Archive for the ‘Noninvasive Diagnostic Fractional Flow Reserve (FFR) CT’ Category

Expanding 3D Printing in Cardiology

Reporter: Irina Robu, PhD

3D printing is a fabrication technique used to transform digital objects into physical models, which builds structures of arbitrary geometry by depositing material in successive layers on the basis of specific digital design. Even though, the use of 3D bioprinting in cardiovascular medicine is relatively new development, advancement within this discipline is occurring at such a rapid rate. Most cardiologists believed the costs would be too high for routine use such that the price tag was better for academic applications.

Now as the prices are starting to lower, the idea of using 3D printed models of organs vessels and tissue manufactured based on CT, MRI and echocardiography might be beneficial according to Dr. Fadi Matar, professor at University of South Florida. He and his cardiology colleagues use 3D printed models to allow them to view patient’s complex anatomies before deciding what treatments to pursue. The models allow them to calculate the size and exact placement of devices which has led to shorter procedure time and better outcome.

In a study published in Academic Radiology, David Ballard, professor at University School of Medicine appraised the costs of setting up a 3D printing lab including the commercial printer plus software, lab space, materials and staffing. According to Ballard’s team, the commercial printers start at $12,000 but can be as high as high as $500,000.

According to American Medical Association-approved Category III Current Procedural Terminology (CPT) codes allows cardiology relief from setting up a new 3D printing lab such as Codes 0559T and 0560T, for individually prepared 3D-printed anatomical models with one or more components (including arteries and veins) and Codes 0561T and 0562T, which are for the production of personalized 3D-printed cutting or drilling tools that use patient imaging data and often are used to guide or facilitate surgery.

These codes have been met with enthusiasm by teams eyeing 3D printing, but there are noteworthy limitations to Category III codes—which are temporary codes describing emerging technologies, services and procedures that are used for tracking effectiveness data. It is important to note that Category III codes are not reimbursed but often are a step toward reimbursement.

New and improved materials also might lead to a sharper focus on 3D printing in cardiology. Dr. Fadi Matar says companies are working on materials that better mimic elements of the heart. Such “mimicry” ought to enhance the value of 3D-printed models since they will give cardiologists more realistic insights into how specific devices will interact with an individual patient’s heart. Even with the complex modalities of using 3D bioprinting, in time there would be less obstacles to being able to set up a 3D bioprinter lab.



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Artificial Intelligence Innovations in Cardiac Imaging

Reporter: Aviva Lev-Ari, PhD, RN


3.3.23   Artificial Intelligence Innovations in Cardiac Imaging, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

‘CTA-for-All’ fast-tracks intervention, improves LVO detection in stroke patients

A “CTA-for-All” stroke imaging policy improved large vessel occlusion (LVO) detection, fast-tracked intervention and improved outcomes in a recent study of patients with acute ischemic stroke (AIS), researchers reported in Stroke.

“Combined noncontrast computed tomography (NCCT) and CT angiography (CTA) have been championed as the new minimum standard for initial imaging of disabling stroke,” Mayer, a neurologist at Henry Ford Hospital in Detroit, and co-authors wrote in their paper. “Patient selection criteria that impose arbitrary limits on time from last known well (LKW) or baseline National Institutes of Health Stroke Scale (NIHSS) score may delay CTA and the diagnosis of LVO.”

“These findings suggest that a uniform CTA-for-All imaging policy for stroke patients presenting within 24 hours is feasible and safe, improves LVO detection, speeds intervention and can improve outcomes,” the authors wrote. “The benefit appears to primarily affect patients presenting within six hours of symptom onset.”



How to integrate AI into the cardiac imaging pipeline

Hsiao said physicians can expect “a little bit of generalization” from neural networks, meaning they’ll work okay on data that they’ve never seen, but they’re not going to produce perfect results the first time around. If a model was trained on 3T MRI data, for example, and someone inputs 1.5T MRI data, it might not be able to analyze that information comprehensively. If some 1.5T data were fed into the model’s training algorithm, though, that could change.

According to Hsiao, all of this knowledge means little without clinical validation. He said he and his colleagues are working to integrate algorithms into the clinical environment such that a radiologist could hit a button and AI could auto-prescribe a set of images. Even better, he said, would be the ability to open up a series and have it auto-prescribe itself.

