-source PCD-CT is accurate at various tube voltages, offering the possibility of substantial radiation dose reduction.

Coronary Calcium Scoring with First Generation Dual-Source Photon-Counting CT-First Evidence from Phantom and In-Vivo Scans

We evaluated the accuracy of coronary artery calcium (CAC) scoring on a dual-source photon-counting detector CT (PCD-CT). An anthropomorphic chest phantom underwent ECG-gated sequential scanning on a PCD-CT at 120 kV with four radiation dose levels (CTDIvol, 2.0–8.6 mGy). Polychromatic images at 120 kV (T3D) and virtual monoenergetic images (VMI), from 60 to 75 keV without quantum iterative reconstruction (no QIR) and QIR strength levels 1–4, were reconstructed. For reference, the same phantom was scanned on a conventional energy-integrating detector CT (120 kV; filtered back projection) at identical radiation doses. CAC scoring in 20 patients with PCD-CT (120 kV; no QIR and QIR 1–4) were included. In the phantom, there were no differences between CAC scores of different radiation doses (all, p > 0.05). Images with 70 keV, no QIR (CAC score, 649); 65 keV, QIR 3 (656); 65 keV; QIR4 (648) and T3D, QIR4 (656) showed a <1% deviation to the reference (653). CAC scores significantly decreased at increasing QIR levels (all, p < 0.001) and for each 5 keV-increase (all, p < 0.001). Patient data (median CAC score: 86 [inter-quartile range: 38–978] at 70 keV) confirmed relationships and differences between reconstructions from the phantom. First phantom and in-vivo experience with a clinical dual-source PCD-CT system shows accurate CAC scoring with VMI reconstructions at different radiation dose levels.