Intraoperative transit time flow measurements during off-pump coronary artery bypass surgery: The impact of coronary stenosis on competitive flow.

BACKGROUND: Combining preoperative angiography findings with intraoperative transit time flow measurements (TTFM) may improve patency of coronary artery bypass grafts. Nevertheless, graft flow might be impaired by native coronary flow based on the severity of stenoses, with inferior long-term outcomes. This study investigates the impact of left anterior descending artery (LAD) stenosis on competitive flow measured in left internal mammary artery (LIMA) grafts during off-pump coronary artery bypass grafting. METHODS: Fifty patients were included in this prospective single-center cohort study. LAD stenosis was assessed with quantitative coronary analysis (QCA) and stratified into three groups based on its severity. TTFM of LIMA grafts were performed with LAD open and temporarily occluded. Change in mean graft flow after LAD snaring was the primary endpoint. Secondary endpoints included further TTFM parameters, clinical outcomes, and competitive flow index (CFI), defined as the ratio of mean graft flow with open or closed LAD. RESULTS: Mean LAD stenosis as objectified with QCA was 58 ± 15%. Mean LIMA graft flow increased from 20 ml/min with open LAD to 30 ml/min with snared LAD (p < .001). TTFM cut-off values for graft patency improved in 26%-42% of patients after LAD occlusion. Median CFI was 0.66 (IQR: 0.56-0.82). Postoperative myocardial infarction occurred in 2.0% of patients, 120-day mortality was 0%, and 2-year mortality was 6.0%. CONCLUSIONS: Routine snaring of the LAD with CFI calculation during coronary artery bypass grafting is useful to detect significant competitive flow in LIMA grafts, potentially preventing unnecessary intraoperative graft revisions.

Contrast-enhanced ultrasound for quantification of tissue perfusion in humans.

Contrast-enhanced ultrasound is an imaging technique that can be used to quantify microvascular blood volume and blood flow of vital organs in humans. It relies on the use of microbubble contrast agents and ultrasound-based imaging of microbubbles. Over the past decades, both ultrasound contrast agents and experimental techniques to image them have rapidly improved, as did experience among investigators and clinicians. However, these improvements have not yet resulted in uniform guidelines for CEUS when it comes to quantification of tissue perfusion in humans, preventing its uniform and widespread use in research settings. The objective of this review is to provide a methodological overview of CEUS and its development, the influences of hardware and software settings, type and dosage of ultrasound contrast agent, and method of analysis on CEUS-derived perfusion data. Furthermore, we will discuss organ-specific imaging challenges, advantages, and limitations of CEUS.

Clinical and inflammatory phenotyping by breathomics in chronic airway diseases irrespective of the diagnostic label.

Asthma and chronic obstructive pulmonary disease (COPD) are complex and overlapping diseases that include inflammatory phenotypes. Novel anti-eosinophilic/anti-neutrophilic strategies demand rapid inflammatory phenotyping, which might be accessible from exhaled breath.Our objective was to capture clinical/inflammatory phenotypes in patients with chronic airway disease using an electronic nose (eNose) in a training and validation set.This was a multicentre cross-sectional study in which exhaled breath from asthma and COPD patients (n=435; training n=321 and validation n=114) was analysed using eNose technology. Data analysis involved signal processing and statistics based on principal component analysis followed by unsupervised cluster analysis and supervised linear regression.Clustering based on eNose resulted in five significant combined asthma and COPD clusters that differed regarding ethnicity (p=0.01), systemic eosinophilia (p=0.02) and neutrophilia (p=0.03), body mass index (p=0.04), exhaled nitric oxide fraction (p<0.01), atopy (p<0.01) and exacerbation rate (p<0.01). Significant regression models were found for the prediction of eosinophilic (R2=0.581) and neutrophilic (R2=0.409) blood counts based on eNose. Similar clusters and regression results were obtained in the validation set.Phenotyping a combined sample of asthma and COPD patients using eNose provides validated clusters that are not determined by diagnosis, but rather by clinical/inflammatory characteristics. eNose identified systemic neutrophilia and/or eosinophilia in a dose-dependent manner.