Abstract
Purpose
This study aimed to explore the reliability and stability of ultrasound-guided attenuation parameter (UGAP) values obtained by two measuring methods and different measuring times.
Methods
Patients who underwent liver UGAP examinations in our hospital from September 2022 to December 2022 were retrospectively analyzed. The clinical data and UGAP measurements results were collected. Two different measuring methods: static single-frame multi-point measuring and dynamic multi-frame single-point measuring, were performed for each patient, and 10 UGAP values of each measuring method were recorded. The medians of the UGAP values of the 1st–3rd, 1st–5th, 1st–7th and 1st–10th by each measuring method were taken as the final UGAP values of measuring 3, 5, 7 and 10 times. The UGAP values obtained by the two different measuring methods and different measuring times (3, 5, 7 or 10 times) were compared.
Results
206 patients were included in this study. There was no statistical difference between UGAP values measured by static single-frame multi-point measuring and dynamic multi-frame single-point measuring (P = 0.689, P = 0.270, P = 0.298, P = 0.091), regardless of measuring times (3, 5, 7, 10 times). No significant difference between the UGAP values obtained by 3, 5, 7 and 10 measurements was found (P = 0.554, P = 0.916).
Conclusion
The UGAP values obtained by the two different measuring methods and different measuring times (3, 5, 7 and 10 times) are stable and reliable. Additionally, 3 times of UGAP measurements might be enough for each patient in clinical practice.
Keywords: Ultrasound-guided attenuation parameters, Ultrasound, Hepatic steatosis, Nonalcoholic fatty liver disease
Introduction
Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, affecting about 25% people worldwide [1]. In China, the prevalence of NAFLD increased from 23.8% to 32.9% from 2001 to 2018, replacing hepatitis B as the leading cause of chronic liver disease [2]. NAFLD comprises a wide spectrum of conditions, and may progress from the simple fatty liver to nonalcoholic steatohepatitis (NASH), even liver cirrhosis and liver cancer, if no effort was made [1]. Early detection, evaluation, and quantification of hepatic steatosis, as well as timely intervention are of great significance for preventing the progression of NAFLD to NASH and other serious consequences [3].
Conventional ultrasound is the most common imaging modality for hepatic steatosis evaluation and follow-up because of its portability, no radiation, ease of use, relatively low cost and repeatable evaluation [4–6]. However, only those fatty livers with fat content above 12.5–20% can be detected by conventional ultrasound [5, 7]. And the accuracy of evaluation can be influenced by the performance, setup, adjustment of the ultrasonic equipment and the experience of the examiners [8, 9]. In addition, it is difficult to quantify the degree of steatosis in the liver by conventional ultrasound.
In recent years, a variety of acoustic parameters obtained from raw radiofrequency data, such as attenuation coefficient, backscattering coefficient, speckle statistics, speed of sound, have been gradually verified to be helpful for the hepatic steatosis quantification [3, 10, 11]. Among them, the attenuation coefficient is the most widely used. It quantifies hepatic steatosis by calculating the attenuation of ultrasonic energy as the acoustic waves pass through the tissues [7, 8]. Generally, ultrasound attenuation increases with hepatic fat infiltration [3]. The ultrasound-guided attenuation parameter (UGAP) is one of the representative technologies applied by this principle [7, 12]. It is economical, convenient, safe and noninvasive, and the UGAP values can be measured under the real-time guidance of ultrasound [8]. Previous studies have confirmed the high diagnostic accuracy of UGAP in detecting and grading hepatic steatosis, which indicated its high potential in hepatic steatosis quantification [12–16].
Although the UGAP technology has been gradually applied in clinical practice, some of the methodology contents have not been standardized and unified. Firstly, the manufacturer provided static single-frame multi-point measuring and dynamic multi-frame single-point measuring for UGAP measurements, but the reliability and stability of UGAP values obtained by these two different measuring methods are lack of relevant research to verify. Secondly, the measuring times required to decide the final UGAP values differ from centers, ranging from 5 to 12 times [13–15, 17–21]. It was unclear whether the effectiveness and reliability of the final UGAP values will be affected by different measuring times. Therefore, the purpose of this study was to explore the reliability and stability of UGAP values obtained by the two measuring methods (including static single-frame multi-point measuring and dynamic multi-frame single-point measuring) and different measuring times, so as to provide methodological reference for the subsequent UGAP related clinical practice and studies.
