Quantitative Measurement of Erythrocyte Aggregation as a Systemic Inflammatory Marker by Ultrasound Imaging: A

Prajwal Gyawali1, Daniela Ziegler2, Jean-François Cailhier3

  • 1Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada.

This systematic review is aimed at answering two questions: (i) Is erythrocyte aggregation a useful biomarker in assessing systemic inflammation? (ii) Does quantitative ultrasound imaging provide the non-invasive option to measure erythrocyte aggregation in real time? The search was executed through bibliographic electronic databases CINAHL, EMB Review, EMBASE, MEDLINE, PubMed and the grey literature. The majority of studies correlated elevated erythrocyte aggregation with inflammatory blood markers for several pathologic states. Some studies used "erythrocyte aggregation" as an established marker of systemic inflammation. There were limited but promising articles regarding the use of quantitative ultrasound spectroscopy to monitor erythrocyte aggregation. Similarly, there were limited studies that used other ultrasound techniques to measure systemic inflammation. The quantitative measurement of erythrocyte aggregation has the potential to be a routine clinical marker of inflammation as it can reflect the cumulative inflammatory dynamics in vivo, is relatively simple to measure, is cost-effective and has a rapid turnaround time. Technologies like quantitative ultrasound spectroscopy that can measure erythrocyte aggregation non-invasively and in real time may offer the advantage of continuous monitoring of the inflammation state and, thus, may help in rapid decision making in a critical care setup.

Related Concept Videos

Review and Preview01:10

Review and Preview

In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...
8.4K
Review and Preview01:13

Review and Preview

Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
11.6K
Lifecycle of Erythrocytes01:22

Lifecycle of Erythrocytes

Erythrocytes, also known as red blood cells, constantly move through blood capillaries. As a result, they damage their plasma membrane due to the continuous friction. Typically, after 100 to 120 days, erythrocytes become rigid and fragile as they wear out. As they pass through small vessels in the spleen and liver, they can get trapped and break apart into fragments.
The resident phagocytic macrophages deal with these damaged cells by engulfing them and separating their globin and heme groups....
5.4K
Disorders of Erythrocytes01:27

Disorders of Erythrocytes

Disorders of erythrocytes, or red blood cells (RBCs), include a range of conditions affecting their number, shape, or function.
Erythrocyte disorders can be broadly categorized into two main types: anemic and polycythemic conditions.
A low oxygen-carrying capacity of the blood due to the loss, lower production, or destruction of erythrocytes is termed anemia. Hemorrhagic anemia, for example, occurs when bleeding from an external wound or internal ulcer reduces erythrocyte counts.
On the other...
2.3K
Random and Systematic Errors01:20

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
15.2K
Structure and Function of Erythrocytes01:29

Structure and Function of Erythrocytes

There are between 4.2 and 6 million erythrocytes, also known as red blood cells, in every microliter of blood. These cells are small, flattened biconcave discs with centers that are depressed.
The erythrocyte plasma membrane is associated with proteins such as spectrin, which forms a flexible cytoplasmic meshwork. This meshwork allows erythrocytes to twist, turn, become cup-shaped, and regain their biconcave shape as they pass through narrow capillaries. Additionally, erythrocytes can form...
6.1K