Use of Computed Tomography (CT)-Scan in the Current Coronavirus Pandemic

*Ibrahima Niang, Géraud Akpo, Khadidiatou Ndiaye Diouf and Sokhna Ba*

#### **Abstract**

CT is a medical imaging technique that uses X-rays to provide three-dimensional reconstructed images of the explored anatomical region. Its sensitivity has already been demonstrated in the exploration of pulmonary lesions of traumatic, neoplastic and especially infectious origin. In this chapter we present and highlight the usefulness of CT-scan imaging for diagnosis and management of the thoracic involvement of the COVID-19 pandemic. We also present the use of CT in extra-thoracic involvement, in particular, the angio-CT of the limbs in cases of suspected arterial thrombosis of the limbs during COVID-19. Finally, we evoke the other tools such as artificial intelligence which coupled with the CT-scan allows a greater accuracy and thus are to popularize in order to reinforce the CT as a tool of first plan in the fight against future pandemics with thoracic tropism.

**Keywords:** CT-scan, diagnosis, coronavirus, COVID-19, ground-glass opacity, post-mortem CT, mobile CT, Artificial Intelligence

#### **1. Introduction**

Computed tomography (CT) is a diagnostic tool that uses X-rays to visualize anatomical structures of the body with a good resolution [1]. It allows the identification of abnormalities related to a pathology. It has proven itself particularly in the exploration of lung parenchyma where it has a high sensitivity in the detection of neoplastic and infectious diseases [2]. Knowing that its realization lasts only about ten seconds and that the results can be immediately available, the CT scan is a tool of choice in case of high influx of symptomatic patients and requiring triage [3]. Since the occurrence of the COVID-19 pandemic, whose main symptoms are respiratory with lung parenchymal lesions responsible for a desaturation that can be rapidly fatal, CT has taken a place of choice in the management of both suspected and confirmed cases. This is due to the fact that the reference diagnostic tool, RT-PCR on nasopharyngeal swabs, has a low sensitivity despite a good specificity [4]. Moreover, this PCR test gives results delayed by one to several days, which does not facilitate the management of patients in emergency. Thus, CT is positioned both as an emergency triage tool and as a prognostic tool to assess the extent of lung parenchymal lesions while identifying other associated lesions or other complications such as pulmonary embolism [3, 5].

#### **2. Technique**

A thoracic CT scan is performed on a patient in dorsal recumbency, with the hands placed behind the head. The patient must maintain a deep inspiration during the acquisition, which lasts about ten seconds. This acquisition must cover the whole thorax from the apex to the costo-diaphragmatic cul-de-sac. Ideally, for patients with COVID or suspected COVID, it is better to perform the examination with a dose optimization protocol (low-dose) [6]. This will reduce the cumulative irradiation dose, when we know that these patients may have to undergo several CT scans depending on their evolution.

However, the examination should be performed with injection of iodinated contrast medium, in thoracic angio-CT, when there is a clinical suspicion of pulmonary embolism [7].

#### **3. Results**

#### **3.1 Positive diagnosis**

The CT scan essentially allows the identification of the elementary lesions attributable to COVID-19, which are ground-glass opacity, crazy-paving and non-systematized condensation [8, 9].

The ground-glass opacity, which corresponds to an opacity of the lung parenchyma that does not erase the pulmonary vessels (**Figure 1A** and **B**), is the most frequent sign found in COVID-19 between 88% and 94% [9, 10].

However, ground glass opacity is a non-specific sign of COVID-19 and therefore it is above all its distribution on the lung parenchyma that is decisive for the diagnosis. In the typical form, this distribution is in bilateral sub pleural patches, predominantly in the posterior and basal regions (**Figure 1A** and **B**) [11]. However, there are less typical forms with a central, unilateral, predominantly apical or nodular distribution [10].

Crazy-paving, which corresponds to ground-glass opacity associated with thickening of the lobular septa (**Figure 2A** and **B**), is usually found in the evolution of ground-glass lesions [12].

