Abstract
The frequency characteristics of lung sounds have great significance for noninvasive diagnosis of respiratory diseases. The rales in the lower respiratory tract region that can provide rich information about symptoms of respiratory diseases are not clear. In this paper, a three-dimensional idealized bifurcated lower respiratory tract geometric model, which contains 3rd to 13th generation (G3–G13) bronchi is constructed, where \({\text{Re}}\sim 10^{1} - 10^{3}\), and then the large eddy simulation and volume of fluid are used to study the fluid flow characteristics. Ffowcs Williams and Hawkings model are subsequently used to study the frequency characteristics of rale of different generations of bronchi. The results showed that bronchial blockage and sputum movement will enhance the turbulence intensity and vortex shedding intensity of flow. The dominant frequency and highest value of sound pressure level (SPL) of rhonchi/moist crackles decrease with the increase of bronchial generation. The change rates of dominant frequency of rhonchi / moist crackles in adjacent generations were 5.0 ± 0.1 ~ 9.1 ± 0.2% and 3.1 ± 0.1 ~ 11.9 ± 0.3%, respectively, which is concentrated in 290 ~ 420 Hz and 200 ~ 300 Hz, respectively. The change rates of SPL of rhonchi/moist crackles were 8.8 ± 0.1 ~ 15.7 ± 0.1% and 7.1 ± 0.1 ~ 19.5 ± 0.2%, respectively, which is concentrated in 28 ~ 50 dB and 16 ~ 32 dB, respectively. In the same generation of bronchus (e.g., G8, G9) with the same degree of initial blockage, the dominant frequency and SPL of moist crackles can be 3.7 ± 0.2% and 4.5 ± 0.3% slightly higher than that of rhonchi, respectively. This research is conducive to the establishment of a rapid and accurate noninvasive diagnosis system for respiratory diseases.
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References
Augusto Z, Raffaele F, Enrico B, Luciano C, Carlo A, Vittorio G (1991) Snoring and risk of cardiovascular disease. Int J Cardiol 32(3):347–351. https://doi.org/10.1016/0167-5273(91)90297-3
Abbasi Z, Bozorgmehry Boozarjomehry R (2021) Various reduced-order surrogate models for fluid flow and mass transfer in human bronchial tree. Biomech Model Mechanobiol 20:2203–2226. https://doi.org/10.1007/s10237-021-01502-z
Alexandre F, Molinier V, Hayot M, Chevance G, Moullec G, Varray A (2022) Association between long-term oxygen therapy provided outside the guidelines and mortality in patients with copd. BMJ Open 12(1):e049115. https://doi.org/10.1136/bmjopen-2021-049115
Au YK, Muqeem T, Fauveau VJ, Cardenas JA, Geris BS, Hassen GW, Glass M (2022) Continuous monitoring versus intermittent auscultation of wheezes in patients presenting with acute repiratory distress. J Emerg Med 63(4):582–591. https://doi.org/10.1016/j.jemermed.2022.07.001
Chen X, Shao J, Long Y, Que C, Zhang J, Fang J (2014) Identification of Velcro rales based on Hilbert–Huang transform. Physica A 401:34–44. https://doi.org/10.1016/j.physa.2014.01.018
Deng Q, Ou C, Chen J, Xiang Y (2018) Particle deposition in tracheobronchial airways of an infant, child and adult. Sci Total Environ 612:339–346. https://doi.org/10.1016/j.scitotenv.2017.08.240
Deng Q, Ou C, Shen YM, Xiang Y, Miao Y, Li Y (2019) Health effects of physical activity as predicted by particle deposition in the human respiratory tract. Sci Total Environ 657:819–826. https://doi.org/10.1016/j.scitotenv.2018.12.067
Emmanouilidou D, McCollum ED, Park DE, Elhilali M (2015) Adaptive noise suppression of pediatric lung auscultations with real applications to noisy clinical settings in developing countries. IEEE Trans Bio-Med Eng 62(9):2279–2288. https://doi.org/10.1109/TBME.2015.2422698
Fujioka H, Halpern D, Gaver DP (2013) A model of surfactant-induced surface tension effects on the parenchymal tethering of pulmonary airways. J Biomech 46:319–328. https://doi.org/10.1016/j.jbiomech.2012.11.031
