Investigation of Radiofrequency Ultrasound-Based Fibrotic Tissue Strain Imaging Method Employing Endogenous Motion

The Ultrasound Window Into Vascular Ageing: A Technology Review by the VascAgeNet COST Action

Non-invasive ultrasound (US) imaging enables the assessment of the properties of superficial blood vessels. Various modes can be used for vascular characteristics analysis, ranging from radiofrequency (RF) data, Doppler- and standard B/M-mode imaging, to more recent ultra-high frequency and ultrafast techniques. The aim of the present work was to provide an overview of the current state-of-the-art non-invasive US technologies and corresponding vascular ageing characteristics from a technological perspective. Following an introduction about the basic concepts of the US technique, the characteristics considered in this review are clustered into: 1) vessel wall structure; 2) dynamic elastic properties, and 3) reactive vessel properties. The overview shows that ultrasound is a versatile, non-invasive, and safe imaging technique that can be adopted for obtaining information about function, structure, and reactivity in superficial arteries. The most suitable setting for a specific application must be selected according to spatial and temporal resolution requirements. The usefulness of standardization in the validation process and performance metric adoption emerges. Computer-based techniques should always be preferred to manual measures, as long as the algorithms and learning procedures are transparent and well described, and the performance leads to better results. Identification of a minimal clinically important difference is a crucial point for drawing conclusions regarding robustness of the techniques and for the translation into practice of any biomarker.

Performance Evaluation of an Ultrasonic Imaging System Using Tissue-Mimicking Phantoms for Quality Assurance

Diagnostic ultrasound or sonography is an image that can provide valuable information for diagnosing and treating a variety of diseases and conditions. The aim of this research study is to examine the performance and accuracy of the ultrasonic imaging system for the guarantee of diagnosis quality assurance, and to adjust the penetration settings to minimize the time of repeat scans and maintenance duration during research experiments. Measurements in this experiment included the resolution (axial and lateral) and focal zones. Moreover, the evaluation was done by completing all the measurements at different depths on a multipurpose phantom model 539. The phantom was bought from the market and was not fabricated by the author. The measurements were achieved by applying two different transducers: curved and linear (flat). The ultrasound images were obtained and tested by using calipers (electronic), and the estimations and observations were read by using all the taken measurements and images. As a result, because the phantom depths were different, the penetration settings were different too, indicating that the depth impacted the penetrations of the created ultrasound image. Moreover, after the comparison of the recorded measurements and results, it was found that all measurements were within the accepted (standard) value and that the true value was specified by the production of the phantom.

Simulation of Ultrasound RF Signals Backscattered from a 3D Model of Pulsating Artery Surrounded by Tissue

Arterial stiffness is an independent predictor of cardiovascular events. The motion of arterial tissues during the cardiac cycle is important as a mechanical deformation representing vessel elasticity and is related to arterial stiffness. In addition, arterial pulsation is the main source of endogenous tissue micro-motions currently being studied for tissue elastography. Methods based on artery motion detection are not applied in clinical practice these days, because they must be carefully investigated in silico and in vitro before wide usage in vivo. The purpose of this paper is to propose a dynamic 3D artery model capable of reproducing the biomechanical behavior of human blood vessels surrounded by elastic tissue for endogenous deformation elastography developments and feasibility studies. The framework is based on a 3D model of a pulsating artery surrounded by tissue and simulation of linear scanning by Field II software to generate realistic dynamic RF signals and B-mode ultrasound image sequential data. The model is defined by a spatial distribution of motions, having patient-specific slopes of radial and longitudinal motion components of the artery wall and surrounding tissues. It allows for simulating the quantified mechanical micro-motions in the volume of the model. Acceptable simulation errors calculated between modeled motion patterns and those estimated from simulated RF signals and B-scan images show that this approach is suitable for the development and validation of elastography algorithms based on motion detection.

Performance Evaluation of Ultrasonic Imaging System (Part I)

Background:

Diagnostic ultrasound or sonography is an image which can provide valuable information for diagnosing and treating a variety of diseases and conditions. This experiment was done to check the performance and evaluate the ultrasonic imaging system. There were three tests performed in this experiment: dead zone (transducer ring-down), vertical measurement calibration, and horizontal measurement calibration.

Methods:

The evaluation was made by performed all the tests with different depth on two different multipurpose phantom model #539. The tests were also performed by two different probes which were curved and flat (linear probe). The images were taken, and the measurements were made by electronic calipers on the ultrasound machine system. Observations and evaluations were done via all images and measurements taken.

Results:

The images formed by two various probes were different. The penetration settings were different since the depths were different. The depth influenced the penetrations to the formed image. From the comparison of all results and measurements recorded were all under the accepted value of the standard that was given by the manufacture of the phantom.

Conclusion:

Therefore, it can be concluded that the measurements were all not exceeding 2% of the standard value given based on the result that we get.

