A Comparison of the Efficacy of Diagnostic Imaging Modalities in Detecting COVID-19

Mohamed Nashnoush1*, David Chen2, Devdigvijay Singh3, Emily Su4, Helen Yin5, Jessica Wong5, Melissa Ma6
1Dalhousie University

2Western University

3Princeton University 

4Unionville High School 

5Bayview Secondary School 

6University of Toronto 
Corresponding author: [email protected]

DOI
doi.org/10.7244/cmj.2020.11.004
Image by Michal Jarmoluk from Pixabay

Abstract

Aims

As COVID-19 continues to spread globally, the urgency for effective diagnostic testing escalates. Medical imaging has revolutionized healthcare as a critical step to early diagnosis, leading to immediate isolation and optimized treatment pathways. Current imaging modalities such as the lung ultrasound, chest X-ray, and computed tomography (CT) scan are critical in COVID-19 detection. However, overlap in clinical characteristics with other viral respiratory illnesses poses a significant risk for misdiagnosis.

Methodology

To address the need for information concerning the effectiveness of Coronavirus disease 2019 (COVID-19) diagnostic procedures, this paper reviews different imaging modalities, evaluating various factors including sensitivity, specificity, cost, diagnosis time, accessibility, safety, ease of implementation, and potential for optimization. The literature search reviewed databases including PubMed, Google Scholar, Sonography Canada, Cochrane Review, and Novanet using keywords to filter results. A utilitarian approach was employed to further refine selection criteria and to assess credibility and relevance. Applicable data was then extracted from literature for analysis considering the relationships between studies.

Results and Conclusions

The imaging modalities reviewed in this paper each have unique advantages. The lung ultrasound, with moderate sensitivity, permits regular monitoring due to its accessibility. Chest X-rays are effective at processing detailed images of the lungs to detect abnormalities but are not confirmed as a precise method for diagnosis. While CT scans show morphological features of COVID-19 with superior sensitivity, it is incapable of accurately differentiating coronavirus from other pulmonary diseases. Overall, a multimodality approach would be most effective for COVID-19 diagnosis and monitoring, preventing over dependence on CT scans.

 

Introduction

 

In recent months, the outbreak of Coronavirus disease 2019 (COVID-19) has been declared a global pandemic by the World Health Organization (WHO). As of June 20, 2020, WHO has reported 8,525,042 cases and 456,973 deaths globally from the virus [1]. Current diagnostic procedures for COVID-19 include reverse transcription polymerase chain reaction (RT-PCR), lung ultrasound (US), chest X-ray, and computed tomography (CT) scan. While the Centers for Disease Control and Prevention (CDC) cites that the American College of Radiology (ACR) recommends RT-PCR as an initial diagnostic intervention for COVID-19, imaging modalities are used in hospitals with symptomatic patients who require them for specific clinical indications if they have other illnesses [2]. As the number of cases increases rapidly in countries such as the United States and Canada, it raises concerns regarding the shortage in supply of RT-PCR tests [3]. Thus, imaging modalities are another form of diagnostic testing for patients who need them for specific clinical indication or in the absence of RT-PCR testing.   


The most commonly used diagnostic imaging modality is CT scan due to its high sensitivity. However, in a review of current CT scan literature, it scrutinizes current literature pertaining to the effectiveness of COVID-19 imaging modalities and discusses overarching conclusions that have been made based on low-quality tests with faulty criteria and biased cohorts [4]. This poses issues surrounding the optimization of varying diagnostic tests as these studies do not disclose limitations such as selection bias of cohorts and use faulty methodologies to assess imaging modalities in diagnosing. It is due to this that instigates this review which will further evaluation of the effectiveness and sensitivity of current imaging modalities.


With the fast-paced clinical setting, the absence of a vaccine, and clinical management being important during the COVID-19 outbreak, utilizing the most effective imaging modality alongside or in the absence of RT-PCR testing is critical. This will potentially maximize the efficiency of patient triaging and treatment workflows, minimize the further possibility of transmission at the population level, and decrease the risk of misdiagnosis.


Unlike other reviews, this paper aims to provide a holistic review of current clinically relevant medical diagnostic imaging techniques employed during the COVID-19 outbreak while considering any potential limitations such as the logistics, and discuss the future direction of this field.


