How CT technology assists in the fight against COVID-19
Tanuj | February 05, 2021There are two popular tests for coronavirus (COVID-19): molecular diagnostic test and antigen
diagnostic test. Some of these tests may require at least a few days to provide a positive or a negative result. Also, these methods can not inform about the stage of the COVID-19 and results can suffer from false-negatives, which may affect patient management. Furthermore, a worldwide shortage of testing labs or kits for COVID-19 has led scientists to search for alternative techniques.
The imaging technique of computed tomography (CT), taken at the patient’s chest (including lungs), has
been shown to be promising as an alternative method of diagnosing COVID-19. The CT images can be acquired within minutes, and a radiologist may be able to analyze them and provide results within hours. Therefore, the patients can receive results much quicker than the regular COVID-19 tests. The early detection and diagnosis of COVID-19 using CT may also help monitor the clinical course, disease evaluation, disease progression or help to identify early warning signals even in the absence of other testing.
How does CT work?
CT is a structural imaging technique that can provide information about physical structures. The CT imaging technique is nothing but a 3D version of an X-ray planar (2D) imaging technique. An X-ray image is obtained by firing X-rays from a beam source on an object to be imaged and collecting the transmitted rays in a detector at the opposite end (Figure 1).
(Learn more about X-ray systems on GlobalSpec.)
Figure 1. Scheme of CT technology. Source: Aron Saar/ CC BY-SA 3.0The X-rays lose part of their energy due to attenuation as they travel through the object (and its surroundings). This attenuation generally depends on the density of the object and the penetrating characteristics of the X-rays. The non-attenuated X-rays are then collected at the detector as a “signature” that can be used to represent the object in a planar 2D image.
A CT image can be generated when the entire X-ray source-detector set-up is rotated around the object
(Figure 1), and data about multiple X-rays at various angles are combined using a mathematical algorithm.
CT in COVID-19 diagnosis
Figure 2: A transverse view of a normal chest CT image of a 35-year-old female. Source: Radiopaedia/CC BY-SA 3.0A normal lung CT scan appears substantially black (Figure 2) because lungs are filled with air, and X-rays passing through the lungs lose only a small amount of energy due to minimal attenuation in their path.
Research has shown that pneumonia is the main contributing factor to the appearance of COVID-19 in CT lung images. Pneumonia is an infection that inflames air sacs in the lungs, which are replaced by a fluid (i.e., edema), giving a white-spotted appearance on CT images. It is possible that COVID-19 invades the respiratory tract, initiating immune responses and increasing cellular deposition of angiotensin-converting enzyme 2.
The inflammatory cell aggregation causes decreased air spaces, obstructing blood exchange that can progress to organ failure. Ground-glass opacities (GGOs) and consolidation are common CT features used (along with the clinical symptoms) to diagnose COVID-19. GGOs may refer to the collapse of the air spaces or the filling of pulmonary air spaces with fluid (without covering blood vessels or bronchial walls), which appear as grey-ish or white-ish colored hazy patches - as if some parts of the lung are covered with ground-glass. Consolidation refers to the filling of pulmonary air spaces with fluid or other products of inflammation, leading to an increase in density of parenchyma by covering the margins of pulmonary blood vessels or bronchial walls. GGOs and consolidation may present in various patterns and increase the density of lung regions (compared to air).Figure 3. A coronal view of a chest CT image in patients with COVID-19 disease showing ground-glass opacities. Source: Opzwartbeek/CC BY-SA 4.0
Therefore, the X-rays may get attenuated more (compared to air) and appear white-ish. COVID-19 features on CT images may be distributed in mid and lower regions of the lungs. The features are in the shape of patches or segments located away from the center and between the pleura and the parenchyma's body wall. The density of these patches can vary depending upon the severity of the disease, thus altering the lung opacity (i.e., the capacity of matter to obstruct the transmission of X-rays).
Using COVID-19 in patient treatment
CT imaging could be used for disease evaluation or progression (from an early to late-stage), for monitoring the clinical course of patients with COVID-19 or for identifying early warning signals. Figure 4 shows the four stages that can be identified/differentiated on CT images in the order of severity, from left to right, showing early, advanced, severe and dissipation stages. It is important to note that the GGO density seems to increase from an early stage to a severe stage; however, at the dissipation stage, the areas of GGOs and consolidation are nearly resolved, leaving some amount of residue.
Figure 4. The image shows four different stages in COVID-19 patients that can be differentiated using CT. Only the right-lung is shown here to illustrate th epoint and to avoid copyrights issues. Source: National Institutes of Health
CT is also more sensitive in detecting COVID-19 in the early stage than 2D or planar X-ray images because X-ray images have lower resolution than CT. This is because a CT image contains more information than an X-ray image (which is simply a projection of the object without any depth-related information in it).
For example, a 2D X-ray image may be of size 512 x 512 pixels in X and Y direction; however, a 3D CT image may be of 512 x 512 x 47 pixels in X, Y and Z direction (i.e., it contains 47 times more pixels or information in it). The main advantage of CT over other molecular imaging techniques, like magnetic resonance imaging or positron emission tomography, is that it can be performed quickly, it is reproducible, easy to perform and can provide a good indication of disease progression. The COVID-19 missed diagnosis using a chest CT has been reported to be 3.9%, similar to that of molecular/antigen diagnostic tests currently in use.
On the other hand, since pneumonia can be caused by a variety of organisms (including bacteria, viruses or
fungi), it is quite challenging to distinguish COVID-19 pneumonia from other viral pneumonia or infections. For example, atypical pneumonia may lead to GGO, but bacterial infections may lead to consolidation in the lungs’ lobes.
However, it is becoming more apparent from preliminary case reports that infections within close proximity of the pleura could be a specific indicator of COVID-19. This is an area of cutting-edge research that is rapidly evolving using automated techniques including machine learning algorithms and artificial intelligence
Summary
CT technology has a clear potential to be used as a standard method for the diagnosis, assessment of disease progression and assessment of treatment of COVID-19 patients. The technology is ubiquitous throughout hospitals globally and offers clearer insight into stages than other types of testing.
About the author
Tanuj Puri obtained a Ph.D in medical image analysis from University College Dublin and did further research at the University of Oxford, King's College London and Newcastle University. He has co-authored numerous scientific manuscripts in the areas of PET-CT imaging for various clinical trials. More information on Puri is available here.