Alistair A Young

• Professor at King's College London

A cardiac digital twin is a virtual replica of a patient's heart for screening, diagnosis, prognosis, risk assessment, and treatment planning of cardiovascular diseases. This requires an anatomically accurate patient-specific 3D structural representation of the heart, suitable for electro-mechanical simulations or study of disease mechanisms. Howev...

Cardiac resynchronization therapy (CRT) guidelines are based on clinical trials with limited female representation and inconsistent left bundle branch block (LBBB) definitions. Conventional QRS duration (QRSd) criteria show variable diagnostic accuracy between sexes, partly due to differences in heart size and remodeling. We evaluated the influence...

Cardiac resynchronization therapy (CRT) guidelines are based on clinical trials with limited female representation and inconsistent left bundle branch block (LBBB) definitions. Conventional QRS duration (QRSd) criteria show variable diagnostic accuracy between sexes, partly due to differences in heart size and remodeling. We evaluated the influence...

Large-cohort imaging and diagnostic studies often assess cardiac function but overlook underlying biological mechanisms. Cardiac digital twins (CDTs) are personalized physics-constrained and physiology-constrained in silico representations, uncovering multi-scale insights tied to these mechanisms. In this study, we constructed 3,461 CDTs from the U...

The left atrium (LA) plays a pivotal role in modulating left ventricular filling, but our comprehension of its hemodynamics is significantly limited by the constraints of conventional ultrasound analysis. 4D flow magnetic resonance imaging (4D Flow MRI) holds promise for enhancing our understanding of atrial hemodynamics. However, the low velocitie...

Background: Aortic diameter remains the most utilised criterion for considering surgical correction. In uncomplicated cases guidelines do not differentiate between the size of aneurysms at the root and ascending aorta. In order to improve practice, greater understanding of site-specific TAA is needed. A nationwide echocardiographic dataset linked t...

Cardiovascular magnetic resonance (CMR) offers diverse imaging contrasts for assessment of cardiac function and tissue characterization. However, acquiring each single CMR modality is often time-consuming, and comprehensive clinical protocols require multiple modalities with various sampling patterns, further extending the overall acquisition time...

Background Myocardial strain is a valuable biomarker for diagnosing and predicting cardiac conditions, offering additional prognostic information to traditional metrics such as ejection fraction. While cardiovascular magnetic resonance (CMR) methods, particularly cine displacement encoding with stimulated echoes (DENSE), are the gold standard for s...

“Just Accepted” papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could aff...

Background Statistical shape atlases have been used in large-cohort studies to investigate relationships between heart shape and risk factors. The generalisability of these relationships between cohorts is unknown. The aims of this study were to compare left ventricular (LV) shapes in patients with differing cardiovascular risk factor profiles from...

4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive technique for volumetric, time-resolved blood flow quantification. However, apparent trade-offs between acquisition time, image noise, and resolution limit clinical applicability. In particular, in regions of highly transient flow, coarse temporal resolution can hinder accurate capt...

Cardiac Magnetic Resonance (CMR) imaging is widely used for heart modelling and digital twin computational analysis due to its ability to visualize soft tissues and capture dynamic functions. However, the anisotropic nature of CMR images, characterized by large inter-slice distances and misalignments from cardiac motion, poses significant challenge...

Heart shape captures variation in cardiac structure beyond traditional phenotypes of mass and volume. Although observational studies have demonstrated associations with cardiometabolic risk factors and diseases, its genetic basis is less understood. We utilised cardiovascular magnetic resonance images from 45,683 UK Biobank participants to construc...

Background Myocardial work is an emerging technique for the assessment of left ventricular (LV) performance. Using blood pressure as an afterload determinate offers further insight into LV mechanics than can be detected with load-sensitive parameters of ejection fraction or global longitudinal strain (GLS). Observational studies have signalled bene...

Background Accurate echocardiographic assessment of left ventricular (LV) function is dependent on both image acquisition and analysis. Although 3D echocardiography (3DE) is increasingly recommended for volume quantification, manually derived volumes are limited by operator subjectivity, variable image quality, and the lengthy duration of analysis....

Background: The prognostic value of late gadolinium enhancement (LGE) in cardiac magnetic resonance (CMR) imaging is well-established. However, the direct relationship between image pixels and outcomes remains poorly understood. We hypothesised that leveraging artificial intelligence (AI) to analyse qualitative LGE images based on American Heart As...

Thanks to recent developments in cardiovascular magnetic resonance (CMR), cardiac diffusion-weighted magnetic resonance is fast emerging in a range of clinical applications. Cardiac diffusion-weighted imaging (cDWI) and diffusion tensor imaging (cDTI) now enable investigators and clinicians to assess and quantify the tridimensional microstructure o...

Cardiac magnetic resonance (CMR) imaging and computed tomography (CT) are two common non-invasive imaging methods for assessing patients with cardiovascular disease. CMR typically acquires multiple sparse 2D slices, with unavoidable respiratory motion artefacts between slices, whereas CT acquires isotropic dense data but uses ionising radiation. In...

Introduction Ultrasound is well-established as an imaging modality for diagnostic and interventional purposes. However, the image quality varies with operator skills as acquiring and interpreting ultrasound images requires extensive training due to the imaging artefacts, the range of acquisition parameters and the variability of patient anatomies....

4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique capable of quantifying blood flow across the cardiovascular system. While practical use is limited by spatial resolution and image noise, incorporation of trained super-resolution (SR) networks has potential to enhance image quality post-scan. However, these ef...

Background Cardiovascular magnetic resonance (CMR) is increasingly utilized to evaluate expanding cardiovascular conditions. The Society for Cardiovascular Magnetic Resonance (SCMR) Registry is a central repository for real-world clinical data to support cardiovascular research, including those relating to outcomes, quality improvement, and machine...

Cardiac magnetic resonance imaging (MRI) has emerged as a clinically gold-standard technique for diagnosing cardiac diseases, thanks to its ability to provide diverse information with multiple modalities and anatomical views. Accelerated cardiac MRI is highly expected to achieve time-efficient and patient-friendly imaging, and then advanced image r...

Background Echocardiography is widely used to evaluate left ventricular (LV) diastolic function in patients suspected of heart failure. For patients in sinus rhythm, a combination of several echocardiographic parameters can differentiate between normal and elevated LV filling pressure with good accuracy. However, there is no established echocardiog...

Aims Standard methods of heart chamber volume estimation in cardiovascular magnetic resonance (CMR) typically utilize simple geometric formulae based on a limited number of slices. We aimed to evaluate whether an automated deep learning neural network prediction of 3D anatomy of all four chambers would show stronger associations with cardiovascular...

Background A reduced left atrial (LA) strain correlates with the presence of atrial fibrillation (AF). Conventional atrial strain analysis uses two-dimensional (2D) imaging, which is, however, limited by atrial foreshortening and an underestimation of through-plane motion. Retrospective gated computed tomography (RGCT) produces high-fidelity three-...

Background: Prediction of clinical outcomes in coronary artery disease (CAD) has been conventionally achieved using clinical risk factors. The relationship between imaging features and outcome is still not well understood. This study aims to use artificial intelligence to link image features with mortality outcome. Methods: A retrospective study wa...

In cardiovascular magnetic resonance (CMR), typical acquisitions often involve a limited number of short and long axis slices. However, reconstructing the 3D chambers is crucial for accurately quantifying heart geometry and assessing cardiac function. Neural Implicit Representations (NIR) learn implicit functions for anatomical shapes from sparse m...

Hypertension is a major risk factor for cardiovascular disease. Pressure-strain loop analysis has recently been introduced as a clinical tool to quantify the pumping efficiency of the left ventricle (LV), as an alternative to the classical pressure-volume loop analysis. The aims of this study were to: (i) combine global longitudinal strain (GLS) fr...

Segmentation of the right ventricle (RV) from 3D echocardiography (3DE) is a challenging task. In comparison to the left ventricle (LV), the complex geometry of the RV hinders accurate and reproducible volume quantification. While more accessible, 3DE falls short of gold-standard cardiac magnetic resonance (CMR) imaging for volume quantification du...

Segmentation of 2D echocardiography (2DE) images is an important prerequisite for quantifying cardiac function. Although deep learning can automate analysis, variability in image quality and limitations in model generalisability can result in inaccurate segmentations. We present an automated quality control (QC) methodology to identify invalid segm...

Background Quantification of three-dimensional (3D) cardiac anatomy is important for the evaluation of cardiovascular diseases. Changes in anatomy are indicative of remodeling processes as the heart tissue adapts to disease. Although robust segmentation methods exist for computed tomography angiography (CTA), few methods exist for whole-heart cardi...

Large-cohort studies using cardiovascular imaging and diagnostic datasets have assessed cardiac anatomy, function, and outcomes, but typically do not reveal underlying biological mechanisms. Cardiac digital twins (CDTs) provide personalized physics- and physiology- constrained in-silico representations, enabling inference of multi-scale properties...