#### **Figure 1.**

*Chest CT in lung window, axial section (A) and sagittal reconstruction (B) typical form of COVID-19 pulmonary lesions with bilateral areas of ground glass opacities limited to the sub pleura and predominantly at the lung bases.*

*Use of Computed Tomography (CT)-Scan in the Current Coronavirus Pandemic DOI: http://dx.doi.org/10.5772/intechopen.101197*

#### **Figure 2.**

*Chest CT in lung window, axial sections (A and B). Thickening of the septa on a ground glass background giving the appearance of crazy-paving.*

The same is true for non-systematic condensation which can occur by transformation of the initial lesions [12]. This condensation will appear as an increase in density of the lung parenchyma but unlike the ground-glass opacity, it will erase the pulmonary vessels (**Figure 3A** and **B**).

#### **3.2 Differential diagnosis**

As important as it is to know how to recognize CT signs compatible with COVID-19 infection, it is equally important to know how to differentiate it from other pathologies that require a different management and that can be life-threatening emergencies.

These differential diagnoses are first and foremost the other causes of groundglass opacity. This is a long list covering several diffuse interstitial lung disease, acute pulmonary edema and alveolar hemorrhage among others [13]. Other causes of crazy-paving and condensation will also be a differential diagnosis, including several diffuse interstitial lung diseases, pneumonia, acute pulmonary edema, bronchioloalveolar carcinoma among others [14].

On imaging, it is important to differentiate the lesions of covid-19 with those of acute pulmonary edema and alveolar hemorrhage which are high emergencies and require specific treatment. What helps in this distinction is essentially the

#### **Figure 3.**

*Chest CT in lung window, axial section (A) and coronal reconstruction (B) bilateral patches of non-systematic sub pleural condensation, corresponding to an evolution of ground glass lesions in relation to COVID-19.*

#### **Figure 4.**

*Chest CT in lung window, axial section (A) and coronal reconstruction (B) bilateral areas of condensation and ground glass opacities, confluent, centrally distributed, clearly sparing the sub pleural regions. This gives the butterfly wing appearance which is in favor of pulmonary edema and rules out the suspicion of Covid-19 in the patient.*

distribution of the lesions which are typically sub pleural in COVID-19 and on the contrary spares the sub pleural regions in alveolar hemorrhage and acute pulmonary edema (**Figure 4A** and **B**) [15].

However, in each case, this differential diagnosis must consider the clinical elements, the evolution and the biological data.

#### **3.3 Severity and complications**

The most important factor of severity is the degree of extent of the lesions on the lung parenchyma. A visual grading of these lung lesions has been proposed by the Society of Thoracic Imaging (STI) in five stages ranging from less than 10% involvement (minimal) to more than 75% involvement (critical) [16]. This degree of lung involvement is important to specify because it constitutes a prognostic element.

Other elements of severity are the existence of sequelae or evolving pulmonary lesions (pulmonary emphysema, sequelae of granulomatosis, active tuberculosis infection, among others).

Among the complications, the most feared and expected is pulmonary embolism [17]. The risk of embolism is high because of the significant inflammatory response during COVID-19, which makes it a highly thrombogenic pathology [18]. The search for a clinically suspected pulmonary embolism is the main indication for thoracic angio-CT in COVID-19 (**Figure 5A** and **B**) [7].

Other complications are pneumothorax and pneumomediastinum, which may occur spontaneously or as a result of mechanical ventilation [19].

Bacterial reinfection can also occur in COVID-19 pneumonia. In this case, there is a systematized condensation at a lobe or a segment, unlike the condensations related to COVID which follow the distribution of ground glass lesions, remaining sub pleural and not systematized [20].

All these elements of severity and complications influence the prognosis of the patient, which makes thoracic CT an important prognostic tool.

#### **3.4 Evolution**

The evolution of COVID-19 lung disease can be towards a regression of the lesions with possible restitution ad integrum if an adequate treatment has been *Use of Computed Tomography (CT)-Scan in the Current Coronavirus Pandemic DOI: http://dx.doi.org/10.5772/intechopen.101197*

#### **Figure 5.**

*Thoracic CT angiography in mediastinal window with coronal (A) and sagittal (B) reconstruction pulmonary embolism with endoluminal defect at the level of a left posterobasal segmental pulmonary artery branch (red arrows).*

initiated in time. However, it should be kept in mind that regression of lesions on CT is lagging behind clinical improvement [21]. Therefore, it is important to avoid too frequent CT scans, which would be a source of unnecessary irradiation.

The evolution may also take the form of fibrosing parenchymal sequelae [21]. Furthermore, it should be borne in mind that pulmonary embolism may occur

during the evolution of the disease.