“That’s where we’re moving next, so you don’t have to hit any buttons at all,” he said.



DiA Imaging, IBM pair to take the subjectivity out of cardiac image analysis



FDA clears Ultromics’ AI-based CV image analysis system

Smartphone app accurately finds, identifies CV implants—and fast

According to the study, the finalized model achieved 95% sensitivity and 98% specificity.

Ferrick et al. said that since their training sample size was somewhat small and limited to a single institution, it would be valuable to validate the model externally. Still, their neural network was able to accurately identify CIEDs on chest radiographs and translate that ability into a phone app.

“Rather than the conventional ‘bench-to-bedside’ approach of translational research, we demonstrated the feasibility of ‘big data-to-bedside’ endeavors,” the team said. “This research has the potential to facilitate device identification in urgent scenarios in medical settings with limited resources.”



Machine learning cuts cardiac MRI analysis from minutes to seconds

“Cardiovascular MRI offers unparalleled image quality for assessing heart structure and function; however, current manual analysis remains basic and outdated,” Manisty said in a statement. “Automated machine learning techniques offer the potential to change this and radically improve efficiency, and we look forward to further research that could validate its superiority to human analysis.”

It’s estimated that around 150,000 cardiac MRIs are performed in the U.K. each year, she said, and based on that number, her team thinks using AI to read scans could mean saving 54 clinician-days per year at every health center in the country.

“Our dataset of patients with a range of heart diseases who received scans enabled us to demonstrate that the greatest sources of measurement error arise from human factors,” Manisty said. “This indicates that automated techniques are at least as good as humans, with the potential soon to be ‘superhuman’—transforming clinical and research measurement precision.



General SOURCE

From: Cardiovascular Business <news@mail.cardiovascularbusiness.com>

Reply-To: Cardiovascular Business <news@mail.cardiovascularbusiness.com>

Date: Tuesday, December 17, 2019 at 9:31 AM

To: Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu>

Subject: Cardiovascular Imaging | December 2019

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2019 Trends in Cardiology

Reporter: Aviva Lev-Ari, PhD, RN



A 40,000 Foot View of Trends in Cardiology

A 40,000 Foot View of Trends in Cardiology


I was recently asked about my thoughts on the big picture, over arching trends effecting cardiology. Here is the outline I gave them.


Cardiology Cost Drivers

Reimbursements from Centers for Medicare and Medicaid Services (CMS) and insurance providers drive trends for the adoption of new technologies. However, new technologies that can show empirical evidence for being able to improve outcomes at lower costs are being moved up for better payments. CMS and other insurers are also using a carrot and stick approach with increased use of CMS bundled payments. These give a flat fee for diagnosing and treating a heart attack or heart failure, rather than hospitals being paid for all the tests and procedures they did. This approach makes the hospitals want to find new ways to be more cost effective to increase their bottom lines to capture more of the bundled payment as revenue.


Heart failure makes up about a third or more of the costs to Medicare. This has caused CMS to look closely at what is driving costs, and really high readmission rates are mainly to blame. There are penalties or no reimbursements for patients who come back for repeat treatments because they were not managed properly the first time. New technologies to address heart failure and other chronic diseases are of major interest to DAIC readers. Many of these include information technology (IT) solutions, rather than treatment device technologies.


Other conditions like atrial fibrillation (AF) also drive up costs, so vendors are attempting to find better ways to diagnose and treat this condition. Current treatments are only effective in the first attempt in about 60 percent of patients.


Consolidation of Hospitals and Outside Physicians

This is a continuing trend where single hospitals or smaller hospital systems are being bought up by bigger fish to create economy of scale with larger healthcare systems. These often cover specific geographic areas and often cast a wide net to include some luminary hospitals, smaller community hospitals, immediate care centers and minute clinics inside drug partner pharmacies. Duplicate staff and services are sometimes eliminated after mergers and consolidation. Outside physicians, including cardiologists and radiologists, are also being brought into the fold as employees of the health systems, rather than the old model as outside contractors who have access to the hospital’s amenities.


