Mathematical Models Derived Indices for the Selection and Planning of a Specific Optimal Treatment to the Patient in Heart Failure

Study Overview
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Brief Summary
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Heart failure is a growing throughout pathology in Europe. It is a public health issue and an economic issue. The management to be effective needs to be early but specific. Generic treatment (medication, rehabilitation, hygienic dietary measures) known for over 15 years and has demonstrated its effectiveness, come s'ajouter solutions specific, technically complex and expensive to implement. Because of the potential risk to the patient and their cost to the company, these new techniques need to be adapted to each case. The passage of a generic simple treatment for everyone in the single treatment tailored to each patient requires decision support tools for the clinician. These tools or decision trees are developed using mathematical and statistical models fed by all patient data (imaging, biology physiology ...) before and after implementation of treatment. Predictive response models of a treatment applied to a particular pathology can thus be generated. It is this type of models applied in systolic heart failure complicated by mitral regurgitation and / or cardiac synchronization that will be generated in this project from 150 patients included in 3 European clinical studies (London, Brussels, Caen). In Caen we will include 30 patients in this single-center study

Detailed Description
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Heart failure (HF) is a clinical problem increasingly common throughout Europe, partly because of the aging population and increasing numbers of patients now survive after myocardial infarction [1, 2] . The IC is a progressive disease and when patients require hospitalization, long-term prognosis is poor [3]. The treatment of IC is focused on improving the work of the failing heart via the use of specific drugs, if necessary by cardiovascular interventions correcting structural lesions (mitral regurgitation) or correcting a disorganized contraction (therapy resynchronization). However, the IC is a disease complex with multiple factors pathophysiological interdependent making difficult treatment choices optimal or of a combination therapeutic optimal. The technologies HPV predictive, such as tools for processing data, statistical models and simulations biophysical that incorporate these factors pathophysiological have tremendous potential to help improve our understanding of the response to treatment in the context of the IC. In particular, they have the potential to improve the selection of patients for cardiovascular interventions such as cardiac resynchronization therapy and / or that an intervention on the mitral valve [4]. Projects recent - European (HPV or Human physiological virtual) and national - have developed a large number of these technologies, but n'ont not been fully released into the environment clinic to help care for patients IC. The objective of VP2HF project is to develop and validate in clinical settings computer modeling platform to integrate non-invasive clinical and imaging evidence acquired in patients with heart failure ( IC) for two reasons: Identify for each patient, the likely response to different therapeutic interventions with all clinical data processed by a decision support system. Optimize responses or interventions selected for each patient to maximize treatment response. This is a pilot study to generate complete data sets used to parameterize the model calculations. All patients will have an accurate imaging assessment and a detailed assessment of bio-signals at times (time points) accurate (as shown above) with variations depending on the sustained cardiovascular procedure described below . Preoperatively Evaluation of symptoms with the Minnesota Quality of Life Questionnaire in patients with heart failure (MLHFQ) 6 minute walk test cardiopulmonary stress test (CPET) to assess VO2 max Reference initials Blood tests (CBC, urea and electrolytes, NT-proBNP) 2D and 3D cardiac echocardiography Cardiac MRI including myocardial tattoo 3D sequences (tagging 3D) and 4D sequences for blood circulation Non-invasive measurement of central blood pressure Peri-interference Whatever the treatment envisaged by the surgical team in charge of processing (resynchronization, mitral clip, mitral valve repair or mitral valve replacement) operative techniques and monitoring procedures will be those normally used by operators. Cardiac resynchronization therapy (CRT) can be considered that 70% of patients in our cohort eligible for a CRT are also eligible for this project. Invasive measurement of left ventricular pressure with and without stimulation may also be acquired to study the acute hemodynamic effects of CRT and to make comparisons with the extent of NBP in order to test and validate the noninvasive pressure estimates and mechanical modeling tools. Repair and replacement of the mitral valve: It is expected that 30% of our cohort of patients have significant mitral regurgitation requiring intervention, mainly to repair the mitral valve and the occasional replacement of the mitral valve when the repair is unsuccessful. In some of these patients, the repair will be carried out by trans-catheter track and they will hemodynamic measurements in the aorta, the left ventricle and the left atrium before and after the repair of the mitral valve that will be used for the purposes of test and validate non-invasive estimates of pressure and mechanical modeling tools. Immediately after surgery All patients will again echocardiography, non-invasive measurement of central blood pressure. Followed at 6 months We will again perform , 6 months after surgery , complete postoperative evaluation unless cardiac MRI in patients with a CRT ( because this review is against - indicated ) . in addition to standard care pathway exams non-invasive measurement of central blood pressure The non -invasive blood pressure management Centron Diagnostics uses a humeral standard oscillatory cuff estimate both the PA peripheral and central aortic pressure. For the patient, this is an experiment similar to that of an automatic blood pressure recording . All patients benefit from this measure . Exams IRM3T to Cycéron (M0 and M6)

Official Title
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Mathematical Models Derived Indices for the Selection and Planning of a Specific Optimal Treatment to the Patient in Heart Failure

Conditions
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Heart Failure

Intervention / Treatment
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* Other: expert system development


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Have given informed consent for participation in the study. Male or female, aged 18 years Heart failure stage II -IV NYHA . Be awaiting a response to cardiac resynchronization therapy (CRT ) or replacement / repair of the mitral valve (MVR / r ) Affiliated to social security scheme Francophone Exclusion Criteria: Age <18 years Major Adult guardianship Pregnancy , lactation, or desire to start a pregnancy during the study period ( for women) Contraindications to MRI Continuous Treatment or continuous infusion with an inotropic agent for heart failure. Recent myocardial infarction ( <1 month) requiring revascularization unbalanced severe hypertension ( BP> 160/110 mmHg) Significant hepatic impairment Any other significant disease or condition, which in the opinion of the investigator , may create a risk for the participant because of its participation in the study , or affect the results of the study, or to affect the patient's ability to participate in the study .

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Other: expert system<br>System for predicting patients heart failure, that can predict response to a personalized treatment from the analysis of a set of data (images, physiological data , treatment outcomes ) . | Other: expert system development<br>* data collection (imaging, biology physiology ... ) of patients with systolic heart failure complicated by mitral regurgitation and / or cardiac synchronization before and after implementation of the recommended standard treatments and modeling using mathematical and statistical models fed all data .<br>* Other names: System that can predict response to a personalized treatment;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Prediction from the model computer remodeling reverse | Prediction from the model computer remodeling reverse as defined by reduced LVESV 15 % (on ultrasound or MRI) 6 months after the intervention (CRT or VCR / r ) . | 6 month after intervention | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| MLHFQ Questionnaire | Prediction based computer model of the response to intervention as defined by an improvement 6 months after intervention | 6 month after intervention | 
| 6 minute walk test ( 6MWT ) | Prediction based computer model of the response to intervention as defined by an improvement 6 months after intervention | 6 month after intervention | 
| VO2 max | Prediction based computer model of the response to intervention as defined by an improvement 6 months after intervention | 6 month after intervention | 
| NT-proBNP | Prediction based computer model of the response to intervention as defined by an improvement 6 months after intervention | 6 month after intervention | 
| non-invasive measurement of central blood pressure | Prediction based computer model of the response to intervention as defined by an improvement 6 months after intervention | 6 month after intervention |