Journal of cardiovascular computed tomography最新文献

Background: High temporal resolution (TR) in CT is essential for reducing motion artifacts from rapidly moving structures like the heart. Although the conventional impulse method can measure TR, it requires specialized equipment to accelerate a sphere, which limits its practicality.

Objectives: This study aimed to develop and validate a simplified pendulum method for TR measurement and validate that it provides equivalent measurements to the conventional approach.

Methods: TR was measured using the proposed pendulum method and the conventional slingshot method. Fifty scans were acquired for each method at pitch factors (PF) of 0.8 and 1.2. TR was quantified using full width at half maximum (FWHM) and full width at tenth maximum (FWTM). Equivalence was evaluated with the two one-sided tests (TOST).

Results: The pendulum method demonstrated statistical equivalence to the slingshot method across all tested parameters. For PF 0.8, the FWHM was 0.55 ​± ​0.03 ​s for the pendulum method versus 0.54 ​± ​0.04 ​s for the slingshot method (TOST, p ​= ​0.005). At PF of 1.2, the FWHM was 0.15 ​± ​0.01 ​s for both methods, which were also statistically equivalent (TOST, p ​= ​0.021).

Conclusion: The pendulum method provides a simple, reproducible approach for TR measurement, facilitating parameter optimization in clinical and research imaging.

Background: Vascular inflammation is a key aspect of plaque vulnerability. Cross-sectional studies suggest that increased carotid perivascular adipose tissue (PVAT) attenuation on CTA, which is thought to reflect vascular inflammation, is associated with stroke.

Objectives: We investigated the predictive value of carotid PVAT attenuation for ischemic stroke and TIA in a longitudinal study of symptomatic patients with carotid plaque.

Methods: We included patients with recent TIA or stroke and a ≥2 ​mm carotid plaque with <70 ​% stenosis who underwent CTA and MRI and were clinically followed-up for 5 years. Mean PVAT attenuation (-190 to -30 Hounsfield Units (HU)) was quantified within a radial distance from the outer vessel wall equal to the vessel diameter on the CTA slice containing the thickest plaque. Cox proportional hazards models assessed associations with ipsilateral stroke and TIA risk. Predictive value was compared with intraplaque hemorrhage (IPH) and the European Carotid Surgery Trial (ECST) score using the C-index.

Results: Among 159 patients (74 ​% men; 69 (63-73) years), 11 ischemic strokes and 10 TIAs occurred over 5.1 (3.1-5.6) years. Increased PVAT attenuation was independently associated with ischemic stroke or TIA (HR: 3.21 per 10 HU increase, 95%CI:1.70-6.05) and ischemic stroke alone (HR: 5.60, 95%CI:1.93-16.31). PVAT attenuation alone predicted ischemic stroke or TIA (C-index: 0.71, 95%CI:0.70-0.73) and ischemic stroke alone (C-index: 0.78, 95%CI:0.63-0.93). Adding PVAT attenuation improved prediction beyond IPH (C-index: 0.66-0.68 to 0.81-0.84) and the ECST score (0.64-0.75 to 0.75-0.86, respectively).

Conclusion: In symptomatic patients, PVAT attenuation is an independent marker for ischemic stroke and TIA risk.

Background: Deep learning-based fractional flow reserve derived from coronary CT angiography (CT-FFR) enables noninvasive assessment of lesion-specific ischemia. Onsite CT-FFR systems provide near-real-time physiologic evaluation at the workstation, potentially reducing unnecessary invasive testing. This study evaluated the diagnostic performance of a novel onsite deep learning CT-FFR algorithm compared with invasive instantaneous wave-free ratio (iFR).

Methods: We retrospectively analyzed 44 patients (44 lesions) who underwent clinically indicated coronary CT angiography (CCTA) and invasive iFR. CT-FFR values were generated using an onsite deep learning algorithm (cFFR v6) 1-2 ​cm distal to visually identified stenoses. Physiologic significance was defined as CT-FFR ≤0.80 or iFR ≤0.89. Diagnostic performance metrics were calculated overall and within CCTA stenosis strata (<50 ​%, 50-70 ​%, >70 ​%). ROC analysis and Pearson correlation assessed discriminative ability and linear association. Additional comparative analyses evaluated diagnostic accuracy of CCTA ≥50 ​% and ≥70 ​% thresholds relative to iFR and quantified incremental diagnostic value of CT-FFR over CCTA alone.

Results: Of 44 lesions, 28 (63.6 ​%) were iFR-positive and 30 (68.2 ​%) were CT-FFR-positive. CT-FFR demonstrated a sensitivity of 89.3 ​%, specificity of 68.8 ​%, positive predictive value of 83.3 ​%, negative predictive value of 78.6 ​%, and accuracy of 81.8 ​%; the area under the ROC curve was 0.79 (95 ​% CI, 0.66-0.92). CT-FFR and iFR showed a modest but significant correlation (r ​≈ ​0.37). Performance remained favorable in moderate (40-70 ​%) stenoses (AUC 0.73) and severe (>70 ​%) stenoses (AUC 0.84). In contrast, CCTA ≥50 ​% and ≥70 ​% thresholds showed limited discriminatory ability versus iFR (AUC 0.44 and 0.52, respectively). Compared with CCTA alone, CT-FFR improved both sensitivity and specificity and substantially increased AUC across both thresholds.

Conclusion: The onsite deep learning CT-FFR algorithm demonstrated good diagnostic agreement with invasive iFR and maintained performance across stenosis severity categories, while providing clear incremental value over CCTA stenosis assessment alone. These findings support the feasibility of rapid, workstation-integrated physiologic assessment during CCTA interpretation. Larger multicenter studies are needed to validate these results and clarify the clinical role of onsite CT-FFR.

