Clinical applications of intra-cardiac four-dimensional flow cardiovascular magnetic resonance: A systematic review

Background: Four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) is an emerging non-invasive imaging technology used to visualise and quantify intra-cardiac blood flow. The aim of this systematic review is to assess the literature on the current clinical applications of intra-cardiac 4D flow CMR. Methods: A systematic review was conducted to evaluate the literature on the intra-cardiac clinical applications of 4D flow CMR. Structured searches were carried out on Medline, EMBASE and the Cochrane Library in October 2016. A modified Critical Skills Appraisal Programme (CASP) tool was used to objectively assess and score the included studies. Studies were categorised as ‘highly clinically applicable’ for scores of 67–100%, ‘potentially clinically applicable’ for 34–66% and ‘less clinically applicable’ for 0–33%. Results: Of the 1608 articles screened, 44 studies met eligibility for systematic review. The included literature consisted of 22 (50%) mechanistic studies, 18 (40.9%) pilot studies and 4 (9.1%) diagnostic studies. Based on the modified CASP tool, 27 (62%) studies were ‘highly clinically applicable’, 9 (20%) were ‘potentially clinically applicable’ and 8 (18%) were ‘less clinically applicable’. Conclusions: There are many proposed methods for using 4D flow CMR to quantify intra-cardiac flow. The evidence base is mainly mechanistic, featuring single-centred designs. Larger, multi-centre studies are required to validate the proposed techniques and investigate the clinical advantages that 4D flow CMR offers over standard practices

Whole-heart four-dimensional flow can be acquired with preserved quality without respiratory gating, facilitating clinical use: a head-to-head comparison

Background: Respiratory gating is often used in 4D-flow acquisition to reduce motion artifacts. However, gating increases scan time. The aim of this study was to investigate if respiratory gating can be excluded from 4D flow acquisitions without affecting quantitative intracardiac parameters. Methods: Eight volunteers underwent CMR at 1.5 T with a 5-channel coil (5ch). Imaging included 2D flow measurements and whole-heart 4D flow with and without respiratory gating (Resp(+), Resp(-)). Stroke volume (SV), particle-trace volumes, kinetic energy, and vortex-ring volume were obtained from 4D flow-data. These parameters were compared between 5ch Resp(+) and 5ch Resp(-). In addition, 20 patients with heart failure were scanned using a 32-channel coil (32ch), and particle-trace volumes were compared to planimetric SV. Paired comparisons were performed using Wilcoxon's test and correlation analysis using Pearson r. Agreement was assessed as bias +/- SD. Results: Stroke volume from 4D flow was lower compared to 2D flow both with and without respiratory gating (5ch Resp(+) 88 +/- 18 vs 97 +/- 24.0, p = 0.001; 5ch Resp(-) 86 +/- 16 vs 97.1 +/- 22.7, p < 0.01). There was a good correlation between Resp(+) and Resp(-) for particle-trace derived volumes (R-2 = 0.82, 0.2 +/- 9.4 ml), mean kinetic energy (R-2 = 0.86, 0.07 +/- 0.21 mJ), peak kinetic energy (R-2 = 0.88, 0.14 +/- 0.77 mJ), and vortex-ring volume (R-2 = 0.70, -2.5 +/- 9.4 ml). Furthermore, good correlation was found between particle-trace volume and planimetric SV in patients for 32ch Resp(-) (R-2 = 0.62, -4.2 +/- 17.6 ml) and in healthy volunteers for 5ch Resp(+) (R-2 = 0.89, -11 +/- 7 ml), and 5ch Resp(-) (R-2 = 0.93, -7.5 +/- 5.4 ml), Average scan duration for Resp(-) was shorter compared to Resp(+) (27 +/- 9 min vs 61 +/- 19 min, p < 0.05). Conclusions: Whole-heart 4D flow can be acquired with preserved quantitative results without respiratory gating, facilitating clinical use

Roadmap on signal processing for next generation measurement systems

Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects