Proceedings of the NHLBI Workshop on Artificial Intelligence in Cardiovascular Imaging: Translation to Patient Care.

Artificial intelligence (AI) promises to revolutionize many fields, but its clinical implementation in cardiovascular imaging is still rare despite increasing research. We sought to facilitate discussion across several fields and across the lifecycle of research, development, validation, and implementation to identify challenges and opportunities to further translation of AI in cardiovascular imaging. Furthermore, it seemed apparent that a multidisciplinary effort across institutions would be essential to overcome these challenges. This paper summarizes the proceedings of the National Heart, Lung, and Blood Institute-led workshop, creating consensus around needs and opportunities for institutions at several levels to support and advance research in this field and support future translation

The Physiological Basis of Myocardial Hibernation

Introduction Myocardial hibernation is the active downregulation of myocardial function in response to recurrent episodes of non-lethal ischaemia. It develops as part of an adaptive programme which favours cell survival over contractility, with clear evidence of progressive cellular changes including metabolic switches, regression of the contractile apparatus and glycogen deposition. Early hibernation is reversible if the ischaemic stimulus is removed or reduced; whilst this was traditionally considered specific to revascularisation, emerging evidence suggests that any intervention which favourably alters the balance of myocardial oxygen supply against demand has comparable effects. Due to the potential for functional recovery, hibernation has become a key therapeutic target in ischaemic left ventricular dysfunction. Viability testing refers to the prospective identification of the substrate of myocardial hibernation using a variety of non-invasive imaging methods including cardiac magnetic resonance imaging (CMR), nuclear imaging and stress echocardiography, and has become an important part of the assessment of patients with ischaemic left ventricular dysfunction being considered for revascularisation. All modalities have similar diagnostic performance, though techniques which assess both the viability of the myocardial tissue and the presence of inducible ischaemia have higher specificity for reversibility and functional recovery. However, the need for multiple tests, including invasive coronary angiography and non-invasive viability testing, is a potential barrier to patients undergoing revascularisation and places a significant burden on healthcare resources. Invasive coronary physiology is an established alternative to non-invasive imaging. Assessment of arterial physiology with fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR) is the most widely accepted vessel specific surrogate for inducible myocardial ischaemia, and there is emerging evidence that pathophysiological states of the myocardium can be differentiated through assessing myocardial physiology by coronary wave intensity analysis (cWIA), by measuring the magnitude of the myocardial-originating backward compression wave (BCW) and backward expansion wave (BEW). The studies in this thesis have been designed to further our understanding of both the invasive and non- invasive assessment of myocardial viability and ischaemia in patients with ischaemic left ventricular dysfunction (ILVD). Methods Patients with a recent diagnosis of ILVD, defined as the presence of extensive coronary artery disease (British Cardiovascular Intervention Society jeopardy score ≥ 6) and left ventricular dysfunction (ejection fraction ≤ 40%) were enrolled. Those with a recent acute myocardial infarction or severe valvular heart disease were excluded. Participants underwent invasive physiological assessment during cardiac catheterisation, with simultaneous measurement of aortic and distal coronary pressure, and coronary blood flow velocity, measured at rest, during adenosine induced hyperaemia and low dose dobutamine stress. Pressure-based indices of coronary stenosis severity, coronary stenosis resistance, microvascular resistance, and coronary wave intensity analysis were calculated from ensemble-averaged signals. Myocardial viability was determined by CMR using a dark-blood late gadolinium-enhanced phase-sensitive inversion-recovery (PSIR) turbo field echo pulse sequence at either 1.5 or 3-Tesla, with viability defined as scar burden ≤ 25% on quantitative assessment. Stress perfusion data were acquired using a saturation-recovery k-t sensitivity encoding accelerated gradient-echo method at 3-Tesla. Regional left ventricular function was assessed at baseline and 6-month or 12-month follow up after optimisation of medical therapy +/- revascularisation, using transthoracic echocardiography. The primary outcome was functional recovery, defined either regionally (as an improvement in wall motion score index ≥ 0.5 across the subtended territory) or segmentally (as an improvement in wall motion score ≥1). In the first study, hyperaemic stenosis resistance was used as a reference standard to investigate the diagnostic accuracy of FFR and iFR in 40 patients with ILVD who underwent cardiac catheterisation and invasive coronary physiology studies, compared to a control population of 13 patients with normal left ventricular function. The second