Materials and methods
Patients
Patients who underwent liver UGAP examinations in our hospital from September 2022 to December 2022 were included in this retrospective study. The demographic information, basic medical history, and other basic information of the patients were collected. The inclusion criteria were as follows: (1) age 18–80 years old, male or female; (2) simultaneously underwent conventional ultrasound examinations and UGAP examinations for liver. The exclusion criteria were as follows: (1) only static single-frame multi-point measuring or dynamic multi-frame single-point measuring was performed for UGAP measurements; (2) unreliable UGAP measurements, with the inter quartile range/median (IQR/Med) of UGAP values larger than 30%; (3) incomplete patient information and data. This retrospective study had been approved by the Institutional Review Board of the hospital and was in accordance with the regulations of medical ethics.
Equipment
Conventional ultrasound examinations and UGAP examinations were performed using the GE Logic E10 ultrasound system (GE Healthcare, USA), which was equipped with abdominal convex array probe (C1-6-D, frequency 1–6 MHz) and built-in UGAP imaging technology.
Methods
All the UGAP examinations were performed by two ultrasound physicians (X.Z. and L.L) who have been engaged in abdominal ultrasound examinations for more than 3 years and have undergone strict and standardized UGAP imaging training, being proficient in both liver ultrasound scanning and UGAP imaging.
UGAP imaging
Preparation
All the patients fasted for at least 6 h before ultrasound examinations and UGAP examinations. The patients were supine on the examination bed with their arms raised and abducted, so as to open the intercostal space as much as possible. The convex array probe C1-6-D was selected, and the preset condition of "abdomen" was chosen. The two-dimensional gain and time-gain compensation of the ultrasonic images were adjusted appropriately, and the imaging depth was kept within the range of 10–12 cm. All the imaging parameters above remained unchanged during the examinations. The probe was placed in the intercostal space along the S5 and S6 segments of the liver. An ideal liver imaging section for UGAP should be evenly distributed hepatic parenchyma, avoiding the structures such as the large vessels, diaphragm, liver capsule and focal liver lesions (FLLs) as far as possible.
Acquisition of UGAP values
After activating the UGAP examination, a sampling box (fixed at 7 × 5 cm) was automatically set at the depth of the 3cm from the transducer surface within the image. It was located in the center of the image and its position was immovable. The "Color Dual" image display mode was used to display quality map and attenuation map at the same time when the UGAP imaging was performed. The UGAP value measurement box was set at the depth of 4cm from the transducer surface within the sampling box, with the size of 4 × 1 cm. Both the size and the depth of the UGAP value measurement box were unchangeable, which has been already fixed by the equipment. The UGAP value measurement box could be moved horizontally, but not vertically.
Two different UGAP measuring methods, including static single-frame multi-point measuring and dynamic multi-frame single-point measuring, were performed for each patient as clinical routine in our center. For static single-frame multi-point measuring, a frame of UGAP image was obtained after the patient held his/her breath, and 10 measurement boxes of 10 different positions were set within the sampling box. Then the corresponding values of 10 UGAP measurements were obtained (Fig. 1a). For dynamic multi-frame single-point measuring, continuous and dynamic multiple frames of UGAP images were obtained while the patient holding his/her breath (lasted for about 5 s). Among them, 10 frames of UGAP images were selected, and only one measurement box was set in each sampling box. Finally, the corresponding values of 10 UGAP measurements by dynamic multi-frame single point measuring were obtained (Fig. 1b). The UGAP values were expressed in dB/cm/MHz.
Fig. 1.
Two different measuring methods: a static single-frame multi-point measuring, b dynamic multi-frame single-point measuring
Quality control of UGAP measurements
No matter the static single-frame multi-point measuring or the dynamic multi-frame single-point measuring, the measurement boxes were set in the area with evenly distributed hepatic parenchyma, in where the quality map was uniformly filled in blue and the color difference of the attenuation map was low. A group of UGAP values were considered to be relatively reliable when the IQR/Med of them were ≤ 30%.
Determination of UGAP values
In this study, the UGAP values of the 1st–3rd, 1st–5th, 1st–7th and 1st–10th for each patient under the same measuring methods were defined as the results of measuring 3, 5, 7 and 10 times, respectively. And the corresponding median UGAP values were taken as the final UGAP values for the hepatic steatosis evaluation.
Statistical analysis
Mean ± standard deviation was used to describe the continuous quantitative data conforming to normal distribution, and median (IQR) was used to describe the continuous quantitative data not conforming to normal distribution. Counting data was expressed as absolute number.