Background: Low-kilovolt (kV), low-dose scanning combined with deep learning-based image reconstruction (DLIR) is increasingly adopted in clinical practice. However, it often introduces biases in the quantification and risk stratification of coronary artery calcification (CAC).

Objective: This study proposes a voxel-based CT attenuation correction method to enable accurate CAC assessment under low-kV imaging.

Methods: Phantom scans containing various inserts were acquired using a standard protocol (120 ​kVp with filtered back projection, STD group) and a low-kV protocol (80 ​kVp with DLIR, low-kV group). A linear regression model was established to derive a correction formula mapping CT attenuation from the low-kV to the STD. Subsequently, patients referred for CAC scoring were prospectively enrolled. Each patient underwent two scans (STD and low-kV). Voxel-wise CT attenuations in the low-kV images were corrected using the phantom-derived calibration formula. Automated CAC analysis software was used to compute calcified volume, equivalent mass, and Agatston score, followed by risk stratification into standard categories (0, 10, 100, 400). Corrected low-kV measurements were compared to those from the STD. Objective image quality was assessed through CT attenuation, standard deviation (SD) and signal-to-noise ratio (SNR). Subjective quality was evaluated using a 5-point Likert scale.

Results: A total of 190 patients were included. The low-kV group achieved a 77.6 ​% reduction in radiation dose compared to the STD group. Prior to correction, the low-kV group significantly overestimated calcified volume, equivalent mass, Agatston score, and risk category (all P ​< ​0.05). After voxel-based correction, no statistically significant differences remained compared to the STD group (all P ​> ​0.05). The bias in calcified volume, equivalent mass, and Agatston score were reduced from 48.14 ​± ​73.66, 19.48 ​± ​33.44, and 62.44 ​± ​94.46 to 6.63 ​± ​23.56, -0.44 ​± ​6.68, and 3.05 ​± ​28.25, respectively. The risk stratification misclassification rate decreased from 20.53 ​% to 5.79 ​%. The low-kV group outperformed the STD group in objective image assessments, showing superior CT attenuation, SD and SNR. There were no significant differences in subjective image assessments.

Conclusion: The proposed voxel-based correction method effectively mitigates the overestimation bias introduced by low-kV protocols in CAC assessment.

Background: The Agatston score is commonly used for coronary artery calcium (CAC) quantification which integrates calcium volume and density into a single measure. Recent studies suggest CAC volume and mean density offer independent prognostic value. However, normative distributions of these parameters across demographic subgroups are not well characterized.

Methods: A total of 23,844 patients were analyzed who underwent non-contrast ECG-gated cardiac CT at 120 ​kVp from 2010 to 2023 ​at our institution. Patients included were older than 35, asymptomatic, and without prior atherosclerotic cardiovascular disease. CAC volume and mean density were directly quantified using a validated deep learning-based software. Participants were stratified by sex, self-reported race (White, Black), and age (in 10-year strata). Percentile distributions were constructed for CAC total volume and average mean density using a LOESS-based approach to account for the zero-inflated nature of the data. Between-group comparisons were conducted with Mann-Whitney U.

Results: The cohort (mean age 58 ​± ​9 years) included 41 ​% women and 74 ​% White and 10 ​% Black participants. Men had significantly higher CAC volume than women across all race/age strata (59 mm³ (IQR 14-223) vs 28 mm³ (IQR 8-100), p ​< ​0.001). Black men and women generally had lower CAC volumes than their White counterparts, with the exception of Black women, who demonstrated higher CAC volumes than White women in several age strata. Average mean CAC density increased with age and was consistently higher in White patients compared to Black patients (194 HU (IQR 163-226) vs 171 HU (IQR 152-205), p ​< ​0.001), independent of sex. Sex-based differences in CAC volume persisted after stratification by race. Age-related increases in both volume and density were observed in all groups.

Conclusion: This analysis provides percentile distributions of directly measured CAC volume and average mean density across age, sex, and race. The data may better contextualize CAC interpretation and risk stratification.

Introduction: Remnant cholesterol (RC) is an independent predictor of cardiovascular risk (CVR) beyond low-density lipoprotein cholesterol (LDL-C) and has been associated with major adverse cardiovascular events (MACE). However, its prognostic interaction with coronary atherosclerotic burden as assessed by coronary CT angiography (CCTA) remains poorly defined. The aim of this study was to evaluate whether RC acts as an independent factor or as a modulator of the effect of atherosclerotic burden on the risk of death, myocardial infarction, or revascularization in patients without prior coronary events.

Methods: This was a retrospective cohort study including 296 consecutive patients undergoing CCTA for chest pain with no history of coronary events. RC was calculated indirectly and stratified into quartiles. Coronary atherosclerotic burden was assessed using coronary artery calcium (CAC) score, CAD-RADS, segment involvement score (SIS), visual plaque burden, and the presence of high-risk plaques. Adjusted Cox regression models and four-way mediation analyses were employed to evaluate the interaction between RC, plaque burden, and MACE during follow-up.

Results: After a mean follow-up of 6.3 years, 44 MACE occurred in 41 patients (13.3 ​%). Elevated RC (>30 ​mg/dL) was associated with an increased risk of MACE (HR 4.16; 95 ​% CI: 1.2-14.9). No direct association was found between RC and atherosclerotic burden; however, a significant interaction was observed, whereby the likelihood of MACE in patients with higher plaque burden increased more markedly in the presence of elevated RC. These findings were robust and consistent across various models and sensitivity analyses.

Conclusions: RC amplifies the effect of coronary atherosclerosis on the risk of MACE. Its integration with atherosclerotic burden assessment via CCTA may help optimize cardiovascular risk stratification.