ABSTRACT
AIMS: This study was aimed at investigating whether a machine learning (ML)-based coronary computed tomographic angiography (CCTA) derived fractional flow reserve (CT-FFR) SYNTAX score (SS), 'Functional SYNTAX score' (FSSCTA), would predict clinical outcome in patients with three-vessel coronary artery disease (CAD). METHODS AND RESULTS: The SS based on CCTA (SSCTA) and ICA (SSICA) were retrospectively collected in 227 consecutive patients with three-vessel CAD. FSSCTA was calculated by combining the anatomical data with functional data derived from a ML-based CT-FFR assessment. The ability of each score system to predict major adverse cardiac events (MACE) was compared. The difference between revascularization strategies directed by the anatomical SS and FSSCTA was also assessed. Two hundred and twenty-seven patients were divided into two groups according to the SSCTA cut-off value of 22. After determining FSSCTA for each patient, 22.9% of patients (52/227) were reclassified to a low-risk group (FSSCTA ≤ 22). In the low- vs. intermediate-to-high (>22) FSSCTA group, MACE occurred in 3.2% (4/125) vs. 34.3% (35/102), respectively (P < 0.001). The independent predictors of MACE were FSSCTA (OR = 1.21, P = 0.001) and diabetes (OR = 2.35, P = 0.048). FSSCTA demonstrated a better predictive accuracy for MACE compared with SSCTA (AUC: 0.81 vs. 0.75, P = 0.01) and SSICA (0.81 vs. 0.75, P < 0.001). After FSSCTA was revealed, 52 patients initially referred for CABG based on SSCTA would have been changed to PCI. CONCLUSION: Recalculating SS by incorporating lesion-specific ischaemia as determined by ML-based CT-FFR is a better predictor of MACE in patients with three-vessel CAD. Additionally, the use of FSSCTA may alter selected revascularization strategies in these patients.
ABSTRACT
PURPOSE: We prospectively investigate the feasibility of a patient specific automated tube voltage selection (ATVS)-based coronary artery calcium scoring (CACS) protocol, using a kV-independent reconstruction algorithm, to achieve significant dose reductions while maintaining the overall cardiac risk classification. METHODS: Forty-three patients (mean age, 61.8 ± 9.0 years; 40% male) underwent a clinically indicated CACS scan at 120kVp, as well as an additional CACS acquisition using an individualized tube voltage between 70 and 130kVp based on the ATVS selection (CARE-kV). Datasets of the additional CACS scans were reconstructed using a kV-independent algorithm that allows for calcium scoring without changing the weighting threshold of 130HU, regardless of the tube voltage chosen for image acquisition. Agatston scores and radiation dose derived from the different ATVS-based CACS studies were compared to the standard acquisition at 120kVp. RESULTS: Thirteen patients displayed a score of 0 and were correctly identified with the ATVS protocol. Agatston scores derived from the standard 120kVp (median, 33.4; IQR, 0-289.7) and the patient-tailored kV-independent protocol (median, 47.5; IQR, 0-287.5) showed no significant differences (p = 0.094). The intra-class correlation for Agatston scores derived from the two different protocols was excellent (ICC = 0.99). The mean dose-length-product was 29.8 ± 11.9 mGy × cm using the ATVS protocol and 31.7 ± 11.4 mGy × cm using the standard 120kVp protocol (p < 0.001). Additionally, 95% of patients were classified into the same risk category (0, 1-10, 11-100, 101-400, or > 400) using the patient-tailored protocol. CONCLUSIONS: ATVS-based CACS, using a kV-independent algorithm, allows for high accuracy compared to the standard 120kVp scanning, while significantly reducing radiation dose parameters. KEY POINTS: ⢠ATVS allows for CT scanning with reduced radiation dose values. ⢠KV-independent CACS is feasible at any tube voltage between 70 and 130 kVp. ⢠ATVS applied to kV-independent CACS can significantly reduce the radiation dose.