While there is fear about consolidation, it can also offer advantages in many cases. This includes faster access to the newest technologies and devices through the system’s luminary hospitals, which can train staff at other hospitals, and more complex cases can be referred to the larger hospital. Read about this in more detail in the article “Hospital Consolidation May Increase Access to TAVR, New Cardiac Technologies.”
Trends in Cardiovascular Technologies

Any techniques and technologies that can improve outcomes, cut costs, reduce hospital length of stay or prevent readmissions can capture hospital and cardiologist attention in today’s healthcare environment. There has been a massive movement over the past two decades away from traditional open heart or vascular surgical procedures to catheter-based interventional procedures. This includes improvements in the durability and complexity of percutaneous coronary intervention (PCI), reopening chronic total occlusions (CTOs)endovascular aortic repair (EVAR), expanded interest in treating peripheral artery disease (PAD), and structural heart cases that used to be the realm of the cardiac surgeon.


There is a major revolution and rapid uptake in transcatheter valve technologies to replace open heart surgery. Structural heart procedures to repair or replace failing heart valves have had positive clinical trial after positive trial over the last several years. Several key cardiac surgeons in the field say catheter based interventions will likely be the way of the future and surgical case volumes will see stead declines over the next decade.


The Role of Information Technology and AI in Cardiology

IT solutions are now increasingly being leveraged in more sophisticated ways since most hospitals have converted to integrated electronic medical records (EMRs) over the past decade. These allow all patient and departmental data to be accessible in one location. Analytics software is now being used to mine this data to identify workflow inefficiencies and areas to cut costs or improve charge capture. Clinical decision support (CDS) software to help hospitals and doctors better meet guideline-based care in all specialties is being introduced to help clinicians make better care decisions. This includes choosing appropriate tests and procedures in an effort to reduce costs or avoid tests that will not be reimbursed.


Artificial intelligence (AI) will be taking over many of the manual tasks for monitoring data and to answer questions more quickly. AI will also be used to alert administrators or doctors when it autonomously identifies a problem. Applications to watch also include AI to monitor population health in the background. This can identify patients at risk for various cardiovascular diseases before they present with any symptoms. The software also can identify patients who need extra care and counseling because of the high likelihood they will not be compliant with discharge orders and be readmitted. AI also will offer a second set of eyes on cardiac imaging to help identify anomalies or greatly reduce time by performing all the measurements automatically without human intervention.


This use of IT also includes patient portals to engage with patients and allow better access to their records and care. This is already starting to filter down to apps on smart phones to improve care, compliance with doctor’s orders and to aid diagnosis of conditions before they become problematic, such as heart failure and AF.


Cardiac Imaging Trends

Cardiac ultrasound (echo) remains the No.1 imaging modality in cardiology because of its broad availability, low cost and no radiation. However, computed tomography (CT) is poised to become the front-line imaging test for acute chest pain patients in the emergency department. It is also the gold standard for structural heart procedure planning, and the number of these cases is rapidly rising. CT fractional flow reserve (CT-FFR) technology is widely expected to become the main test for chest pain in the next decade, since it has the potential to save both time and money. CT-FFR also will become the primary gate-keeper to the cath lab to significantly lower, or possibly eliminate, the need for diagnostic catheter angiograms.


Cardiac MRI has seen numerous advances in recent years that cut imaging times by 50 percent and automate quantification, cutting the time to read and process these exams. MRI is expected to see and increase for cardiac exams in the coming years. MRI and CT-FFR may greatly reduce the number of nuclear exams, which are currently the gold standard for cardiac perfusion imaging.

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What is the Role of Noninvasive Diagnostic Fractional Flow Reserve (FFR) CT vs Invasive FFR for PCI?

