Analysis of induced sputum in patients with bronchial asthma

Sputum induction and its diagnostic applications in inflammatory airway disorders: a review

Sputum induction is a technique that covers the induction and the subsequent processing of the expectorate primarily for the analysis of cells and different inflammatory biomarkers present in the airways to further understand the pathophysiology of different inflammatory respiratory disorders such as asthma and chronic obstructive pulmonary disease (COPD) as well as the diagnosis of lung diseases such as lung cancer, tuberculosis, and Pneumocystis jirovecii pneumonia. It is a non-invasive, safe, cost-effective, and reliable technique reported to exhibit a high success rate. However, due to being technically demanding and time-consuming and having the need of employing trained staff, this technique is only used in restricted research centres and in limited centres of clinical use. When the sputum is collected after induction, the primary goal is to obtain a differential cell count and evaluate the molecular biomarkers of airway inflammation such as eosinophil cationic protein, eosinophil-derived neurotoxin, major basic protein, tryptase, cytokine production [e.g., interleukin (IL)-5], albumin, and fibrinogen. In addition, cytospins from the processed sputum are used for immunocytochemical staining of cellular products such as EG-2 reactive protein, granulocyte-macrophage colony-stimulating factor, tumour necrosis factor alpha, and IL-8 that play significant roles in understanding the pathophysiology of inflammatory airway diseases. Nowadays, this technique can be further used by performing an additional analysis such as flow cytometry and in situ hybridisation on the sputum supernatant to investigate more the immune response and pathophysiological process of such various respiratory diseases. In addition, the application of sputum fluid phase to assess the biomarkers could be used more routinely in pathological laboratories for diagnosing lung cancer, COPD, and asthma as well as for monitoring lung cancer progression and asthma and COPD treatment, allowing for early detection and a better treatment provided by the clinicians.

Sidelobe reduction for plane wave compounding with a limited frame number

BACKGROUND

In ultrasound plane wave imaging (PWI), image details are often blurred by the off-axis artefacts resulting from high sidelobe. Recently plane wave compounding (PWC) is proposed as a promising technique for the sidelobe suppression in the PWI. However, its high demand for the frame number results in an obvious frame rate loss, which is intolerable in the ultrafast imaging modality. To reduce the number of frames required for compounding, coherence in the compounding frames should be exploited.

METHODS

In this paper, we propose a global effective distance-based sidelobe suppressing method for the PWC with a limited frame number, where the global effective distance is introduced to measure the inter-frame coherence. Specifically, the effective distance is firstly computed by using a sparse representation-based algorithm. Then, the sidelobe localization is carried out on the basis of the effective distance. Finally, the target-dependent weighting factor is adopted to suppress the sidelobe.

RESULTS

To assert the superiority of our proposed method, we compare the performances of different sidelobe reduction methods on both simulated and experimental PWC data. In case of 5 steering angles, our method shows a 19 dB reduction in the peak sidelobe level compared to the normal PWC in the point spread function test, and the contrast ratio is enhanced by more than 10% in both the simulation and phantom studies.

CONCLUSIONS

Consequently, the proposed method is convinced to be a promising approach in enhancing the PWC image quality.

Airway inflammation phenotype prediction in asthma patients using lung sound analysis with fractional exhaled nitric oxide

BACKGROUND

We previously reported the results of lung sound analysis in patients with bronchial asthma and demonstrated that the exhalation-to-inhalation sound pressure ratio in the low frequency range between 100 and 200 Hz (E/I LF) was correlated with the presence of airway inflammation and airway obstruction. We classified asthma patients by airway inflammation phenotype using the induced sputum eosinophil and neutrophil ratio and determined whether this phenotype could be predicted using E/I LF and fractional exhaled nitric oxide values.

METHODS

Steroid-naive bronchial asthma patients were classified into four phenotypes, including "Low inflammation" (35 patients), "Eosinophilic type" (58 patients), "Neutrophilic type" (15 patients), and "Mixed type" (15 patients) based on the results of induced sputum examinations. The E/I LF data and FeNO levels were then evaluated for the four phenotype groups; the prediction powers of these two indices were then analyzed for each phenotype.

RESULTS

The median E/I LF value was highest in the "Mixed type" and lowest in the "Low inflammation" group. FeNO differentiated between the "Low inflammation" and "Eosinophilic type" groups, "Low inflammation" and "Neutrophilic type" groups, and "Neutrophilic type" and "Mixed type" (p < 0.0001, p = 0.007, and p = 0.04, respectively). E/I LF differentiated between the "Low inflammation" and "Eosinophilic type" groups (p = 0.006). E/I LF could distinguish the "Mixed type" group from the "Low inflammation" and "Eosinophilic type" groups (p = 0.002).

CONCLUSIONS

A combination of the E/I LF value and FeNO may be useful for the classification of the airway inflammation phenotype in patients with bronchial asthma.