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临床试验/NCT04320511
NCT04320511终止不适用

COVID CT, Beaumont Quantitative Lung Function Imaging to Characterize Patients With SARS-COV 2

William Beaumont Hospitals1 个研究点 分布在 1 个国家目标入组 15 人开始时间: 2020年6月24日最近更新:
适应症

试验速览

阶段
不适用
状态
终止
入组人数
15
试验地点
1
主要终点
Predictive association between CT-V, PBM score and disease progression

研究概览

简要总结

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.

详细描述

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.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者
否

入选标准

  • 未提供

排除标准

  • 未提供

结局指标

主要结局

Predictive association between CT-V, PBM score and disease progression

时间窗: 30 days

Disease progression will be characterized as requiring mechanical ventilator support, non-invasive positive pressure ventilation, high flow nasal cannula or mortality within 30 days.CT-V and PBM scores will be calculated at a voxel level from inhalation-exhalation CT scan. Several CT-V pulmonary function metrics, including the volume of identified "cold spots" (areas with decreased ventilation and perfusion), total ventilation and perfusion and radiographic fibrosis score will be calculated to assess regional ventilation/perfusion and compared to disease progression. The number of participants with correlation between these factors will be reported.

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Girish B. Nair, MD

Pulmonary Medicine Physician

William Beaumont Hospitals

研究点 (1)

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