Value of homodyned K distribution in ultrasound parametric imaging of hepatic steatosis: An animal study

Zhou, Zhuhuang; Fang, Jui; Cristea, Anca; Lin, Ying-Hsiu; Tsai, Yu-Wei; Wan, Yung‐Liang; Yeow, Kee‐Min; Ho, Ming-Chih; Tsui, Po-Hsiang

doi:10.1016/j.ultras.2019.106001

Cited by 28 publications

(31 citation statements)

References 59 publications

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“…The entropy value estimated from ultrasound backscattered signals increases with fat infiltration in the human liver [ 14 , 15 ], indicating a promising ability to diagnose moderate and severe hepatic steatosis [ 16 , 17 ]. The entropy of ultrasound backscattered signals increases because the distribution density of scatterers (fat droplets) in the liver tissue increases [ 8 ], resulting in changes in the backscattered statistics from pre-Rayleigh to Rayleigh distributions [ 8 , 16 ]. Because advanced hepatic steatosis is a critical factor in grading nonalcoholic steatohepatitis and fatty liver disease [ 36 ], evaluating moderate and severe grades has clinical significance.…”

Section: Discussionmentioning

confidence: 99%

“…The homodyned-K (HK) and Nakagami distribution models in particular provide a generalized description of ultrasound backscattered statistics measured from biological tissues [ 7 ]. Ultrasound parametric imaging based on the HK [ 8 , 9 ] and Nakagami models [ 10 , 11 ] has been shown to support the identification of hepatic steatosis. However, a prerequisite for using both methods is that ultrasound envelope data conform to the used distribution [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

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Clinical Value of Information Entropy Compared with Deep Learning for Ultrasound Grading of Hepatic Steatosis

Chen

Chao

Tsai

et al. 2020

Entropy

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Entropy is a quantitative measure of signal uncertainty and has been widely applied to ultrasound tissue characterization. Ultrasound assessment of hepatic steatosis typically involves a backscattered statistical analysis of signals based on information entropy. Deep learning extracts features for classification without any physical assumptions or considerations in acoustics. In this study, we assessed clinical values of information entropy and deep learning in the grading of hepatic steatosis. A total of 205 participants underwent ultrasound examinations. The image raw data were used for Shannon entropy imaging and for training and testing by the pretrained VGG-16 model, which has been employed for medical data analysis. The entropy imaging and VGG-16 model predictions were compared with histological examinations. The diagnostic performances in grading hepatic steatosis were evaluated using receiver operating characteristic (ROC) curve analysis and the DeLong test. The areas under the ROC curves when using the VGG-16 model to grade mild, moderate, and severe hepatic steatosis were 0.71, 0.75, and 0.88, respectively; those for entropy imaging were 0.68, 0.85, and 0.9, respectively. Ultrasound entropy, which varies with fatty infiltration in the liver, outperformed VGG-16 in identifying participants with moderate or severe hepatic steatosis (p < 0.05). The results indicated that physics-based information entropy for backscattering statistics analysis can be recommended for ultrasound diagnosis of hepatic steatosis, providing not only improved performance in grading but also clinical interpretations of hepatic steatosis.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Clinical Value of Information Entropy Compared with Deep Learning for Ultrasound Grading of Hepatic Steatosis

Chen

Chao

Tsai

et al. 2020

Entropy

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“…In this circumstance, the waveforms of the ultrasound backscattered signals are altered, and the corresponding statistical properties of echoes will be varied. [18][19][20][21][22]78 In addition to the Nakagami model, the homodyned K distribution is another important generalized statistical model that has a physical meaning. [11][12][13] Ultrasound homodyned K parametric imaging have been proposed for characterizing hepatic steatosis.…”

Section: Discussionmentioning

confidence: 99%

“…10 Quantitative ultrasound (QUS) has become an important technique for tissue characterization with quantified information, including spectral information, backscatter envelope statistics, scatterer properties, backscatter coefficient, and acoustic attenuation. [11][12][13][14][15][16][17][18][19][20][21][22][23] Backscatter coefficient has been investigated for liver fibrosis characterization. 24,25 Ultrasound backscatter envelope statistics parametric imaging is an important group of QUS techniques that have been applied to characterizing different kinds of tissue.…”

Section: Introductionmentioning

confidence: 99%

“…24,25 Ultrasound backscatter envelope statistics parametric imaging is an important group of QUS techniques that have been applied to characterizing different kinds of tissue. [11][12][13]15,[17][18][19][20][21][22] In particular, its application in liver fibrosis assessment has developed over the past two decades. However, a state-of-the-art review of ultrasound backscatter envelope statistics parametric imaging for liver fibrosis characterization has not been conducted.…”

