Jorge Mariscal-Harana

King's College London | KCL · Department of Biomedical Engineering

Aims Artificial intelligence (AI) techniques have been proposed for automating analysis of short-axis (SAX) cine cardiac magnetic resonance (CMR), but no CMR analysis tool exists to automatically analyse large (unstructured) clinical CMR datasets. We develop and validate a robust AI tool for start-to-end automatic quantification of cardiac function...

Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Wellcome/EPSRC Centre for Medical Engineering at King’s College London (WT 203148/Z/16/Z), the National Institute for Health Research (NIHR) Cardiovascular MedTech Co-operative award to the Guy’s and St Thomas’ NHS Foundation Trust, and...

Flow analysis carried out using phase contrast cardiac magnetic resonance imaging (PC-CMR) enables the quantification of important parameters that are used in the assessment of cardiovascular function. An essential part of this analysis is the identification of the correct CMR views and quality control (QC) to detect artefacts that could affect the...

The Atherosclerotic Cardiovascular Disease Risk (ASCVD) score by pooled cohort equation is a reliable predictor for future ASCVD events and is used to guide primary prevention in asymptomatic aging subjects. ASCVD risk is associated with burden of coronary artery disease as measured from computed tomography angiography. Purpose We aim to investiga...

Flow analysis carried out using phase contrast cardiac magnetic resonance imaging (PC-CMR) enables the quantification of important parameters that are used in the assessment of cardiovascular function. An essential part of this analysis is the identification of the correct CMR views and quality control (QC) to detect artefacts that could affect the...

Background Artificial intelligence (AI) techniques have been proposed for automation of cine CMR segmentation for functional quantification. However, in other applications AI models have been shown to have potential for sex and/or racial bias. The objective of this paper is to perform the first analysis of sex/racial bias in AI-based cine CMR segme...

Current artificial intelligence (AI) algorithms for short-axis cardiac magnetic resonance (CMR) segmentation achieve human performance for slices situated in the middle of the heart. However, an often-overlooked fact is that segmentation of the basal and apical slices is more difficult. During manual analysis, differences in the basal segmentations...

Ventricular-vascular interaction is central in the adaptation to cardiovascular disease. However, cardiomyopathy patients are predominantly monitored using cardiac biomarkers. The aim of this study is therefore to explore aortic function in dilated cardiomyopathy (DCM). Fourteen idiopathic DCM patients and 16 controls underwent cardiac magnetic res...

Objective: A novel method was presented to separate the central blood pressure wave (CBPW) into five components with different biophysical and temporal origins. It includes a time-varying emission coefficient () that quantifies pulse wave generation and reflection at the aortic root. Methods: The method was applied to normotensive subjects with...

Background/Introduction Pressure-volume loops (PVloops) provide a wealth of information on cardiac function that is not readily available from cardiac imaging alone. Methods To estimate left ventricular (LV) PVloops non-invasively have been available, but have so far not been used to interrogate ventricular function in large patient cohorts, due t...

Current artificial intelligence (AI) algorithms for short-axis cardiac magnetic resonance (CMR) segmentation achieve human performance for slices situated in the middle of the heart. However, an often-overlooked fact is that segmentation of the basal and apical slices is more difficult. During manual analysis, differences in the basal segmentations...

Background Artificial intelligence (AI) techniques have been proposed for automation of cine CMR segmentation for functional quantification. However, in other applications AI models have been shown to have potential for sex and/or racial bias. Objectives To perform the first analysis of sex/racial bias in AI-based cine CMR segmentation using a lar...

Background: Artificial intelligence (AI) has the potential to facilitate the automation of CMR analysis for biomarker extraction. However, most AI algorithms are trained on a specific input domain (e.g., scanner vendor or hospital-tailored imaging protocol) and lack the robustness to perform optimally when applied to CMR data from other input domai...

For the Remotely Piloted Aircraft Systems (RPAS) market to continue its current growth rate, cost-effective ‘Detect and Avoid’ systems that enable safe beyond visual line of sight (BVLOS) operations are critical. We propose an audio-based ‘Detect and Avoid’ system, composed of microphones and an embedded computer, which performs real-time inference...

For the Remotely Piloted Aircraft Systems (RPAS) market to continue its current growth rate, cost-effective "Detect and Avoid" systems that enable safe beyond visual line of sight (BVLOS) operations are critical. We propose an audio-based "Detect and Avoid" system, composed of microphones and an embedded computer, which performs real-time inference...

Central blood pressure (cBP) is a highly prognostic cardiovascular (CV) risk factor whose accurate, invasive assessment is costly and carries risks to patients. We developed and assessed novel algorithms for estimating cBP from noninvasive aortic hemodynamic data and a peripheral blood pressure measurement. These algorithms were created using three...

For the Remotely Piloted Aircraft Systems (RPAS) market to continue its current growth rate, cost-effective "Detect and Avoid" systems which enable safe beyond visual line of sight (BVLOS) operations are critical. We propose an audio-based "Detect and Avoid" system, composed of microphones and an embedded computer, which performs real-time inferenc...

The influence of arterial and ventricular parameters on the main fiducial pressure points and index during systole has been investigated using a mix of in silico and in vivo data. Notably, an index, QIx, based entirely on ventricular ejection patterns has been developed and its potential in describing the augmentation pressure index, AIx, has been...

Aortic tapering is a known characteristic of the arterial tree affecting the development of pressure in the aorta. With tapering, the cross-sectional area of vessels decreases moving towards the periphery causing reflections to travel back to the heart. The reflection waves present in the aorta are an amalgamation of reflections from tapering, bifu...

The angle of arterial tapering increases with aging, and the geometrical changes of the aorta may cause an increase in central arterial pressure and stiffness. The impact of tapering has been largely studied using frequency‐domain transmission line theories. In this work, we revisit the problem of tapering and investigate its effect on blood pressu...

The arterial pulse wave (PW) is a rich source of information on cardiovascular (CV) health. It is widely measured by both consumer and clinical devices. However, the physical determinants of the PW are not yet fully understood, and the development of PW analysis algorithms is limited by a lack of PW datasets containing reference CV measurements. Ou...

As computational models of the cardiovascular system are applied in modern personalized medicine, maximizing certainty of model input becomes crucial. A model with a high number of arterial segments results in a more realistic description of the system, but also requires a high number of parameters with associated uncertainties. In this paper, we p...

Supplementary material for optimization of complexity for arterial blood flow models

Accepted abstract submission for the American Heart Association's 2017 Scientific Sessions and Resuscitation Science Symposium. Title: Validation of non-invasive MRI-based assessment of central blood pressure in a population of repaired coarctation patients

Non-invasive assessment of haemodynamic data, such as pressure and flow profiles, is helpful in detecting cardiac disease at an early stage. However, current methods lack spatial accuracy and do not take local variations into account. This paper presents a software tool that extracts the arterial geometry and blood inflow profiles from MR images, w...