Av Malgorzata Isabela Magelssen, PhD Candidate at CIUS, NTNU

Cardiac diseases are a major health concern and many of the patients in a general practitioner’s (GPs) office have heart conditions. Hand-held ultrasound device (HUD) can improve the GP’s diagnostic possibilities. We want to evaluate if a training program with focus on practical ultrasound skills can help the GP’s to correctly diagnose certain heart conditions by using HUD. If successful, unnecessary referrals could be avoided and patients in need of specialist care would avoid delay in diagnosis and treatment.

Diagnostic ultrasound represents a potential tool to improve the accuracy of the diagnostics. Diagnosis in often inaccurate when based on medical history and clinical examination alone. Studies have shown that fellows in internal medicine and family practice have a poor identification rate for important and commonly encountered cardiac events. On the other hand, several clinical conditions are difficult to recognize with physical examination alone, but easy to recognize by ultrasound; examples are pericardial effusion, heart failure and even early LV dysfunction. Traditionally GPs refer patients to a specialist for cardiac ultrasound. Many of the referred patients are not in need of specialized care and could potentially be diagnosed and treated out of hospital. Due to long waiting lists, the time to diagnosis can be prolonged and further lead to delayed treatment. Quick and accurate diagnoses is essential in order to preserve the health and quality of life of the patients.

HUDs have in many hospitals become a routine part of the initial evaluation of patients with suspected heart disease. The low cost and easy accessibility have also made them available outside the more conventional settings. Previous studies have shown that when used by experts, residents or dedicated nurses, HUDs can improve the diagnostic accuracy. The accuracy is lower when used by non-experts, and thus, proper education and training is important.

Our research group at CIUS (Centre for Innovative Ultrasound Solutions), NTNU (Norwegian University of Science and Technology) is currently conducting a study where GPs utilize HUDs for evaluation of patients with suspected heart failure. The study is conducted in the outpatient clinic at Nord-Trøndelag Health Trust, Levanger Hospital. Before we started the inclusion of patients, 5 randomly selected GPs underwent both theoretical and practical training. One of our main question is what amount and which type of training is adequate for GPs to accurately evaluate patients with potential heart disease?

In our study, each GP was individually trained with focus on practical skills. First, they all received a theoretical review of the basics of cardiac ultrasound including the most common pitfalls. We focused at the most important projections in cardiac ultrasound; parasternal long-axis and apical 4-chamber. Automatic applications to measure cardiac function were demonstrated. Further, they all received 5-6 individual days of “hands-on” training at Levanger Hospital. They spent the days examining patients and there was always a “teacher” present to aid in the examinations. At the end of the day, we went through the images and discussed future improvements. We also encouraged det GPs to use the HUDs at their own clinical practice as part of the training.

After the training period, we started the inclusion of patients in the study (150 in total). The patients were examined by a GP, a dedicated nurse and a Cardiologist. The purpose of the study is to evaluate if GPs can accurately diagnose heart failure when HUD is added as a supplement to the clinical examination. A focused cardiac ultrasound with the support of telemedicine and automatic measurements of heart function will hopefully help the GPs in this evaluation. A cardiac ultrasound performed by a specialist in cardiology works as a reference.
We hope to show that our approach for training GPs improves the accuracy of their everyday diagnostics to the best for the patients, and we hypothesize that by the dedicated training and the use of supportive tools the goal is achievable!

Children with dysfunction of the right heart chamber (ventricle), which pumps blood to the lungs, have lower tolerance to exercise and are at risk of sudden cardiac death in more severe cases. This dysfunction usually sets in progressively and detection at earlier stages is crucial to guiding therapies and interventions that improve symptoms and survival. New ultrasound techniques, make it easier detect and quantify the problem.

Assessing the right ventricular function has always been challenging with conventional ultrasound techniques. However, using the new high frame-rate ultrasound imaging techniques combined with speckle tracking (both developed at NTNU), we are now able to measure the energy that is lost in the blood. This is a promising new way of detecting ventricular dysfunction.