Hardin JC, Pope DS (2015) Sound generation by a stenosis in a pipe. AIAA J 30(2):312–317. https://doi.org/10.2514/6.1990-3919
İçer S, Gengeç Ş (2014) Classification and analysis of non-stationary characteristics of crackle and rhonchus lung adventitious sounds. Digit Signal Process 28:18–27. https://doi.org/10.1016/j.dsp.2014.02.001
Jering K, Claggett B, Redfield MM, Shah SJ, Anand IS, Martinez F, Sabarwal SV, Seferovic PM, Kerr Saraiva JF, Katova T (2021) Burden of heart failure signs and symptoms, prognosis, and response to therapy: the PARAGON-HF trial. JACC Heart Fail 9(5):386–397. https://doi.org/10.1016/j.jchf.2021.01.011
Jin Y, Cui H, Chen L, Liu Z, Sun K (2022a) Study of the flow mechanism and influencing factors of sputum excretion from the distal lung. Int J Numer Method Heat Fluid Flow 32(12):3782–3799. https://doi.org/10.1108/HFF-02-2022-0095
Jin Y, Cui H, Chen L, Sun K, Liu Z (2022b) Effects of airway deformation and alveolar pores on particle deposition in the lungs. Sci Total Environ 831:154931. https://doi.org/10.1016/j.scitotenv.2022.154931
Jin Y, Cui H, Chen L, Sun K, Yin H, Liu Z (2023) Tessellation-based modeling and flow simulation of pulmonaryacinus with alveolar pore. Int J Numer Method Heat Fluid Flow 33(1):42–64. https://doi.org/10.1108/HFF-12-2021-0801
Koullapis PG, Hofemeier P, Sznitman J, Kassinos SC (2018) An efficient computational fluid-particle dynamics method to predict deposition in a simplified approximation of the deep lung. Eur J Pharm Sci 113:132–144. https://doi.org/10.1016/j.ejps.2017.09.016
Lai SK, Wang YY, Wirtz D, Hanes J (2009) Micro- and macrorheology of mucu. Adv Drug Deliver Rev 61:86–100. https://doi.org/10.1016/j.addr.2008.09.012
Lee GS, Lee LA, Wang CY, Chen NH, Fang TJ, Huang CG, Cheng WN, Li HY (2016) The frequency and energy of snoring sounds are associated with common carotid artery intima-media thickness in obstructive sleep apnea patients. Sci Rep-UK 6:30559. https://doi.org/10.1038/srep30559
Mittal R, Erath B, Plesniak M (2013) Fluid dynamics of human phonation and speech. Annu Rev Fluid Mech 45(1):437–467. https://doi.org/10.1146/annurev-fluid-011212-140636
Monnier P, Dikkers FG, Eckel H, Sittel C, Piazza C, Campos G, Remacle M, Peretti G (2015) Preoperative assessment and classification of benign laryngotracheal stenosis: a consensus paper of the European Laryngological Society. Eur Arch Oto-Rhino-L 272(10):2885–2896. https://doi.org/10.1007/s00405-015-3635-4
Ma H, Fujioka H, Halpern D, Gaver DP (2020) Surfactant-mediated airway and acinar interactions in a multi-scale model of a healthy lung. Front Physiol 11:941. https://doi.org/10.3389/fphys.2020.00941
Miki K, Tsujino K, Miki M, Yoshimura K, Kagawa H, Oshitani Y, Fukushima K, Matsuki T, Yamamoto Y, Kida H (2020) Managing COPD with expiratory or inspiratory pressure load training based on a prolonged expiration pattern. ERJ Open Res 6(3):00041–02020. https://doi.org/10.1183/23120541.00041-2020
Nagasaka Y, Tsuchiya M (2012) Lung sounds in bronchial asthma. Allergol Int 61(3):353–363. https://doi.org/10.2332/allergolint.12-RAI-0449
Neelakantan S, Xin Y, Gaver DP, Cereda M, Rizi R, Smith BJ, Avazmohammadi R (2022) Computational lung modelling in respiratory medicine. J R Soc Interface 19:20220062. https://doi.org/10.1098/rsif.2022.0062
Oldham MJ, Moss OR (2019) Pores of Kohn: forgotten alveolar structures and potential source of aerosols in exhaled breath. J Breath Res 13:021003. https://doi.org/10.1088/1752-7163/ab0524
Pancaldi F, Pezzuto GS, Cassone G, Morelli M, Manfredi A, D’Arienzo M, Vacchi C, Savorani F, Vinci G, Barsotti F (2022) VECTOR: An algorithm for the detection of COVID-19 pneumonia from velcro-like lung sounds. Comput Biol Med 142:105220. https://doi.org/10.1016/j.compbiomed.2022.105220
