Prognostic Value of Cardiac CT Delayed Enhancement Imaging in Patients With Suspected Coronary Artery Disease

Regional Distribution of Extracellular Volume Quantified by Cardiac CT in Aortic Stenosis: Insights Into Disease Mechanisms and Impact on Outcomes

BACKGROUND

Extracellular volume fraction (ECV) is a marker for myocardial fibrosis and infiltration, can be quantified using cardiac computed tomography (ECVCT), and has prognostic utility in several diseases. This study aims to map out regional differences in ECVCT to obtain greater insights into the pathophysiological mechanisms of ECV expansion and its clinical implications.

METHODS

Three prospective cohorts were included: patients with aortic stenosis (AS) and coexisting AS and transthyretin cardiac amyloidosis were referred for a transcatheter aortic valve replacement and had ECG-gated CT angiography and Technetium-99m-labelled 3,3-diphosphono-1,2-propanodicarboxylic acid scintigraphy to differentiate between the 2 cohorts. Controls had CT angiography and cardiac magnetic resonance demonstrating no significant coronary artery disease or infarction. Global and regional ECVCT was analyzed, and its association with mortality was assessed for patients with AS.

RESULTS

In 199 patients, controls (n=65; 66% male), AS (n=115), and coexisting AS and transthyretin cardiac amyloidosis (n=19) had a global ECVCT of 26.1 (25.0-27.8%) versus 29.1 (27.5-31.1%) versus 37.4 (32.5-46.6%), respectively; P<0.001. Across cohorts, ECVCT was higher at the base (versus apex), the inferoseptum (versus anterolateral wall), and the subendocardium (versus subepicardium); P<0.05 for all. Among patients with AS, epicardial ECVCT, rather than any other regional value or global ECVCT, was the strongest predictor of mortality at a median of 3.9 (max 6.3) years (adjusted hazard ratio, 1.21 [95% CI, 1.08-1.36]; P=0.002).

CONCLUSIONS

Regional differences in ECVCT suggest a predilection for fibrosis and amyloid infiltration at the base, subendocardium, inferior wall, and septum more than the anterior and lateral myocardium. ECVCT can predict long-term mortality with the subepicardium demonstrating the strongest discriminatory power.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifiers: NCT03029026 and NCT03094143.

Myocardial late enhancement and extracellular volume with single-energy, dual-energy, and photon-counting computed tomography

Computed tomography late enhancement (CT-LE) is emerging as a non-invasive technique for cardiac diagnosis with wider accessibility compared to MRI, despite its typically lower contrast-to-noise ratio. Optimizing CT-LE image quality necessitates a thorough methodology addressing contrast administration, timing, and radiation dose, alongside a robust understanding of extracellular volume (ECV) quantification methods. This review summarizes CT-LE protocols, clinical utility, and advances in ECV measurement through both single-energy and dual-energy CT. It also highlights photon-counting detector CT technology as an innovative means to potentially improve image quality and reduce radiation exposure.

The cardiac computed tomography-derived extracellular volume fraction predicts patient outcomes and left ventricular mass reductions after transcatheter aortic valve implantation for aortic stenosis

BACKGROUND

Transcatheter aortic valve implantation (TAVI) improved outcome of patients with severe aortic valve stenosis (AS). Myocardial fibrosis is associated with AS-related pathological left ventricular (LV) remodeling and predicts cardiovascular mortality after TAVI. The present study aimed to investigate the impact of preoperative extracellular volume (ECV) assessed by computed tomography (CT) on left ventricular mass (LVM) regression and clinical outcomes in severe AS patients after TAVI.

METHODS

We examined 71 consecutive severe AS patients who underwent CT with ECV determination before TAVI. ECV was calculated as the ratio of the change in Hounsfield units in the myocardium and LV blood before and after contrast administration, multiplied by (1-hematocrit). Delayed scan was performed at 5 min after contrast injection. Echocardiography was performed before and 6 months after TAVI. The primary endpoint was heart failure (HF) hospitalization after TAVI. Patients were divided into two subgroups according to the median value of global ECV with 32 % (Low-ECV group: n = 35, and High-ECV group: n = 36).

RESULTS

No significant differences were observed in background characteristics between the 2 groups. However, the preoperative LV ejection fraction and LVM index were similar between the 2 groups, the Low-ECV group had greater LVM index reduction than the High-CV group after 6 months (p < 0.001). Kaplan-Meier curves demonstrated that the High-ECV group had significantly higher rate of HF hospitalization than the Low-ECV group (p = 0.016). In addition, multivariate analyses identified high global ECV as an independent predictor of HF hospitalization (HR 10.8, 95 % confidence interval 1.36 to 84.8, p = 0.024).

CONCLUSION

The low preoperative ECV assessed by CT is associated with the greater LVM regression, and predict better outcome in AS patients after TAVI.

Deep Learning-based Post Hoc CT Denoising for Myocardial Delayed Enhancement

Background To improve myocardial delayed enhancement (MDE) CT, a deep learning (DL)-based post hoc denoising method supervised with averaged MDE CT data was developed. Purpose To assess the image quality of denoised MDE CT images and evaluate their diagnostic performance by using late gadolinium enhancement (LGE) MRI as a reference. Materials and methods MDE CT data obtained by averaging three acquisitions with a single breath hold 5 minutes after the contrast material injection in patients from July 2020 to October 2021 were retrospectively reviewed. Preaveraged images obtained in 100 patients as inputs and averaged images as ground truths were used to supervise a residual dense network (RDN). The original single-shot image, standard averaged image, RDN-denoised original (DL_original) image, and RDN-denoised averaged (DL_ave) image of holdout cases were compared. In 40 patients, the CT value and image noise in the left ventricular cavity and myocardium were assessed. The segmental presence of MDE in the remaining 40 patients who underwent reference LGE MRI was evaluated. The sensitivity, specificity, and accuracy of each type of CT image and the improvement in accuracy achieved with the RDN were assessed using odds ratios (ORs) estimated with the generalized estimation equation. Results Overall, 180 patients (median age, 66 years [IQR, 53-74 years]; 107 men) were included. The RDN reduced image noise to 28% of the original level while maintaining equivalence in the CT values (P < .001 for all). The sensitivity, specificity, and accuracy of the original images were 77.9%, 84.4%, and 82.3%, of the averaged images were 89.7%, 87.9%, and 88.5%, of the DL_original images were 93.1%, 87.5%, and 89.3%, and of the DL_ave images were 95.1%, 93.1%, and 93.8%, respectively. DL_original images showed improved accuracy compared with the original images (OR, 1.8 [95% CI: 1.2, 2.9]; P = .011) and DL_ave images showed improved accuracy compared with the averaged images (OR, 2.0 [95% CI: 1.2, 3.5]; P = .009). Conclusion The proposed denoising network supervised with averaged CT images reduced image noise and improved the diagnostic performance for myocardial delayed enhancement CT. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Vannier and Wang in this issue.