In the case of high blood pressure in the lungs (pulmonary hypertension), an early diagnosis is crucial to direct therapies, which can lower the resistances in the lung vessels and facilitate the function of the right ventricle, and reduce the risk of heart failure and sudden cardiac death.  We have included 9 children, aged 5 months to 8 years of age, to study energetics and flow patterns within the right ventricle and pulmonary arteries, and compare these to controls.

Another particularly challenging group with regards to assessing cardiac function, is patients with single ventricle physiologies. This type of circulation refers to situations where one of the ventricles is inadequate to participate in pumping the blood to the body or to the lungs. The entire pumping function then falls on one ventricle instead if two.  This type of circulation depends heavily on good ventricular performance and a large number of these patients experience ventricular dysfunction during adulthood. This can even go as far as requiring heart transplant, although this has limited success. Recognising dysfunction before patients develop symptoms is very important as it can offer a window of opportunity to intervene, either with medication or surgery, to improve cardiac function.  Flow dynamics and energetics are particularly interesting to study in these patients as they may reflect dysfunction earlier than conventional echocardiographic parameters. We have included 21 patients, aged 4 to 9 years old, with this condition and will shortly start studying their intracardiac flow characteristics, including energy loss.

Studying these flow phenomena by imaging requires high frame rates because the blood moves much faster than the heart muscle (myocardium), with important phenomena occurring in short times intervals. Recent advances in imaging technologies have given us access to characterising the speed and volume of the blood flow (blood flow velocities) as never before. Blood speckle tracking, which is the technique our group is working with, combines ultra-high frame rate imaging (in the KHz range – see figure below), and tracking of speckles within the blood pool. From there, the velocities of these speckles can be measured without the use of contrast agents or the need for mathematical assumptions. These velocities measurements enable us to, amongst other things, to assess the energy loss.

Previously, we have studied cardiac flow dynamics in repaired tetralogy of Fallot, a condition where there is narrowing between the right ventricle and the lung artery requiring surgery. After the surgical repair, there is a necessary incompetence of the lung valve, which causes gradual dilatation and dysfunction of the right ventricle. A total of 57 children aged two weeks to 10 years were included. Of this group, 21 had repaired tetralogy of Fallot and 11 had an atrial septal defect (ASD) which is a hole between the upper chambers of the heart also causing right ventricular dilatation. In the latter 2 group, we found significantly higher diastolic energy loss compared to normal controls. Inefficiencies within the heart has long been suspected but to demonstrate these using non-invasive, ultrasound imaging is very promising in allowing early detection of flow inefficiencies at an earlier stage where interventions might be more beneficial.

Now that these techniques are available more widely, there are many challenges for our community to better understand, validate and compare flow parameters in normal and abnormal hearts. More technical improvements are needed with regard to developing 3D techniques, where NTNU is making great leaps.

How these new insights alter our management to improve our patients’ outcomes is to be seen as our community continues to explore these new imaging technologies.

Aortic valve stenosis is a narrowing of the valve that separates the left ventricle from the aorta. A reduced opening increases the effort required by the left ventricle to pump blood. Being a degenerative disease, patients with aortic stenosis must undergo a clinical follow-up, which is usually performed by ultrasound. At the Centre for Innovative Ultrasound Solutions (CIUS), we are developing a new method that exploits 3-D high frame-rate imaging to increase the degree of automation in aortic stenosis flow measurements. The goal is to speed up the workflow in the clinics and increase the accuracy of measurements.

Aortic valve stenosis is a narrowing of the aortic valve, which increases the force required to pump blood. This concept can be grasped by trying to exhale while keeping your lips almost closed. The green area highlights the available space for blood to pass through. IMAGES: By BruceBlaus [CC BY 3.0 (https://creativecommons.org/licenses/by/3.0)], from Wikimedia Commons and Pixabay.com, respectively.

