Clinical Trial Details
— Status: Terminated
Administrative data
NCT number |
NCT04320511 |
Other study ID # |
2020-087 |
Secondary ID |
|
Status |
Terminated |
Phase |
|
First received |
|
Last updated |
|
Start date |
June 24, 2020 |
Est. completion date |
May 14, 2021 |
Study information
Verified date |
August 2021 |
Source |
William Beaumont Hospitals |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
The goal of this study is to evaluate if CT (Computerized Tomography) can effectively and
accurately predict disease progression in patients with SARS-CoV-2 (severe acute respiratory
syndrome coronavirus 2). You may be eligible if you have been diagnosed with SARS-CoV-2, are
an inpatient at Beaumont Hospital-Royal Oak and meet eligibility criteria. After consent and
determination of eligibility, enrolled patients will have a CT scanning session. After the CT
scan, patients are followed for 30 days by reviewing their medical records and by phone after
discharge from hospital.
Description:
Beaumont Quantitative CT lung function imaging (BQLFI) uses mathematical modeling to
determine regional differences in ventilation (CT-V) and pulmonary blood mass (PBM) from a
pair of inspiration-expiration CT scans or time-resolved four-dimensional (4D) CT scans. CT-V
and PBM images provide surrogates for pulmonary ventilation and perfusion, respectively, in
the form of detailed functional maps. CT-V and PBM therefore allow us to distinguish healthy
from abnormal lung. Moreover, the technique generalizes to recover lung compliance imaging
(LCI) when the CT is acquired at different pressure settings, in order to characterize lung
stiffness. PBM and CT-V can detect parenchymal lung function changes at a voxel level and can
be used to 1) assess disease progression in SARS-CoV-2, 2) detect treatment effects, and 3)
identify early changes in high-risk patients prior to their development of disease. BQLFI
affords the opportunity to provide imaging biomarkers that enable the early diagnosis of lung
injury, which in turn cause impairment in gas exchange at the level of alveolar capillary
interface. Currently, there are no available imaging biomarkers to predict patients at risk
of progression or identify those at risk of developing severe disease with SARS-CoV-2. Our
proposed study will validate a novel methodology, based on state-of-the-art CT-V and PBM
imaging that can accurately measure regional ventilation and perfusion, as a means for
improving surveillance, diagnosis, and prognostication of patients with SARS-CoV-2. This is a
prospective, pilot study of 25 adult patients with SARS-CoV-2, who have mild to moderate
disease, defined as positive PCR screen and not requiring invasive mechanical ventilator
support or noninvasive ventilation or high flow nasal cannula. Participants will provide
informed consent and eligibility will be confirmed. Demographics and medical history will be
obtained. Participants will undergo one inspiration-expiration CT. Outcomes and adverse
events will be assessed over 30 day using chart review or phone interview.