The acoustic characteristics of fine crackles predict honeycombing on high-resolution computed tomography View Full Text


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Article Info

DATE

2019-08-17

AUTHORS

Toshikazu Fukumitsu, Yasushi Obase, Yuji Ishimatsu, Shota Nakashima, Hiroshi Ishimoto, Noriho Sakamoto, Kosei Nishitsuji, Shunpei Shiwa, Tomoya Sakai, Sueharu Miyahara, Kazuto Ashizawa, Hiroshi Mukae, Ryo Kozu

ABSTRACT

BackgroundHoneycombing on high-resolution computed tomography (HRCT) is a distinguishing feature of usual interstitial pneumonia and predictive of poor outcome in interstitial lung diseases (ILDs). Although fine crackles are common in ILD patients, the relationship between their acoustic features and honeycombing on HRCT has not been well characterized.MethodsLung sounds were digitally recorded from 71 patients with fine crackles and ILD findings on chest HRCT. Lung sounds were analyzed by fast Fourier analysis using a sound spectrometer (Easy-LSA; Fukuoka, Japan). The relationships between the acoustic features of fine crackles in inspiration phases (onset timing, number, frequency parameters, and time-expanded waveform parameters) and honeycombing in HRCT were investigated using multivariate logistic regression analysis.ResultsOn analysis, the presence of honeycombing on HRCT was independently associated with onset timing (early vs. not early period; odds ratios [OR] 10.407, 95% confidence interval [95% CI] 1.366–79.298, P = 0.024), F99 value (the percentile frequency below which 99% of the total signal power is accumulated) (unit Hz = 100; OR 5.953, 95% CI 1.221–28.317, P = 0.029), and number of fine crackles in the inspiratory phase (unit number = 5; OR 4.256, 95% CI 1.098–16.507, P = 0.036). In the receiver-operating characteristic curves for number of crackles and F99 value, the cutoff levels for predicting the presence of honeycombing on HRCT were calculated as 13.2 (area under the curve [AUC], 0.913; sensitivity, 95.8%; specificity, 75.6%) and 752 Hz (AUC, 0.911; sensitivity, 91.7%; specificity, 85.2%), respectively. The multivariate logistic regression analysis additionally using these cutoff values revealed an independent association of number of fine crackles in the inspiratory phase, F99 value, and onset timing with the presence of honeycombing (OR 33.907, 95% CI 2.576–446.337, P = 0.007; OR 19.397, 95% CI 2.311–162.813, P = 0.006; and OR 12.383, 95% CI 1.443–106.293, P = 0.022; respectively).ConclusionsThe acoustic properties of fine crackles distinguish the honeycombing from the non-honeycombing group. Furthermore, onset timing, number of crackles in the inspiratory phase, and F99 value of fine crackles were independently associated with the presence of honeycombing on HRCT. Thus, auscultation routinely performed in clinical settings combined with a respiratory sound analysis may be predictive of the presence of honeycombing on HRCT. More... »

PAGES

153

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http://scigraph.springernature.com/pub.10.1186/s12890-019-0916-5

DOI

http://dx.doi.org/10.1186/s12890-019-0916-5

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https://app.dimensions.ai/details/publication/pub.1120376534