Assessment of aortic stenosis severity by ultrasound

The effect of a narrowing on blood flow is straightforward. The smaller the opening, the faster the blood travels through it. In fact, an important marker used in aortic valve stenosis assessment is the maximum blood speed (velocity) through the aortic valve. Velocities > 4 m/s indicate a severe stenosis and that the patient may need a valve replacement soon. A severe aortic stenosis with symptoms or reduced cardiac function are the main indications for valve intervention (also see this previous blog about aortic valve stenosis – in Norwegian).

Ultrasound is used to estimate blood velocities in several clinical applications, including aortic stenosis assessment. Measurement are performed by exploiting the the Doppler Effect. We experience this phenomenon every time we perceive a shift in the siren’s pitch as an ambulance is driving towards or away from us.

Unfortunately, there is a major challenge that cardiologists must face when using Doppler Ultrasound: if the cardiologist fails to align the probe with the aortic flow, the maximum velocity is underestimated, potentially leading to a wrong diagnosis. For this reason clinical examinations often take several minutes and the quality of the diagnosis is highly dependent on the cardiologist’s skills.

When measuring aortic flow velocities it is of utmost importance that the probe is aligned with the blood flow direction. Failing to comply leads to an underestimation of blood velocities. The ultrasound probe is shown as a blue rectangle in the picture. The red arrow indicates the direction of blood flow. The narrowing is a schematic representation of a stenotic aortic valve. The ultrasound waves propagate along the gray dashed line.

Towards automatic aortic jet direction estimation

As explained by my colleague Morten Smedsrud Wigen in a previous post, new imaging techinques allow us to record the blood signal arising from a volume with really high frame rates, which can be combined with algorithms that trace the motion of blood. Our goal is to apply the same method to automatically estimate the direction of aortic jets, and use this information to compensate for the above-mentioned effects of misalignment when measuring blood velocities with Doppler ultrasound, reducing the risks of user mistakes and speeding up the examination process.

Results from simulations show that it is possible to estimate the aortic flow direction with good accuracy, provided that the signal is strong enough. However, the method eventually does not work  for high degrees of misalignment or low signal levels. A small pilot study on 12 patients showed that while misalignment is hardly an issue, low signal levels are a source of concern. An ongoing clinical feasibility study will provide valuable information to improve both the algorithm and the acquisition set-up.

3D visualization of the heart in a patient affected by aortic stenosis. The arrow shows the estimated direction of flow right after the aortic valve. This direction can be used to correct for the angle dependence in ultrasound Doppler-based method.

Despite constant improvements within the field of medical ultrasound, there are still a considerable number of difficult-to-image patient. Echocardiograms (heart images) taken from these patients do not have the quality that is needed for correct diagnosis. Therefore it is important to further improve the quality of echocardiograms.

Understanding the reasons behind low-quality images is essential to find methods to improve the quality. At the Centre for Innovative Ultrasound Solutions (CIUS), we have performed a systematic study to understand the mechanisms causing the problems in difficult-to-image patients.

In my previous blog post, we showed that the tip of a needle placed out of the imaging plane (the cross section of the object that is imaged), is seen in the ultrasound image if some part of the ultrasound signal hits the bones and gets deflected towards the needle. The question was then if there are some types of tissue in the body that can play the role of the needle and make noise by sending the deflected signal back to the ultrasound transducer.

We have now attempted to answer this question by performing different water tank experiments where we imaged an artificial heart chamber in the presence of two pieces of rib bones. In these experiments, we placed the bones at different angles relative to the ultrasound transducer and used different types of tissue such as skin, fat and lung to study the effect of these on the images.

Figure 1- Beamprofile measurement of an ultrasound transducer. a) without ribs, b) with ribs partly blocking the transducer, and c) with ribs at a different angle from b).

