Study rationale and design of the PEOPLHE trial.

PURPOSE: Lung cancer screening (LCS) by low-dose computed tomography (LDCT) demonstrated a 20-40% reduction in lung cancer mortality. National stakeholders and international scientific societies are increasingly endorsing LCS programs, but translating their benefits into practice is rather challenging. The "Model for Optimized Implementation of Early Lung Cancer Detection: Prospective Evaluation Of Preventive Lung HEalth" (PEOPLHE) is an Italian multicentric LCS program aiming at testing LCS feasibility and implementation within the national healthcare system. PEOPLHE is intended to assess (i) strategies to optimize LCS workflow, (ii) radiological quality assurance, and (iii) the need for dedicated resources, including smoking cessation facilities. METHODS: PEOPLHE aims to recruit 1.500 high-risk individuals across three tertiary general hospitals in three different Italian regions that provide comprehensive services to large populations to explore geographic, demographic, and socioeconomic diversities. Screening by LDCT will target current or former (quitting < 10 years) smokers (> 15 cigarettes/day for > 25 years, or > 10 cigarettes/day for > 30 years) aged 50-75 years. Lung nodules will be volumetric measured and classified by a modified PEOPLHE Lung-RADS 1.1 system. Current smokers will be offered smoking cessation support. CONCLUSION: The PEOPLHE program will provide information on strategies for screening enrollment and smoking cessation interventions; administrative, organizational, and radiological needs for performing a state-of-the-art LCS; collateral and incidental findings (both pulmonary and extrapulmonary), contributing to the LCS implementation within national healthcare systems.

Histogram-based analysis in progressive pulmonary fibrosis: relationships between pulmonary functional tests and HRCT indexes.

OBJECTIVES: To investigate relationships between histogram-based high-resolution CT (HRCT) indexes and pulmonary function tests (PFTs) in interstitial lung diseases. METHODS: Forty-nine patients having baseline and 1-year HRCT examinations and PFTs were investigated. Histogram-based HRCT indexes were calculated; strength of associations with PFTs was investigated using Pearson correlation. Patients were divided into progressive and non-progressive groups. HRCT indexes were compared between the two groups using the U-test; within each group, baseline and follow-up Wilcoxon analysis was performed. Receiver operating characteristic analysis was used for predicting disease progression. RESULTS: At baseline, moderate correlations were observed considering kurtosis and diffusion capacity of the lungs for carbon monoxide (DLCO) (r = 0.54) and skewness and DLCO (r = 0.559), whereas weak but significant correlations were observed between forced vital capacity and kurtosis (r = 0.368, p = 0.009) and forced vital capacity and skewness (r = 0.391, p = 0.005). Negative correlations were reported between HAA% and PFTs (from r = -0.418 up to r = -0.507). At follow-up correlations between quantitative indexes and PFTs were also moderate, except for high attenuation area (HAA)% -700 and DLCO (r = -0.397). In progressive subgroup, moderate and strong correlations were found between DLCO and HRCT indexes (r = 0.595 kurtosis, r = 0.672 skewness, r=-0. 598 HAA% -600 and r = -0.626 HAA% -700). At follow-up, we observed significant differences between the two groups for kurtosis (p = 0.029), HAA% -600 (p = 0.04) and HAA% -700 (p = 0.02). To predict progression, ROC analysis reported sensitivity of 90.9% and specificity of 51.9% using a threshold value of δ kurtosis <0.03. CONCLUSION: At one year, moderate correlations suggest that progression could be assessed through HRCT quantification. ADVANCES IN KNOWLEDGE: This study promotes histogram-based HRCT indexes in the assessment of progressive pulmonary fibrosis.