According to the Centers for Disease Control and Prevention, heart disease is the number one killer in America today. Nearly 2,400 people die each day from heart and blood vessel diseases and more than 7 million Americans have suffered a heart attack in their life time, according to American Heart Association data. Around 500,000 of these individuals will experience recurrence in a year. More than two million patients are triaged and treated for acute coronary syndrome in emergency wards across the country each year. These statistics are increasing by the day. A significant amount of research has therefore been devoted to screening for coronary artery disease (CAD) and to the delineation of mild and moderate from significant CAD disease. Despite the expensive and elaborate testing modalities that are being utilized, the incidence of sudden coronary events and cardiac death is still the leading cause of mortality and disability in the US. Therefore, coronary angiography is still the gold standard to identify significant CAD. With increased coronary angiography, there is increased coronary angioplasty. Hence, CAD is also the number one offender of healthcare spending. Unfortunately, despite the extensive investment in high cost modalities for differentiating mild to moderate CAD from significant CAD, no clear confidence has been instilled in cardiologists to safely avoid unnecessary catheterizations and coronary angioplasties.  Hence, the need exists for a cost effective, reliable, non-invasive and universally easy to use modality to differentiate mild to moderate CAD from significant CAD. In this manuscript, we introduce a novel noninvasive coronary ischemia screening and CAD evaluation protocol using the CS-100 (Cardio Scan–100) Frequency Cardiograph (FCG) analysis system. 

Keywords: CAD, Acute coronary syndrome, Coronary care, Cardio Scan–100

BACKGROUND

Acute coronary syndrome (ACS) is the umbrella term for clinical presentations of different stages of myocardial ischemia, ranging from angina/unstable angina (USA) with mild to moderate coronary artery disease (CAD) to acute ST-segment elevation myocardial Infarction (STEMI). Coronary Artery Disease (CAD) with plaque build-up in the coronary arteries compromises myocardial blood flow and modifies myocardial compliance, contractility, and blood flow dynamics. Coronary insufficiency can be from mechanical obstruction due to plaque build-up or from abnormal vasoreactivity due to vascular endothelial cell dysfunction and vascular inflammation. Abnormal vascular wall homeostasis with low vascular wall nitric oxide concentration and increased free radical (reactive oxygen species-ROS) pool occurs from dysautonomia-induced endothelial cell dysfunction. These are dynamic modifications that can be difficult to quantify. Abundant laboratory evidence indicates that inflammation plays a major role in all stages of atherosclerosis. Clinical evidence from several prospective studies demonstrates that inflammatory biomarkers independently predict vascular disease risk with a magnitude of effects as significant as increased blood pressure or high cholesterol. Prospective analysis from JUPITOR trial data indicate that achieving low levels of inflammation may be as important as achieving low levels of LDL-c cholesterol [1]. JUPITOR data prospectively confirms data from several prior studies including CARE, AFCAPS/TexCAPS, PROVE IT, TIMI22, A to Z, REVERSAL. These trials corroborate laboratory evidence that anti-inflammatory processes reduce cell adhesion, monocyte recruitment at the arterial wall, augmented expression of the transcription factor KLF2 with consequent migration of inflammatory and thrombotic mediators, altered smooth muscle migration and reduction in IL-6 and other cytokines triggering plaque development.

Extensive research and a plethora of non-invasive testing modalities such as nuclear stress testing with Dobutamine Stress ECHO (DSE), SPEC imaging, pharmacologic stress testing with imaging, positron emission tomography (PET) imaging, coronary computed tomography angiography (CCTA) and coronary calcium scoring are some of the newer modalities that are being investigated to assess CAD and delineate mild to moderate CAD from significant CAD. This differentiation has both prognostic and therapeutic value. While significant CAD has a strong correlation to mortality and morbidity, mild to moderate CAD has good long-term prognosis with medical management alone. Fear of missing the monster (significant CAD) has driven research and the cost of caring for patients with CAD. Unfortunately, despite the extensive investment in high cost modalities for differentiating mild to moderate CAD from significant CAD, no clear confidence has been instilled in cardiologists to safely avoid unnecessary catheterizations and coronary angioplasties. This has been clearly demonstrated in the recent National Cardiovascular Registry (NCDR) data. Retrospective NCDR registry analysis of >400,000 positive non-invasive coronary ischemia tests found obstructive CAD association in only 38% overall [2]. In female patients, particularly, only 33% had obstructive CAD, while >55% had normal angiograms. Appropriate use criteria (AUC) and unnecessary angioplasty recommendations generated by ACC and AHA, based on NCDR registry findings, have been arguably debated by interventionists for lack of high specificity and sensitivity in the available modalities to delineate false positivity and prevent false negative results. This forces interventional cardiologists to err on the side of safety. Hence, the need exists for a cost effective, reliable, non-invasive and universally easy to use modality to differentiate mild to moderate CAD from significant CAD.

