Analysis With Clusters of QUAntitative Tomodensitometric Vascular, bronchIal and Parenchymal Pulmonary Parameters for COPD Patients (ACQUAVIP)

University Hospital of Bordeaux

Status: Unknown

Conditions: Chronic Obstructive Pulmonary Disease

Study type: Observational

Funder types: Other

Identifiers

NCT03337854

2017/44

Details and patient eligibility

About

Chronic obstructive pulmonary disease (COPD) is caused by tobacco consumption. The goal is to characterize on clinical and radiological data, using computed tomography, this illness in order to improve diagnostic and be able to evaluate the prognostic of each patient.

Full description

Chronic obstructive pulmonary disease (COPD) is characterized by emphysematous destruction of pulmonary parenchyma, airway obstruction that participate in chronic temporary obstruction of airways. COPD has multiple clinical presentations that define phenotypes but doesn't take into account those anatomo-pathologic modifications. Moreover, the prognostic interest of those structural alteration is unknown. Until now, only PFT allowed to define the severity of the disease, whereas multiple others tools may be useful, such as, symptoms scores, exacerbation frequencies, denutrition. Those structural alterations are available using computed tomography (CT), that may also have an interest in prognostic or in treatment follow- up.

CT is widely used in clinical practice for COPD patients at basal state and in exacerbations. Quantitative CT is able to combine acquisition of objective and reproductible informations on parenchymal destruction (emphysema), bronchial wall remodeling, and pulmonary vessels alteration. The investigators' team developed software tools to determine quantitative structural modifications of airways, emphysema and small pulmonary vessels1,2.

The team has been able to build a score "Paw score" combining PaO2 with CT parameters of bronchial wall thickness and small pulmonary vessels percentage2. This score allowed to predict the presence of severe pulmonary hypertension in patients with COPD. Pulmonary hypertension is a complication of COPD that increase morbi-mortality.

The hypothesis is that morphological quantitative analysis combined with structural alterations of airways has a prognostic interest.

The main goal is to determine morphological phenotypes of COPD using a cluster analysis combining emphysema, bronchial wall thickness and pulmonary vessels.

The other main goal is to predict evolution of COPD patients based on clinical outcomes (exacerbations frequency, mortality, mMRC, SGQLQ) and lung function testing (decline in FEV-1 TLCO, PaO2).

The team also wants to analyze clinical data of survival, exacerbation and symptoms in following years of the CT of each cluster in historic-prospective way.

The secondary goals are to describe clinical, functional and biological clusters. Analyse of correlations will be studied. Moreover, we will investigate the interest of the "Paw score" as a prognostic marker and as a correlated parameter.

This is a retrospective study. We want to take information from the year before CT, to the year after CT. At the date of the consultation concomitant with CT we want to know all the clinical, functional and biological data of each patient.

Enrollment: 270 estimated patients

Sex: All

Ages: 40+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Age ≥ 40 years

• Inhalated toxic exposure:

  • Tobacco exposure (present or past, over 10 pack years)
  • And/or professional exposure to a toxic

• Obstructive syndrome with a FEV1/FVC ≤ 0.7 after inhalation of a bronchodilatator and measured at stable state (without exacerbation)

• Computed tomography performed without injection contrast during common care

Exclusion criteria

• Patients with an exacerbation within 6 weeks before computed tomography
• Artefacts movements on computed tomography incompatible with quantitative analyse
• Broncho-pulmonary cancer (old or present)
• History of pulmonary surgery
• No follow-up for 1 year after scan
• Opposition of the patient to the use of his data (clinical, functional and imaging).