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COPD phenotypes platform. V. 1.1 beta
  
  

  
 A framework to support the assessment of COPD phenotypes in clinical practice
Chronic Obstructive Pulmonary Disease (COPD) is one of the leading cause of death worldwide and represents one of the major causes of chronic morbidity. Cigarette smoking is the most important risk factor for COPD. In these patients, the airflow limitation is caused by a mixture of airways disease and parenchyma destruction, the relative contribution of which varies from person to person.

The website copdphenotypes.com contains four applications dedicated to COPD phenotypes evaluation:


The application N. 1 was developed to dissect and quantify the relative contribution of functional gas-trapping (%fGT) and parenchymal destruction (emphysematous gas trapping) by using standard inspiratory and expiratory CT attenuation thresholds indexes (%LAA-950insp and %LAA-856exp). The output report provides also a classification plot to evaluate the prevalent phenotype according to the relative contribution of functional gas trapping and gas trapping due to parenchymal destruction. The app is a numeric implementation of a recent algorithm for the evaluation of functional gas trapping without using co-registration or other complex techniques.


The application N. 2 provides an estimation of the parenchymal destruction (%LAA-950insp index) using functional indexes acquired during standard PFTs and DLco%.
The output is a probability value which can be used as support to grade and to estimate the parenchymal destruction as quantified by %LLA-950_insp parameter obtained by densitometric CT analysis.


The application N. 3 provides an estimation of the parenchymal destruction (%LAA-950insp index) using functional indexes acquired during standard PFTs. This version does not implement the DLco% contribution and the output values are calculated by functional indexes only.
The output is a probability value which can be used as support to grade and to estimate the parenchymal destruction as quantified by %LLA-950_insp parameter obtained by densitometric CT analysis.


The application N. 4 implements a multivariate model reflecting the specific predominant mechanism of airflow limitation in COPD patients. The identification of the predominant COPD phenotype is performed analysing few findings derived from clinical and functional evaluation, as well as by standardized reading of conventional chest radiography. This approach may offer the opportunity to characterize this heterogeneous disease beyond its unifying spirometric definition (FEV1 %, FEV1/FVC).


The application N. 5 is an optimized re-engineered implementation of two recently published models for the estimation of gas trapping percentage as measured during expiratory CT scan. The two CT derived indexes %LAA-856exp and %LAA-910exp are estimated by PFTs functional variables.

All these methods was tested and validated analysing the reference data sets provided by the University of Florence - CLIP COPD Project.

Please contact us for detailed info and accounts.



References:

- Pistolesi, Massimo; Camiciottoli, Gianna; Paoletti, Matteo; Marmai, Cecilia; Lavorini, Federico; Meoni, Eleonora; Marchesi, Carlo; Giuntini, Carlo; Identification of a predominant COPD phenotype in clinical practice, Respiratory medicine,102, 3, 367-376, 2008, Elsevier

- Paoletti, Matteo; Camiciottoli, Gianna; Meoni, Eleonora; Bigazzi, Francesca; Cestelli, Lucia; Pistolesi, Massimo; Marchesi, Carlo; Explorative data analysis techniques and unsupervised clustering methods to support clinical assessment of Chronic Obstructive Pulmonary Disease (COPD) phenotypes, Journal of biomedical informatics, 42, 6, 1013-1021, 2009, Elsevier
 
- Paoletti, Matteo; Cestelli, Lucia; Bigazzi, Francesca; Camiciottoli, Gianna; Pistolesi, Massimo; Chronic obstructive pulmonary disease: pulmonary function and CT lung attenuation do not show linear correlation, Radiology, 276, 2, 571-578, 2015, Radiological Society of North America

- Camiciottoli, Gianna; Bigazzi, Francesca; Paoletti, Matteo; Cestelli, Lucia; Lavorini, Federico; Pistolesi, Massimo; Pulmonary function and sputum characteristics predict computed tomography phenotype and severity of COPD, European Respiratory Journal, 42, 3, 626-635, 2013, European Respiratory Society





 

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