The results of these experiments show that depending on the angle between the ultrasound beam and the ribs, the ultrasound signal can be partly reflected either outside or inside the ribcage (see Figure 1). The measured energy from the transducer can be seen as a single beam in Figure 1a. In Figure 1b and 1c, the ultrasound signal is split in two parts after hitting the rib. Different angles between the transducer and the ribs in these two measurements results in reflection of signal outside the ribcage (above the bones) in 1b and inside the ribcage (below the bones) in 1c. Therefore, we can consider two cases:

Case 1: the reflection of signal is outside the patient’s chest.

Figure 2- Watertank experiment with rib bones and a layer of fat. State 1) large distance between the ribs, state 2) reduced distance between the ribs, and state 3) the fat layer is removed.

This reflected signal can then hit the subcutaneous fat and travel back to the transducer. The received echoes from subcutaneous fat are then shown as noise over the image of the heart. We experimentally demonstrated this case by the setup shown in Figure 2. In this experiment, the bones were placed in a way that the reflection of the signal was outside the ribcage (same as in Figure 1b). The upper row shows three instances of this experiment, while the lower row shows the corresponding ultrasound images taken by the transducer. A layer of fat was placed over the ribs to simulate the effect of the subcutaneous fat inside the body. A clear ultrasound image of the heart chamber can be seen in State 1 where there is a big enough distance between the bones and therefore no reflection of signal towards the fat layer. In State 2, however, where the distance between the bones is reduced, the ultrasound image of the heart chamber is covered with a haze-like noise. Finally, in State 3, the fat layer is removed while keeping the distance between the ribs as short as in State 2. The haze-like noise is mostly removed from the ultrasound image in this state.

Case 2: the reflection of signal is inside the patient’s chest.

Figure 3- Watertank experiment with rib bones and a piece of sponge. State 1) large distance between the ribs, state 2) reduced distance between the ribs, and state 3) the sponge is removed.

In this case, the lung tissue can send the signal back to the transducer and cause the degradation of the image quality. This case was experimentally demonstrated by the setup shown in Figure 3. In this experiment, the bones were placed at a slightly different angle from the first experiment so that the reflection of the signal was inside the ribcage (same as in Figure 1c). The same steps were followed as in the first experiment, but instead of the fat layer over the ribs a piece of sponge was placed under the ribs and close to the heart chamber. The sponge simulates the effect of the lungs in the body because of the air trapped inside it. Similar ultrasound images as in previous experiment can be seen here.

The results of these experiments confirm that the deflection of ultrasound signal by the ribs in unwanted directions followed by a second reflection from either fat layers or lung tissue can generate noise in echocardiograms. This knowledge can be applied to implement new techniques in order to improve the quality of echocardiograms in difficult-to-image patients.

A collaboration between several institutions, including the Norwegian University of Science and Technology (NTNU), the University of Michigan Medical School, Geisinger and Regeneron, and deCODE Genetics/Amgen in Iceland, has resulted in surprising results linking atrial fibrillation in adults to fetal heart development. 

The group studied an unprecedented sample size of over one million people, including over 60,000 individuals with atrial fibrillation, to discover over 140 genetic changes associated with this common, adult-onset cardiac arrhythmia. The results were surprising in that they identified a number of genes that control heart development in the fetus.

This could have important implications for future treatment and possibly prevention of atrial fibrillation.

Experiments in rabbits with induced heart failure showed that at least one of the fetal genes becomes active again in the damaged heart. Because the fetal genes have different rates of conduction of the cardiac electrical impulses relative to the adult form of the gene, atrial fibrillation is induced. This could have important implications for future treatment and possibly prevention of atrial fibrillation.

The group are hopeful that additional molecular biology experiments will determine how to create sustained regular heart rhythms by studying the genes they, and others, have identified.

Significance of the expression enrichment for the atrial fibrillation candidate genes.

They also found that for each individual, they could count the number of genetic changes that each person carries to predict which people are most at risk for developing atrial fibrillation in the future. This may have important implications for precision health and prevention of cardiovascular disease.

Another paper on atrial fibrillation was also published recently in Nature Genetics and we look forward to bringing these two collaborative groups together to generate an even larger study for the benefit of those afflicted by atrial fibrillation.