Main Uncertainties in the RF Ultrasound Scanning Simulation of the Standard Ultrasound Phantoms

Ultrasound echoscopy technologies are continuously evolving towards new modalities including quantitative parameter imaging, elastography, 3D scanning, and others. The development and analysis of new methods and algorithms require an adequate digital simulation of radiofrequency (RF) signal transformations. The purpose of this paper is the quantitative evaluation of RF signal simulation uncertainties in resolution and contrast reproduction with the model of a phased array transducer. The method is based on three types of standard physical phantoms. Digital 3D models of those phantoms are composed of point scatterers representing the weak backscattering of the background material and stronger backscattering from inclusions. The simulation results of echoscopy with sector scanning transducer by Field II software are compared with the RF output of the Ultrasonix scanner after scanning standard phantoms with 2.5 MHz phased array. The quantitative comparison of axial, lateral, and elevation resolutions have shown uncertainties from 9 to 22% correspondingly. The echoscopy simulation with two densities of scatterers is compared with contrast phantom imaging on the backscattered RF signals and B-scan reconstructed image, showing that the main sources of uncertainties limiting the echoscopy RF signal simulation adequacy are an insufficient knowledge of the scanner and phantom’s parameters. The attempt made for the quantitative evaluation of simulation uncertainties shows both problems and the potential of echoscopy simulation in imaging technology developments. The analysis presented could be interesting for researchers developing quantitative ultrasound imaging and elastography technologies looking for simulated raw RF signals comparable to those obtained from real ultrasonic scanning.

Quantitative evaluation of liver fibrosis based on ultrasound radio frequency signals: An animal experimental study

BACKGROUND

Chronic liver disease is an important cause of liver failure and death worldwide, and liver fibrosis is a common pathological process of most chronic liver diseases. There still lacks a useful tool for evaluating liver fibrosis progression precisely and non-invasively. The purpose of this study was to explore the use of ultrasound radio frequency (RF) signals combined with deep learning approach to evaluate the degree of liver fibrosis quantitatively.

METHODS

In this study, by extracting the output of deep learning models as a prediction value, a quantitative liver fibrosis prediction method was achieved based on the bidirectional long short-term memory (Bi-LSTM) network to analyze radio frequency (RF) signals. The dataset consisted of 160 sets of ultrasound RF signals of rat livers, including five fibrosis stages 0-4, upon pathological diagnosis. In total, 150 sets of RF signals were used to train four deep learning classification models, the output of which contained quantitative information. In each training stage of the four models, a large number of signal segments were extracted from the 150 sets and divided randomly into training and validation sets in a ratio of 80:20. Ten sets of RF data using the gold standard of quantitative fibrosis parameter (q-FP) of liver tissues were left for independent testing. To validate the proposed method, correlation analysis was carried out between q-FP and the quantitative prediction results based on the independent test data.

RESULTS

The accuracy of the four deep learning networks using the training and validation data was above 0.83 and 0.80, and the corresponding areas under the receiver operating characteristic curves were higher than 0.95 and 0.93, respectively. For the quantitative analysis in the independent test set, the determination coefficient, R², of the linear regression analysis between the quantitative prediction results and q-FP was above 0.93. liver fibrosis is a common pathological process of most chronic liver diseases.

CONCLUSIONS

This study indicates that a prediction system based on ultrasound RF signals and a deep learning approach is promising for realizing quantitative and visualized diagnosis of liver fibrosis, which would be of great value in monitoring liver fibrosis non-invasively.

Endogenous motion of liver correlates to the severity of portal hypertension

BACKGROUND

Degree of portal hypertension (PH) is the most important prognostic factor for the decompensation of liver cirrhosis and death, therefore adequate care for patients with liver cirrhosis requires timely detection and evaluation of the presence of clinically significant PH (CSPH) and severe PH (SPH). As the most accurate method for the assessment of PH is an invasive direct measurement of hepatic venous pressure gradient (HVPG), the search for non-invasive methods to diagnose these conditions is actively ongoing.

AIM

To evaluate the feasibility of parameters of endogenously induced displacements and strain of liver to assess degree of PH.

METHODS

Of 36 patients with liver cirrhosis and measured HVPG were included in the case-control study. Endogenous motion of the liver was characterized by derived parameters of region average tissue displacement signal (d_antero, d_retro, d_RMS) and results of endogenous tissue strain imaging using specific radiofrequency signal processing algorithm. Average endogenous strain µ and standard deviation σ of strain were assessed in the regions of interest (ROI) (1 cm × 1 cm and 2 cm × 2 cm in size) and different frequency subbands of endogenous motion (0-10 Hz and 10-20 Hz).

RESULTS

Four parameters showed statistically significant (P < 0.05) correlation with HVPG measurement. The strongest correlation was obtained for the standard deviation of strain (estimated at 0-10 Hz and 2 cm × 2 cm ROI size). Three parameters showed statistically significant differences between patient groups with CSPH, but only d_retro showed significant results in SPH analysis. According to ROC analysis area under the curve (AUC) of the σ_{ROI[0…10Hz, 2 cm × 2 cm]} parameter reached 0.71 (P = 0.036) for the diagnosis of CSPH; with a cut-off value of 1.28 μm/cm providing 73% sensitivity and 70% specificity. AUC for the diagnosis of CSPH for µ_{ROI[0…10Hz, 1 cm × 1 cm]} was 0.78 (P = 0.0024); with a cut-off value of 3.92 μm/cm providing 73% sensitivity and 80% specificity. D_retro parameter had an AUC of 0.86 (P = 0.0001) for the diagnosis of CSPH and 0.84 (P = 0.0001) for the diagnosis of SPH. A cut-off value of -132.34 μm yielded 100% sensitivity for both conditions, whereas specificity was 80% and 72% for CSPH and SPH respectively.

CONCLUSION

The parameters of endogenously induced displacements and strain of the liver correlated with HVPG and might be used for non-invasive diagnosis of PH.