Method


The review comprised four stages: literature search, quality assessment, and data extraction and data analysis.


The review methodology (literature search) covered peer-reviewed studies published post-January 2020, as this timeframe reflects the development of diagnostic technological advancements addressed as part of this review. Studies with a minimum population of at least 50 subjects and were documented in English were considered. The minimum age of 18 was employed as a filter to ensure that the populations under consideration were composed of adults. Randomized control trials (RCTs), cohort, longitudinal studies, and meta-analyses were evaluated using the Cochrane handbook for systematic reviews of interventions [5]. Databases used include PubMed, where the MeSh terms “Coronavirus disease-19 testing”, “Diagnostic Imaging”, and “Patient Care Management” were utilized to investigate COVID-19 imaging. Boolean operators such as “AND” and “OR” were employed to refine the search, maximizing the relevance of the results. Additional databases used include Google Scholar, Sonography Canada, Novanet, and Cochrane Review. 


The review methodology (quality assessment) employed a utilitarian approach to further refine the selection criteria of COVID-19 imaging articles. This approach sampled articles based on key factors that indicate their credibility and relevance. These included recency, authority, objectivity, and if it is published in a peer-reviewed journal. Papers that did not meet the criteria for credibility or relevance were excluded.


Relevant information extracted include, but are not limited to, the date of data extraction, identification features of the study, study characteristics, participant characteristics, intervention, setting, and outcome data/results. The following areas were to be addressed in the outcome data/results:

 

  • Accuracy of diagnoses (sensitivity and specificity averages).
  • Average cost of diagnoses.
  • Average time of scan and diagnosis.
  • Accessibility of scanning hardware in both developing and developed nations.
  • Safety of healthcare workers and patients.
  • Ease of implementation of potential improvements and optimizations.


To avoid bias and maintain integrity, data extraction, database search, title/abstract screening, and study selection were respectively performed independently by at least two review authors. Disagreements between review authors were resolved by general consensus.


Tabulation of collected information in the data extraction stage facilitated the classification of studies into appropriate subgroups for the purpose of identification and cross-comparison of outcome measures. Due to time constraints, clinical and methodological diversity involved in employed studies, and possible biases, a narrative synthesis was employed au lieu a meta-analysis for the data analysis stage of this review.


Primarily, data were synthesized in three categories of chest imaging modalities; CTs, X-rays, and Ultrasounds. Two predominant areas of consideration at this stage of research were exploring relationships within and between studies and assessing the robustness of the synthesis to answer our underlying question of a gold standard of imaging modalities. Due to the subjectivity of the employed data analysis approach, emerging trends and patterns from the preliminary synthesis were rigorously scrutinized through verifying the source validity, identifying outliers and confounding variables in order to limit biases and to explain possible variations of effect measures. In order to assess the robustness of synthesis, studies from higher impact sources were given greater credence in addition to a critical discussion of synthesis results (possible limitations and their impact on results, sources of bias, assumptions, discrepancies etc.)

 

Discussion

Lung Ultrasound

Although the most common modalities of detecting COVID-19 are currently reverse transcription polymerase chain reaction (RT-PCR) and computer tomography (CT) chest scans [6], Point-Of-Care Ultrasound (POCUS) and bedside lung ultrasound offer several advantages that have led several researchers to propose it as a gold-standard imaging modality despite its generally well-known disadvantages [6, 7].


