Radiologists find chest X-rays highly predictive of COVID-19
Date:
September 3, 2020
Source:
Louisiana State University Health Sciences Center
Summary:
Radiologists investigated the usefulness of chest X-rays in
COVID-19 and found they could aid in a rapid diagnosis of the
disease, especially in areas with limited testing capacity or
delayed test results.
FULL STORY ==========================================================================
A team of LSU Health New Orleans radiologists investigated the usefulness
of chest x-rays in COVID-19 and found they could aid in a rapid diagnosis
of the disease, especially in areas with limited testing capacity
or delayed test results. Their findings are published in Radiology: Cardiothoracic Imaging, available here.
==========================================================================
"In mid to late March of this year, when COVID-19 cases were spiking
in New Orleans, we recognized an unusual pattern on chest x-rays that
seemed to correlate with COVID positivity," notes David Smith, MD,
Associate Professor of Clinical Radiology at LSU Health New Orleans
School of Medicine. The radiologists conducted a retrospective
study of nearly 400 persons under investigation (PUI) for COVID-19
in New Orleans. They reviewed the patients' chest X-rays along with
concurrent reverse-transcription polymerase chain reaction (RT-PCR)
virus tests. Using well-documented COVID-19 imaging patterns, two
experienced radiologists categorized each chest x-ray as characteristic, nonspecific, or negative in appearance for COVID-19. The radiologists
found a characteristic chest x-ray appearance is highly specific (96.6%)
and has a high positive predictive value of 83.8% for SARS-CoV-2 infection
in the setting of pandemic.
"The presence of patchy and/or confluent, band-like ground glass opacity
or consolidation in a peripheral and mid-to-lower lung zone distribution
on a chest radiograph is highly suggestive of SARS-CoV-2 infection and
should be used in conjunction with clinical judgment to make a diagnosis,"
says Bradley Spieler MD, Associate Professor of Diagnostic Radiology and
Vice Chairman of Research in the Department of Radiology at LSU Health
New Orleans School of Medicine.
"The chest radiograph, while low in sensitivity, can indicate COVID-19
in patients whose radiographs exhibit characteristic COVID-19 findings,
when used in concert with clinical factors," adds John-Paul Grenier, MD,
an LSU Health New Orleans Radiology Resident. "While not a substitute
for RT-PCR virus tests or Chest CT, radiographs could provide a rapid, cost-effective diagnosis of COVID-19 in a subset of infected patients
during the COVID-19 pandemic. The utility of this technique is described
in the context of known disadvantages of RT-PCR, considered the gold
standard in COVID-19 diagnosis, and Chest CT, which is currently not recommended for COVID-19 diagnosis. " "This discovery is useful to aid
in diagnosis in the setting of pandemic spread of COVID-19, especially
when adequate testing is lacking," says Dr. Smith.
"We believe this work has great potential to aid all health care providers
in the fight against COVID-19," concludes Dr. Spieler.
Catherine Batte, MS, from the Department of Physics and Astronomy at
Louisiana State University, also collaborated on the study.
"The COVID-19 pandemic has been especially tough on the people of New
Orleans," declares Dr. Grenier. "We hope that the insights we've gained
from studying this disease in our community can be used to help other communities across the globe."
========================================================================== Story Source: Materials provided by Louisiana_State_University_Health_Sciences_Center. Note: Content may be
edited for style and length.
========================================================================== Journal Reference:
1. David L. Smith, John-Paul Grenier, Catherine Batte, Bradley
Spieler. A
Characteristic Chest Radiographic Pattern in the Setting of COVID-19
Pandemic. Radiology: Cardiothoracic Imaging, 2020; 2 (5): e200280
DOI: 10.1148/ryct.2020200280 ==========================================================================
Link to news story:
https://www.sciencedaily.com/releases/2020/09/200903123254.htm
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