© Hong Kong Academy of Medicine. CC BY-NC-ND 4.0
EDITORIAL
Radiology and COVID-19
Jason CX Chan, FHKCR, FHKAM (Radiology)1; KY Kwok, FHKCR, FHKAM (Radiology)1;
Johnny KF Ma, FHKCR, FHKAM (Radiology)2; YC Wong, FHKCR, FHKAM (Radiology)1
1 Department of Radiology, Tuen Mun Hospital, Hong Kong
2 Department of Radiology, Princess Margaret Hospital, Hong Kong
Corresponding author: Dr Jason CX Chan (jasonchancx@gmail.com)
Within a few short months, the coronavirus disease
2019 (COVID-19) pandemic has rapidly spread
across the globe, affecting at least 10.5 million people
in more than 210 countries and territories, with over
500 000 deaths reported.1 As a result of the collective
effort of the medical community and the general
public, the number of confirmed cases in Hong Kong
and the local mortality rate were kept at a low level
relative to many other parts of the world.
Owing to the rapid response from the
research community during the pandemic, we have
increasing evidence and our understanding of the
disease is improving. Accurate diagnosis relies on
epidemiology, real-time reverse transcription–polymerase chain reaction (RT-PCR) assays, and
imaging findings. For confirming severe acute
respiratory syndrome coronavirus 2 infection, which
is the cause of COVID-19, RT-PCR is regarded as
the gold standard. However, its limited availability,
long turnaround time, and variable diagnostic
performance have hindered the swift detection and
containment of COVID-19 patients necessary to
mitigate the exponential spread of the pandemic.
Therefore, radiology has a crucial role in diagnosing
patients suspected to have COVID-19.
Chest radiograph is inexpensive, highly
accessible, easy to operate, and portable. An initial
chest radiograph helps not only to detect features
of pneumonia but also to provide an alternative
diagnosis. Medical triage is recommended for
patients who present with moderate to severe
clinical features in places with a high prevalence of
COVID-19.2 Mobile radiography systems in isolation
wards or intensive care unit facilitate monitoring of
the disease severity and progression without the
need for patient transportation, which increases
the risk of virus transmission within the hospital.3
Common chest radiograph findings of COVID-19
pneumonia include ground-glass opacities and
consolidations, more often in bilateral, peripheral,
and lower zone distributions.4 5 Lymphadenopathy
or pleural effusion is rare. Nevertheless, a plain
chest radiograph cannot exclude the diagnosis
of COVID-19 because its sensitivity depends on
the time of imaging and severity of pulmonary
involvement.
Chest computed tomography (CT) provides superior delineation of disease involvement with
high sensitivity of up to 98%.6 During the early
outbreak of COVID-19 in Hubei Province, China,
when RT-PCR assays and isolation beds were
scarce, CT was used together with epidemiological
criteria to provide screening for or diagnosis of
COVID-19. The early experience in Hong Kong
also indicated that CT was useful in achieving early
diagnosis, especially in patients with initial negative
RT-PCR results.7 8 However, the imaging features
of COVID-19 overlap with other viral pneumonia
such as influenza and even those of non-infectious
states such as drug reactions. The framing of such a
pivotal role of imaging in disease diagnosis is likely
due to the high pre-test probability.9 Support for
CT as a screening or diagnostic test for COVID-19
has now been challenged, as CT provides no
additional clinical benefit but might lead to a false
sense of security, because up to 20% of symptomatic
patients have negative CT scan results.10 Patients
with a high index of suspicion should be isolated
pending confirmation with RT-PCR tests, or until
quarantine has lapsed. The result of a chest CT
does not alter patient management. Safe usage of
CT scanners to image COVID-19 patients is also
logistically challenging and can overwhelm the
available resources. Even with proper cleaning
protocols, CT scanners are still at risk of becoming
vectors of infection to vulnerable patients and staff.
Therefore, multiple societies recommend against the
use of chest CT for screening and diagnosis of the
disease.11
The pulmonary abnormalities of COVID-19
pneumonia in chest CT scans echo but predate
those in chest radiographs. Typical findings include
bilateral distribution of ground-glass opacities in
the peripheral and posterior lungs.12 As the disease
progresses, the ground-glass opacities can increase
in size as well as extent of involvement, with
additional crazy-paving patterns or consolidations
observed. It is atypical to see pleural effusion,
multiple tiny pulmonary nodules, or mediastinal
lymphadenopathy.9 However, the presence of
consolidations with air bronchogram, central lung
involvement, and pleural effusion on initial chest CT
are more commonly seen in severe patients who need
intensive care.13 The abnormalities generally peak around 14 days after the disease onset, with some
patients developing bilateral and diffuse infiltration
of all segments of the lungs and thus manifesting
as “white lung”.14 After that, healing of pulmonary
inflammation is observed, with gradual replacement
of cellular components by scar tissues shown as
fibrous stripes.15 Currently, the long-term pulmonary
sequalae of the disease remain unclear and further
research is needed to explore the relationship
between fibrosis and patients’ prognosis.
Artificial intelligence algorithms have been
employed to aid radiologists to interpret images
more rapidly and accurately in this pandemic. An
early study showed that artificial intelligence could
augment radiologists’ performance in distinguishing
COVID-19 from pneumonia of other aetiologies on
chest CT, yielding higher accuracy (90%), sensitivity
(88%), and specificity (96%).16 By analysing CT
radiomics and clinical and demographic factors,
researchers have developed machine learning
models which can predict the likelihood of
COVID-19 patients requiring mechanical ventilation
with a promising accuracy up to 75%.17 However, the
only way to combat and contain this disease is to
establish a fast, sensitive, and cost-effective triaging
tool. A recently developed nowcast deep learning
model might provide a solution that can identify
COVID-19 on chest radiographs more accurately
than radiologists, with an area under the receiver
operating characteristic curve of 0.81, sensitivity of
84.7%, and specificity of 71.6%.18
The COVID-19 pandemic has had a profound
impact on radiology practices across the world.
Many radiology units have reported a decline in
patient numbers of 50% to 70%19 due to governmental
limits on patient movement and curtailment of
non-urgent imaging, as well as patient cancellations
and no-shows due to fear of viral exposure. In the
aftermath of the outbreak, radiology departments
must take steps to restore public confidence in
their ability to conduct radiological investigations
safely. Logistic arrangements should be made to
decrease the waiting room exposure and maximise
social distancing in waiting areas. Each department
also needs to create strategic plans to redistribute
deferred cases by increasing the capacity of imaging
services and re-evaluating all cases to allow efficient
prioritisation across all specialties and referrers.
This system should be based on assessing urgent and
emergent imaging, time-critical imaging, imaging
of known versus potential disease, and screening
programmes.20 As the crisis recedes, proactive
and careful management should allow radiology
departments to actively manage the recovery process
that will ultimately ensure the safety of patients
and staff and enable radiologists to respond
accordingly as the uncertainty of the coming months
unfolds.
Author contributions
All authors contributed to the editorial, approved the final
version for publication, and take responsibility for its accuracy
and integrity.
Conflicts of interest
The authors have disclosed no conflicts of interest.
Funding/support
This editorial received no specific grant from any funding
agency in the public, commercial, or not-for-profit sectors.
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