Recent NCDR registry 2010 data analysis by Patel et al. [2] demonstrated poor yield from non-invasive testing in identifying significant CAD by coronary angiography and identified coronary angiography as the culprit for wasted healthcare dollars and demonstrated poor health care delivery. The American Heart Association (AHA) and the American College of Cardiology (ACC) therefore updated practice guidelines and performance measures for CAD to help clinicians adhere to standard of care. Appropriate use criteria (AUC) were developed by a task force from ACC to limit overuse of angiography and revascularization procedures. This was prompted due to recent literature demonstrating comparable mortality and morbidity between aggressive medical management and coronary revascularization. The cost for revascularization has skyrocketed in the last three decades. Despite the widespread use of percutaneous coronary interventions (PCI), the appropriateness of these procedures in contemporary practice is unknown and the mortality from CAD has not been affected by PCI. Based on this premise, there was a recent prospective study conducted to evaluate appropriateness of PCI highlighting inappropriate use of PCI [3-5]. However, stakes are high in ACS in high-risk groups to not intervene with PCI and adapt medical management safely. An expert panel published a study recently offering constructive criticism of the AUC and pointed out the deficiencies in AUC and the risk involved in adapting the AUC in high risk groups (Percutaneous coronary intervention uses in the United States: Defining Measures of Appropriateness by Arbab-Zadeh et al. [4]. They argued that while minimizing overuse of PCI is important, the AUC that were developed do not assess properly the effectiveness of PCI in high risk subgroups such as DM-II, known as significant CAD. In their criticism, they highlighted a few facts and made recommendations for revisions to AUC [6]: 

•          Relying on these tests for authorization for coronary angiography would be inappropriate.

•          Provocative testing in high-risk symptomatic patients is risky.

•          Minimizing overuse and underuse of PCI should be a national healthcare priority.

•          The AUC do not assess effectiveness (PCI can be appropriate without improvement of symptoms).

•          Scenario 12B (1- or 2-vessel disease, without proximal LAD, low-risk findings on noninvasive testing, 0 or 1 anti-angina medications (of CCS class I or II) should be changed to ‘uncertain.’

•          The CTO-specific AUC categories should be removed.

The above concerns by experts highlight the unpredictability of CAD and the inadequacy of current noninvasive testing in assessing obstructive CAD (OCAD). This is more so in high-risk groups such as women and diabetics. Various types of testing modalities for coronary ischemia are recognized as sensitive but lack specificity with high false positivity. There is growing consensus that this lack of specificity results in a significant number of unnecessary coronary angiographies thereby exposing patients to risk of invasive procedures without commensurate clinical benefit. Patel et al published an analysis of the ACC-NCDR of patients undergoing coronary angiography, which included 397,954 patients. CAD was absent in 39.2% of patients. The authors created four separate models for predicting positive results on angiography: 1) Framingham risk score alone; 2) Framingham score plus clinical risk factors; 3) Framingham score, clinical risk factors and presence of symptoms; and 4) results of non-invasive testing (i.e., stress testing). The pre-test predictability of significant OCAD after clinical presentation was 0.67 in this study. Adding Framingham scoring improved the positive predictability to 0.74. Additional non-invasive testing improved the positive predictability to only 0.76 for a significant increase in the cost of care that is not justified.

In patients presenting with ACS, the presence of 2 or more Framingham risk factors, diabetes and female gender predisposes to higher mortality. Sudden cardiac death is the first presentation of CAD in up to 52% of women. Silent myocardial ischemia and silent infarctions are common in diabetics and women. Among patients with known previous CAD, the occurrence of false positive test leading to unnecessary catheterization and false negative test resulting in costly miss of significant OCAD is high, particularly in diabetics and women, as demonstrated in the Patel et al.’s NCDR analysis [2]. We have also found up to 49% discordance in a retrospective analysis of three years of catheterization lab census between stress test results and findings at coronary angiography in patients undergoing coronary angiography based on noninvasive testing at our institution. Therefore, using AUC to guide therapy and relying on noninvasive testing with poor yield and specificity is not prudent. We believe these findings in diabetics and women are due to abnormal vasoreactivity paradoxical vasoconstriction to acetylcholine stimulation (can be tested by brachial artery reactivity testing (BART)) from endothelial cell dysfunction and vascular inflammation. Provocative testing such as exercise stress testing and pharmacologic stress testing in these patients is unreliable and can induce vasospasm that results in false positive tests. At RENU-CA research we have extensively demonstrated dysautonomia and abnormal vasoreactivity clinically over the last 12 years in >1000 patients. Framingham risk scoring system for 10 year coronary heart disease prediction has been developed based on which patients can be categorized into mild, moderate and high-risk groups. This is standard of care practice and has stood the test of time by the cardiology community. National cholesterol education program (NCEP) and American Heart Association guidelines now recommend presence of Diabetes Mellitus to be considered as known independent CAD risk. Dysautonomia is a common association in type-II diabetes and women; hence there is a higher incidence of abnormal vasoreactivity. Patel study therefore demonstrated lower yield in Women and diabetics with high false positivity. Also, these sub-groups of patients have a higher predisposition to acute coronary events therefore are independent risk factors [7].

