In vivo assessment of pulmonary fibrosis and edema in rodents using the backscatter coefficient and envelope statistics

Abstract

Quantitative ultrasound methods based on the backscatter coefficient (BSC) and envelope statistics have been used to quantify disease in a wide variety of tissues, such as prostate, lymph nodes, breast, and thyroid. However, to date, these methods have not been investigated in the lung. In this study, lung properties were quantified by BSC and envelope statistical parameters in normal, fibrotic, and edematous rat lungs in vivo. The average and standard deviation of each parameter were calculated for each lung as well as the evolution of each parameter with acoustic propagation time within the lung. The transport mean free path and backscattered frequency shift, two parameters that have been successfully used to assess pulmonary fibrosis and edema in prior work, were evaluated in combination with the BSC and envelope statistical parameters. Multiple BSC and envelope statistical parameters were found to provide contrast between control and diseased lungs. BSC and envelope statistical parameters were also significantly correlated with fibrosis severity using the modified Ashcroft fibrosis score as the histological gold standard. These results demonstrate the potential for BSC and envelope statistical parameters to improve the diagnosis of pulmonary fibrosis and edema as well as monitor pulmonary fibrosis.

State of the Art in Lung Ultrasound, Shifting from Qualitative to Quantitative Analyses

“…Indeed, when the quantity of fluid increases, the mean distance between scatterers increases, thus increasing L* (Mohanty et al 2017). In the following years, similar techniques were experimentally tested to differentiate rat lungs with pulmonary fibrosis (PF) from healthy lungs (Mohanty et al 2020), detect pulmonary nodules (regions inside lungs containing no scatterers) (Roshankhah et al 2021a) and differentiate rat lungs affected by PF (or edema) from healthy lungs of control rats (Lye et al 2021).…”

Operational Status Monitoring and Fault Diagnosis System of Transformer Equipment

“…Examples presented are data on electrical power distribution to identify the effectiveness of data-driven analysis algorithms for data acquisition. In it, the electronic power supply receives the system, instantaneous active and reactive power, three-or two-phase cur-rent, and voltage amplitudes, and all power types are closed [16]. In these measurements, it is difficult to apply the current power or power values to determine whether the input voltage of the transformer is normal, and the fluctuation of phase voltage is usually small.…”

Lung quantitative ultrasound to stage and monitor interstitial lung diseases

“…This resulted in a 128 * 128 * t Inter-element Response Matrix (IRM), where t is the number of time points, with a 62.5 MHz sampling rate. Each of the 128 * 128 time trace was truncated into overlapping time windows T. LQUS parameters estimations have been presented in our previous studies 18 ; they are briefly summarized below.…”