Cardiovascular Disease (CVD) is characterized by multidimensional risks including drug, diet, lifestyle, stress, and metabolomics diseases which cause mortality and morbidity depending on age and status of chronic diseases. However, emerging evidence indicated it is preventable health complications that depend on risk management along with lifestyle change, and personalized medication that include alternative measures like Diet use following molecular diagnostic and imaging analysis. CVD is mainly attributed to the narrowing of blood vessels through atherosclerotic lesions and/or thrombosis. Hypertension, obesity, and hyperlipidemia are major risk factors for the development of CVD and treating these diseases is essential in slowing down progression of CVD. Inflammation appears to play a pivotal role in CVD and can be measured through a simple blood assay (CRP). Multi-omics approaches have been essential in the development of treatments for CVD, in the prevention of CVD, and in the diagnosis of CVD. There are many outcomes available to help with diagnosing CVD and omics platforms have helped scientists and clinician develop these diagnostic tools. Radiomics has played a key part in the diagnosis of CVD as being able to view the diseased heart is essential in determining CVD progression and the treatment options suitable for that secondary disease related. Nutrigenomics is emerging as the future of medicine such as utilizing treatment strategy innovation instead of medications, but it is still in its infancy. Nutrigenomics will open the doors to different therapeutic drug targets and allow us the ability to be more specific in our treatment options. There are only a few gene-diet interactions documented that increase a person’s chances of developing CVD. Curating an individual diet and treatment plan based on somebody’s genetic disposition or skewed immune responses following personalized diagnosis will be essential in the survival of these severe CVD patients. Key issues referring to risk surveillance and prevention is a distant approach which reflects several factors: for example, what type of tools can be used to conduct diagnosis, molecular diagnostic tools detect what type of biomarkers are present prior to prescribing the personalized diet and to ensure diagnostic accuracy. Recently, increasing findings emphasize dual aspects of diet such as immune enhancers and modulators in which gut microbiota has been proven to play a major factor in development of CVD. The future direction of omics studies will foster the ability to test the impact of gut microbiome of a patient with CVD following diet driven organ protection as well as prescribe essential components of the diet that can be adjusted with proper probiotic medication. Proper diet adjustments can correct the organ dysfunction that occurred due to interaction between molecular mismatch and cellular damage following stress-mediated damage or chronic disease. Further micro-scale assays and molecular diagnostic techniques following nutrigenomics application to the patient could be beneficial to allow patient’ care shift from physician driven and clinic based to self-management with knowledge based at home treatment programs that work by envisioning molecular reprogramming and rejuvenation of damaged organ. These at home treatments can be utilized with development of radiological data with innovation of software. The aim of the short review is to visualize the current role of nutrigenomics and diet formulation for integrative care (e.g., diagnosis, prevention, and treatment of CVD) which would take advantage of earlier prevention synchronized with current medical tests, imaging techniques. Health economy like management can reduce medical cost with disease prevention disease and could modulate the following: enhance knowledge-based interaction between body and diet, discuss cognitive enhancement how sensing with molecular behavior under image-management platform, monitor drug surveillance of current treatment options in CVD and the pitfalls of current omics application and data transformation needs for patient care in the future.