COMPUTERIZED CORONARY TOMOGRAPHY ANGIOGRAPHY

Due to poor yield in delineating OCAD by noninvasive testing, newer modalities of testing have been developed. Computerized coronary tomography angiography (CCTA) is a newer modality for CAD assessment. In a recent publication, researchers used Medicare administrative data analysis and found that patients undergoing CCTA were more likely to undergo subsequent confirmatory coronary angiography and revascularization relative to those receiving traditional stress testing thereby, increasing the cost of care [8-12]. Yet despite this increased cost from utilization of resources, the short-term outcomes were similar. The CORE-64 (Coronary Artery Evaluation using 64-Row Multi-Detector Computed Tomography Angiography) International Multicenter Study published recently concluded that both pre-test probability for CAD and coronary calcium scoring should be considered before using CTA for excluding OCAD [13-19]. This study highlighted the inadequacies of CTA and its lack of efficacy in patients with calcium scores of >600 and in patients with a high pre-test probability of OCAD. The negative predictive value of CTA dropped from 0.93 to 0.50 in patients with known CAD and 0.93 to 0.75 in patients with calcium score of <100 [5]. Based on these findings, CTA is not recommended for diagnostic purposes in patients with substantial coronary calcification and in very low coronary calcification. CTA is also unreliable in high-risk groups with known prior CAD. CTA is also an anatomic marker of CAD and does not indicate functional significance. In determining the use of coronary CTA, one needs to also consider the potential harmful effects of radiation. The doses of radiation needed are substantial, 12-15Sv, equivalent to 600-800 chest X-rays or 3-7 coronary catheterizations. This may predispose to malignancy notwithstanding the expense of performing CTA. CTA also has exclusion criteria such as serum creatinine >1.5 mg/dl, prior cardiac surgery, Class-III/IV heart failure and atrial fibrillation, recent coronary intervention within 6 months, intolerance to beta-blockers and BMI>40 kg/m² BSA. In summary, newer testing modalities for CAD assessment are expensive, cumbersome with minimal yield or added benefit to patient care. A recent comparison study of Coronary CT Angiography, SPECT, PET and Hybrid imaging for diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve (FFR) from the Netherlands was published in JAMA Cardiology fall 2017. Their conclusion in this head-to-head comparison in 208 patients is PET scan exhibits the highest accuracy and FFR did not add incremental diagnostic yield [18].

Percutaneous coronary intervention and Visual-Functional mismatch

With over use of coronary angiography comes the problem of over use of PCI. In a multi-center trial of patients within the NCDR undergoing PCI during the period of July 2009-September 2010 in 1091 hospitals in the US, Chan et al. addressed appropriateness of PCI [2]. In this multi-center study, the appropriateness of PCI was adjudicated using AUC developed by ACC. Results were stratified by whether the procedure was performed for an acute (STEMI or non-STEMI or high-risk USA) or non-acute indication. Over 500,000 PCIs were evaluated. In this large contemporary cohort, nearly all PCIs were appropriate in the acute situation. In the non-acute cohort, however 12% PCI’s were classified as inappropriate with significant inter-hospital variability. This study has obviously created a controversy in interventional cardiology, particularly because the NCDR data collection forms have quite a few shortcomings in being truly representative of real world scenarios and AUC criteria are not optimal. Nevertheless, it raises an issue with the appropriateness of elective PCIs. Several investigators have reported discrepancies between the severity of coronary angiographic stenosis and the functional severity – the so-called Visual-Functional mismatch. In one study of 143 patients with angiographic 3-vessel disease, 77 (54%) had no perfusion defects or only 1-vessel pattern as determined by perfusion imaging [19]. In another study of 67 patients with angiographic multi-vessel disease, 26 patients had no perfusion defects and 24 had only 1-vessel perfusion defect according to myocardial perfusion imaging performed after coronary angiography [20]. The fractional flow reserve versus angiography for multi-vessel evaluation (FAME) study published recently is a landmark study exposing the Visual-Functional mismatch phenomenon. A recently published sub-analysis of the FAME study thoroughly evaluated the Visual-Functional mismatch phenomenon of CAD [21]. Of the patients with 3-vessel disease as assessed by visual estimation, only 14% had 3-vessel disease after FFR (Fractional Flow Reserve) measurement, whereas 9% had no functionally significant stenosis. These findings indicate that in the absence of FFR, approximately 40% of the PCIs would have been performed in functionally insignificant stenotic lesions. Furthermore, a significant number of so called 3-vessel disease patients sent for bypass surgery can be treated by PCI. This phenomenon of Visual-Functional mismatch occurs due to multiple factors. These include lesion factors such as lesion length, eccentricity, size of the vessel and the amount of myocardium in jeopardy. A moderate stenosis in a vessel that supplies large myocardial territory can be functionally significant; whereas, a significant stenosis in a small vessel with minimal myocardium at risk may not be functionally significant. This is a mathematically driven phenomenon; therefore, FFR is very sensitive in this situation. Perfusion imaging may not be able to differentiate subtle ischemic burden from significant ischemia functionally.

