Beaumont Quantitative Lung Function Imaging to Characterize Patients With SARS-COV 2
Purpose
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.
Conditions
- SARS-COV2
- Severe Acute Respiratory Syndrome
- COVID-19
Eligibility
- Eligible Ages
- Over 18 Years
- Eligible Genders
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- Adults >18 years of age 2. Written Informed consent 3. A confirmed diagnosis of SARS-CoV-2 with mild to moderate disease, on room air or supplemental oxygen not more than 12L 4. Concomitant medications for the treatment are allowed
Exclusion Criteria
- Patients <18 years 2. Pregnant females 3. Invasive ventilator support or non-invasive ventilator support including high flow nasal cannula 4. COPD or Congestive Heart Failure patients requiring home oxygen 5. History of lung cancer and radiation to lung or had prior radiation to the chest
Study Design
- Phase
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Prospective
Arm Groups
Arm | Description | Assigned Intervention |
---|---|---|
Patients with SARS-COV 2 | Patients with SARS-COV 2 undergoing CT-V |
|
Recruiting Locations
More Details
- NCT ID
- NCT04320511
- Status
- Terminated
- Sponsor
- William Beaumont Hospitals
Detailed 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.