#### **4. Use of CT in extra-thoracic disease**

COVID 19 is a systemic disease, although thoracic and particularly pulmonary involvement is prominent. CT can be an important tool for some of these extra thoracic conditions [22].

#### **Figure 6.**

*Angio-CT of the lower limbs in a COVID patient with ischemia of the left lower limb. (A) Angiographic reconstruction showing the thrombosis of the superficial femoral artery from its origin (red arrow) to its lower third with revascularization by collaterals from the deep femoral artery. (B) VRT reconstruction showing the thrombosis extending over a height of 18.6 cm.*

Among the extra thoracic uses of CT, we note in particular the angio-CT of the limbs in cases of suspected arterial thrombosis of the limbs during COVID-19 (**Figure 6A** and **B**).

#### **5. Advantages and disadvantages of CT compared to other diagnostic tools**

#### **5.1 Advantages**

CT has the advantage of having good spatial resolution but also availability and speed of image acquisition, which only takes about ten seconds. The reading of the images is also fast and quite easy compared to other imaging methods.

In addition, CT has good sensitivity in the detection of COVID-19 lung lesions, when compared with the reference diagnostic tool that is RT-PCR [23].

Another advantage is its contribution to the prognosis of patients by providing an overview of the lung volume affected by the lesions.

#### **5.2 Disadvantages**

The main disadvantage of CT is the irradiation, which justifies the use of dose optimization (low-dose CT) to minimize the consequences that could result from it [24].

The other disadvantage is the low specificity of lesions on CT, compared to RT-PCR. This should be considered to avoid overdiagnosis of COVID-19 on CT [23].

#### **6. New features and perspectives**

#### **6.1 Mobile CT**

The mobile CT allows to palliate the need for specialized transport of patients with or suspected of having COVID-19 for whom a CT scan is necessary. This transport may require particularly important logistics, especially for patients in intensive care [25]. For these patients, it is often easier and safer to bring a mobile device to their bedside than to move them to the imaging department, hence the importance of mobile CT in their management. And this mobile CT provides good quality images with a sensitivity that remains superior to the PCR test [25, 26].

#### **6.2 Post mortem CT**

Postmortem CT has positioned itself as an alternative to autopsy in deceased COVID-19 patients or in those suspected of having COVID-19. In these patients there is a high risk of contamination during the autopsy and this examination requires protective equipment that is not always available [27]. The thanatoradiological semiology of COVID-19 on CT is identical to that of living patients.

#### **6.3 Artificial intelligence**

Artificial intelligence is increasingly used as a means of fluidity and ease in several fields using technology, imaging and particularly CT is no exception. In the case of Covid-19, artificial intelligence associated with CT helps to make the diagnosis more accurate and also provides greater precision on the lung volume affected by the lesions [28].

*Use of Computed Tomography (CT)-Scan in the Current Coronavirus Pandemic DOI: http://dx.doi.org/10.5772/intechopen.101197*

#### **7. Conclusion**

This chapter has demonstrated the great usefulness of CT-scan in the fight against coronavirus pandemic, due to its rapid image acquisition, its immediate availability of results, its good spatial resolution and especially its high sensitivity in the detection of COVID-19 lesions. These assets are reinforced by mobile CT facilitating access to quality imaging in intensive care patients and the coupling with artificial intelligence tools providing greater diagnostic accuracy and assessment of lesion extent.

All of this should give CT a primary place in the response to future lung-tropic pandemics, such as the coronavirus.

#### **Conflict of interest**

The authors declare no conflict of interest.

## **Author details**

Ibrahima Niang1 \*, Géraud Akpo1,2, Khadidiatou Ndiaye Diouf1 and Sokhna Ba1

1 Radiology Department, Fann University Hospital Center, Dakar, Senegal

2 Radiology Department, Aristide Le Dantec University Hospital Center, Dakar, Senegal

\*Address all correspondence to: niangibrahimaniang@gmail.com

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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#### **Chapter 3**

