Preclinical Research

For a better understanding of cardiovascular diseases

By imaging animal models of cardiovascular diseases with Magnetic Resonance Imaging, researchers gain a better understanding of disease pathophysiology and progression, ultimately aiding the discovery of novel therapeutic targets.

The leading cause of death worldwide

Cardiovascular diseases caused more than 19 million deaths globally in 2020¹

Accelerating factors

Unhealthy diet, physical inactivity, tobacco use and harmful use of alcohol

Influencing risks

Poverty, stress, environmental pollutants.

Multifaceted causes

Age, Coronary heart disease, Cerebrovascular disease

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Preclinical Research

Preclinical cardiovascular research

Cardiovascular diseases (CVDs) caused approximately 19.1 million deaths globally in 2020¹ and, according to the World Health Organization (WHO), are the leading cause of death worldwide.² This trend of high incidence and mortality is on the rise in low- to middle-income countries whose populations are living considerably longer than before and are therefore at higher risk of developing CVD.

Age is not the only risk factor, however. The underlying causes of different types of CVD, such as coronary heart disease and cerebrovascular disease, can be complicated and are not limited to diet and smoking. Poverty, stress, and environmental pollutants have been shown to influence risk of CVD.

Magnetic resonance imaging (MRI) is a widely used diagnostic method for CVD, and is also an important tool in preclinical research. By investigating animal models of CVD with magnetic resonance imaging techniques, such as magnetic resonance angiography, magnetic resonance spectroscopy (MRS), and magnetic resonance angiography (MRA), researchers gain a better understanding of disease pathophysiology and progression.

This non-invasive method allows longitudinal measurements over extended periods of time and provides a multitude of quantifiable parameters, such as ventricle volume or strain.

A new generation of MR technology

Preclinical MR is a well-established imaging technique to investigate a multitude of small animal cardiac disease models. While CT contrast agents (e.g. iodinated agents) typically used in clinical CT cardiograph protocols clear too quickly for use in small animal models, preclinical MR provides strong cardiac contrast for both enhanced and non-enhanced contrast imaging.

As mice and rats have heart rates up to 5x faster than humans, high-contrast CINE imaging with good slice and/or frame coverage is often required to resolve exquisitely small features of rodent cardiac tissue, and to obtain functional measurements such as ejection fraction.

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Accelerated SMS (Red) CINE imaging provides more slice coverage compared conventional (Yellow) CINE imaging without increasing scan time. Scans were acquired on a BioSpec 70/30 with a mouse cardiac array, and only varying SMS Factor (None or SMS2) and Slice Number (2 or 4). All other parameters were constant TE/TR: 1.6/10 ms, Res.: (130 x 130) μm², Slice Thick.: 800 μm Movie Frames: 12, Acquisition Time (triggered): ~8 m 30 s.

Preclinical Research

Speeding up MR workflows

Streamlined cardiac function analysis leveraging AI-based segmentation in PMOD PCARDM. Epi- and endocardial contours are displayed and can be easily adjusted if necessary. The volume-cardiac-cycle curve is produced, and functional parameters tabulated.

Preclinical MR hardware and software methods that allow for high signal-to-noise ratios (SNR) while minimizing total scan time can be highly beneficial in small animal cardiology. Bruker MR instrument hardware and methods, including ergonomically designed cardiac array coils, fast gradients and amplifiers, self-gated methods (i.e. IntraGate), and artificial intelligence (AI)-based segmentation, can reduce overall measurement times considerably, to increase cardiac imaging performance.

Beyond improvements of the preclinical cardiac measurement method itself, a streamlined and robust workflow from setup to evaluation of cardiac parameters makes cardiac investigations and analysis a straightforward process, supporting preclinical researchers.

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