Section: Introductionmentioning

confidence: 99%

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Ultrasound Backscatter Envelope Statistics Parametric Imaging for Liver Fibrosis Characterization: A Review

et al. 2020

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Early detection and diagnosis of liver fibrosis is of critical importance. Currently the gold standard for diagnosing liver fibrosis is biopsy. However, liver biopsy is invasive and associated with sampling errors and can lead to complications such as bleeding. Therefore, developing noninvasive imaging techniques for assessing liver fibrosis is of clinical value. Ultrasound has become the first-line tool for the management of chronic liver diseases. However, the commonly used B-mode ultrasound is qualitative and can cause interobserver or intraobserver difference. Ultrasound backscatter envelope statistics parametric imaging is an important group of quantitative ultrasound techniques that have been applied to characterizing different kinds of tissue. However, a state-of-the-art review of ultrasound backscatter envelope statistics parametric imaging for liver fibrosis characterization has not been conducted. In this paper, we focused on the development of ultrasound backscatter envelope statistics parametric imaging techniques for assessing liver fibrosis from 1998 to September 2019. We classified these techniques into six categories: constant false alarm rate, fiber structure extraction technique, acoustic structure quantification, quantile–quantile probability plot, the multi-Rayleigh model, and the Nakagami model. We presented the theoretical background and algorithms for liver fibrosis assessment by ultrasound backscatter envelope statistics parametric imaging. Then, the specific applications of ultrasound backscatter envelope statistics parametric imaging techniques to liver fibrosis evaluation were reviewed and analyzed. Finally, the pros and cons of each technique were discussed, and the future development was suggested.

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Association of Backscattered Ultrasonographic Imaging of the Tongue With Severity of Obstructive Sleep Apnea in Adults

Liu

Bosschieter

Abdelwahab

et al. 2023

JAMA Otolaryngol Head Neck Surg

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ImportanceDetermining interventions to manage obstructive sleep apnea (OSA) depends on clinical examination, polysomnography (PSG) results, and imaging analysis. There remains the need of a noninvasive and cost-effective way to correlate relevant upper airway anatomy with severity of OSA to direct treatment and optimize outcome.ObjectiveTo determine whether backscattered ultrasonographic imaging (BUI) analysis of the tongue is associated with severity of OSA in adults.Design, Setting, and ParticipantsIn this prospective, single-center, diagnostic study of a consecutive series of patients (aged ≥18 years) at a sleep surgery clinic, the 89 included patients had a PSG within 3 years at the time of ultrasonography and BUI analysis between July 2020 and March 2022. Patients were excluded if body mass index had changed more than 10% since time of PSG. A standardized submental ultrasonographic scan with laser alignment was used with B-mode and BUI analysis applied to the tongue. The B-mode and BUI intensity were associated with the apnea-hypopnea index (AHI), a measure of severity of apnea from normal (no OSA) to severe OSA.ExposuresUltrasonography and PSG.Main Outcomes and MeasuresThe main outcomes were BUI parameters and their association with AHI value.ResultsEighty-nine patients were included between July 2020 and March 2022. A total of 70 (78.7%) male patients were included; and distribution by race and ethnicity was 46 (52%) White participants, 22 (25%) Asian participants, and 2 (2%) African American participants, and 19 (21%) others. Median (IQR) age was 37.0 (29.0-48.3) years; median (IQR) BMI was 25.3 (23.2-29.8); and median (IQR) AHI was 11.1 (5.6-23.1) events per hour. At the middle to posterior tongue region, the 4 OSA severity levels explained a significant portion of the BUI variance (η2 = 0.153-0.236), and a significant difference in BUI values was found between the subgroups with AHI values of less than 15 (no OSA and mild OSA) and greater than or equal to 15 (moderate OSA and severe OSA) events per hour. The echo intensity showed no significant differences. The BUI values showed a positive association with AHI, with a Spearman correlation coefficient of up to 0.43. Higher BUI values remained associated with higher AHI after correction for the covariates of BMI and age.Conclusions and RelevanceIn this prospective diagnostic study, standardized BUI analysis of the tongue was associated with OSA severity. With the practicality of ultrasonography, this analysis is pivotal in connecting anatomy with physiology in treatment planning for patients with OSA.

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Value of homodyned K distribution in ultrasound parametric imaging of hepatic steatosis: An animal study

Cited by 28 publications

References 59 publications

Clinical Value of Information Entropy Compared with Deep Learning for Ultrasound Grading of Hepatic Steatosis

Clinical Value of Information Entropy Compared with Deep Learning for Ultrasound Grading of Hepatic Steatosis

Ultrasound Backscatter Envelope Statistics Parametric Imaging for Liver Fibrosis Characterization: A Review

Association of Backscattered Ultrasonographic Imaging of the Tongue With Severity of Obstructive Sleep Apnea in Adults

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