The repeated-measures single factor analysis of variance was used to compare the results of 3, 5, 7, or 10 UGAP measurements under the same measuring method. To compare the IQR/Med of UGAP values obtained by various measuring times, the Friedman test was performed. Bonferroni statistical test was used for pairwise comparisons of data with intra-group differences. The differences in UGAP values between static single-frame multi-point measuring and dynamic multi-frame single-point measuring under the same measuring times (3, 5, 7 or 10 times) were compared using the paired t-test. Wilcoxon test for two paired samples was used to compare the differences of IQR/Med of UGAP values between the two measuring methods under the same measuring times (3, 5, 7 or 10 times).
Pearson correlation test was used to analyze the correlations of UGAP values obtained by the two measuring methods and different measuring times. The relationships among them were determined by Pearson’s correlation coefficient (r), which was classified as minimal (|r|< 0.2), weak (|r|= 0.2–0.4), moderate (|r|= 0.4–0.7), or strong (|r|≥ 0.7).
Variables were considered significant when P values were < 0.05. SPSS version 22.0 software (SPSS, Chicago, Illinois, USA) was used to perform data analysis.
Results
Basic information
A total of 214 patients underwent liver UGAP examinations in our hospital from September 2022 to December 2022. 206 patients were ultimately included in this study based on the inclusion and exclusion criteria. Eight patients were excluded because only static single-frame multi-point measuring or dynamic multi-frame single-point measuring was collected. There were 69 females and 137 males, with a mean age of 48.7 ± 13.8 years and a mean BMI of 25.7 ± 3.7 kg/m2. The demographic information, basic medical history and other information of all included patients are summarized in Table 1.
Table 1.
Baseline characteristics of all included cases
| Variable | Results |
|---|---|
| Patients | 206 |
| Gender (male/female) | 137/69 |
| Age (years) | 48.7 ± 13.8 |
| BMI (kg/m2) | 25.7 ± 3.7 |
| Diabetes mellitus (yes/no) | 68/138 |
| Alcoholics (yes/no) | 36/170 |
| Depth of skin-liver capsulea (mm) | 19.2 ± 4.0 |
aDepth of skin-liver capsule means the linear distance between the skin and the liver capsule when performing UGAP measurements
The IQR/Med of UGAP values obtained by the same measuring method increased gradually with the increase of the measuring times. Under the same measuring times, the IQR/Med of UGAP values of dynamic multi-frame single-point measuring method were significantly lower than those of static single-frame multi-point measuring method (P < 0.001). But all the IQR/Med of the included cases were less than 30%, indicating that the UGAP values of each measuring group were relatively reliable (Table 2).
Table 2.
IQR/Med of UGAP values under different measuring methods and measuring times
| IQR/Med | 3 times (%) | 5 times (%) | 7 times (%) | 10 times (%) | P |
|---|---|---|---|---|---|
| Static | 3.57b,c,d (2.34–5.83) | 4.58a,c,d (2.66–7.93) | 5.86a,b (4.11–8.83) | 6.37a,b (4.61–9.02) | < 0.001 |
| Dynamic | 2.44b,c,d (1.47–4.19) | 3.05a,c,d (1.52–4.92) | 3.63a,b (2.24–5.39) | 4.06a,b (2.73–5.89) | < 0.001 |
| P | < 0.001 | < 0.001 | < 0.001 | < 0.001 |
Static means static single-frame multi-point measuring; dynamic means dynamic multi-frame single-point measuring
aVersus 3 times under the same measuring method: P < 0.05
bVersus 5 times under the same measuring method: P < 0.05
cVersus 7 times under the same measuring method: P < 0.05
dVersus 10 times under the same measuring method: P < 0.05
Comparisons of UGAP values under the two measuring methods
No matter 3, 5, 7 or 10 measurements were taken, there was no statistical difference between the final UGAP values obtained by static single-frame multi-point measuring and those obtained by dynamic multi-frame single-point measuring (P = 0.689, P = 0.270, P = 0.298, P = 0.091) (Table 3).
Table 3.
