0
Research Papers

Early Acoustic Warning for the Onset of Acute Chest Syndrome in Sickle Cell Patients

[+] Author and Article Information
Brian Henry, Gardner Yost, Thomas J. Royston

Richard and Loan Hill
Department of Bioengineering,
University of Illinois at Chicago,
Chicago, IL 60607

Robert Molokie

Department of Medicine,
University of Illinois at Chicago,
Chicago, IL 60612;
Jesse Brown VA Medical Center,
Chicago, IL 60612

Manuscript received October 2, 2017; final manuscript received January 15, 2018; published online March 7, 2018. Editor: Ahmed Al-Jumaily.

ASME J of Medical Diagnostics 1(2), 021006 (Mar 07, 2018) (7 pages) Paper No: JESMDT-17-2047; doi: 10.1115/1.4039177 History: Received October 02, 2017; Revised January 15, 2018

Acute chest syndrome (ACS) is a leading cause of death for those with sickle cell disease (SCD). ACS is defined by the development of a new pulmonary infiltrate on chest X-ray, with fever and respiratory symptoms. Efforts have been made to apply various technologies in the hospital setting to provide earlier detection of ACS than X-ray, but they are expensive, increase radiation exposure to the patient, and are not technologies that are easily transferrable for home use to help with early diagnosis. We present preliminary studies on patients suggesting that acoustical measurements recorded quantitatively with contact sensors (electronic stethoscopes) and analyzed using advanced computational analysis methods may provide an earlier diagnostic indicator of the onset of ACS than is possible with current clinical practice. Novel in silico models of respiratory acoustics utilizing image-based and algorithmically developed lungs with full conducting airway trees support and help explain measured acoustic trends and provide guidance on the next steps in developing and translating a diagnostic approach. More broadly, the experimental and computational techniques introduced herein, while focused on monitoring and predicting the onset of ACS, could catalyze further advances in mobile health (mhealth)-enabled, computer-based auscultative diagnoses for a wide range of cardiopulmonary pathologies.

FIGURES IN THIS ARTICLE
<>
Copyright © 2018 by ASME
Topics: Acoustics , Lung
Your Session has timed out. Please sign back in to continue.