From a medical standpoint, lung ultrasound offers several unique advantages which, in certain situations, may not be available through other imaging modalities. Firstly, lung ultrasound enables the frequent monitoring of cardiac function [8], tracking of the growth of pleural effusions along with other COVID-19 symptoms, and general insight into the progression of the disease during hospitalization [9]. Information such as this can aid in both treating the patient earlier and in a more effective manner through more personalized treatment plans. Secondly, lung ultrasound is found to have high specificity (86%) and sensitivity (88%) values of diagnosing pneumonia [6]. Lung ultrasound is also highly sensitive (91%) and specific (98%) for the detection of pleural effusions [6] as well as pleural irregularity and thickening, subpleural consolidations, and ground-glass opacification [10, 11], all common findings in COVID-19 patients [12]. Furthermore, according to an Italian study on the identification and treatment follow-up of COVID-19 patients, lung ultrasound was found to be more sensitive (80%) in distinguishing between a bacterial pneumonia and a non-bacterial infection than chest x-rays (60%) [13]. Thirdly, a study by Shokoohi et al. investigated the feasibility of using lung ultrasound to monitor patients during home isolation. While the study acknowledges the lack of data “on the progression of sonographic findings in patients with COVID-19” [14], its findings included a successful correspondence between symptom onset with three patients confirmed with COVID-19 during a 14-day isolation period. Thus, we encourage further studies discussing the use of POCUS as a means of monitoring patients in self-isolation to reduce direct operator exposure to COVID-19 patients. Fourthly, lung ultrasound scans and diagnosis may potentially serve as a screening mechanism between low— and high—risk patients who require further imaging. Ultimately, this would ensure that these two groups of patients would not be exposed to the same equipment, reducing the risk of cross-infection. Fifthly, due to the fact that lung ultrasound is radiation-free, it can be used on a wider range of patients and on a more frequent basis. Another paper reported a case study in which a 32 year-old woman 35 weeks into pregnancy was initially falsely found negative for COVID-19 through RT-PCR, but then later positive by the detection of thick B-lines bilaterally through point-of-care lung ultrasound before other modalities reported positive [15, 16]. Overall, these instances support the use of POCUS in the detection and monitoring of COVID-19 symptomatic manifestations.


However, we also acknowledge the several medical drawbacks involved with employing ultrasound techniques to detect COVID-19. The largest disadvantage is the fact that there has been no identification of symptoms that are pathognomonic to COVID-19 [12, 13, 17]. Additionally, the lower resolution imaging [11] increases the need for trained professionals to diagnose COVID-19, which may be of concern in regions with medical staff shortages. Furthermore, there are cases in which lung ultrasound cannot be employed for certain patient groups. For instance, lung ultrasound may not work with patients with pre-existing pulmonary conditions due to its “[inability] to discern the chronicity of a lesion” [10]. Finally, in cases where lung ultrasound does not lead to a confident diagnosis of a patient, additional imaging may be required, leading to longer exposure times of medical equipment operators to COVID-19 patients.


In addition to their medical advantages, point-of-care and bedside lung ultrasound also offer numerous advantages with respect to their accessibility and safety. Due to the highly contagious nature of COVID-19, the use of a portable POCUS device, which requires less operator activity, reduces the overall risk of transferring the disease to medical staff [8]. It also reduces the use of personal protective equipment (PPE), a factor that is especially important in countries where there is a lack of medical funding, and/or a lack of medical staff due to the economic impact of the pandemic. Thus, the recent rise of availability, accessibility, and affordability of lung ultrasound equipment [6, 7, 10, 18] make it ideal for these low-resource environments. However, due to the poorer imaging quality, some studies assert that the need for trained sonographers is high to reduce scanning time and increase diagnosis accuracy. The process of training additional sonographers may further deplete PPE resources faster than using other modalities for quicker scans [8, 19]. Finally, the recent exploration into employing neural networks to automatically detect COVID-19 from lung ultrasound imaging has proven to be effective and accurate, thus reducing the need for trained operators to diagnose COVID-19. A study using a relatively small dataset of just 1102 total images reported an overall accuracy of 89%, sensitivity of 0.96, and a specificity of 0.79 [20, 21, 22, 23] for automatic detection of COVID-19. Further imaging and a building of a more comprehensive dataset may increase these numbers, thus adding to the previously discussed advantages of using lung ultrasound.


Chest X-ray

Chest X-ray imaging has not been proven to accurately diagnose COVID-19 in affected patients but can supplement screening efforts in the diagnosis of the family of illnesses described by Influenza Like Illness (ILI) and coronavirus-related respiratory complications. The use of chest X-rays as the initial imaging method to screen patients who present COVID-19 symptoms compared to less portable and more intensive imaging modalities is already employed in most Italian hospitals in an attempt to reduce patient transmission due to intra-facility transport [27]. General radiography should be utilized to assess coronavirus-related physiological complications and other respiratory etiologies.