4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique capable of quantifying blood flow across the cardiovascular system. While practical use is limited by spatial resolution and image noise, incorporation of trained super-resolution (SR) networks has potential to enhance image quality post-scan. However, these ef...

Background Prediction of mortality and cardiovascular (CVS) events in coronary artery disease (CAD) has been conventionally achieved using clinical risk factors. Conventional qualitative visual assessment and quantitative analysis of stress perfusion cardiac magnetic resonance (SP-CMR) has previously been shown to have independent prognostic value...

Introduction Changes in left atrial (LA) hemodynamics have been suggested reflective of left ventricular (LV) disease progression. Kinetic energy (KE), viscous energy loss, and vorticity could be promising indices for the assessment of left atrial dynamics by time resolved four-dimensional cardiac magnetic resonance (4D flow CMR). Hypertrophic card...

Introduction: Stress perfusion cardiac magnetic resonance (CMR) is a guidelines-backed non-invasive test for the assessment of coronary artery disease (CAD), and its prognostic value is well validated. However, image interpretation requires a high level of expertise. Furthermore, the direct relationship between image pixels and outcome is not well...

Background: Stress perfusion cardiac magnetic resonance (SP-CMR) is a well validated and guidelines backed diagnostic test for non-invasive assessment of patients with known or suspected coronary artery disease. The prognostic value of SP-CMR is enhanced by adding clinical information, however, most electronic health records (EHR) are stored in an...

Large amounts of labelled data are typically needed to develop robust deep learning methods for medical image analysis. However, issues related to the high costs of acquisition, time-consuming analysis, and patient privacy, have limited the number of publicly available datasets. Recently, latent diffusion models have been employed to generate synth...

Cine cardiac magnetic resonance (CMR) imaging is considered the gold standard for cardiac function evaluation. However, cine CMR acquisition is inherently slow and in recent decades considerable effort has been put into accelerating scan times without compromising image quality or the accuracy of derived results. In this paper, we present a fully-a...

Anatomical heart mesh models created from cine cardiac images are useful for the evaluation and monitoring of cardiovascular diseases, but require challenging and time-consuming reconstruction processes. Errors due to reduced spatial resolution and motion artefacts limit the accuracy of 3D models. We proposed ModusGraph to produce a higher quality...

Importance: Longer leukocyte telomere length (LTL) is associated with a lower risk of adverse cardiovascular outcomes. The extent to which variation in LTL is associated with intermediary cardiovascular phenotypes is unclear. Objective: To evaluate the associations between LTL and a diverse set of cardiovascular imaging phenotypes. Design, sett...

Background: Left ventricular (LV) global longitudinal strain (GLS) has been proposed as an early imaging biomarker of cardiac mechanical dysfunction. Objective: To assess the impact of angiotensin-converting enzyme (ACE) inhibitor treatment of hypertensive heart disease on LV GLS and mechanical function. Methods: The spontaneously hypertensive...

Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Wellcome Trust. Background Stress perfusion cardiac magnetic resonance (SP-CMR) is a well validated and guidelines backed diagnostic test for non-invasive assessment of patients with known or suspected coronary artery disease (CAD)(1)....

The 3D shape of the atria and ventricles is important for studying the mechanisms of disease processes. Common imaging methods such as cardiovascular magnetic resonance (CMR) often acquire a limited number of short and long axis slices. We trained a label completion U-Net (LC-U-Net) to automatically predict 3D shapes for the ventricles, atria, and...

Diastolic dysfunction of the heart is present in most forms of cardiac failure. Left ventricular (LV) diastolic chamber stiffness has been proposed as a metric for obtaining insights into the progression of this disease and help to inform treatment decisions. However, the challenges in robustly estimating chamber stiffness have limited the evaluati...

Displacement ENcoding with Stimulated Echoes (DENSE) is a CMR modality that can encode myocardial tissue displacement at a pixel level, enabling the characterization of cardiac disease at early stages. However, we do not currently have a way of evaluating the accuracy of derived results, since the ground truth is unknown. In this study, we develope...

Atrial fibrillation (AF) is associated with stroke and heart failure, and poses a significant global health burden. Consequently, efforts remain ongoing in better characterising and understanding AF and its underlying mechanisms. This study explores cardiac energetics associated with AF by testing the hypothesis that left ventricular stroke work an...

Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): This project is supported by the Wellcome Trust and EPSRC Centre for Medical Engineering. Background QRS duration derived from 12-lead ECGs provides an estimate of the ventricular depolarization time and is an important metric to asses...

Cardiovascular imaging studies provide a multitude of structural and functional data to better understand disease mechanisms. While pooling data across studies enables more powerful and broader applications, performing quantitative comparisons across datasets with varying acquisition or analysis methods is problematic due to inherent measurement bi...

This chapter deals with important considerations to factor in when translating technical advances in AI to real clinical workflows. The importance of considering existing workflows is emphasized, including identifying and addressing the right question and assessing positive and negative impacts on patients. The important issue of data provenance is...

The development of cerebrovascular disease is tightly coupled to regional changes in intracranial flow and relative pressure. Image-based assessment using phase contrast magnetic resonance imaging has particular promise for non-invasive full-field mapping of cerebrovascular hemodynamics. However, estimations are complicated by the narrow and tortuo...

Background: Cine Displacement Encoding with Stimulated Echoes (DENSE) facilitates the quantification of myocardial deformation, by encoding tissue displacements in the cardiovascular magnetic resonance (CMR) image phase, from which myocardial strain can be estimated with high accuracy and reproducibility. Current methods for analyzing DENSE images...

Background: Most electronic health record (EHR) is unstructured. Artificial intelligence (AI) might improve precision to extract data and predict outcome. The aim is to use AI tools to extract unstructured data from stress perfusion cardiac magnetic resonance (SP-CMR) database and test its plausibility for outcome prediction. Methods: SP-CMR case...

Background: Cardiac shape modeling is a useful computational tool that has provided quantitative insights into the mechanisms underlying dysfunction in heart disease. The manual input and time required to make cardiac shape models, however, limits their clinical utility. Here we present an end-to-end pipeline that uses deep learning for automated...

Changes in cardiovascular hemodynamics are closely related to the development of aortic regurgitation (AR), a type of valvular heart disease. Metrics derived from blood flows are used to indicate AR onset and evaluate its severity. These metrics can be non-invasively obtained using four-dimensional (4D) flow magnetic resonance imaging (MRI), where...

Abstract Current indications for pulmonary valve replacement (PVR) in repaired tetralogy of Fallot (rTOF) rely on cardiovascular magnetic resonance (CMR) image-based indices but are inconsistently applied, lead to mixed outcomes, and remain debated. This study aimed to test the hypothesis that specific markers of biventricular shape may discriminat...

Biventricular statistical atlases are useful dimensionality reduction tools that have demonstrated utility for discovering improved diagnostic and prognostic markers. Patient-specific geometries used to generate these atlases are obtained from in-vivo tomographic images of end diastole (ED) and/or end-systole (ES). However, because these are pressu...

Aims: Left atrial volume is commonly estimated using the bi-plane area-length method from two-chamber (2CH) and four-chamber (4CH) long axes views. However, this can be inaccurate due to a violation of geometric assumptions. We aimed to develop a deep learning neural network to infer 3D left atrial shape, volume and surface area from 2CH and 4CH v...

Stress-perfusion cardiac MRI (pCMR) is an economical and accurate alternative to stress-SPECT for diagnosis of Coronary Artery Disease. The ideal for accessibility is quantitative mapping of perfusion, which requires motion correction robust to the changing contrast distribution across the time series. An in-house method successfully performs group...

2D cardiac MR cine images provide data with a high signal-to-noise ratio for the segmentation and reconstruction of the heart. These images are frequently used in clinical practice and research. However, the segments have low resolution in the through-plane direction, and standard interpolation methods are unable to improve resolution and precision...

Quantification of heart geometry is important in the clinical diagnosis of cardiovascular diseases. Changes in geometry are indicative of remodelling processes as the heart tissue adapts to disease. Coronary Computed Tomography Angiography (CCTA) is considered a first line tool for patients at low or intermediate risk of coronary artery disease, wh...

Background: Myocardial strain analysis plays a key role in assessing cardiovascular conditions. Cine Displacement ENcoding with Stimulated Echoes (DENSE) encodes displacement in the image phase, enabling accurate and high-resolution strain extraction [1, 2]. Strain processing with DENSE is done using standardized tools like DENSEanalysis [3], which...

Segmentation of the left ventricle (LV) in echocardiography is an important task for the quantification of volume and mass in heart disease. Continuing advances in echocardiography have extended imaging capabilities into the 3D domain, subsequently overcoming the geometric assumptions associated with conventional 2D acquisitions. Nevertheless, the...