Read the full article in Nature Genetics. 

Many potential heart patients that are referred to specialists, turn out not to need specialist care. If general practitioners (GPs) could use handheld ultrasound devices with built-in diagnostic tools, could this improve patient outcome and reduce cost for the health services?

Heart failure is among the most common reasons for hospitalisation and constitutes a major public health concern. The number of patients with heart failure is expected to increase due to prolonged life expectancy and improved treatment of medical conditions.

Cardiac ultrasound (echocardiography) is one of the main tools for evaluating heart disease such as heart failure, valve disorders and fluid around the heart (pericardial effusion). An accurate diagnosis should be made as quickly as possible to preserve the health and quality of life for the patients, as well as to keep down costs and save time for the healthcare services.

Currently GPs upon suspicion of heart disease, refer patients to a cardiac specialist, and most often echocardiography is the next diagnostic step. However, for several cardiac conditions, the diagnostic accuracy is only modest when based on medical history and clinical examination alone. Therefor a significant proportion of the patients referred do not actually need follow-up from a specialist. This takes up valuable places from those patients who do need specialised care.

The Vscan handheld ultrasound device. (Image courtesy of GE Ultrasound.)

Smaller and cheaper ultrasound devices have been developed during the last decade. These handheld ultrasound devices can be brought to the patient, and allow for diagnostic imaging at the patient’s point of care. The small size, low cost and easy access of handheld ultrasound has enabled inexperienced users to perform ultrasound diagnostics outside the conventional laboratories.

Significant efforts are being made to improve the diagnostic accuracy of handheld ultrasound. This can enhance the art of clinical examination by revealing disease at an earlier stage, and help the GPs to better identify patients in need for specialised care.

Here at the Centre for Innovative Ultrasound Solutions (CIUS), we have evaluated the Vscan handheld ultrasound device from GE Ultrasound. Several studies have been conducted, most of them in collaboration with the Department of medicine, Levanger hospital. Studies show that the use of handheld ultrasound improves diagnostic accuracy by experts, residents, GPs, medical students and dedicated nurses. Compared to handheld ultrasound used by specialists, the diagnostic accuracy is somewhat lower when the users are inexperienced, but with education and training accuracy can be improved.

In one of our upcoming projects, we have trained five randomly selected GPs in the use of diagnostic cardiac ultrasound using a handheld device. Each of the physicians has received theoretical education and at least five days of practical training. Patients with signs and symptoms suggesting heart failure will be included in the study after giving their informed consent. In total, 150 patients will be included in the study. Firstly, the patients will be examined by a GP. The same physician will then perform a focused cardiac ultrasound using handheld ultrasound. The GP will interpret the images as well as transfer the recordings for expert interpretation using a new telemedicine solution. The function of the left ventricle (the main cardiac chamber) will also be analysed automatically by two new methods integrated in the handheld ultrasound (see animations below). The accuracy of the different diagnostic steps will be compared to a standard echocardiographic examination performed by experienced cardiologists.

Automatic tracking of the basal part of the left ventricle.

Automatic tracking of the left ventricle borders to estimate the ejection volumes of the heart.

We believe that the use of focused cardiac ultrasound by GPs using handheld ultrasound, supported by either automatic analysis or by experts per telemedicine, can improve diagnostics and allow for better treatment of patients. Furthermore, we aim to evaluate the cost-utility of the innovative diagnostic algorithm, which may better select patients in need for follow-up by specialised healthcare services.

Coronary heart disease is a condition where the heart muscle (myocardium) does not receive enough oxygen and nutrients due to obstruction of blood flow in the heart’s blood vessels, known as the coronary arteries. It is therefore important to investigate the blood flow in these vessels. However, it is challenging to obtain accurate measurements due to the combination of poor blood flow, the constant movement of the heart throughout the cardiac cycle, and surrounding tissue causing noise signals.

Here at the Centre for Innovative Ultrasound Solutions (CIUS), we work on filtering away the noise signal generated from the tissue, and to automate this filtering process.