Recent COVID-19 imaging modality literature have centered around CT due to its higher specificity and sensitivity compared to chest X-ray and higher speed compared to MRI [28].  Furthermore, chest X-ray has a vital role due to its accessibility in regions of the world with limited access to more expensive and reliable technologies such as CT and reverse transcription polymerase chain reaction (RT-PCR) tests.  

The physiological appearance of COVID-19 during its time course in affected patients classically features lower lobe alveolar opacities with superimposed atelectasis [29]. As COVID-19 disease progression becomes increasingly more severe in affected patients, chest X-ray can detect patchy and diffuse, asymmetric opacities throughout the lungs. The time course of chest X-ray images progresses from focused unilateral opacities to diffuse bilateral opacities over the course of 3 weeks, peaking at around 6-12 days following the initial clinical diagnosis. Bilateral, multi-lobe lung opacities due to viral pneumonia differs from unilateral, single-lobe opacities characteristic of bacterial, community-acquired pneumonia [30]. Hazy pulmonary opacities can make concluding diagnosis based on X-ray images challenging. The diffuse opacities found in COVID-19 patients share similar X-ray patterns with other pulmonary infections and inflammatory processes, such as acute respiratory distress disorder (ARDS). Confluent opaque patches can appear as “whited out” and progressively increase in opacity and consolidation over the course of the disease [31]. In more severe cases, pleural fluid effusion has been observed on chest X-ray images, in addition to the opaque features characteristic of pulmonary infection. Pulmonary cavities of thick-walled gas-filled spaces associated with inflammatory masses have also been observed on chest X-ray images in rare cases. Jacobi et al. reported that chest X-rays were particularly useful in identifying nuanced physiological effects of diffuse chest wall emphysema observed on a small subset of COVID-19 patients [32]. 

Weinstock et al. notes that among confirmed COVID-19 cases, 58.3% of chest x-rays read as normal, with 89% of cases reading as either normal or mild. The study also states that of the 636 chest x-rays examined, 42% of chest x-rays reading as abnormal, 195 demonstrated mild disease, 65 had moderate disease, and five had severe disease. The most common qualitative findings were interstitial changes (23.7%) and ground glass opacities (19%). About 33% of these abnormalities were in the lower lobe, though 25% were multifocal and about 21% were bilateral. The observational findings by Weinstock et al. are consistent with current COVID-19 chest x-ray literature and suggests that chest x-ray modalities can be used as screening rather than diagnostic tools [33]. 

When the disease spreads to the majority of the lung parenchyma, patients will generally require mechanical intubation to prevent hypoxia. Daily chest X-rays in intubated patients were beneficial in monitoring the progression of the disease and discovering novel changes in the lung parenchyma. Purdy et al. note that implementation of chest X-rays as a monitoring tool in interventionist settings should be closely supervised to limit overuse of resources. This is particularly important in clinical settings with limited resources and the need for prioritization of severe and novel cases. Restrictive use of X-rays for clinical monitoring leads to higher percentage of novel X-ray findings without affecting patient quality of care or length of intubation [34].

 

Computerized Tomography 

Computerized tomography (CT) scans have served as the recommended imaging modality for screening suspected COVID-19 infection by the American College of Radiology (ARC) as of March 11, 2020 [35]. The ARC announced on March 22, 2020 that CT scans can be used to inform decisions on whether further serological testing is required for a suspected patient with COVID-19 in some medical practices [35]. The usage of CT scans as a screening tool for future testing depends on the availability of testing resources that can be used to filter patients based on physiological symptoms to a limited extent. In cases where a patient has been testing and confirmed positive with COVID-19, CT should be used sparingly for hospitalized patients to monitor the progression of pulmonary symptoms. 

The common features of chest CT examinations include multifocal bilateral ground-glass opacities, consolidation of interlobular vascular thickening and predominantly peripheral and subpleural lesions that can be located in multiple lobes of the lung parenchyma. Li and Xia report that chest CT studies reported the disease incidence rate of 74.5% for patients affected in all five lobes, 15.7% in both lower lobes, 5.9% in the right lower lobe, and 2.0% in the left upper lobe and right lower lobe [36]. Lesions were generally peripheral and subpleural in 96.1% of patients, with a decreased incidence of lesions near the bronchovascular bundles [36]. 

