Development of a High-performance Dual-energy Chest Imaging System

Abstract

Rationale and Objectives-To assess the performance of a newly developed dual-energy (DE) chest radiography system in comparison to digital radiography (DR) in the detection and characterization of lung nodules.Materials and Methods-An experimental prototype has been developed for high-performance DE chest imaging with total dose equivalent to a single posterior-anterior DR image. Low-and highkVp projections were used to decompose DE soft-tissue and bone images. A cohort of 55 patients (31 male, 24 female, mean age 65.6 years) was drawn from an ongoing trial involving patients referred for percutaneous CT guided biopsy of suspicious lung nodules. DE and DR images were acquired of each patient prior to biopsy. Image quality was assessed by means of human observer tests involving 5 radiologists independently rating the detection and characterization of lung nodules on a 9-point scale. Results were analyzed in terms of the fraction of cases at or above a given rating, and statistical significance was evaluated from a Wilcoxon signed rank test. Performance was analyzed for all cases pooled as well as by stratification of nodule size, density, lung region, and chest thickness.Results-The studies demonstrate a significant performance advantage for DE imaging compared to DR (p<0.001) in the detection and characterization of lung nodules. DE imaging improved the detection of both small and large nodules and exhibited the most significant improvement in regions of the upper lobes, where overlying anatomical noise (ribs and clavicles) are believed to reduce nodule conspicuity in DR.Conclusions-DE imaging outperformed DR overall, particularly in the detection of small, solid nodules. DE imaging also performed better in regions dominated by anatomical noise such as the lung apices. The potential for improved nodule detection and characterization at radiation doses equivalent to DR is encouraging and could augment broader utilization of DE imaging. F studies will

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Comparison of model and human observer performance for detection and discrimination tasks using dual‐energy x‐ray images

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Automatic algorithm for determining bone and soft-tissue factors in dual-energy subtraction chest radiography

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