Imaging Lung Sound Behavior with Vibration Response Imaging
| Imaging Lung Sound Behavior with Vibration Response Imaging | |
|---|---|
| Purpose | physiologic vibration generated during the breathing process |
In medicine, Imaging Lung Sound Behavior with Vibration Response Imaging (VRI) is a novelty computer-based technology that takes the concept of the stethoscope to a more progressive level. Since the invention of the stethoscope by René-Théophile-Hyacinthe Laennec France in 1816, physicians have been utilizing lung sounds to diagnose various chest conditions. Today auscultation provides physicians with extensive information on the examination of the patient. The skills of the examiner however, vary, as seen in a clinical study that was conducted on the diagnosis of pneumonia in 2004.[1]
The technology is based on the physiologic vibration generated during the breathing process when flow of air distributing through the bronchial tree creates vibration of the bronchial tree walls and the lung parenchyma itself. Emitted vibration energy propagating through the lung parenchyma and the chest wall reaches the body surface where is captured and recorded by a set of acoustic sensors. The sensors are positioned over the lung areas on the back that allows for the simultaneous reception of these signals from both lungs. These signals are then transformed by a complex algorithm to display the spatial changes in energy intensity during the breathing cycle. The intensity changes follow changes of airflow through the breathing cycle - i.e.: flow increases and decreases during inspiration and expiration.[2] The VRI technology represents these changes as a grey scale-based dynamic image. The darker the higher the vibration intensity and the lighter the lower the vibration intensity is.[3]
VRI and Lung Sound Behavior
[edit]The foremost information that the VRI provides on vibration energy, is how lung sounds behave and function during inspiration and expiration, which also includes individual breathing intensity (or vibration energy) graphs for each lung along the time period of 12 seconds. The distribution pattern of normal lung vibration energy for healthy individuals evolves centrally (presumably reflecting early airflow distribution in central large airways) and develops centrifugally in a simultaneous fashion for left and right lungs. Following peak inspiration, there is centripetal regression of vibration energy toward the end of inspiration. The same pattern is repeated during expiration phase accordingly. The peak of inspiratory vibration energy is higher than expiratory energy peak due to inspiration being more active process compared to expiration. At the Maximum Energy Frame (MEF) (a frame on the dynamic image representing the maximum distribution of vibration energy at the peak of inspiration), the right and left zones has a similar shape, area and image intensity, with a tendency, however, to greater intensity on the left.[4] The vibration energy graph is a graphical representation of the behavioral pattern for both lungs and each lung individually. For a healthy individual with normal lungs, the graph has a consistent pattern that is repeated throughout the 12 second breathing period. The graph increases to the peak at the MEF frame on inspiration, and then decreasing to expiration. During expiration the graph pattern looks similar to that of inspiration, however at a lower intensity. When comparing right to left intensity graphs, the graphs are synchronized and peak at the same time and are almost at the same intensity level.[citation needed]
Lung ailments such as Chronic Obstructive Pulmonary Disease (COPD) cause the narrowing of airways in the lungs, limiting airflow and causing shortness of breath. Due to the limitation of airflow the VRI breathing pattern differs from that of a healthy individual. The patterns show asynchrony between lungs; with peaks in vibration energy difference. Because of this asynchrony, the contours of the lung periphery are not smooth, but have a "bumpy-lumpy" or "disco" appearance.[5] The vibration energy graph displays an inconsistent pattern and it is difficult to delineate inspiration from expiration. When comparing the right to the left lung the energy graphs peak at different times, and differs at the intensity level.[citation needed]
Conclusion
[edit]Studies have shown that normal lung sounds have distinctive characteristics that can be differentiated from abnormal lung sounds,[6] thus supporting the potential clinical value of acoustic lung imaging. By using the VRI that simultaneously records the vibration energy from 40 points over 12 seconds and presents all of the derived information in a single image the physician can be less dependent on memory. Another advantage of using this method is the ability to store and later compare the data to subsequent recordings.[7] Finally, the VRI examination is harmless, doesn't emit any energy, and is non-invasive and radiation-free, unlike potentially harmful radiologic studies.[8] It is important to note that even though a lot of literature has been published on the VRI method, it is still fairly new and as such has its limitations. Clinical value is limited to afore mentioned studies, and crucial elements such a complete patient work-up, that includes extensive patient history, medication and present presentation of symptoms are invaluable to the decision making process as to how any physician will proceed with the patients' treatment.[citation needed]
See also
[edit]References
[edit]- ^ Murphy RL, Vyshedskiy A, Power-Charnitsky VA, Bana Dhirendra S, Marinelli Patricia M, Wong-Tse A, Paciej R (2004). "Automated lung sound analysis in patients with pneumonia". Respiratory Care. 49 (12): 1490–7. PMID 15571639. Archived from the original on 23 July 2012.
- ^ Yosef M, Langer R, Lev S, Glickman YA (17 September 2009). "Effect of airflow rate on vibration response imaging in normal lungs". Open Respir Med J. 3: 116–22. doi:10.2174/1874306400903010116. PMC 2761668. PMID 19834576.
- ^ Becker, Heinrich D. (2009). "Vibration response imaging--finally a real stethoscope". Respiration. 77 (2): 236–239. doi:10.1159/000181147. PMID 19052444. S2CID 35193741.
- ^ Maher TM, Gat M, Allen D, Devaraj A, Wells AU, Geddes DM (2008). "Reproducibility of dynamically represented acoustic lung images from healthy individuals". Thorax. 63 (6): 542–8. doi:10.1136/thx.2007.086405. PMC 2571960. PMID 18024534.
- ^ Wang, Zhen; Jean, Smith; Bartter, Thaddeus (2009). "Lung Sound Analysis in the Diagnosis of Obstructive Airway Disease". Respiration. 77 (2): 134–138. doi:10.1159/000178023. PMID 19033680. S2CID 20555396.
- ^ Kompis, M; Pasterkamp, H; Wodicka, GR (2001). "Acoustic imaging of the human chest". Chest. 120 (4): 1309–21. doi:10.1378/chest.120.4.1309. PMID 11591576.
- ^ Mor R, Kushnir I, Meyer JJ, Ekstein J, Ben-Dov I (2007). "Breath Sound Distribution Images of Patients With Pneumonia and Pleural Effusion" (PDF). Respir. Care. 52 (12): 1753–60. PMID 18028567. Archived from the original (PDF) on 15 July 2011. Retrieved 27 December 2009.
- ^ Mauri D, Kamposioras K, Proiskos A, Xilomenos A, Peponi C, Dambrosio M, Zacharias G, Koukourakis G, Pentheroudakis G, Pavlidis N (2006). "Old Habits Die Hard: Chest Radiography for Screening Purposes in Primary Care". The American Journal of Managed Care. 12 (11): 650–656. PMID 17090221.