study assessed the ability of backward-originating coronary wave energy (the BCW and BEW) to predict the presence of hibernation (defined as the observation of functional recovery in the subtended territory): the same forty patients also underwent CMR (the current clinical reference standard viability test) and baseline echocardiography; 25 had follow-up echocardiography. The ability of BCW, BEW and CMR to predict functional recovery were compared by the area under the curve (AUC) on receiver operator characteristic (ROC) analysis. The final study determined whether the combination of ischaemia and viability assessment, with a combined stress perfusion/late gadolinium enhancement (SP/LGE) CMR protocol, would improve the prediction of hibernation (defined as segmental functional recovery) compared to LGE alone, in twenty-nine patients with ILVD who underwent CMR and baseline and follow-up echocardiography. Results In the ILVD group, hyperaemic stenosis resistance was positive in 20 vessels, FFR positive in 26 vessels and iFR positive in 32 vessels: FFR had a sensitivity of 95% and specificity of 83% whilst iFR had a sensitivity of 95% and specificity of 68%. In controls, hyperaemic stenosis resistance was positive in 12 vessels, FFR positive in 13 vessels and iFR positive in 23 vessels; FFR had a sensitivity of 100% and specificity of 93%, and iFR had a sensitivity of 100% and specificity of 21%. However, when FFR and iFR were assessed as a continuum, there was increasing inaccuracy with increasing stenosis resistance, with a tendency to underestimate severity in high grade lesions in ILVD compared to normal controls. Microvascular resistance, wall thickening, and late enhancement were all found to influence FFR results in patients with ILVD. The resting BCW was significantly larger in recovering than non-recovering territories (-5564 ± 4054 vs. -1853 ± 1735 W.m-2.s-1, p <0.001). The BEW did not differ significantly (-6377 ± 4833 vs. -5053 ± 5929 W.m-2.s-1, p = 0.476) (figure 4.3). The BCW was the most effective predictor of functional recovery (AUC 0.814, 95% CI 0.671-0.957), with comparable diagnostic accuracy to LGE-CMR (AUC 0.771, 95% CI 0.617-0.925), difference between AUC 0.0425, 95% CI -0.140-0.225, p = 0.649). A BCW threshold of -2351 W.m2.s-1 had 92% sensitivity and 73% specificity for predicting functional recovery. Dobutamine stress did not improve the diagnostic accuracy of cWIA. The BEW, previously identified as the most effective predictor of functional recovery following an acute coronary syndrome, did not predict functional recovery but was closely related to the regional scar burden at baseline. Microvascular resistance did not differentiate viable from non-viable territories. Four-hundred and fifty-eight segments were included in the analysis. Scar was identified in 162 segments (1-25% in 48, 26-50% in 49, 51-75% in 25 and 76-100% in 40); 296 segments had no evidence of scar. Stress perfusion defects were identified in 166 segments in 26 patients. The primary outcome occurred in 167 of 458 segments (36.5%). On univariate analysis, the demonstration of the full substrate of hibernation (both inducible ischaemia and viability), assessed by a combined SP/LGE-CMR protocol, significantly increased specificity for predicting functional recovery (76.8% vs. 26.8%, p < 0.001) compared to LGE-CMR alone. The increase in specificity came at a significant cost to sensitivity (34.3% with SP/LGE-CMR vs. 78.4% with LGE- CMR alone, p <0.001). Diagnostic accuracy was greatest in segments which exhibited both inducible ischaemia and preserved viability (60.3%), followed by SP-CMR alone (57.9%): both were significantly more accurate than LGE- CMR (45.6%, p < 0.001). On multiple regression analysis, however, scar burden and baseline wall motion predicted segmental recovery, whilst the presence of an inducible perfusion defect and revascularisation status did not. Conclusion The combined assessment of inducible ischaemia and viability during invasive cardiac catheterisation is feasible. Backward expansion wave magnitude measured with cWIA in resting conditions provides an accurate prediction of functional recovery, comparable to LGE-CMR and as an adjunct to coronary angiography may permit timely, streamlined revascularisation for patients with ischaemic left ventricular dysfunction. The addition of pharmacological stress does not improve diagnostic performance. The results of both FFR and iFR are influenced by microvascular function and myocardial pathology in patients with ILVD, producing a less accurate estimation of stenosis resistance. Further validation of pressure-derived indices in ILVD is needed. The addition of ischaemia assessment to LGE-CMR improved overall diagnostic performance, although the diagnostic accuracy was limited with all techniques, with a low observed rate of functional recovery in this population. Adjusted analyses demonstrated that scar burden and baseline wall motion remained the best predictors of functional recovery, and the routine addition of stress perfusion sequences to LGE-CMR in ILVD is unlikely to be beneficial. This thesis advances our understanding of the invasive and non-invasive assessment of ischaemia and viability as integral parts of the physiology of hibernation. In time such detailed phenotyping may provide the key to truly personalised decision making for patients in this high-risk population