Reporter: Aviva Lev-Ari, PhD, RN


UPDATED on 7/31/2019

During the AHRA presentation, Ali Westervelt cited a study published in the Journal of the American College of Cardiology indicating that questions about obstructive coronary artery disease (CAD) in six of 10 patients who might otherwise be sent for cardiac catheterization could be answered with FFRct.  During the presentation, Westervelt described a slide indicating that FFR-CT can dramatically reduce the need for cardiac catheterization.  Its use, she said, focuses  attention on patients most likely to test positively for CAD, as three of four patients sent to cardiac cath are found to have coronary artery disease.
The slide was based on research presented in the paper “1-Year Outcomes of FFRCT-Guided Care in Patients With Suspected Coronary Disease.” Westervelt and her colleague in the presentation, Curt Bush, noted that at one-year follow-up, no cardiac events were seen in 117 patients who had cardiac cath cancelled based on FFR-CT results.  Additionally, mean costs were 33 percent lower with FFRct versus  the usual care strategy — $8,127 compared with $12,145, respectively. The authors of the paper concluded that “selective FFR-CT was associated with equivalent clinical outcomes, quality of life, and lower costs, compared with usual care over one-year follow-up.”
FFR-CT has been proven to reduce unnecessary hospital admissions, according to Bush and Westervelt.  In their presentation, they cited research showing that FFRct provides the information that cardiologists need without the expense, time or patient inconvenience of tests done in the nuclear medicine or cardiac catheterization labs.
Despite the advantages of FFR-CT, however, only about 200 facilities in the United States perform this procedure, according to Westervelt, who speculated that the young age of the procedure and its reimbursement status may have been barriers to wider adoption. “It is only about a three-year-old technology and until recently was not reimbursable,” she said.
The Centers for Medicare and Medicaid Services (CMS) began paying for FFR-CT January 2018.  “I think there was just not a lot of interest because everybody is looking at their business plan,” said Westervelt, who is transitioning to a new job in which she expects to perform FFR-CT.

UPDATED on 7/17/2018

WATCH VIDEO – Interview with Patrick Serruys, MD, PhD, Prof. of Interventional Cardiology, Imperial College, London

VIDEO: Will CT-FFR Replace Diagnostic Angiograms?


An interview with Patrick Serruys, M.D., Ph.D., Imperial College London, principal investigator of the SYNTAX III Trial presented earlier this year as a late-breaker at EuroPCR. He presented the trial again at the Society of Cardiovascular Computed Tomography (SCCT) 2018 meeting.

Read the article “SYNTAX III Revolution Trial Shows CT-FFR Could Replace Cine-angiography in Coming Years.”



What is the Role of Noninvasive Diagnostic Fractional Flow Reserve (FFR) CT vs Invasive FFR for PCI?


We know that FFRCT, the method of obtaining FFR from computed tomography angiographic (CTA) images, has been approved by Medicare and other third-party payers. It is used before patients come to the cath lab. The use of FFRCT in the PLATFORM study1reduced the number of unnecessary cardiac caths that had normal coronary angiography, while maintaining the same number of patients needing PCI.  Before discussing the role of angio-derived FFR, let’s review how FFRCT is obtained (Figure 1). Starting with any good quality CTA, the images are sent, offline, to HeartFlow Inc.2 To derive the FFR, the CTA images are reconstructed into a 3-dimensional coronary tree, segmenting it into individual points with each point undergoing processing by specialized equations (i.e., Navier-Stokes equations) to compute pressure loss along the course of the artery at rest and again during an assumed hyperemic state. These computational fluid dynamic equations require several assumptions from a population model regarding the myocardial blood flow rates as a function of the myocardial arterial branches and the resistance of the myocardium. These values are put into the computational flow dynamics (CFD) model, and using high-power computers, the FFR is generated along the entire course of each vessel. FFRCT has been validated against invasive FFR and found to be about 80% correlative in several studies.3,4 FFRCT has better correlation with FFR than most stress tests, and based on clinical outcome data, will likely replace traditional stress testing, with a reduction in procedures in patients without significant coronary disease. However, there are some operators who may be confused, thinking that FFRCT will replace invasive FFR. FFRCT screens for important coronary artery disease (CAD) before the patient comes to the cath lab, and then once in the lab, the operators can confirm lesion significance with FFR.

Noninvasive FFR Derived From Angiography: Wireless FFR in the Lab?

Wouldn’t it be great to get the FFR from the angiogram without having to put in a guidewire? This is in our near future. The generation of a “virtual” FFR derived from angiography or other modalities (Table 1A-B, Figures 2-4) has been proposed using computational flow dynamics (CFD) or rapid flow analysis to obtain wireless image-based FFR, incorporated into the diagnostic angiography workflow. As one might expect, online implementation of angio-derived FFR requires novel concepts and systems to reduce computation time and make the analysis process acceptable to in-lab functions. Early data shows that angio-derived FFR can be obtained within several minutes during a regular coronary angiogram.5