When dealing with CAD, which can become life threatening rapidly, one of the concerns among physicians is the long-term safety of differing invasive treatment. Nuclear imaging studies have suggested that treatment of non-ischemic coronary lesions may be different, but safe [22]. In a meta-analysis of thallium single photon emission computed tomography (SPECT), the annual incidence of death or myocardial infarction was less than 1% per year in these patients. Patients with lesions with insignificant FFR values were also shown to have favorable outcomes [23,24]. A randomized trial to address this concern is the DEFER study (FFR to Determine Appropriateness of Angioplasty in Moderate Coronary Stenosis). In this study, 5 year outcomes in patients were randomized to medical therapy vs. PCI based on FFR<0.75 or >0.75 for death or myocardial infarction was <1% [25]. In response to these findings, there is a big push in interventional cardiology for using intravascular ultrasound (IVUS) and FFR in guiding PCI. Recently published results of the FAME study demonstrated that patient and lesion selection and treatment decisions based on systematic assessment of FFR may improve clinical outcomes of PCI and save costs as well, particularly in the multi-vessel disease due to limiting unnecessary PCIs [26]. Because of the data from this pivotal trial, the results have been incorporated into the current guidelines for patients with CAD. United States PCI guidelines now have classification of recommendation class-IIa for FFR with a level of evidence A. European PCI guidelines have also adopted FFR. FFR is unique and preferred in the accurate assessment of functional significance of stenosis of individual coronary artery because FFR has a sound mathematical basis that has been validated extensively. Adding routine use of FFR and IVUS during all PCI procedures, however, becomes a cost issue and to some degree a safety issue as well. FFR and IVUS are also assessments during angiography and may have some limitations in some patients such as those with diffuse distal disease, where FFR may over estimate and in tortuous vessels where FFR and IVUS may not be feasible. Since it is an assessment done during angiography, there may be an element of bias in committing to PCI due to the effort and time involvement by the operator to arrive at a conclusion that may favor PCI. In a recent analysis of 661,063 patients undergoing coronary angiography for abnormal noninvasive coronary ischemia evaluation including single photon emission computed tomography-myocardial perfusion image (SPECT-MPI) and CCTA, out of 81% with abnormal studies prior to angiography only 45% had significant obstructive CAD>50% [27].

Therefore, noninvasive FFR assessment modality is under investigation and studies have been published evaluating the usefulness and accuracy of noninvasive FFR assessment derived from CT angiography as shown in a recent report [28]. In these studies, the efficacy and usefulness of non-invasive assessment of functional coronary stenosis has been demonstrated to be comparable to invasive FFR. FFR derived from CCTA images (FFRct) is emerging as a novel non-invasive method to evaluate lesion-specific diagnosis of CAD. CT-derived FFR is calculated by processing the same images used for evaluating coronary arteries under resting conditions. The significance of coronary lesions at hyperemic flow condition can be estimated by computational flow modeling, and no adenosine is required. Thus, CT-derived FFR estimates virtual hyperemia for the calculation. Hence, additional image acquisition, radiation exposure, or pharmacological stress during CCTA scanning, are not necessary for the computation of FFR from coronary CT. Based on the recent FFRct data the Centers for Medicare and Medicaid Services (CMS) will begin reimbursing for the HeartFlow FFRCT Analysis under a New Technology Ambulatory Payment Classification (APC). The reimbursement will be $1,450.50 for the technical component of the test. A HeartFlow-guided strategy reduced the overall costs to the healthcare system by more than $4,000 per patient after one year. The mean one-year per-patient cost for the usual care strategy was $12,145 compared to the $8,127 cost for the HeartFlow-guided strategy. When including the $1,500 cost of the HeartFlow Analysis, the cost reduction is 26% [28-36].