In order to achieve this, we are using certain components of the ultrasound signals called eigenvectors, which have shown to be very promising for blood and clutter separation. From the theory, we know that the eigenvectors with highest power are those containing tissue signal, so we sort the eigenvectors by descending power and we remove the first set of eigenvectors.

Here the challenge begins: How do we select which eigenvectors to remove? One option is to do it manually, which means looking at the 3D coronary images when removing different numbers of eigenvectors and deciding which is best. It would be better, however, to automate the process of selecting the appropriate eigenvectors.

In Fig. 1 you can see 2D projections of 3D coronary images using a standard high cut-off filter. The coronary is displayed in middle diastole (relaxation) which is the part of the cardiac cycle where the coronary vessel is most visible. During systole (contraction) there is almost no flow in the coronary arteries. Our goal is to remove flashing artifacts in early and late diastole in order to be able to detect blood flow. At these time points, tissue signal might be highly accelerated, which makes clutter suppression challenging.

Fig. 2 shows 3D coronary images at different time points of the cardiac cycle using a manual filter based on eigenvectors. In panels b) and d) there is still some tissue signal left but in a) and c) the coronary (blue circle) can be more easily identified.

In the future, we will investigate whether varying parameters such as increasing the frame rate could help to improve clutter filtering. It might also be interesting to examine coronary arteries situated in different locations. In general, we think that we are on the right way and eigenvectors represent the key to solve the clutter filtering challenge! Eigen-based filters are indeed able to adapt to the different phases of the cardiac cycle, while the conventional filters do not vary over time.

Artificial intelligence can now help clinicians by automatically measuring the heart in ultrasound images. This can save time and may in the future enable inexperienced users to perform accurate measurements of the heart.

When performing ultrasound examinations of the heart, several measurements are done in order to determine how healthy the heart is. One of these measurements is left ventricular ejection fraction, which measures the pumping efficiency of the heart.

In order to calculate the ejection fraction, we need to calculate the volume of the heart chamber. To do this, clinicians have to acquire images from two perpendicular angles, also knownn as views, of the heart, and then manually draw the heart chamber wall on the images. This can be time-consuming, and is also subject to large interobserver variability, meaning that two different doctors may draw the heart chamber wall quite differently, thereby resulting in different volume measurements.

An inexperienced user may not even know were to draw the heart wall, an automatic tool may in the future enable these users to perform necessary measurements. At the Centre for Innovative Ultrasound Solutions (CIUS), we are working on completely automating ultrasound heart measurements using deep learning.

Two ultrasound images acquired at different angles of the heart with the left ventricle wall drawn in green. Illustrations by Helene Mørk (www.helemork.com).

Learning by example

Deep learning is a type of machine learning which are algorithms that learn to solve a task by looking at a large amount of examples. Most machine learning methods today use what is called deep neural networks, which are inspired by the way human brains work. For instance, to create a neural network which can detect whether an image contains a dog or not, you collect a large set of images with and without dogs. You then train the neural network with these images, and for every image the system has to say whether the image contains dogs or not. If the result is incorrect, the neural network has to adjust itself, so that it will not make the same mistake again. By doing this many enough times and with enough variation in the input images, the system will learn what a dog
looks like automatically!

In order to automate the ejection fraction measurements, the neural networks have to learn several tasks such as:

• View classification: Learns to identify which images are of the different angles/views of the heart.
• Left ventricle segmentation: Learns to draw the heart chamber wall.

To learn these tasks, ultrasound images from several hundred patients were collected in cooperation with CREATIS in France and manually annotated by human experts. The neural networks are quite big, having several million parameters which have to be
adjusted during training.

The neural network result of finding the heart walls, identifying the different views, and when the chamber is largest and smallest.

Does it work in real-life?

