Influence of coronary stenosis location on diagnostic performance of machine learning-based fractional flow reserve from CT angiography

BackgroundCompared with invasive fractional flow reserve (FFR), coronary CT angiography (cCTA) is limited in detecting hemodynamically relevant lesions. cCTA-based FFR (CT-FFR) is an approach to overcome this insufficiency by use of computational fluid dynamics. Applying recent innovations in computer science, a machine learning (ML) method for CT-FFR derivation was introduced and showed improved diagnostic performance compared to cCTA alone. We sought to investigate the influence of stenosis location in the coronary artery system on the performance of ML-CT-FFR in a large, multicenter cohort.MethodsThree hundred and thirty patients (75.2% male, median age 63 years) with 502 coronary artery stenoses were included in this substudy of the MACHINE (Machine Learning Based CT Angiography Derived FFR: A Multi-Center Registry) registry. Correlation of ML-CT-FFR with the invasive reference standard FFR was assessed and pooled diagnostic performance of ML-CT-FFR and cCTA was determined separately for the following stenosis locations: RCA, LAD, LCX, proximal, middle, and distal vessel segments.ResultsML-CT-FFR correlated well with invasive FFR across the different stenosis locations. Per-lesion analysis revealed improved diagnostic accuracy of ML-CT-FFR compared with conventional cCTA for stenoses in the RCA (71.8% [95% confidence interval, 63.0%–79.5%] vs. 54.8% [45.7%–63.8%]), LAD (79.3 [73.9–84.0] vs. 59.6 [53.5–65.6]), LCX (84.1 [76.0–90.3] vs. 63.7 [54.1–72.6]), proximal (81.5 [74.6–87.1] vs. 63.8 [55.9–71.2]), middle (81.2 [75.7–85.9] vs. 59.4 [53.0–65.6]) and distal stenosis location (67.4 [57.0–76.6] vs. 51.6 [41.1–62.0]).ConclusionIn a multicenter cohort with high disease prevalence, ML-CT-FFR offered improved diagnostic performance over cCTA for detecting hemodynamically relevant stenoses regardless of their location.     

Mortality prediction in chronic obstructive pulmonary disease and obstructive sleep apnea

BackgroundWe aimed to assess mortality in chronic obstructive pulmonary disease (COPD), obstructive sleep apnea (OSA), and overlap syndrome, and evaluate which polysomnographic indices—apnea-hypopnea index (AHI) or hypoxemic load measurements—better predict mortality within 10 years.MethodsAdults with symptoms suggestive of sleep apnea and airway disease who underwent both polysomnography and spirometry plus bronchodilator response tests between 2000 and 2018 were included and divided into four groups according to presence of COPD and moderate-to-severe OSA (AHI ≥15/h). We estimated mortality using a Cox model adjusted for demographic/anthropometric covariates and comorbidities; this was called clinical model. To evaluate prognostic performance, we compared the concordance index (C-index) between clinical model and extended models, which incorporated one of polysomnographic indices—AHI, sleep time spent with SpO₂ < 90% (TS90), and mean and lowest SpO₂.ResultsAmong 355 participants, patients with COPD alone (57/355, 16.1%) and COPD–OSA overlap syndrome (37/355, 10.4%) had increased all-cause mortality than those who had neither disease (152/355, 42.8%) (adjusted HR, 2.98 and 3.19, respectively). The C-indices of extended models with TS90 (%) and mean SpO₂ were significantly higher than that of clinical model (0.765 vs. 0.737 and 0.756 vs. 0.737, respectively; all P < 0.05); however, the C-index of extended model with AHI was not (0.739 vs. 0.737; P = 0.15).ConclusionsIn this cohort with symptoms of sleep apnea and airway disease, patients with overlap syndrome had increased mortality, but not higher than in those with COPD alone. The measurement of hypoxemic load, not AHI, better predicted mortality.     

Position paper on stress cardiac MRI in chronic coronary syndrome: Endorsed by the Société Française de Radiologie (SFR) the Société Française d’Imagerie CardioVasculaire (SFICV) and the Société Française de Cardiologie (SFC)

This position paper was intended to update the former consensus between the French Societies of Radiology and Cardiology about the use of stress cardiac magnetic resonance imaging (MRI) in chronic coronary syndrome published in 2009. The Delphi method was used to build the present consensus. This expert panel consensus includes recommendations for indications, procedure with patient preparation, stress inducing drugs, acquisition protocol, interpretation and risk stratification by stress MRI.     

Shortcomings on genetic testing of Familial hypercholesterolemia (FH) in India: Can we collaborate to establish Indian FH registry?

Familial hypercholesterolemia (FH) is a common autosomal dominant disorder that affects ～1 in 250–500 individuals globally. The only prevalence study in India shows FH in 15% of patients with premature CAD in North Indians. There are only 6 genetic studies in India of the total mutations, 32% are LDLR mutations, 4% are ApoB, 2% are PCSK9 mutations and the mutational spectrum for 37% is unknown. This calls for widespread genetic screening which could help identify definite FH patients.European Atherosclerosis Society-Familial Hypercholesterolemia Studies Collaboration (EAS- FHSC) has taken an initiative to develop a worldwide registry of FH. India is also a part of the collaboration and 3 groups from Mumbai, Delhi and Chennai are actively contributing to this registry. We believe this review might help to understand the Indian scenario of FH and investigators across India can contribute in managing FH in India and further help in the detection, diagnosis and treatment.