Angio-FFR Validation StudiesTwo contenders for introduction to the cath labs in the near future are QFR and FFRangio. QFR (Quantitative Flow Ratio, Medis Medical Imaging Systems) validation was reported in the FAVOR II China study, which reported the vessel-level diagnostic accuracy of QFR in identifying hemodynamically-significant coronary stenosis was 97.7% and patient-level diagnostic accuracy was 92.4% (P<0.001 for both).6 In addition, the FAVOR II Europe-Japan trial demonstrated that QFR had superior sensitivity and specificity in comparison to 2-D QCA with FFR as the gold standard: 88% vs 46% and 88% vs 77% (P<0.001 for both). The overall diagnostic accuracy of QFR was 88%.7 For FFRangio (CathWorks), the sensitivity, specificity, and diagnostic accuracy of FFRangio were 88%, 95%, and 93%, respectively.5 The strong concordance with invasive, wire-based FFR will likely make these methods widely available, but of course, early favorable results require confirmation. Once confirmed in larger studies and for a wider spectrum of coronary lesions, angio-derived FFR should become a routine part of diagnostic angiography.

Accuracy in computing noninvasive FFR is based on the implementation of complex computational methods that can differ among the various competing methods. In contrast to FFRCT, which creates a complete and detailed 3D model of the coronary tree from CTA scans, Tu et al8 constructed vessel geometry from routine angiography, applying a simpler model for flow, derived from the division of coronary branches (as opposed to using an estimate of flow from myocardial mass)2, and an approximate algebraic computational method from experimental studies of flow through single arterial stenosis models8 (as opposed to CFD equations) to solve for pressure drop and FFR (Figure 5). Because Tu et al8 do not employ the complicated Navier-Stokes equations, the computational time is almost instantaneous once the geometry is segmented into “sub segments” from the 3D rendering. Pellicano et al5 constructed 3D artery geometry from routing angiography alone, applying rapid flow analysis where all stenoses are converted into resistances in a lumped model, while scaling laws (of branches) are used to estimate the microcirculatory bed resistance.

Competition for a winning method of angiographically-derived FFR is underway, with different companies using different models and different assumptions regarding flow and resistance inputs (Table 1A-B). An example is QFR that uses several assumptions related to flow variables. fQFR is specified hyperemic inflow, assuming a fixed inflow velocity of 0.35 m/s. cQFR is “virtual” hyperemic flow, determined from a model based on TIMI [Thrombolysis In Myocardial Infarction] frame count, relating measured flow under baseline conditions to hyperemic flow. Lastly, aQFR is the variable of directly measured hyperemic flow. From these assumptions, QFR gives highly comparable results to invasive FFR.

Advantages of Angio-Derived FFR

The in-lab computations of angio-derived FFR are fast and have the potential to provide wireless FFR lesion assessment to every angiographic procedure. Other advantages of angio-derived FFR are obvious. There is no need to insert a pressure guidewire. Pharmacologic hyperemia is not necessary. It is nearly operator independent. The angio-derived FFR is also co-registered on the angiogram with accurate and reproducible results. In addition, 3D reconstruction of the coronary tree can enhance the identification of reference vessel diameters for selection of stent sizing, and ultimately predict anatomic and physiological outcomes.5

Limitations of Angio-Derived FFR 

The image acquisition requirements and the user interface of an image-based FFR system should be seamlessly incorporated into the standard work of the catheterization laboratory. Data acquisition should minimally disrupt routine angiography. Angio-derived FFR should only require the acquisition of 2 to 3 conventional radiographic projections in which the lesions can be clearly seen. It is important to visualize the entire coronary tree on the screen and to optimize vessel opacification. Poor images or overlapped segments will limit the accuracy of angio-derived FFR. The image acquisition angles needed for angio-derived FFR are the same as those used for routine procedures. High resolution imaging at >10 frames/sec are needed.5

On the technical side, coronary microvascular resistance (CMV) is a fundamental assumption to compute pressure from flow. CMV in one study was derived from invasive measurements, something which will limit future acceptance.9 As the data sets are accumulated, it is hoped that invasive CMV will not be needed. One angio-derived FFR method, vFFR9,10, requires rotational angiography, which is not yet widely available, and may produce asymmetric coronary segmentations — a concern for accurate analysis.

