Coronary artery disease (CAD) is the main cause of cardiovascular morbidity and mortality with a global estimation of 110.55 million prevalent cases and 8.92 million deaths, which makes CAD the leading cause of death in the world. The relationship between cardiovascular risk...
Coronary artery disease (CAD) is the main cause of cardiovascular morbidity and mortality with a global estimation of 110.55 million prevalent cases and 8.92 million deaths, which makes CAD the leading cause of death in the world. The relationship between cardiovascular risk factors, atherosclerosis and clinical events in CAD patients is considerably complex and, despite its huge socio-economic impact in Europe, primary and secondary prevention of CAD is far from optimal. A comprehensive predictive model of CAD severity/progression that integrates vascular and systemic factors into a unique tool for clinical decision support through a personalized medicine approach is not currently available.
SMARTool output is a computerised platform, based on cloud technology, for decision support to clinical management of patients with stable CAD, by standardization and integration of heterogeneous health data. Models included in the platform are based on the implementation of the existing multiscale and multilevel models developed by the former EU-funded project ARTreat. Systemic/demographic patient data as well as molecular markers, including lipidomics and transcriptomics, eventually acquired with the utilization of a microfluidic device for on-chip blood analysis (LoC), are used in the final version of SMARTool clinical decision support system (CDSS) platform.
The CDSS is expected to help cardiologists assessing CAD presence/severity risk, predicting CAD progression and tailoring therapeutic interventions. In particular, the platform supports: 1. Patient-specific diagnosis of CAD extent and severity. SMARTool platform includes a gene expression-based pre-test CAD prediction algorithm to stratify high risk patients to non-invasive coronary CT angiography (CCTA). Plaque-specific CCTA-based tools enhance the diagnostic accuracy of CT scans by virtual fractional flow reserve assessment (Smart-FFR) of functional significance of stenosis. 2. Patient-specific and plaque specific CAD progression prediction. Site specific plaque growth and machine learning-based patient specific CAD progression prediction models implementation and validation. 3. Patient-specific CAD treatment: Patient-specific optimal medical treatment and/or support to revascularization interventions are provided. CCTA based virtual angioplasty supports the interventional cardiologist in optimal stent deployment and revascularisation assessment by computation of smartFFR.
The following activities have been conducted during SMARTool:
• A multicentric clinical trial with clinical, imaging and molecular data upload into a standardized repository (CRFA): all results of the learning cohort, including omics analysis results of patient RNA and DNA sequencing, had been provided to technical partners for implementation of CDSS models and modules.
• Development of the prototype of the LoC; functionalization with antibodies and validation tests on blood samples for molecular and cellular assay.
• Development and integration into the platform of the pre-imaging module (PIM) of the CDSS by implementing a pre-test algorithm based on clinical and biomolecular features, in particular gene-expression mRNA profile with good discriminative accuracy in stratifying CAD presence/severity within the learning cohort of patients.
• Implementation and refinement plus internal clinical validation of imaging-driven tools: 1. CCTA images 3D coronary reconstruction 2. virtual fractional flow reserve computation (Smart-FFR) 3. site-specific plaque growth prediction and patient-specific CAD progression prediction, 4. virtual stenting for functionally significant coronary stenoses 5.) optimal medical therapy (OMT) module for patients with no significant stenosis but high risk for CAD progression. Integration of these models into the corresponding modules of on-cloud platform.
• Design of the architecture of SMARTool CDSS and integration of all components into the final version 2.0, released at the end of the Project: clinical usability testing of the platform (Fig. 1-2). Users requirements, technical system usability assessment and intentions to adopt the CDSS platform have been acquired by dedicated questionnaires filled by stakeholders/clinical end users.
• Exploitation strategy, evaluation of the regulatory framework for SMARTool platform adoption in current practice and cost-effectiveness analysis of SMARTool CDSS-based management of suspected stable CAD compared to standard practice.
Table 1 summarises the main scientific/clinical and technical results achieved during the Project while figure 3 summarises the roadmap of the final exploitation plan of SMARTool platform.
The future activity after Project end is dedicated at promoting the exploiting SMARTool platform as a whole and single components/modules in the current clinical workflow of suspected or established stable CAD management. The clinical validation required by European regulatory agencies for SMARTool CDSS - software as medical device - falls under European Medical Device Regulation compliance and requires large trials before commercialization.
Finally, SMARTool dissemination is an activity wherein the whole consortium is active and engaged for boosting communication of the project results: as the dissemination of SMARTool outcomes is important not only for communication but also to achieve the exploitation objectives, several scientific articles to high impact journals have been already published and more are under submission/preparation.
The final outcome of SMARTool is a CDSS platform beyond the state of the art with integrated functionalities for clinical management of patients with suspected CAD and/or asymptomatic patients with risk factors (Fig. 1-2). The first module of CDSS is the PIM calculator of CAD presence/severity risk score. CCTA based models include the 3D coronary reconstruction, the plaque growth and CAD progression prediction, smart FFR computation and virtual stenting. They integrate the information obtained by a CT scan in terms of plaque features, quantitative measurements, virtual estimation of FFR, prediction of CAD progression and simulation of stent deployment for stent implantation procedure. The novel CDSS, combined with cost effective miniaturized devices for Point of Care Testing such as Lab on-chip and RNA panel kit, is expected to considerably optimise patient monitoring and CAD management, with impact on the quality, accessibility and cost-effectiveness of healthcare. The expected benefits are: 1. Benefits to the patients to gain a more accurate diagnosis, prevention/prediction and treatment of CAD and CAD related clinical events. 2. Benefits to healthcare professionals due to optimised primary and secondary prevention of CAD (less unplanned visits, re/hospitalization, etc). 3. Benefits to the healthcare system and policy makers, by re-organizing prevention, diagnosis and treatment strategies of CAD by translating multiscale modeling into practice. 4. Indirect benefits to the other actors, such as the eHealth market and medical pharma in terms of competitiveness and revenues increase. The medical software and devices industry can integrate the gained knowledge, developing software for diagnosis, prediction and treatment in other chronic diseases at high social impact.
More info: http://www.smartool.eu/.