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/31419981


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    "description": "BackgroundHoneycombing on high-resolution computed tomography (HRCT) is a distinguishing feature of usual interstitial pneumonia and predictive of poor outcome in interstitial lung diseases (ILDs). Although fine crackles are common in ILD patients, the relationship between their acoustic features and honeycombing on HRCT has not been well characterized.MethodsLung sounds were digitally recorded from 71 patients with fine crackles and ILD findings on chest HRCT. Lung sounds were analyzed by fast Fourier analysis using a sound spectrometer (Easy-LSA; Fukuoka, Japan). The relationships between the acoustic features of fine crackles in inspiration phases (onset timing, number, frequency parameters, and time-expanded waveform parameters) and honeycombing in HRCT were investigated using multivariate logistic regression analysis.ResultsOn analysis, the presence of honeycombing on HRCT was independently associated with onset timing (early vs. not early period; odds ratios [OR] 10.407, 95% confidence interval [95% CI] 1.366\u201379.298, P\u2009=\u20090.024), F99 value (the percentile frequency below which 99% of the total signal power is accumulated) (unit Hz\u2009=\u2009100; OR 5.953, 95% CI 1.221\u201328.317, P\u2009=\u20090.029), and number of fine crackles in the inspiratory phase (unit number\u2009=\u20095; OR 4.256, 95% CI 1.098\u201316.507, P\u2009=\u20090.036). In the receiver-operating characteristic curves for number of crackles and F99 value, the cutoff levels for predicting the presence of honeycombing on HRCT were calculated as 13.2 (area under the curve [AUC], 0.913; sensitivity, 95.8%; specificity, 75.6%) and 752\u2009Hz (AUC, 0.911; sensitivity, 91.7%; specificity, 85.2%), respectively. The multivariate logistic regression analysis additionally using these cutoff values revealed an independent association of number of fine crackles in the inspiratory phase, F99 value, and onset timing with the presence of honeycombing (OR 33.907, 95% CI 2.576\u2013446.337, P\u2009=\u20090.007; OR 19.397, 95% CI 2.311\u2013162.813, P\u2009=\u20090.006; and OR 12.383, 95% CI 1.443\u2013106.293, P\u2009=\u20090.022; respectively).ConclusionsThe acoustic properties of fine crackles distinguish the honeycombing from the non-honeycombing group. Furthermore, onset timing, number of crackles in the inspiratory phase, and F99 value of fine crackles were independently associated with the presence of honeycombing on HRCT. Thus, auscultation routinely performed in clinical settings combined with a respiratory sound analysis may be predictive of the presence of honeycombing on HRCT.", 
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23 schema:description BackgroundHoneycombing on high-resolution computed tomography (HRCT) is a distinguishing feature of usual interstitial pneumonia and predictive of poor outcome in interstitial lung diseases (ILDs). Although fine crackles are common in ILD patients, the relationship between their acoustic features and honeycombing on HRCT has not been well characterized.MethodsLung sounds were digitally recorded from 71 patients with fine crackles and ILD findings on chest HRCT. Lung sounds were analyzed by fast Fourier analysis using a sound spectrometer (Easy-LSA; Fukuoka, Japan). The relationships between the acoustic features of fine crackles in inspiration phases (onset timing, number, frequency parameters, and time-expanded waveform parameters) and honeycombing in HRCT were investigated using multivariate logistic regression analysis.ResultsOn analysis, the presence of honeycombing on HRCT was independently associated with onset timing (early vs. not early period; odds ratios [OR] 10.407, 95% confidence interval [95% CI] 1.366–79.298, P = 0.024), F99 value (the percentile frequency below which 99% of the total signal power is accumulated) (unit Hz = 100; OR 5.953, 95% CI 1.221–28.317, P = 0.029), and number of fine crackles in the inspiratory phase (unit number = 5; OR 4.256, 95% CI 1.098–16.507, P = 0.036). In the receiver-operating characteristic curves for number of crackles and F99 value, the cutoff levels for predicting the presence of honeycombing on HRCT were calculated as 13.2 (area under the curve [AUC], 0.913; sensitivity, 95.8%; specificity, 75.6%) and 752 Hz (AUC, 0.911; sensitivity, 91.7%; specificity, 85.2%), respectively. The multivariate logistic regression analysis additionally using these cutoff values revealed an independent association of number of fine crackles in the inspiratory phase, F99 value, and onset timing with the presence of honeycombing (OR 33.907, 95% CI 2.576–446.337, P = 0.007; OR 19.397, 95% CI 2.311–162.813, P = 0.006; and OR 12.383, 95% CI 1.443–106.293, P = 0.022; respectively).ConclusionsThe acoustic properties of fine crackles distinguish the honeycombing from the non-honeycombing group. Furthermore, onset timing, number of crackles in the inspiratory phase, and F99 value of fine crackles were independently associated with the presence of honeycombing on HRCT. Thus, auscultation routinely performed in clinical settings combined with a respiratory sound analysis may be predictive of the presence of honeycombing on HRCT.
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29 schema:keywords Fourier analysis
30 HRCT
31 Hz
32 ILD patients
33 acoustic characteristics
34 acoustic features
35 acoustic properties
36 analysis
37 association
38 auscultation
39 characteristic curve
40 characteristics
41 chest HRCT
42 clinical setting
43 crackles
44 curves
45 cutoff level
46 cutoff value
47 disease
48 fast Fourier analysis
49 features
50 findings
51 fine crackles
52 group
53 honeycombing
54 independent association
55 inspiration phase
56 inspiratory phase
57 interstitial lung disease
58 interstitial pneumonia
59 levels
60 logistic regression analysis
61 lung disease
62 lung sounds
63 multivariate logistic regression analysis
64 number
65 number of crackles
66 onset timing
67 outcomes
68 patients
69 phase
70 pneumonia
71 poor outcome
72 presence
73 properties
74 receiver-operating characteristic curve
75 regression analysis
76 relationship
77 respiratory sound analysis
78 setting
79 sound
80 sound analysis
81 spectrometer
82 timing
83 tomography
84 usual interstitial pneumonia
85 values
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