References

Weatherall, D. J. , 2010, “ The Inherited Diseases of Hemoglobin are an Emerging Global Health Burden,” Blood, 115(22), pp. 4331–4336. [CrossRef] [PubMed]
Platt, O. S. , Brambilla, D. J. , Rosse, W. F. , Milner, P. F. , Castro, O. , Steinberg, M. H. , and Klug, P. P. , 1994, “ Mortality in Sickle Cell Disease—Life Expectancy and Risk Factors for Early Death,” N. Engl. J. Med., 330(23), pp. 1639–1644. [CrossRef] [PubMed]
Quinn, C. T. , Rogers, Z. R. , McCavit, T. L. , and Buchanan, G. R. , 2010, “ Improved Survival of Children and Adolescents With Sickle Cell Disease,” Blood, 115(17), pp. 3447–3452. [CrossRef] [PubMed]
Brousseau, D. C. , Owens, P. L. , Mosso, A. L. , Panepinto, J. A. , and Steiner, C. A. , 2010, “ Acute Care Utilization and Rehospitalizations for Sickle Cell Disease,” JAMA, 303(13), pp. 1288–1294. [CrossRef] [PubMed]
Charache, S. , Scott, J. C. , and Charache, P. , 1979, “ Acute Chest Syndrome in Adults With Sickle Cell Anemia: Microbiology, Treatment, and Prevention,” Arch. Intern. Med., 139(1), pp. 67–69. [CrossRef] [PubMed]
Castro, O. , Brambilla, D. J. , Thorington, B. , Reindorf, C. A. , Scott, R. B. , Gillette, P. , Vera, J. C. , and Levy, P. S. , 1994, “ The Acute Chest Syndrome in Sickle Cell Disease: Incidence and Risk Factors. The Cooperative Study of Sickle Cell Disease,” Blood, 84(2), pp. 643–649. http://www.bloodjournal.org/content/84/2/643 [PubMed]
Paul, R. N. , Castro, O. L. , Aggarwal, A. , and Oneal, P. A. , 2011, “ Acute Chest Syndrome: Sickle Cell Disease,” Eur. J. Haematol., 87(3), pp. 191–207. [CrossRef] [PubMed]
Bartolucci, P. , Habibi, A. , Khellaf, M. , Roudot-Thoraval, F. , Melica, G. , Lascaux, A.-S. , Moutereau, S. , Loric, S. , Wagner-Ballon, O. , Berkenou, J. , Santin, A. , Michel, M. , Renaud, B. , Lévy, Y. , Galactéros, F. , and Godeauc, B. , 2016, “ Score Predicting Acute Chest Syndrome During Vaso-Occlusive Crises in Adult Sickle-Cell Disease Patients,” EBioMedicine, 10, pp. 305–311. [CrossRef] [PubMed]
Mekontso Dessap, A. , Deux, J. F. , Habibi, A. , Abidi, N. , Godeau, B. , Adnot, S. , Brun-Buisson, C. , Rahmouni, A. , Galacteros, F. , and Maitre, B. , 2014, “ Lung Imaging During Acute Chest Syndrome in Sickle Cell Disease: Computed Tomography Patterns and Diagnostic Accuracy of Bedside Chest Radiograph,” Thorax, 69(2), pp. 144–151. [CrossRef] [PubMed]
Taylor, C. , Carter, F. , Poulose, J. , Rolle, S. , Babu, S. , and Crichlow, S. , 2004, “ Clinical Presentation of Acute Chest Syndrome in Sickle Cell Disease,” Postgrad. Med. J., 80(944), pp. 346–349. [CrossRef] [PubMed]
Cohen, R. T. , Madadi, A. , Blinder, M. A. , DeBaun, M. R. , Strunk, R. C. , and Field, J. J. , 2011, “ Recurrent, Severe Wheezing is Associated With Morbidity and Mortality in Adults With Sickle Cell Disease,” Am. J. Hematol., 86(9), pp. 756–761. [CrossRef] [PubMed]
Morris, C. R. , 2009, “ Asthma Management: Reinventing the Wheel in Sickle Cell Disease,” Am. J. Hematol., 84(4), pp. 234–241. [CrossRef] [PubMed]
Sobota, A. , Graham, D. A. , Heeney, M. M. , and Neufeld, E. J. , 2010, “ Corticosteroids for Acute Chest Syndrome in Children With Sickle Cell Disease: Variation in Use and Association With Length of Stay and Readmission,” Am. J. Hematol., 85(1), pp. 24–28. [CrossRef] [PubMed]
Strouse, J. J. , Takemoto, C. M. , Keefer, J. R. , Kato, G. J. , and Casella, J. F. , 2008, “ Corticosteroids and Increased Risk of Readmission After Acute Chest Syndrome in Children With Sickle Cell Disease,” Pediatr. Blood Cancer, 50(5), pp. 1006–1012. [CrossRef] [PubMed]
Knight-Madden, J. , and Greenough, A. , 2014, “ Acute Pulmonary Complications of Sickle Cell Disease,” Paediatr. Respir. Rev., 15(1), pp. 13–16. [PubMed]
Royston, T. J. , Zhang, X. , Mansy, H. A. , and Sandler, R. H. , 2002, “ Modeling Sound Transmission Through the Pulmonary System and Chest With Application to Diagnosis of a Collapsed Lung,” J. Acoust. Soc. Am., 111(4), pp. 1931–1946. [CrossRef] [PubMed]
Ozer, M. B. , Acikgoz, S. , Royston, T. J. , Mansy, H. A. , and Sandler, R. H. , 2007, “ Boundary Element Model for Simulating Sound Propagation and Source Localization Within the Lungs,” J. Acoust. Soc. Am., 122(1), pp. 657–671. [CrossRef] [PubMed]
Acikgoz, S. , Ozer, M. B. , Royston, T. J. , Mansy, H. A. , and Sandler, R. H. , 2008, “ Experimental and Computational Models for Simulating Sound Propagation Within the Lungs,” ASME J. Vib. Acoust., 130(2), p. 021010. [CrossRef]
Peng, Y. , Dai, Z. , Mansy, H. A. , Sandler, R. H. , Balk, R. A. , and Royston, T. J. , 2014, “ Sound Transmission in the Chest Under Surface Excitation: An Experimental and Computational Study With Diagnostic Applications,” Med. Biol. Eng. Comput., 52(8), pp. 695–706. [CrossRef] [PubMed]
Dai, Z. , Peng, Y. , Henry, B. , Mansy, H. A. , and Royston, T. J. , 2014, “ A Comprehensive Computational Model of Sound Transmission Through the Porcine Lung,” J. Acoust. Soc. Am., 136(3), pp. 1419–1429. [CrossRef] [PubMed]
Peng, Y. , Dai, Z. , Mansy, H. A. , Henry, B. H. , Sandler, R. H. , Balk, R. A. , and Royston, T. J. , 2016, “ Sound Transmission in Porcine Thorax Through Airway Insonification,” Med. Biol. Eng. Comput., 54(4), pp. 675–689. [CrossRef] [PubMed]
Dai, Z. , Peng, Y. , Mansy, H. A. , Sandler, R. H. , and Royston, T. J. , 2015, “ Experimental and Computational Studies of Sound Transmission in a Branching Airway Network Embedded in a Compliant Viscoelastic Medium,” J. Sound Vib., 339, pp. 215–229. [CrossRef] [PubMed]
Henry, B. , and Royston, T. J. , 2017, “ A Multiscale Medical Image-Derived Analytical Model of Bronchial Airway Acoustics,” J. Acoust. Soc. Am., 142(4), pp. 1774–1783.
Kompis, M. , Pasterkamp, H. , and Wodicka, G. R. , 2001, “ Acoustic Imaging of the Human Chest,” Chest, 120(4), pp. 1309–1321. [CrossRef] [PubMed]