The incidence rate of ground glass opacities and consolidation are reported to be 86% and 29% respectively [37]. Patchy, round opacities were the most common morphological observation on chest CT scans, followed by linear and triangular opacities [38]. Notable non-specific observations include crazy paving, an observation of ground glass opacities with superimposed septal thickening between and within lobes in 70.6% of patients, and reverse halo sign, a central ground-glass opacities with a denser ring-shaped consolidation characteristic of alveolar septal inflammation in 3.9% of patients [36]. Cavitation, lymphadenopathy, nodules and pleural effusions are rare. 

As the disease progresses in severity, CT findings can reveal more sensitive information needed for clinical monitoring compared to common radiography modalities. Early stages of COVID-19 infection generally produce morphological observations of subsegmental patchy ground glass opacities, irregular consolidation of the lung interstitial and thickening of the vascular lumen observed on CT scans. Bernheim et al. reported the lack of sensitivity of current CT modalities with 56% out of 36 early-stage patients with normal CT examinations [37]. Peak progression severity shows dense multi-lobe consolidations and multiple ground glass opacities that contribute to crazy paving signs. In the remission stage, opacities and consolidation resolve and decrease in vascularity. CT can monitor morphological indicators in patients during the progression of COVID-19 and be used to support meaningful clinical evaluations and outcomes [38]. 

Generally, the findings of chest imaging modalities including CT scans are non-specific due to physiological overlap with other pulmonary infections such as H1N1, SARS and MERS. A recent study by Bai et al. suggests that radiologists in the United States and China were able to differentiate COVID-19 from similar viral pneumonia features with high specificity and moderate sensitivity. The moderate sensitivity suggests the possibility of false negatives in clinical diagnoses where a patient with COVID-19 may not be diagnosed as such. False negatives in diagnoses can arise from patients with early-stage disease progression or otherwise normal morphological features [40]. 

CT examinations play a crucial auxiliary role in the diagnosis of COVID-19 that can supplement the objective gold standard of etiological diagnosis by reverse transcriptase polymerase chain reaction (RT-PCR). In cases where RT-PCR may report a false negative, chest CT can be used to screen for epidemiologic and clinical indicators of COVID-19 in potentially ambiguous patient cases in need for additional auxiliary testing. In some case studies, the sensitivity of chest CT scans (98%) was reported to be greater than RT-PCR (71%) to a statistically significant degree (p<0.001), which further supports its auxiliary role in diagnosis alongside RT-PCR [41]. The moderate specificity of CT scans can support the high specificity of RT-PCR testing that markedly improves the overall predictive value of both approaches

 

Conclusion


All the imaging modalities have their advantages and disadvantages, and the selection of one imaging modality over another will ultimately be contingent upon the stage of COVID-19 development, body habitus, and inter-related medical conditions. The stage of COVID-19 development is intrinsically linked to symptomatic presentation. If the patient presented nonspecific symptoms, such as mild fever and coughing, then RT-PCR will be selected as pulmonary infiltrates, and other diagnostic signs do not develop during the early stages. If the patient presents advanced stages of COVID-19, like bi-lateral pneumonia, then diagnostic imaging would likely be ordered. The establishment of a diagnosis of COVID-19 by exclusively relying on ultrasound is seldom the case. This is the result of the low specificity of ultrasound and the operator-dependence, which necessitate further imaging through CT and X-ray.


Chest X-rays have the advantage of being portable and may reduce the use of PPE. Chest X-rays serve to establish a baseline and an excellent means to monitor the development of COVID-19. The findings of X-rays tend to mirror CT delineations such as hazy opacities and consolidations.


CT superior sensitivity makes it the ideal imaging modality. Diagnostic signs of COVID-19 on CT include ground-glass opacities with or without consolidations. However, these findings are nonspecific, and overreliance on CT will lead to false positives. Differential diagnosis consists of a multitude of infectious diseases.  A temporal multimodality approach that accounts for the severity of the symptoms, patient's medical conditions and body habitus ensures the patient is diagnosed promptly. Future studies should explore the merit of employing nuclear medicine techniques and the prospect of reliable serological screening. 

 

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