Advanced Applications of Cardiac Computed Tomography for the Difficult-to-Image Patient

Throughout the development of computed tomographic (CT) imaging the challenges of capturing the heart, with its perpetual, vigorous motion, and in particular the tiny detail within the coronary arteries, has driven technological progress. Today, CT is a widely used and rapidly growing modality for the investigation of coronary artery disease, as well as other cardiac pathology. However, limitations remain and particular patient groups present a significant challenge to the CT operator. This thesis adds new knowledge to the assessment of these difficult-to-image patients. It considers patients with artefact from coronary artery calcification or stents, examining the remarkable diagnostic performance of high definition scanning, as well as material subtraction techniques using dual energy CT, alongside ways in which current technology might be revisited and refined with the use of alternative image reconstruction methods. Patients with challenging heart rate or rhythm abnormalities are considered in three studies; how to achieve diagnostic image quality in atrial fibrillation, the safety of an aggressive approach to intravenous beta-blocker use prior to coronary imaging, and the development of patient information to address anxiety as a source of tachycardia and motion artefact. Finally, the novel application of a single source, dual energy CT scanner to additional cardiac information is considered, with studies of myocardial perfusion CT and delayed iodine enhancement imaging, to identify ways in which non-coronary imaging might be exploited to more thoroughly evaluate a patient’s coronary artery status. These findings are presented in the context of developing technology and together offer a range of potential options for operators of cardiac CT when faced with a difficult-to-image patient

Translating computational modelling tools for clinical practice in congenital heart disease

Increasingly large numbers of medical centres worldwide are equipped with the means to acquire 3D images of patients by utilising magnetic resonance (MR) or computed tomography (CT) scanners. The interpretation of patient 3D image data has significant implications on clinical decision-making and treatment planning. In their raw form, MR and CT images have become critical in routine practice. However, in congenital heart disease (CHD), lesions are often anatomically and physiologically complex. In many cases, 3D imaging alone can fail to provide conclusive information for the clinical team. In the past 20-30 years, several image-derived modelling applications have shown major advancements. Tools such as computational fluid dynamics (CFD) and virtual reality (VR) have successfully demonstrated valuable uses in the management of CHD. However, due to current software limitations, these applications have remained largely isolated to research settings, and have yet to become part of clinical practice. The overall aim of this project was to explore new routes for making conventional computational modelling software more accessible for CHD clinics. The first objective was to create an automatic and fast pipeline for performing vascular CFD simulations. By leveraging machine learning, a solution was built using synthetically generated aortic anatomies, and was seen to be able to predict 3D aortic pressure and velocity flow fields with comparable accuracy to conventional CFD. The second objective was to design a virtual reality (VR) application tailored for supporting the surgical planning and teaching of CHD. The solution was a Unity-based application which included numerous specialised tools, such as mesh-editing features and online networking for group learning. Overall, the outcomes of this ongoing project showed strong indications that the integration of VR and CFD into clinical settings is possible, and has potential for extending 3D imaging and supporting the diagnosis, management and teaching of CHD