Although numerous studies have shown the prognostic value of anatomical stenosis by CCTA [37,38], this misclassification may influence the treatment decision making among patients with suspected CAD and future risks. In a study of 81 patients who underwent both ICA with FFR and CCTA, when invasive FFR ≤ 0.75 was considered appropriate for revascularization decision making, 30% of patients failed to undergo appropriate revascularization by CCTA guidance due to lack of evidence of functional significance or inappropriate deferral compared to FFR guidance [39]. Thus, based on these issues, we may need a new approach after CCTA performance to more accurately identify patients who would benefit from revascularization.

From all the above data and studies, it is clear that the problem of delineating mild/moderate CAD from significant CAD is an unresolved issue. Furthermore, most modalities that have been developed are prohibitively expensive and cumbersome, with limited access to most patients and the community at large. In this era of cost containment in medicine, appropriate diagnosis and treatment of CAD is a difficult task as the price of missing significant disease among all comers can be mortality and high morbidity from heart attacks. 

OVERVIEW OF THE MULTIFUNCTION CARDIOGRAM (MCG)/FCG-CS100 ANALYSIS

New non-invasive modalities that electronically deconstruct cardio-electrical current data from multiple lead electrodes over 70-90 s of continuous monitoring by complex multi-step mathematical transformational analysis into functional components called indexes. This information is then digitized using standard Fast Fourier Transformation (FFT) analysis. This electrical information from the heart reflects the dynamic interaction of the myocardium and intra-cardiac blood flow over multiple cardiac cycles. The data is then compiled into indexes that are compared against >20,000 validated database of patients with known heart disease and normal people to develop cohesive patterns that allow rapid computerized pattern recognition. Two different operating systems based on the same analysis model and validated database have been developed: MCG and FCG-CS100 systems.  

The Multifunction Cardiogram also referred to as the 3DMP and FCG-CS100 analysis is a completely new approach to diagnosing cardiac disease that uses complex mathematical analysis and are the first examples of tools in the discipline of “Clinical Computational Electrophysiology”. They use mathematical analysis of resting electrical signals from the heart to aid in detecting CAD and thus improve patient selection for angiography and PCI. This has significant prognostic value and is cost effective as well.

MCG uses systems analysis approach in obtaining an objective and quantitative assessment of CAD. It uses six mathematical transformations to study cardiac electrical signals. These transformations enable detection and analysis of changes to the electromyocardial physiologic function that result from alterations in coronary blood flow. Instead of merely retrieving summed information about the electrical activity of cardio-myocytes at a single time point during a single cardiac cycle, as a traditional ECG does, MCG/CS-100 are specifically engineered to collect data over an 82 s period synchronously from only two leads, thereby obtaining information about the dynamic interaction of the myocardium and intracardiac blood flow over multiple complete cardiac cycles. MCG digitizes the individual’s electrical signals, deconstructs them via the six mathematical transformations into multiple functional components (called indices) and then reconstructs them by mathematically integrating the indices into a cohesive pattern that allows rapid computerized pattern recognition. This deconstruction and re-synthesis of the information extracted from these multiple functions allows one to study the interactions between the information obtained from each lead, which is impossible using conventional 12 lead ECG. By comparing the individual’s pattern to other patterns contained in a large database, it is possible to model, quantify and understand the ongoing stress-strain interaction between the myocardium and intracardiac blood flow, which enables one to directly and objectively identify chronic (Hibernating myocardium) or acute coronary ischemic alterations. Therefore, MCG is a comprehensive ischemia and myocardial function test that can be used for identifying various levels of functional myocardial ischemia and for identifying hibernating myocardium. CS-100 analysis also operates on the same principles.

It is important to emphasize that both the analytic approach and the information in the database have been validated. First the indices and patterns obtained from the mathematical transformations have been empirically derived as well as verified and validated to be clinically meaningful. Second, all the patient data entered into the database, against which an individual’s patterns are compared for the purposes of obtaining diagnostic information, has also been validated and verified. The index cluster and pattern for each patient’s data has been correlated with the findings of coronary angiography, other relevant diagnostic work-up and the final diagnosis of the treating physician, which has been verified by at least two independent expert diagnosticians in the field. As information in the database accumulated, additional requisite internal validation, internal to the engineering process, was performed. After these validation procedures were completed and the system’s final iteration met the intended purpose of the original design, external peer review quality clinical validation trials of the entire system were carried out (i.e., published MCG clinical trials). MCG has been cleared by the FDA as an aid to diagnosis by means of analysis of ECG waveforms in the frequency domain (power spectral estimate). FCG-CS100 system is also based on the same system analysis as MCG but utilizes cardio-electrical data generated from 2-lead electrodes as well as 12 leads electrodes thereby allowing localization of stenosis specific to individual coronary artery affected.

