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.
Highlights
Honeycombing on high-resolution computed tomography (HRCT) is a distinguishing feature of usual interstitial pneumonia and predictive of poor outcome in interstitial lung diseases (ILDs)
Sgalla et al reported that fine crackles could predict the presence of fibrotic ILD according to a study in subjects undergoing chest HRCT scans for various clinical indications [7]
We provide a comprehensive analysis of the acoustic characteristics of fine crackles in patients with honeycombing compared to those without honeycombing and investigate whether these acoustic parameters can predict the presence of honeycombing on HRCT
Summary
Honeycombing on high-resolution computed tomography (HRCT) is a distinguishing feature of usual interstitial pneumonia and predictive of poor outcome in interstitial lung diseases (ILDs). Honeycombing on high-resolution computed tomography (HRCT) is a distinguishing feature of usual interstitial pneumonia (UIP), the hallmark of idiopathic pulmonary fibrosis (IPF), and must be present for a definite HRCT diagnosis of UIP to be made. Honeycombing on HRCT is predictive of a poor outcome in IPF and in nonspecific interstitial pneumonia and connective tissue disease-related fibrotic interstitial lung disease (ILD) [2,3,4]. Fine crackles are heard in 60% of patients with interstitial pneumonia [5] as well as in 100% of patients with honeycombing on HRCT and a UIP pattern [6]. Cottin et al advise that physicians should perform chest auscultation and when bilateral fine crackles are heard, conduct an examination of the chest radiograph and/or CT image to detect IPF earlier [8]
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