Comparisons of UGAP values under different measuring times and measuring methods
| UGAP | 3 times (dB/cm/MHz) | 5 times (dB/cm/MHz) | 7 times (dB/cm/MHz) | 10 times (dB/cm/MHz) | P |
|---|---|---|---|---|---|
| Static | 0.695 ± 0.116 | 0.697 ± 0.114 | 0.697 ± 0.113 | 0.698 ± 0.113 | 0.554 |
| Dynamic | 0.694 ± 0.118 | 0.694 ± 0.118 | 0.693 ± 0.118 | 0.693 ± 0.119 | 0.916 |
| P | 0.689 | 0.270 | 0.298 | 0.091 | – |
Static means static single-frame multi-point measuring; dynamic means dynamic multi-frame single-point measuring
Comparisons of UGAP values under different measuring times
For static single-frame multi-point measuring, there was no statistically significant difference among the final UGAP values of 3, 5, 7 and 10 measurements (P = 0.554). For dynamic multi-frame single-point measuring, the final UGAP values of 3, 5, 7 and 10 measurements were not statistically different as well (P = 0.916) (Table 3).
Correlation analysis of UGAP values under the two measuring methods and different measuring times
In this study, Pearson correlation test was used to further evaluate the correlations among UGAP values under the two different measuring methods and different measuring times. The results were shown in Table 4 and Fig. 2. It showed that there were strong positive correlations between the static single-frame multi-point measuring and the dynamic multi-frame single-point measuring under different measuring times (3, 5, 7 or 10 times) (the correlation coefficients were 0.905–0.996, P < 0.001).
Table 4.
Table of correlation coefficients of UGAP values under different measuring methods and measuring times
| UGAP | Static 3 times | Static 5 times | Static 7 times | Static 10 times | Dynamic 3 times | Dynamic 5 times | Dynamic 7 times | Dynamic 10 times |
|---|---|---|---|---|---|---|---|---|
| Static 3 times | 1 | 0.978 | 0.968 | 0.960 | 0.908 | 0.908 | 0.908 | 0.905 |
| Static 5 times | 0.978 | 1 | 0.988 | 0.981 | 0.920 | 0.924 | 0.926 | 0.924 |
| Static 7 times | 0.968 | 0.988 | 1 | 0.991 | 0.922 | 0.924 | 0.924 | 0.923 |
| Static 10 times | 0.960 | 0.981 | 0.991 | 1 | 0.933 | 0.938 | 0.940 | 0.942 |
| Dynamic 3 times | 0.908 | 0.920 | 0.922 | 0.933 | 1 | 0.989 | 0.984 | 0.979 |
| Dynamic 5 times | 0.908 | 0.924 | 0.924 | 0.938 | 0.989 | 1 | 0.996 | 0.992 |
| Dynamic 7 times | 0.908 | 0.926 | 0.924 | 0.940 | 0.984 | 0.996 | 1 | 0.996 |
| Dynamic 10 times | 0.905 | 0.924 | 0.923 | 0.942 | 0.979 | 0.992 | 0.996 | 1 |
All P values above are < 0.001
Static means static single-frame multi-point measuring; Dynamic means dynamic multi-frame single-point measuring
Fig. 2.
Scatter plots of UGAP values of static single-frame multi-point measuring and dynamic multi-frame single point measuring. Static means static single-frame multi-point measuring; dynamic means dynamic multi-frame single-point measuring
Discussion
The attenuation of ultrasonic energy increases when the ultrasound passes through the organ with steatosis [22, 23]. Theoretically, it is relatively more objective and more accurate to reflect the degree of hepatic steatosis by calculating the energy attenuation [11]. The Controlled Attenuation Parameter (CAP) technology of FibroScan is the first technology used for hepatic steatosis quantification by this principle [3, 7]. It is noninvasive, quantifiable, and easy to operate, which is regarded as a good method for fatty liver screening and follow-up monitoring [8]. However, due to the absence of real-time images guidance, and the sampling frame could not be selected, the results of CAP might be affected by the intrahepatic vessels, bile ducts, FLLs, or uneven fatty liver disease [3, 8, 18]. Moreover, its sampling box is too small to provide a result with high accuracy and representative. Finally, the measuring results of CAP could be easily affected by the patient's own factors, such as obesity, ascites, and stenosis of intercostal space, leading to a relatively high rate of measuring failure [3, 8].
The attenuation imaging is a novel ultrasound-based technique embedded in different ultrasonic equipment, by calculating the energy attenuation to evaluate hepatic steatosis. UGAP is one of the representatives [3]. It quantifies hepatic steatosis under the real-time ultrasound guidance, with lower measuring failure rate and higher evaluating accuracy [8]. Hidekatsu Kuroda et al. found that compared with CAP, UGAP had higher accuracy in hepatic steatosis detecting and grading for NAFLD patients [16]. Another large cohort study using MRI-PDFF as the gold standard further validated its accuracy in the assessment of hepatic steatosis, and the diagnostic thresholds of the UGAP values were determined to distinguish different degrees of hepatic steatosis [13].