## Radiation Doses and Risk Assessment during Computed Tomography of the Chest in COVID-19 Patients

*Elena Ivanovna Matkevich and Ivan Vasilievich Ivanov*

#### **Abstract**

Accounting for the effective dose (ED, mSv) and calculating the radiation risk during CT is necessary to predict the long-term consequences of radiation exposure on the population. We analyzed the results of 1003 CT examinations of the chest in patients with suspected COVID-19 in the city diagnostic center. The average ED and confidence intervals (p ≤ 0.05) for patients with a single CT scan were: children (12–14 years) 2.59 0.19 mSv, adolescents (15–19 years) 3.23 0.17 mSv, adults (20–64 years), 3.43 0.08 mSv, older persons (65 years and older) 3.28 0.19 mSv. The maximum radiation risk values were 31.2\*10–<sup>5</sup> in women children and 29.3\*10–<sup>5</sup> in women adolescents, which exceeds the risk values for men in these age groups by 2.3 and 1.9 times, respectively. For the group of adult patients the risk was 11.2\*10–<sup>5</sup> in men and 17.4\*10–<sup>5</sup> in women, which is 1.6 times higher than in men. All these risk values are in the range of 10\*10–<sup>5</sup> –100\*10–<sup>5</sup> , which corresponds to the level LOW. For the group of older age patients, the radiation risk was 2.6\*10–<sup>5</sup> , which corresponds to the level of 1\*10–<sup>5</sup> –10\*10–<sup>5</sup> , VERY LOW. Our materials shows in detail the technique to evaluate effective radiation doses for chest CT and calculate the radiation risk of the carcinogenic effects of this exposure.

**Keywords:** computed tomography, chest CT diagnostics, effective dose, radiation risks levels, the dependence of the radiation risk levels of sex and age

#### **1. Introduction**

In the coming years, due to the introduction of methods of medical diagnostics and treatment using ionizing radiation, the growth of medical exposure of the Russian population expected to continue, especially due to computed tomography (CT). Therefore, it is important to evaluate radiation dose levels and population radiation risks in the form of a possible oncological pathology among the population in the long term after exposure [1–8].

Estimating the stochastic effects on the basis of a linear non-threshold model, *P. Galle* [9] concluded that, compared to 700,000 spontaneous cancers per year, when recalculated to the French population, 7,000 deadly cancers are caused by radiation causes. Of these, 3,000 are associated with high concentrations in radon homes, 1,000- with radiation medical procedures, 10 - with radiation from the work of the

nuclear industry and 1 - from increased natural radiation background. Therefore, from medical exposure, 14.3% of all radiation-related oncological pathologies arise.

Due to the widespread use of CT of the chest organs for the diagnosis of COVID-19, including during repeated examinations, this issue is of particular relevance.

The aim of the study was to assess effective radiation doses for chest CT for the diagnosis of Covid-19 and calculate the radiation risk of the effects of this exposure.

#### **2. Material and methods**

#### **2.1 General characteristics of patients**

We analyzed the results of 1003 CT examinations of the chest performed in patients with suspected COVID-19 during one week in October 2020 in the city diagnostic center. Among these patients were 6.2% children in the ages of 12–14 years old, 15.3% adolescents in the ages of 15–19 years old, 60.1% adults in the ages of 20–64 years old, and 18.4% older persons of ages 65 years and older. The average ages and confidence intervals (p ≤ 0,05) were 13.8 0.20 years old in group 1 (children), 17.1 0.41 years old in group 2 (adolescents); 45.8 1.47 years old in group 3 (adults) (of which 41.8% are of ages 20–45 years old and 58.2% are of ages 46–64 years old); 69.4 1.79 years old in group 4 (older persons). The percentage number of male (female) persons in the groups are 51.6% (48.4%) in group 1, 52.3% (47.7%) in group 2, 46.3% (53.7%) in group 3, 47% (53%) in group 4. The proportion of patients with CT signs of pneumonia and without pathological signs amounted to a total of 54,6% and 45,4%, respectively, for each of the four age groups. The distribution of the patients into groups during CT examination is given in **Table 1**.


#### **Table 1.**

*The distribution of patients in groups during CT examination on COVID-19.*

*Radiation Doses and Risk Assessment during Computed Tomography of the Chest in COVID-19… DOI: http://dx.doi.org/10.5772/intechopen.100177*

#### **2.2 Description of computed tomography technique, calculation of effective dose and radiation risk**

CT studies of the chest were performed on a Siemens Somatom Emotion 16 scanner (16-slice) using a standard algorithm. The voltage on the tube was 130 kV with automatic modulation of the amperage; the slice thickness was 0.8 mm (pitch 1.4) or 1.5 mm (pitch 1.2). Of each patient, the values of the parameters determining the radiation load were entered into the database CTDIvol (mGy), DLP (mGy\*cm) and ED, mSv.

