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Vibration Response Imaging: evaluation of rater agreement in healthy subjects and subjects with pneumonia

DOI: 10.1186/1471-2342-10-6

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Abstract:

The present is a prospective study conducted in a tertiary university hospital. Twenty healthy subjects and twenty three pneumonia cases were included in this study. Six pulmonologists blindly analyzed images of normal subjects and pneumonia cases and evaluated different aspects of VRI images related to the quality of data aquisition, synchronization of the progression of breath sound distribution and agreement between the maximal energy frame (MEF) of VRI (which is the maximal geographical area of lung vibrations produced at maximal inspiration) and chest radiography. For qualitative assessment of VRI images, the raters' evaluations were analyzed by degree of consistency and agreement.The average value for overall identical evaluations of twelve features of the VRI image evaluation, ranged from 87% to 95% per rater (94% to 97% in control cases and from 79% to 93% per rater in pneumonia cases). Inter-rater median (IQR) agreement was 91% (82-96). The level of agreement according to VRI feature evaluated was in most cases over 80%; intra-class correlation (ICC) obtained by using a model of subject/rater for the averaged features was overall 0.86 (0.92 in normal and 0.73 in pneumonia cases).Our findings suggest good agreement in the interpretation of VRI data between different raters. In this respect, VRI might be helpful as a radiation free diagnostic tool for the management of pneumonia.Imaging methods are critical for the diagnosis and management of lung diseases. However, some methods, such as Computed Tomography and radiography, are limited by the fact that they cannot be carried out effectively at the bedside and most importantly that they involve radiation. Other methods, such as ultrasound, use acoustic signals and they do not involve radiation but their diagnostic value meets limitations due to the acoustic damping of the lung parenchyma [1]. In this respect, novel imaging methods based on computer-assisted mapping of lung sounds not complicated by radiation,

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