Robertson AJ, Coope R (1957) Rales, rhonchi, and Laennec. Lancet 273(6992):417–423. https://doi.org/10.1016/S0140-6736(57)92359-0
Russell D, Titlow J, Bemmen Y (1999) Acoustic monopoles, dipoles, and quadrupoles: an experiment revisited. Am J Phys 67(8):660–664. https://doi.org/10.1119/1.19349
Ren S, Cai M, Shi Y (2022) Influence of cough airflow characteristics on respiratory mucus clearance. Phys Fluids 34:041911. https://doi.org/10.1063/5.0088100
Speranza CG, Moraes R (2018) Instantaneous frequency based index to characterize respiratory crackles. Comput Biol Med 102:21–29. https://doi.org/10.1016/j.compbiomed.2018.09.007
Smith MJ, Hayward SA, Innes SM, Miller ASC (2020) Point-of-care lung ultrasound in patients with COVID-19: a narrative review. Anaesthesia 75:1096–1104. https://doi.org/10.1111/anae.15082
Shi S, Tang W, Huang X, Dong X, Hua H (2022) Experimental and numerical investigations on the flow-induced vibration and acoustic radiation of a pump-jet propulsor model in a water tunnel. Ocean Eng 258:111736. https://doi.org/10.1016/j.oceaneng.2022.111736
Taheri MH, Pourmehran O, Sarafraz MM (2021) Effect of swirling flow and particle-release pattern on drug delivery to human tracheobronchial airways. Biomech Model Mechanobiol 20:2451–2469. https://doi.org/10.1007/s10237-021-01518-5
Wang Y, Zhang M, Yu Y, Han T, Zhou J, Bi L (2020) Sputum characteristics and airway clearance methods in patients with severe COVID-19. Medicine 99(46):23257. https://doi.org/10.1097/MD.0000000000023257
Xi J, Si X, Kim J, Su G, Dong H (2014) Modeling the pharyngeal anatomical effects on breathing resistance and aerodynamically generated sound. Med Biol Eng Comput 52:567–577. https://doi.org/10.1007/s11517-014-1160-z
Xi J, Wang Z, Talaat K, Glide-Hurst C, Dong H (2018) Numerical study of dynamic glottis and tidal breathing on respiratory sounds in a human upper airway model. Sleep Breath 22:463–479. https://doi.org/10.1007/s11325-017-1588-0
Xi J, Talaat M (2019) Nanoparticle deposition in rhythmically moving acinar models with interalveolar septal apertures. Nanomater-BASEL 9:1126. https://doi.org/10.3390/nano9081126
Xu X, Wu J, Weng W (2020) Investigation of inhalation and exhalation flow pattern in a realistic human upper airway model by PIV experiments and CFD simulations. Biomech Model Mechanobiol 19:1679–1695. https://doi.org/10.1007/s10237-020-01299-3
Yeh HC, Schum GM (1980) Models of human lung airways and their application to inhaled particle deposition. Bull Math Biol 42:461. https://doi.org/10.1007/BF02460796
Yu G, Yu Z, Shi Y, Wang Y, Liu X, Li Z, Zhao Y, Sun F, Yu Y, Shu Q (2021) Identification of pediatric respiratory diseases using a fine-grained diagnosis system. J Biomed Inform 117:103754. https://doi.org/10.1016/j.jbi.2021.103754
Funding
This work was supported by the National Natural Science Foundation of China (Nos. 42122058, 41977368, 52208126), the National Science and Technology Ministry of China (No. 2021YFF0604000), Natural Science Foundation of Hebei Province (No. E2021502046) and Fundamental Research Funds for the Central Universities (Nos. 2021MS075, 2020YJ007).
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YJ, ZL, HC and Chu performed formal analysis, CFD simulation, postprocessing of the data, validation, writing—original draft, writing—review and editing; ZD, RR, HL, LC. MH and YS analyzed supervision, writing—review and editing; ZL and JL provided supervision and writing—review.
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Jin, Y., Liu, Z., Hu, C. et al. Study on the flow mechanism and frequency characteristics of rales in lower respiratory tract. Biomech Model Mechanobiol 23, 227–239 (2024). https://doi.org/10.1007/s10237-023-01769-4
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DOI: https://doi.org/10.1007/s10237-023-01769-4