CS-100 TESTING

Multiple cycles of complete resting ECG analog signals from 12 leads are recorded by a portable Laptop device from a patient at the point of care over duration of 80-90 s.

Digitization, encryption, Fast Fourier Transformation of the raw data and mathematical transformations of the data and their comparison to database is all built into the system unit at the point of care. The data is then compiled and a total of 113 indexes (60 indexes @5/lead from 12 leads and 53 indexes from 2 leads) are compared against the same 27,000 empirical databases as used by the MCG system. This database consists of 27,000 people with CAD, whose CAD status and severity is included in the database and has been confirmed by coronary angiography. Importantly, database also contains MCG/CS-100 results from many patients who have one or more non-ischemic cardiac diseases. Therefore, the database is used to distinguish patterns in patients with cardiac ischemia and non-ischemic cardiac disease(s). Approximately 13,000 of the patients in the database have had normal coronary angiograms or have been determined to not have CAD after independent evaluations by two cardiologists. The database has been carefully accumulated over many years, and the patterns of each entrant have been validated and correlated with the presence (or absence) and severity of CAD. The database has been designed to be robust and to minimize bias by including, among other things, 49% of its data from women and an age range of 14-100 in the CAD and non-CAD groups, as well as people with many forms of heart disease (e.g. arrhythmias, hypertrophy, cardiomyopathy), in addition to CAD. The database also contains other clinical and diagnostic data from all 40,000+ patients, including information about other non-cardiac disease entities.

MCG data has been used to predict the findings of coronary angiography in several carefully designed and well-conducted prospective double-blind validation clinical trials in seven countries [28-32]. In these studies, MCG was performed on patients who were scheduled for elective coronary angiography based on clinical impression and standard non-invasive testing, with a belief that the patients had an intermediate to high risk of having relevant coronary artery stenosis (CAS) defined as 70% or greater in one or more epicardial coronary arteries or 50% stenosis of the Left Main artery. These studies have some bias in the sense that these were patients who were committed to angiography prior to MCG testing. In our early experience with MCG we did encounter some false positive tests particularly in women and diabetics both of who are vulnerable groups for silent untoward coronary events. MCG system also lacks specific coronary artery localization capability which can be a shortcoming in its application for known CAD patients for follow up monitoring and lesion severity assessment post angiography. CS100 system is a more elaborate and coronary artery specific analysis with the same underlying principles as MCG. CS100 system analyzes 12 leads and 2 lead electrical inputs and therefore has the capability to delineate specific coronary artery territory and can give lesion specific information in the assessment of known CAD patients. This capability of CS-100 allows for delineation of mild to moderate CAD from significant CAD and lesion severity post angiography to make a proper decision for percutaneous coronary angioplasty (PCI). Using time tested Framingham risk scoring model as the background we developed a modification scoring system (Table 1) to apply to raw MCG score and CS-100 analysis to improve the specificity and sensitivity and applied it prospectively in clinical evaluation of patients presenting in various stages of coronary ischemia.

1.       Ridker PM, Danielson E, Fonseca FAH, Genest J, Gotto AM, et al. (2008) Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. N Engl J Med 359: 2195-2207.

2.       Patel MR, Peterson ED, Dai D, Brennan JM, Redberg RF, et al. (2010) Low diagnostic yield of elective coronary angiography, N Eng J Med 362: 86-95.

3.       Chan PS, Patel MR, Klein LW, Krone RJ, Dehmer GJ, et al. (2011) Appropriateness of percutaneous coronary intervention. JAMA 306: 53-63.

4.       Arbab-Zadeh A, Miller JM, Rochitte CE, Dewey M, Niinuma H, et al. (2012) Diagnostic accuracy of computed tomography coronary angiography according to pre-test probability of coronary artery disease and severity of coronary arterial calcification: The CORE-64 (Coronary Artery Evaluation Using 64-ow Multidetector Computed Tomography Angiography) international multicenter study. J Am Coll Cardiol 59: 379-387.

5.       Patel MR, Dai D, Hernandez AF, Douglas PS, Messenger J, et al. (2014) Prevalence and predictors of non-obstructive coronary artery disease identified with coronary angiography in contemporary clinical practice. Am Heart J 167: 846-852-e2.

