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

<p>Abstract</p> <p>Background</p> <p>We evaluated pulmonologists variability in the interpretation of Vibration response imaging (VRI) obtained from healthy subjects and patients hospitalized for community acquired pneumonia.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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).</p> <p>Conclusions</p> <p>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.</p

Sound transmission in the chest under surface excitation: an experimental and computational study with diagnostic applications

Chest physical examination often includes performing chest percussion, which involves introducing sound stimulus to the chest wall and detecting an audible change. This approach relies on observations that underlying acoustic transmission, coupling, and resonance patterns can be altered by chest structure changes due to pathologies. More accurate detection and quantification of these acoustic alterations may provide further useful diagnostic information. To elucidate the physical processes involved, a realistic computer model of sound transmission in the chest is helpful. In the present study, a computational model was developed and validated by comparing its predictions with results from animal and human experiments which involved applying acoustic excitation to the anterior chest while detecting skin vibrations at the posterior chest. To investigate the effect of pathology on sound transmission, the computational model was used to simulate the effects of pneumothorax on sounds introduced at the anterior chest and detected at the posterior. Model predictions and experimental results showed similar trends. The model also predicted wave patterns inside the chest, which may be used to assess results of elastography measurements. Future animal and human tests may expand the predictive power of the model to include acoustic behavior for a wider range of pulmonary conditions

Microarrays as research tools and diagnostic devices

Molecular diagnostics comprises a main analytical division in clinical laboratory diagnostics. The analysis of RNA or DNA helps to diagnose infectious diseases and identify genetic determined disorders or even cancer. Starting from mono-parametric tests within the last years, technologies have evolved that allow for the detection of many parameters in parallel, e.g., by using multiplex nucleic acid amplification techniques, microarrays, or next-generation sequencing technologies. The introduction of closed-tube systems as well as lab-on-a-chip devices further resulted in a higher automation degree with a reduced contamination risk. These applications complement or even stepwise replace classical methods in clinical microbiology like virus cultures, resistance determination, microscopic and metabolic analyses, as well as biochemical or immunohistochemical assays. In addition, novel diagnostic markers appear, like noncoding RNAs and miRNAs providing additional room for novel biomarkers. This article provides an overview of microarrays as diagnostics devices and research tools. Introduced in 1995 for transcription analysis, microarrays are used today to detect several different biomolecules like DNA, RNA, miRNA, and proteins among others. Mainly used in research, some microarrays also found their way to clinical dia- gnostics. Further, closed lab-on-a-chip devices that use DNA microarrays as detection tools are discussed, and additionally, an outlook toward applications of next-generation sequencing tools in diagnostics will be given