Measurement of multiple biomarkers in advanced stage heart failure patients treated with pulmonary artery catheter guided therapy

ABSTRACT: INTRODUCTION: This study was carried out to investigate the prognostic utility of biomarkers in advanced stage heart failure (HF) patients requiring ICU admission for pulmonary artery catheter (PAC) guided therapy. METHODS: Thirty patients admitted to an ICU for PAC guided HF therapy were enrolled; concentrations of soluble ST2 (sST2), highly sensitive troponin I, an experimental ultrasensitive troponin I, amino-terminal pro-B type natriuretic peptide, cystatin C, and myeloperoxidase were measured over the first 48 hours. Outcomes included response of filling pressures and hemodynamics to tailored therapy and 90-day event-free survival (death, left ventricular assist device implantation, transplant). RESULTS: Of the biomarkers evaluated, only sST2 concentrations were higher in those who failed to achieve goals for central venous pressure ((CVP), 225.3 versus 104.6 ng/mL; P = 0.003) and pulmonary capillary wedge pressure ((PCWP), 181.7 versus 88.2 ng/mL; P = 0.05). Only sST2 concentrations were associated with adverse events (186.7 versus 92.2 ng/mL; P = 0.01). In age-adjusted Cox proportional hazards analysis, an elevated sST2 during the first 48 hours following ICU admission independently predicted 90-day outcomes (Hazard Ratio = 5.53; P = 0.03) superior to the Simplified Acute Physiology Score for this application; in Kaplan-Meier analysis the risk associated with elevated sST2 concentrations was present early and sustained through the duration of follow-up (log rank P = 0.01). CONCLUSIONS: In patients undergoing HF therapy guided by invasive monitoring, sST2 concentrations were associated with impending failure to reduce filling pressures and predicted impending events. Elevated sST2 values early in the ICU course theoretically could assist therapeutic decision-making in advanced stage HF patients. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT00595738.     

The effects of noise in cardiac diffusion tensor imaging and the benefits of averaging complex data

There is growing interest in cardiac diffusion tensor imaging (cDTI), but, unlike other diffusion MRI applications, there has been little investigation of the effects of noise on the parameters typically derived. One method of mitigating noise floor effects when there are multiple image averages, as in cDTI, is to average the complex rather than the magnitude data, but the phase contains contributions from bulk motion, which must be removed first. The effects of noise on the mean diffusivity (MD), fractional anisotropy (FA), helical angle (HA) and absolute secondary eigenvector angle (E2A) were simulated with various diffusion weightings (b values). The effect of averaging complex versus magnitude images was investigated. In vivo cDTI was performed in 10 healthy subjects with b = 500, 1000, 1500 and 2000 s/mm². A technique for removing the motion‐induced component of the image phase present in vivo was implemented by subtracting a low‐resolution copy of the phase from the original images before averaging the complex images. MD, FA, E2A and the transmural gradient in HA were compared for un‐averaged, magnitude‐ and complex‐averaged reconstructions. Simulations demonstrated an over‐estimation of FA and MD at low b values and an under‐estimation at high b values. The transition is relatively signal‐to‐noise ratio (SNR) independent and occurs at a higher b value for FA (b = 1000–1250 s/mm²) than MD (b ≈ 250 s/mm²). E2A is under‐estimated at low and high b values with a transition at b ≈ 1000 s/mm², whereas the bias in HA is comparatively small. The under‐estimation of FA and MD at high b values is caused by noise floor effects, which can be mitigated by averaging the complex data. Understanding the parameters of interest and the effects of noise informs the selection of the optimal b values. When complex data are available, they should be used to maximise the benefit from the acquisition of multiple averages. The combination of complex data is also a valuable step towards segmented acquisitions. Copyright © 2016 John Wiley & Sons, Ltd.