The artificial intelligence methods were implemented in a high performance computing framework called FAST. This enables us to stream ultrasound data directly from a scanner and calculate the measurements in real-time while the operator is scanning as shown in this
video:

Together with clinician Ivar Mjåland Salte at the Sørlandet Hospital in Kristiansand, we performed a study to see how well our methods can do these measurements automatically compared to manually drawing the heart wall contour. Ultrasound recordings of 72 patients was collected and manually annotated. The neural network was able to automatically and quite accurately calculate ejection fraction for all patients, even for patients with low image quality ultrasound images.

Ejection fraction is only one of many clinical measurements of the heart, we are currently working on extending the neural networks to learn several other measurements, such as MAPSE, LV mass and strain.

An inexperienced user may not know where to place and how to angle the ultrasound probe correctly. This is necessary to get valid measurements of the heart. At CIUS, we are also developing an artificial intelligent assistant which can guide inexperienced users to acquire correct ultrasound images of the heart.

Are you in a bad shape, struggling with depressive symptoms, or struggling with both? Our research on 15,000 middle-aged and older people who participated in the Nord-Trøndelag Health Study, shows that improving fitness or depressive symptoms can be very important for our health, even at a higher age.

It is possible to influence our health positively by improving fitness or our depressive symptoms. (Illustration photo: iStock)

Depression is a common mental disorder. More than 350 million people suffer from depression worldwide, and the World Health Organization has rated depression as one of the leading causes of years lived with disability.

Physical and mental health are strongly related. Previous research has found that people with depression or depressive symptoms have an increased risk of premature death and of developing cardiovascular disease. The term premature death may sound brutal, but is often used in research settings and can be interpreted as dying earlier than life expectancy (about 84 years for women and 80 years for men in Norway, figures from the Norwegian Institute of Public Health 2015). We are all going to die, but some will die earlier than expected due to disease, accidents or injury, and that’s what we mean by premature death.

We know that depression is a devastating disorder to our health and we know that high fitness reduces the risk of a variety of diseases, such as cardiovascular disease and mental disorders such as depression and anxiety. We also know that people with high fitness have a lower risk of premature death compared to people with low fitness. What we know less about is how a change in these two factors affects our health and we wanted to investigate further. Can we, influence our health positively by improving fitness or our depressive symptoms when we are 50, 65 or 80 years of age?

Trude Carlsen explaining her research:

Our research shows that it is possible. To determine this, we used the Fitness Calculator developed by the Cardiac Exercise Research Group (CERG) at NTNU to calculate the participants’ fitness. Fitness has been shown to be the key factor to living a long and healthy life. Depressive symptoms were measured using a questionnaire that was handed out to the participants. We obtained information about deaths during the follow-up period through the Norwegian Cause of Death Registry. I want to emphasize that our research focuses on depressive symptoms and not depression as a diagnosis. Examples of depressive symptoms may be frustration, unhappiness, do not engage in usual enjoyable activities, sleep problems, and lack of confidence.

Theese findings were published in the medical journal Mayo Clinic Prooceedings: Long-term Changes in Depressive Symptoms and Estimated Cardiorespiratory Fitness and Risk of All-Cause Mortality: The Nord-Trøndelag Health Study.

Trude Carlsen. (Photo Amanda Gerhardsen)

Not surprisingly, we found that the risk was most reduced among the fit with low depressive symptoms over time. The good news is that those who managed to improve their fitness or managed to reduce their depressive symptoms also reduced the risk of premature death. It seems that it is never too late take action to improve fitness or depressive symptoms at a higher age.

What does it take to improve? Regular physical activity is one of the actions. Physical activity is medicine, it is free and influences health in so many ways other than that we feel happier and become in better shape. When it comes to maintaining high fitness, or improving it, regular physical activity is of paramount importance. Regular physical activity is also shown to improve depressive symptoms. Becoming out of breath and breaking a sweat two to three times a week can do wonders for our health.

Doctors and other health professionals should assess depressive symptoms and fitness regularly in their patients and take action to improve one or the other when necessary. There are simple tools for calculating fitness, and questionnaires to measure depressive symptoms. With help of some simple questions and measurements, healthcare professionals can easily calculate fitness using the Fitness Calculator.