Figures

Grahic Jump Location
Fig. 1

Human subject #1: spectral content of breath sounds over posterior middle right lung field of confirmed ACS location in a patient. Spectra calculated based on Welch's method and measured 4 (blue), 3 (yellow), and 2 (red) days before the clinical diagnosis of ACS, and 20 days (green) after diagnosis when patient sent home, considered as this patient's baseline. Black solid and dashed lines are the averaged baseline value and averaged baseline plus one standard deviation of the spectrum of the same measurements taken on 69 different sickle cell patients not undergoing ACS.

Grahic Jump Location
Fig. 2

Human subject #2: spectral content of breath sounds over anterior base left (ABL) and posterior base left lung fields (response at ABL in upper plot, posterior base left in lower plot, respectively) of confirmed ACS in a patient. Spectra calculated based on Welch's method and measured 1 day before (red) the clinical diagnosis of ACS and 1 month prior (green) to the ACS diagnosis, considered as this patient's baseline. Black solid and dashed lines are the averaged baseline value and averaged baseline plus one standard deviation of the spectrum of the same measurements taken on 69 different sickle cell patients not undergoing ACS.

Grahic Jump Location
Fig. 3

Airway acoustic pressure in dB ref. 1 Pa at 400 Hz for healthy (top) and pulmonary infiltrate (bottom) cases caused by acoustic source located at top of trachea (computation time = ∼45 s, additional frequencies would add a few seconds per frequency)

Grahic Jump Location
Fig. 4

Airway wall acoustic radial velocity in dB ref. 1 m/s at 400 Hz for healthy (top) and pulmonary infiltrate (bottom) cases caused by acoustic source located at top of trachea (computation time = ∼45 s, additional frequencies would add a few seconds per frequency)

Grahic Jump Location
Fig. 5

Mean airway wall acoustic radial velocity in dB ref. 1 m/s in the lower left lobe of the lung for healthy and pulmonary infiltrate cases caused by acoustic source located at top of trachea

Grahic Jump Location
Fig. 6

Airway acoustic pressure in dB ref. 1 Pa (top) and wall acoustic radial velocity in dB ref. 1 m/s (bottom) at 400 Hz for pulmonary infiltrate case caused by an acoustic source in a small airway segment (bronchiole) near the site of pulmonary infiltrate (wheeze simulation)

Grahic Jump Location
Fig. 7

Time history of an acoustic pressure pulse originating at the top of the trachea as it propagates through multiple segments to reach a terminal conducting segment in the healthy lung model

Grahic Jump Location
Fig. 8

Time history of an acoustic pressure pulse, approximating a crackle, originating at a small airway segment (bronchiole) near the site of pulmonary infiltration as it propagates through multiple segments to reach the trachea

Grahic Jump Location
Fig. 9

Transfer function estimation fit value for case shown in (a) Fig. 7 and (b) Fig. 8

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In