Finally, the amount of time required to acquire and process the data to produce angio-derived FFR is likely to be longer than the 3-minute computation time. Acquisition time should realistically include the time to overcome the difficulties of imaging complex anatomy, eliminate artifacts, upload the study for CFD analysis, and create the volumetric mesh. Furthermore, there will probably be patient-specific errors related to abnormal coronary physiology which may account for outliers in the correlations between angiography-derived and invasive FFR measurements.11

Angio-derived FFR is currently reported for off-line results, but, recently, online applications have also been presented. Minimal operator interaction is necessary in the flow calculation process, which results in low inter-operator variability.

The Bottom Line

When FFRCT and angio-derived FFR technology ultimately become more widely available, they will radically change the way diagnostic angiography is performed in the same way that invasive FFR changed the way we approach patients needing PCI


  1. Douglas PS, De Bruyne B, Pontone G, et al. 1-Year Outcomes of FFRCT-Guided Care in Patients With Suspected Coronary Disease: The PLATFORM Study.  J Am Coll Cardiol. 2016 Aug 2; 68(5): 435-445. doi: 10.1016/j.jacc.2016.05.057.
  2. Taylor CA, Fonte TA, Min JK. Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis. J Am Coll Cardiol. 2013; 61(22): 2233-2241.
  3. Norgaard BL, Leipsic J, Gaur S, et al. Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease. J Am Coll Cardiol. 2014; 63: 1145-1155.
  4. Min JK, Leipsic J, Pencina MJ, et al. Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA. 2012; 308: 1237-1234.
  5. Pellicano M, Lavi I, Bruyne B, et al. Validation study of image-based fractional flow reserve during coronary angiography. Circ Cardiovasc Interv. 2017; 10: e005259. doi: 10.1161/CIRCINTERVENTIONS.116.005259.
  6. Xu B, Tu S, Qiao S, et al. Diagnostic accuracy of angiography-based quantitative flow ratio measurements for online assessment of coronary stenosis. J Am Coll Cardiol. 2017 Dec 26; 70(25): 3077-3087. doi: 10.1016/j.jacc.2017.10.035.
  7. Westra J. Late-Breaking Clinical Trials 2. Presented at: TCT Scientific Symposium; Oct. 29-Nov. 2, 2017; Denver, Colorado.
  8. Tu S, Westra J, Yang J, et al. Diagnostic accuracy of fast computational approaches to derive fractional flow reserve from diagnostic coronary angiography: the international multicenter FAVOR pilot study. J Am Coll Cardiol Intv. 2016; 9: 2024-2035.
  9. Morris PD, van de Vosse FN, Lawford PV, et al. “Virtual” (computed) fractional flow reserve: current challenges and limitations. JACC Cardiovasc Interv. 2015; 8: 1009-1017. doi: 10.1016/j.jcin.2015.04.006.
  10. Morris PD, Ryan D, Morton AC, et al. Virtual fractional flow reserve from coronary angiography: modeling the significance of coronary lesions: results from the VIRTU-1 (VIRTUal Fractional Flow Reserve From Coronary Angiography) study. JACC Cardiovasc Interv. 2013; 6: 149-157. doi: 10.1016/j.jcin.2012.08.024.
  11. Papafaklis MI, Muramatsu T, Ishibashi Y, et al. Fast virtual functional assessment of intermediate coronary lesions using routine angiographic data and blood flow simulation in humans: comparison with pressure wire – fractional flow reserve. EuroIntervention. 2014; 10: 574-583. doi: 10.4244/EIJY14M07_01
  12. Tu S, Barbato E, Köszegi Z, et al. Fractional flow reserve calculation from 3-dimensional quantitative coronary angiography and TIMI frame count: a fast computer model to quantify the functional significance of moderately obstructed coronary arteries. JACC Cardiovasc Interv. 2014 Jul; 7(7): 768-777. doi: 10.1016/j.jcin.2014.03.004.

Disclosure: Dr. Kern is a consultant for Abiomed, Merit Medical, Abbott Vascular, Philips Volcano, ACIST Medical, Opsens Inc., and Heartflow Inc. 



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Dynamic myocardial CT perfusion imaging for evaluation of myocardial ischemia as determined by MR imaging | DSCT.com – Your Dual-source CT experts

Reporter: Aviva Lev-Ari, PhD, RN




The aim of this study was to determine the feasibility of CT-based dynamic myocardial perfusion imaging for the assessment of myocardial ischemia and infarction compared with cardiac magnetic resonance (CMR).

Source: www.dsct.com

See on Scoop.itCardiovascular and vascular imaging

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