Blogger: Siril S. Bakke, PhD/Post doc, Centre of Molecular Inflammation Research (CEMIR)

Cardiovascular disease resulting from atherosclerosis is one of the most common causes of death worldwide. Our new study reveals molecular mechanisms behind how a cyclic sugar reduces inflammation on the surface of cholesterol crystals.

Inflammation and the activation of the innate immune system, through the complement system, play a crucial role in the development of atherosclerosis. Cholesterol crystals are triggers of these processes as the disease develops. The complement system is a defense system that alters the surface of foreign material so that immune cells can engulf it for destruction.

Cholesterol crystals (CC) initiate inflammatory responses in immune cells called macrophages – this is inhibited by the sugar molecule cyclodextrin (BCD). CC may be recognised by the innate immune system through the complement system (components represented here as shperes and immuno-complexes as stars) and be engulfed by a macrophage. This leads to the transcription of pro-inflammatory genes and cytokine release, thus, causing local inflammation. When the sugar cyclodextrin is present it coats the CC and prevents uptake of the CC by the macrophage. Cyclodextrin can also dissolve CC andwill also enter into the macrophage and activate the transcription factor Liver X receptors and this may lead to a decrease in transcription and release of the pro-inflammatory factors.

Scientists from Centre of Molecular Inflammation Research (CEMIR) at NTNU in Trondheim together with national and international collaborators from University of Bonn, Copenhagen and Oslo have recently published a new paper in Journal of Immunology that shows that a sugar, called 2-hydroxypropyl-β-cyclodextrin (cyclodextrin), reduces inflammation caused by cholesterol crystals.

This is a follow up study from last year, when we found that cyclodextrin reduces and prevents formation of atherosclerotic plaques in mice, as well as dissolve cholesterol crystals. Cyclodextrin also had anti-inflammatory effects on cells in atherosclerotic plaques from humans.  That study promoted large publicity, making patients aware of the new basic results (see link for article in Gemini and Science Daily below).

Patients from all over the world contacted us to be a part of our study. As this was a basic research project we had to turn them down, however, if funding is available there is a great potential for a thorough clinical research project to see if treatment with cyclodextrin can be beneficial for the patients.

We still want to know more about the molecular mechanisms behind how cyclodextrin reduce the inflammation. Our follow-up study shows that cyclodextrin binding to the surface of cholesterol crystals reduces complement activation, and the entering of cholesterol crystals in the immune cells. Thereby, cyclodextrin prevents induction of inflammation.

Both our studies suggest that cyclodextrin can be a promising therapeutic approach for treating atherosclerosis because it inhibits inflammation, and thereby have the potential in lowering the deaths caused by atherosclerosis.

References:

• Cyclodextrin Reduces Cholesterol Crystal-Induced Inflammation by Modulating Complement Activation. Bakke SS/Aune MH, Niyonzima N/Pilely K, Ryan L, Skjelland M, Garred P, Aukrust P, Halvorsen B, Latz E, Damås JK, Mollnes TE, Espevik T. J Immunol. 2017 Aug 30. pii: ji1700302. doi: 10.4049/jimmunol.1700302.
• Cyclodextrin promotes atherosclerosis regression via macrophage reprogramming. Zimmer S/Grebe A, Bakke SS, Bode N, Halvorsen B, Ulas T, Skjelland M, De Nardo D, Labzin LI, Kerksiek A, Hempel C, Heneka MT, Hawxhurst V, Fitzgerald ML, Trebicka J, Björkhem I, Gustafsson JÅ, Westerterp M, Tall AR, Wright SD, Espevik T, Schultze JL, Nickenig G, Lütjohann D, Latz E. Sci Transl Med. 2016 Apr 6;8(333):333ra50. doi: 10.1126/scitranslmed.aad6100.
• Ny behandling av åreforkalkning med sukkerstoff. Gemini (in Norwegian)
• New hope for treating atheriosclerosis. Science Daily.