6.       Rizzello V, Poldermans D, Schinkel AFL, Biagini E, Boersma E, et al. (2006) Long-term prognostic value of myocardial viability and ischemia during dobutamine stress echocardiography in patients with ischemic cardiomyopathy undergoing coronary revascularization. Heart 92: 239-244.

7.       Velazquez EJ, Lee KL, Deja MA, Jain A, Sopko G, et al. (2011) Coronary artery bypass surgery in patients with left ventricular dysfunction. N Engl J Med 364: 1607-1616.

8.       Allman KC, Shaw LJ, Hachamovitch R, Udelson JE (2002) Myocardial viability testing and impact of revascularization on prognosis in patients with coronary artery disease and left ventricular dysfunction: A meta-analysis. J Am Coll Cardiol 391: 1151-1158.

9.       ACCF/SCAI/STS/AATS/AHA/ASNC (2009) Appropriateness criteria for coronary revascularization. J Am Coll Cardiol 53: 530-553.

10.    Mars’ SP, Teirstein PS, Kereiakes DJ, Moses J, Lasala J, et al. (2012) Percutaneous coronary intervention use in the United States: defining measures of appropriateness. JACC Cardiovasc Interv 5: 229-235.

11.    Shreibati JB, Baker LC, Hlatky MA (2011) Association of coronary CT angiography or stress testing with subsequent utilization and spending among Medicare beneficiaries. JAMA 306: 2128-2136.   

12.    Lima RS, Watson DD, Goode AR, Siadaty MS, Ragosta M, et al. (2003) Incremental value of combined perfusion and function over perfusion alone by gated SPECT myocardial perfusion imaging for detection of severe three-vessel coronary artery disease. J Am Coll Cardiol 42: 64-70. 

13.    Melikian N, De Bondt P, Tonino P, De Winter O, Wyffels E, et al. (2010)Fractional flow reserve and myocardial perfusion imaging in patients with angiographic multi-vessel coronary artery disease. JACC Cardiovasc Interv 3; 307-314. 

14.    Tonino PA, Fearon WF, De Bruyne B, Oldroyd KG, Leesar MA, et al. (2010) Angiographic versus functional severity of coronary artery stenosis in the FAME study fractional flow reserve versus angiography in multi-vessel evaluation. J Am Coll Cardiol 55: 2816-2821.

15.     Hachamovitch R, Hayes SW, Friedman JD, Cohen J, Berman DS (2003) Comparison of the short-term survival benefit associated with revascularization compared with medical therapy in patients with no prior coronary artery disease undergoing stress myocardial perfusion single photon emission computed tomography. Circulation 107: 2900-2907.

16.    Pijls NH, van Schaardenburgh P, Manoharan G, Boersoma E, Bech JW, et al. (2007) Percutaneous coronary intervention of functionally non-significant stenosis: 5 year follow-up of the DEFER study. J Am Coll Cardiol 49: 2106-2111.

17.    Pijls NH, Fearon WF, Tonono PA, Siebert U, Ikeno F, et al. (2010) Fractional flow reserve versus angiography for guiding percutaneous coronary intervention in patients with multi-vessel coronary artery disease 2 year follow-up of the FAME study. J Am Coll Cardiol 56: 177-184.

18.    Pijls NH, van Schaardenburgh P, Manoharan G, Boersma E, Bech JW, et al. (2007) Percutaneous coronary intervention of functionally non-significant stenosis: 5 year follow-up of the DEFER Study. J Am Coll Cardiol 49: 2106-2111.

19.    Tonino PA, De Bruyne B, Pijls NH, Siebert U, Ikeno F, et al. (2009) Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med 360: 213-224.

20.    Camici PG, Prasad SK, Rimoldi OE (2008) Stunning, hibernation and assessment of myocardial viability. Circulation 117: 103-114.

21.    Rizzello V, Poldermans D, Biagini E, Schinkel AF, Boersma E, et al. (2009) Prognosis of patients with ischemic cardiomyopathy after coronary revascularization: relation to viability and improvement in left ventricular ejection fraction. Heart 95: 1273-1277.

22.    Multicenter Post-infarction Research Group (1983) Risk stratification and survival after myocardial infarction. N Engl J Med 309: 331-336.

23.    Bax JJ, Van dour Wall EE, Harbinson M (2004) Radionuclide techniques for the assessment of myocardial viability and hibernation. Heart 90: v26-33.

24.    Shaw IJ, Berman DS, Maron DJ, Mancini GB, Hayes SW, et al. (2008) Optimal medical therapy with or without percutaneous coronary intervention to reduce ischemic burden: Results from the Clinical Outcomes Utilization Revascularization and Aggressive Drug Evaluation (COURAGE) trial nuclear sub study. Circulation 117: 1283-1291.

