The primary objective of EurValve was to produce potentially-useable (after regulatory approval) clinical Decision Support System (DSS) tools that could assist clinicians in difficult areas where extra data might assist the decision. EurValve developed a computational tool that provided extra, derived, 'biomarkers' (quantifying aortic stenosis and mitral regurgitation) obtained from 3D analyses of the patient's cardiac geometry. These data were added to an existing commercial valve-sizing system that is currently in clinical use.
The target user will be the healthcare professional, who will make the decision on the nature and timing of the intervention. The major advance of this system over current practice is that it integrates and interprets all heterogeneous data available about the patient, integrates population data where needed, and provides a consistent, repeatable, quantitative and auditable record of the information that contributes to the decision process. The DSS system will allow for in silico simulation of different treatment options and thus allow comparison of their immediate haemodynamic outcome.
The project has constructed a DSS for Heart Valve Disease. It includes a number of important developments and innovations. The DSS includes presentation of clinical guidelines, computational model-based diagnostic and prognostic indications and case-based reasoning. The DSS provides quantitative measures of disease severity and patient impairment, complementary to those gathered in the current clinical pathway, and predicts changes under candidate interventions. The potential of the DSS for improving the management and interventional planning was confirmed by a group of independent clinical users in a control experiment. There has been particular clinical interest in the use of activity monitoring to provide a measure of the degree to which the disease might affect everyday living, and to inform the physiological state in the core computational models.
The design of a practical tool for use by cardiovascular clinicians has been a significant step forward in bringing VPH technology close to the clinic. From the translational perspective, there are significant innovations in the integration of clinical data into the computational workflow and the personalisation of model parameters, and in the streamlining of the analysis process so that it is operable, with acceptable accuracy, in timescales of a few minutes. The process from medical image through data integration to computational results is automated, although there is the facility for inspection and manual correction of valve anatomies for difficult cases. Each case of the 120 cases in the EurValve cohort was processed in approximately four minutes.
The onward exploitation trajectory for EurValve is well-identified, and the prospects for a product with appropriate regulatory approval reaching the market in the foreseeable future are good. It is the intention of the developers to continue with this work, and to bring an enhanced EndoSize product with Decision Support to the market.
