Background: A pathophysiological interplay exists between plaque morphology and coronary physiology. Machine learning (ML) is increasingly being applied to coronary computed tomography angiography (CCTA) for cardiovascular risk stratification. We sought to assess the performance of a ML score integrating CCTA-based quantitative plaque features for predicting vessel-specific ischemia by invasive fractional flow reserve (FFR) and impaired myocardial blood flow (MBF) by positron emission tomography (PET). Methods: This post-hoc analysis of the PACIFIC trial (Prospective Comparison of Cardiac Positron Emission Tomography/Computed Tomography [CT]‚ Single Photon Emission Computed Tomography/CT Perfusion Imaging and CT Coronary Angiography with Invasive Coronary Angiography) included 208 patients with suspected coronary artery disease who prospectively underwent CCTA‚ [ ¹⁵ O]H ₂ O PET, and invasive FFR. Plaque quantification from CCTA was performed using semiautomated software. An ML algorithm trained on the prospective NXT trial (484 vessels) was used to develop a ML score for the prediction of ischemia (FFR≤0.80), which was then evaluated in 581 vessels from the PACIFIC trial. Thereafter, the ML score was applied for predicting impaired hyperemic MBF (≤2.30 mL/min per g) from corresponding PET scans. The performance of the ML score was compared with CCTA reads and noninvasive FFR derived from CCTA (FFR _CT ). Results: One hundred thirty-nine (23.9%) vessels had FFR-defined ischemia, and 195 (33.6%) vessels had impaired hyperemic MBF. For the prediction of FFR-defined ischemia, the ML score yielded an area under the receiver-operating characteristic curve of 0.92, which was significantly higher than that of visual stenosis grade (0.84; P <0.001) and comparable with that of FFR _CT (0.93; P =0.34). Quantitative percent diameter stenosis and low-density noncalcified plaque volume had the greatest ML feature importance for predicting FFR-defined ischemia. When applied for impaired MBF prediction, the ML score exhibited an area under the receiver-operating characteristic curve of 0.80; significantly higher than visual stenosis grade (area under the receiver-operating characteristic curve 0.74; P =0.02) and comparable with FFR _CT (area under the receiver-operating characteristic curve 0.77; P =0.16). Conclusions: An externally validated ML score integrating CCTA-based quantitative plaque features accurately predicts FFR-defined ischemia and impaired MBF by PET, performing superiorly to standard CCTA stenosis evaluation and comparably to FFR _CT .

Acute brain injury (ABI) occurs frequently in patients receiving venoarterial extracorporeal membrane oxygenation (VA-ECMO). We examined the association between peri-cannulation arterial carbon dioxide tension (PaCO₂) and ABI with granular blood gas data. We retrospectively analyzed adult patients who underwent VA-ECMO at a tertiary care center with standardized neuromonitoring. Pre- and post-cannulation PaCO₂ were defined as the mean of all PaCO₂ values in the 12 hours before and after cannulation, respectively. Peri-cannulation PaCO₂ drop (∆PaCO₂) equaled pre- minus post-cannulation PaCO₂. ABI included intracranial hemorrhage (ICH), ischemic stroke, hypoxic-ischemic brain injury, cerebral edema, seizure, and brain death. Univariable logistic regression analysis was performed for the presence of ABI. Out of 129 VA-ECMO patients (median age = 60, 63% male), 43 (33%) patients experienced ABI. Patients had a median of 11 (interquartile range: 8–14) peri-cannulation PaCO₂ values. Comparing patients with and without ABI, pre-cannulation (39 vs. 42 mm Hg; p = 0.38) and post-cannulation (37 vs. 36 mm Hg; p = 0.82) PaCO₂ were not different. However, higher pre-cannulation PaCO₂ (odds ratio [OR] = 2.10; 95% confidence interval [CI] = 1.10–4.00; p = 0.02) and larger ∆PaCO₂ (OR = 2.69; 95% CI = 1.18–6.13; p = 0.02) were associated with ICH. In conclusion, in a cohort with granular arterial blood gas (ABG) data and a standardized neuromonitoring protocol, higher pre-cannulation PaCO₂ and larger ∆PaCO₂ were associated with increased prevalence of ICH.