Dataset Information

Multidimensional clinical phenotyping of an adult cystic fibrosis patient population.

ABSTRACT:

Background

Cystic Fibrosis (CF) is a multi-systemic disease resulting from mutations in the Cystic Fibrosis Transmembrane Regulator (CFTR) gene and has major manifestations in the sino-pulmonary, and gastro-intestinal tracts. Clinical phenotypes were generated using 26 common clinical variables to generate classes that overlapped quantiles of lung function and were based on multiple aspects of CF systemic disease.

Methods

The variables included age, gender, CFTR mutations, FEV1% predicted, FVC% predicted, height, weight, Brasfield chest xray score, pancreatic sufficiency status and clinical microbiology results. Complete datasets were compiled on 211 subjects. Phenotypes were identified using a proximity matrix generated by the unsupervised Random Forests algorithm and subsequent clustering by the Partitioning around Medoids (PAM) algorithm. The final phenotypic classes were then characterized and compared to a similar dataset obtained three years earlier.

Findings

Clinical phenotypes were identified using a clustering strategy that generated four and five phenotypes. Each strategy identified 1) a low lung health scores phenotype, 2) a younger, well-nourished, male-dominated class, 3) various high lung health score phenotypes that varied in terms of age, gender and nutritional status. This multidimensional clinical phenotyping strategy identified classes with expected microbiology results and low risk clinical phenotypes with pancreatic sufficiency.

Interpretation

This study demonstrated regional adult CF clinical phenotypes using non-parametric, continuous, ordinal and categorical data with a minimal amount of subjective data to identify clinically relevant phenotypes. These studies identified the relative stability of the phenotypes, demonstrated specific phenotypes consistent with published findings and identified others needing further study.

SUBMITTER: Conrad DJ

PROVIDER: S-EPMC4378917 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:OBJECTIVE:The imaging evaluation of cystic fibrosis currently relies on chest radiography or computed tomography. Recently, digital chest tomosynthesis has been proposed as an alternative. We have developed a stationary digital chest tomosynthesis (s-DCT) system based on a carbon nanotube (CNT) linear x-ray source array. This system enables tomographic imaging without movement of the x-ray tube and allows for physiological gating. The goal of this study was to evaluate the feasibility of clinical CF imaging with the s-DCT system. MATERIALS AND METHODS:CF patients undergoing clinically indicated chest radiography were recruited for the study and imaged on the s-DCT system. Three board-certified radiologists reviewed both the CXR and s-DCT images for image quality relevant to CF. CF disease severity was assessed by Brasfield score on CXR and chest tomosynthesis score on s-DCT. Disease severity measures were also evaluated against subject pulmonary function tests. RESULTS:Fourteen patients underwent s-DCT imaging within 72 h of their chest radiograph imaging. Readers scored the visualization of proximal bronchi, small airways and vascular pattern higher on s-DCT than CXR. Correlation between the averaged Brasfield score and averaged tomosynthesis disease severity score for CF was -0.73, p = 0.0033. The CF disease severity score system for tomosynthesis had high correlation with FEV1 (r = -0.685) and FEF 25-75% (r = -0.719) as well as good correlation with FVC (r = -0.582). CONCLUSION:We demonstrate the potential of CNT x-ray-based s-DCT for use in the evaluation of cystic fibrosis disease status in the first clinical study of s-DCT. KEY POINTS:• Carbon nanotube-based linear array x-ray tomosynthesis systems have the potential to provide diagnostically relevant information for patients with cystic fibrosis without the need for a moving gantry. • Despite the short angular span in this prototype system, lung features such as the proximal bronchi, small airways and pulmonary vasculature have improved visualization on s-DCT compared with CXR. Further improvements are anticipated with longer linear x-ray array tubes. • Evaluation of disease severity in CF patients is possible with s-DCT, yielding improved visualization of important lung features and high correlation with pulmonary function tests at a relatively low dose.