25.    Grube E, Bootsveld A, Yuecel S, Shen JT, Imhoff M. (2007) Computerized two-lead resting ECG analysis for the detection of coronary artery stenosis. Int J Med Sci 4: 249-263.

26.    Grube E, Bootsveld A, Buellesfeld L, Yuecel S, Shen JT, et al. (2008)Computerized two-lead resting ECG analysis for the detection of coronary artery stenosis after coronary revascularization, Int J Med Sci 5: 50-61.

27.    Weiss MB, Narasimhadevara SM, Feng GQ, Shen JT (2002) Computer-enhanced frequency domain and 12-lead electrocardiography accurately detect abnormalities consistent with obstructive and non-obstructive coronary artery disease. Heart Dis 4: 2-12.

28.    Hosokawa J, Shen JT, Imhoff M (2008) Computerized 2-lead resting ECG analysis for the detection of relevant coronary artery stenosis in comparison with angiographic findings. Congest Heart Fail 14: 251-260.

29.    Strobeck JE, Shen JT, Singh B, Obunai K, Miceli C, et al. (2009)Comparison of a two-lead, computerized, resting ECG signal analysis device, the multifunction cardiogram or MCG (a.k.a. 3DMP), to quantitative coronary angiography for the detection of relevant coronary artery stenosis (<70%) - Meta-analysis of all published trials performed and analyzed in the US. Int J Med Sci 6: 143-155.

30.    Adiraju RK (2017) Autonomic dysfunction and hypertension. Handbook of Interventions for Structural Heart and Peripheral Vascular Disease. Available at: http://www.jaypeebrothers.com

31.    Adiraju RK (2016) Dysautonomia type 2 diabetes and vasculitis. J Indian Coll Cardiol.

32.    Adiraju RK (2017) Dysautonomia: A novel approach to understanding of vasculitis and type Ii Diabetes. J Rheumatol Arthritic Dis 2: 1-12.

33.    Adiraju RK (2001) ANS principal applications - ANS preliminary clinical application of the ANS/RJ1000- Mediterranean Journal of Pacing and Electrophysiology 3: 33-34.

34.    Min JK, Shaw LJ, Devereux RB, Okin PM, Weinsaft JW, et al. (2007) Prognostic value of multidetector coronary computed tomographic angiography for prediction of all-cause mortality. J Am Coll Cardiol 50: 1161-1170.

35.    Min JK, Dunning A, Lin FY, Achenbach S, Al-Mallah M, et al. (2011) Age- and sex-related differences in all-cause mortality risk based on coronary computed tomography angiography findings results from the international multicenter confirm (coronary CT angiography evaluation for clinical outcomes: an international multicenter registry) of 23,854 patients without known coronary artery disease. J Am Coll Cardiol 58: 849-860.

36.    Sarno G, Decraemer I, Vanhoenacker PK, De Bruyne B, Hamilos M, et al. (2009) On the inappropriateness of noninvasive multidetector computed tomography coronary angiography to trigger coronary revascularization: A comparison with invasive angiography. JACC Cardiovasc Interv 2: 550-557.

37.    Douglas PS, De Bruyne B, Pontone G, Patel MR, Norgaard BL, et al. (2016) 1 year outcomes of FFRCT-guided care in patients with suspected coronary disease: The PLATFORM study. J Am Coll Cardio 68: 435-445.

38.    Hlatky MA, De Bruyne B, Pontone G, Patel MR, Norgaard BL, et al. (2015) Quality-of-life and economic outcomes of assessing fractional flow reserve with computed tomography angiography: PLATFORM. J Am Coll Cardiol 66: 2315-2323.

39.    Douglas PS, Pontone G, Hlatky MA, Patel MR, Norgaard BL, et al. (2015) Clinical outcomes of fractional flow reserve by computed tomographic angiography-guided diagnostic strategies vs. usual care in patients with suspected coronary artery disease: The prospective longitudinal trial of FFR(CT): Outcome and resource impacts study. Eur Heart J 36: 3359-3367.

40.    Pontone G, Patel MR, Hlatky MA, Chiswell K, Andreini D, et al. (2015) Rationale and design of the prospective LongitudinAl trial of FFRCT: Outcome and resource IMpacts study. Am Heart J 170: 438-446.

41.    Danad I, Raijmakers PG, Driessen RS, Leipsic J, Raju R, et al. (2017) Comparison of coronary CT angiography, SPECT, PET and hybrid imaging for diagnosis of ischemic heart disease determined by fractional flow reserve. JAMA Cardiol 2: 1100-1107.