Pulmonary Hypertension Clinical Trial
— DECTPHOfficial title:
Quantitative Dual Energy Computed Tomography in Pulmonary Hypertension "DECTPH".
Verified date | March 2021 |
Source | University Hospital, Bordeaux |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
Pathophysiological mechanisms leading to pulmonary hypertension (PH) are complex. Quantitative computed tomography (QCT) can help us to study morphological alterations in patients with PH. These CT morphometrics are useful to predict the degree of PH severity at least in PH secondary to chronic obstructive pulmonary disease (COPD). We hypothesized that assessing lung perfusion using dual energy CT (DECT) can refine our knowledge on PH pathophysiology and help to predict PH severity irrespective of its etiology
Status | Completed |
Enrollment | 60 |
Est. completion date | January 15, 2021 |
Est. primary completion date | January 15, 2021 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years to 65 Years |
Eligibility | Inclusion Criteria: - adults (18 years old and over) - Patient with PH diagnosed at right heart catheterization - Availability of a dual energy chest CT scans with contrast injection performed as part of standard patient workup - Patient's consent or authorisation for data processing. Exclusion Criteria: - patient without any chest CT scan available or planned in the patient workup |
Country | Name | City | State |
---|---|---|---|
France | CHU Bordeaux | Bordeaux |
Lead Sponsor | Collaborator |
---|---|
University Hospital, Bordeaux |
France,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | stence and the severity of PH | Prediction of the existence and the severity of PH using a qCT score combining morphometric parameters (WT(mm), CSA(mm2) and/or VSA(mm3)) and functional parameters (PVB(HU)) | Baseline | |
Secondary | kappa coefficient | Good kappa coefficient (>0.6) for topographic evaluation of pulmonary artery segmentation | baseline | |
Secondary | Dice coefficient | Good Dice coefficient (>0.8) for overlap and similarity between manual (ground truth) and automatic segmentations | Baseline |
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