The calculation of the effective dose (ED, mSv) for a single phase CT scan was performed according to the following equation.

The CTDIvol values were entered into the database from the CT scanner console. Then, the DLP was calculated by the formula:

$$\text{DLP} \left( \text{mGy} \ast \text{cm} \right) = \text{CTDIvol} \left( \text{mGy} \right) \ge \text{irradated length} \left( \text{cm} \right) \tag{1}$$

The procedure for registering the indicator "irradiated length (cm)" was as follows. Previously, the X-ray technician performed an X-ray (tomogram) of the chest. Then the region of interest (ROI) was installed on the CT scanner console in accordance with the Recommendations of EUR16262, 1999 [10]: Volume of investigation (routine chest) - from lung apex to the base of the lungs. The length of this area (irradiated length) was measured individually in each patient. In this area, a CT scan was subsequently performed and, accordingly, the patient was irradiated. DLP was calculated for this zone.

In our study, for the chest the "irradiated length" (Median, 25th and 75th percentile) was (cm): 31.3 (30.1–33.4) - in children, 34.7 (32.6–36.6) - in adolescents, 36.6 (34.9–38.7) - in adults, 33.3 (31.6–36.8) – for persons 65 years and older.

Then, using the DLP, the effective doses was estimated according to the formula [11]:

$$\text{ED, mSv} = \text{K}\_{\text{ED DLP}} \ast \text{DLP}.\tag{2}$$

To calculate the effective dose (ED, mSv) the chest KED DLP conversion factor (mSv\*mGy�<sup>1</sup> \*cm�<sup>1</sup> ) used was KED DLP = 0.012 for both the children group (12– 14 years old) and the adolescent group (15–19 years old) and KED DLP = 0.016 for the subjects older than 19 years [12, 13].

The method of calculating the risk of radiation consequences is based on the analysis of the frequency of leukemia and other oncological diseases, hereditary disorders in subsequent generations in the population after irradiation of people during the atomic explosions in Hiroshima and Nagasaki, the Marshall Islands, after gamma irradiation of patients with cancer and after incidents and accidents at nuclear reactors. Several hundred publications with this information were summarized in ICRP Publication 103, 2007 [11], and the risks of these consequences in persons of different genders and ages were calculated depending on the radiation dose received. In our study, calculations of radiation risk are carried out according to the National Methodological Recommendations [14] as follows:

$$\mathbf{R} = \mathbf{E} \mathbf{D} \ast \mathbf{r},\tag{3}$$

where

R is the radiation risk per 100,000 population at an exposure dose of ED, mSv; ED - effective dose, mSv;

r - risk indicator for exposure of 1 mSv (mSv�<sup>1</sup> ).


#### **Table 2.**

*Lifetime risk of death ratios, taking into account harm from reduced quality of life, calculated [14] per 1 mSv effective dose for medical diagnostic chest irradiation.*


#### **Table 3.**

*The radiation risk levels (individual lifetime risk) to a patient's health associated with medical exposure during diagnostic studies or treatment procedures [14].*

A risk indicator for exposure of 1 mSv used, lifetime cancer risk of radiation is 5.5 \* 10<sup>5</sup> mSv<sup>1</sup> for the entire population regardless of age and sex. However, in this study r (risk indicator) were used, taking into account the age and sex of patients (**Table 2**) in accordance with the National Methodological Recommendations [14]. These values were calculated for the Russian population (mortality and morbidity data for 2008) using risk models and ICRP calculation methods [11, 15]. When calculating Radiation risk level, the scales listed in **Table 3** were used.

The mean and median values of effective doses in the formed groups were close, the assessment of the data according to Kolmogorov–Smirnov test for normality and Shapiro–Wilk's W test showed that the nature of their distribution is close to normal. The measured data were expressed as the average confidence interval (X CI) at p ≤ 0.05, as well as median (Me, 25th and 75th percentile). The significance of differences between the groups according to Student t-criterion, P value<0.05 was considered for statistical significance. STATISTICA statistical software (version 10.0; Stat Soft. Inc., United States) was used for analysis.

#### **3. Results and discussion**

The average effective doses to patients with a single CT scan in the formed groups as illustrated in **Table 4** and **Figure 1A** were 2.59 0.19 mSv in group 1 (children 12–14 years old), 3.23 0.17 mSv in group 2 (adolescents 15–19 years