The manufacturer provided static single-frame multi-point measuring and dynamic multi-frame single-point measuring for UGAP measurements. For static single-frame multi-point measuring, one UGAP image was obtained, and multiple measurement boxes of different points could be put within a single image sampling box. For dynamic multi-frame single-point measuring, the operator was required to capture multiple frames of UGAP images dynamically and continuously while the patients holding their breaths. And then only one single UGAP measurement box was set within each sampling box of the selected images. In this study, there was no significant difference between the UGAP values of the two measuring methods (P > 0.05). And the UGAP values of the two methods showed significantly strong correlations (correlation coefficient 0.905–0.942, P < 0.001). These results suggested that the final UGAP values were similar, no matter static single-frame multi-point measuring or dynamic multi-frame single-point measuring was selected. As a result, we believed that in most cases, these two measuring methods were interchangeable with each other in clinical practice, and could be chosen according to different clinical scenarios or different operators’ preferences. As only one frame of image was required for static single-frame multi-point measuring, it might be more suitable for patients with poor respiratory coordination. In addition, it was important to note that the measurable area within the UGAP image depends more on the selected liver section due to the unchangeable size and depth for both sampling box and measurement box. The structures in the liver such as large vessels, diaphragm, liver capsule and FLLs should be excluded from the sampling box and measurement box as far as possible to ensure the accuracy of the measurements. For patients with small body size and small liver volume, it was often challenging to set multiple measurement boxes in a UGAP image. At this time, the dynamic multi-frame single-point measuring might be better for UGAP measurements.
Furthermore, this study compared the UGAP values of different measuring times (3, 5, 7, 10 times) under the same measuring method. The results showed that there was no statistical difference in terms of the final UGAP values of different measuring times (P = 0.554, P = 0.916). So from the perspective of simplifying examination process and shortening examination time, repeated 3 times of measurements for each patient might be enough. If it was for the purpose of scientific research, different repeated measuring times could be used according to the actual situation and needs. But it was believed that satisfactory repeatability and stability could be obtained in different measuring times.
There were some limitations in this study. Firstly, all the results in this study were based on the UGAP technology used for hepatic steatosis quantification, and the relevant conclusions might not be applicable to other attenuation imaging techniques, other ultrasonic equipment and other organs. Secondly, as the focus of this study was to explore the stability and reliability of UGAP technology under different measuring conditions, the included cases in this study were not strictly limited to NAFLD patients, and the accuracy of UGAP technology in assessing the degree of liver fatty liver was not analyzed.
In conclusion, the UGAP values obtained by static single-frame multi-point measuring and dynamic multi-frame single-point measuring are equivalent for hepatic steatosis quantification. Operators could choose different measuring methods according to different application scenarios or their own preferences. And repeated 3 measurements for each patient might be enough in daily clinical work.
Author contributions
All authors contributed to the study conception and design. Material preparation, data collection were performed by XZ and LL. Data analysis was performed by HL and SL. The first draft of the manuscript was written by XZ and LL. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Funding
This work was supported by the National Natural Science Foundation of China (82272011), the Natural Science Foundation of Guangdong Province, China (2022A1515012155), the Shenzhen Science and Technology Program (JCYJ20220530160208018), and the Futian Healthcare Research Project (FTWS2020022, FTWS2021071).
Data availability
No data have been fabricated or manipulated (including images) to support the conclusions. No data, text, or theories by others are presented as if they are the author's own. All co-authors have contributed sufficiently to the scientific work.
Declarations
Conflict of interest
The authors have no relevant financial or non-financial interests to disclose.
Ethical approval
This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the Eighth Affiliated Hospital of Sun Yat-sen University (Date: 21 June 2023/No. 2023–042-01).
Informed consent
Informed consent was waived by the Ethics Committee of the Eighth Affiliated Hospital of Sun Yat-sen University in view of the retrospective nature of the study and all the procedures being performed were part of the routine care.
Consent for publication
The manuscript has not been submitted elsewhere. The manuscript has not been published previously (partly or in full). It has not been split up into several parts and submitted to various journals or to one journal over time.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Xiaodan Zhang and Liping Luo contributed equally to this work and are co-first authors.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No data have been fabricated or manipulated (including images) to support the conclusions. No data, text, or theories by others are presented as if they are the author's own. All co-authors have contributed sufficiently to the scientific work.