Computational Modelling in the Management of Patients with Aortic Valve Stenosis

Background Stenosis of the aortic valve causes increased left ventricular pressure leading to adverse clinical outcomes. The selection and timing of intervention (surgical replacement or transcatheter implantation) is often unclear and is based upon limited data. Hypothesis A comprehensive and integrated personalised approach, including recognition of cardiac energetics parameters extracted from a personalised mathematical model, mapped to patient activity, has the potential to improve diagnosis and the planning and timing of interventions. Aims This project seeks to implement a simple, personalised, mathematical model of patients with aortic stenosis (AS), which can ‘measure’ cardiac work and power parameters that provide an effective characterisation of the demand on the heart in both rest and exercise conditions and can predict the changes of these parameters following an intervention. The specific aims of this project are: • to critically review current diagnostic methods • to evaluate the potential role of pre- and post-procedural measured patient activity • to implement a simple, personalised, mathematical model of patients with AS • to evaluate the potential role of a clinical decision support system Methods Twenty-two patients with severe AS according to ESC criteria were recruited. Relevant clinical, imaging, activity monitoring, six-minute walk test, and patient reported data were collected, before and early and after treatment. Novel imaging techniques were developed to help in the diagnosis of AS. A computational model was developed and executed using the data collected to create non-invasive pressure volume loops and study the global haemodynamic burden on the left ventricle. Simulations were run to predict the haemodynamic parameters both during exercise and following intervention. Modelled parameters were validated against clinically measured values. This information was then correlated with symptoms and activity data. A clinical decision support tool was created and populated with data obtained and its clinical utility evaluated. Outcomes The results of this project suggest that the combination of imaging and activity data with computational modelling provides a novel, patient-specific insight into patients’ haemodynamics and may help guide clinical decision making in patients with AS

Scenario-based system architecting : a systematic approach to developing future-proof system architectures

This thesis summarizes the research results of Mugurel T. Ionita, based on the work conducted in the context of the STW15 - AIMES16 project. The work presented in this thesis was conducted at Philips Research and coordinated by Eindhoven University of Technology. It resulted in six external available publications, and ten internal reports which are company confidential. The research regarded the methodology of developing system architectures, focusing in particular on two aspects of the early architecting phases. These were, first the generation of multiple architectural options, to consider the most likely changes to appear in the business environment, and second the quantitative assessment of these options with respect to how well they contribute to the overall quality attributes of the future system, including cost and risk analysis. The main reasons for looking at these two aspects of the architecting process was because architectures usually have to live for long periods of time, up to 5 years, which requires that they are able to deal successfully with the uncertainty associated with the future business environment. A second reason was because the quality attributes, the costs and the risks of a future system are usually dictated by its architecture, and therefore an early quantitative estimate about these attributes could prevent the system redesign. The research results of this project were two methods, namely a method for designing architecture options that are more future-proof, meaning more resilient to future changes, (SODA method), and within SODA a method for the quantitative assessment of the proposed architectural options (SQUASH method). The validation of the two methods has been performed in the area of professional systems, where they were applied in a concrete case study from the medical domain. The SODA method is an innovative solution to the problem of developing system architectures that are designed to survive the most likely changes to be foreseen in the future business environment of the system. The method enables on one hand the business stakeholders of a system to provide the architects with their knowledge and insight about the future when new systems are created. And on the other hand, the method enables the architects to take a long view and think strategically in terms of different plausible futures and unexpected surprises, when designing the high level structure of their systems. The SQUASH method is a systematic way of assessing in a quantitative manner, the proposed architectural options, with respect to how well they deal with quality aspects, costs and risks, before the architecture is actually implemented. The method enables the architects to reason about the most relevant attributes of the future system, and to make more informed decisions about their design, based on the quantitative data. Both methods, SODA and SQUASH, are descriptive in nature, rooted in the best industrial practices, and hence proposing better ways of developing system architectures

Tissue mimicking materials for imaging and therapy phantoms: a review

Tissue mimicking materials (TMMs), typically contained within phantoms, have been used for many decades in both imaging and therapeutic applications. This review investigates the specifications that are typically being used in development of the latest TMMs. The imaging modalities that have been investigated focus around CT, mammography, SPECT, PET, MRI and ultrasound. Therapeutic applications discussed within the review include radiotherapy, thermal therapy and surgical applications. A number of modalities were not reviewed including optical spectroscopy, optical imaging and planar x-rays. The emergence of image guided interventions and multimodality imaging have placed an increasing demand on the number of specifications on the latest TMMs. Material specification standards are available in some imaging areas such as ultrasound. It is recommended that this should be replicated for other imaging and therapeutic modalities. Materials used within phantoms have been reviewed for a series of imaging and therapeutic applications with the potential to become a testbed for cross-fertilization of materials across modalities. Deformation, texture, multimodality imaging and perfusion are common themes that are currently under development