Ultrasound Attenuation Estimation in Harmonic Imaging for Robust Fatty Liver Detection

Gong, Ping; Zhou, Chenyun; Song, Pengfei; Huang, Chengwu; Lok, U-Wai; Tang, Shanshan; Watt, Kymberly D.; Callstrom, Matthew R.; Chen, Shigao

doi:10.1016/j.ultrasmedbio.2020.07.006

Cited by 15 publications

(3 citation statements)

References 35 publications

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“…Our H-scan analysis of attenuation within the three liver diseases of metastatic tumor, fibrosis, and steatosis showed consistent with the previous studies. For normal livers, = 0.5 dB/MHz/cm; steatosis has a higher (>0.7, [33][34][35][36] in this study = 0.74 ± 0.04 dB∕MHz∕cm), and fibrosis was reported to have < 0.45 32,33 (this study = 0.40 ± 0.02 dB∕MHz∕cm). Regarding the metastatic tumor model, our estimated attenuation ( = 0.30 ± 0.04 dB/MHz/cm) is less than the normal and could be due to leaky tumor vessels and increase in fluid.…”

Section: Discussionmentioning

confidence: 62%

“…The H‐scan analysis investigated their ultrasound echoes and resulted in meaningful features, identifying liver tissues’ characteristics of attenuation and structure provided by attenuation coefficient

α

(dB/MHz/cm) and %blue , respectively. There has been a long history of research in measuring

α

, employing traditional 32‐34 or currently developed 35,36 methods. Our H‐scan analysis of attenuation within the three liver diseases of metastatic tumor, fibrosis, and steatosis showed consistent

α

with the previous studies.…”

Section: Discussionmentioning

confidence: 99%

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H‐scan trajectories indicate the progression of specific diseases

Baek

Parker

2021

Medical Physics

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Purpose The ability of ultrasound to assess pathology is increasing with the development of quantitative parameters. Among these are a set of parameters derived from the recent H‐scan analysis of subresolvable scattering. The emergence of these quantitative measures of tissue/ultrasound interactions now enables a study of the unique trajectories of multiparametric features in multidimensional space, representing the progression of specific diseases over time. We develop the mathematical and visual tools that are effective for classifying, quantifying, and visualizing the steady progression of several diseases from independent studies, all within a uniform framework. Methods After applying the H‐scan analysis of ultrasound echoes, we trained a support vector machine (SVM) to classify the unique trajectories of progressive liver disease from fibrosis, steatosis, and pancreatic ductal adenocarcinoma (PDAC) metastasis. Our approaches include the development of trajectory maps and disease‐specific color imaging stains. Results The multidimensional SVM image classification reached 100% accuracy across the three different studies. Conclusion H‐scan trajectories can be useful to track the progression of multiple classes of diseases, improving diagnosis, staging, and assessing the response to therapy.

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Section: Discussionmentioning

confidence: 62%

α

(dB/MHz/cm) and %blue , respectively. There has been a long history of research in measuring

α

α

with the previous studies.…”

Section: Discussionmentioning

confidence: 99%

H‐scan trajectories indicate the progression of specific diseases

Baek

Parker

2021

Medical Physics

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“…This study found that fat accumulation leads to an increase in attenuation (Figure 4). Previous studies 35–38 also reported higher attenuation in steatosis compared to normal livers. Third, backscattered US echo displayed in B‐mode intensity was analyzed by measuring the intensity of B‐mode envelope data and fitting the envelope data using a Burr distribution.…”

Section: Discussionmentioning

confidence: 69%

Multiparametric ultrasound imaging for early‐stage steatosis: Comparison with magnetic resonance imaging‐based proton density fat fraction

Baek,

Basavarajappa,

Margolis

et al. 2023

Medical Physics

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BackgroundThe prevalence of liver diseases, especially steatosis, requires a more convenient and noninvasive tool for liver diagnosis, which can be a surrogate for the gold standard biopsy. Magnetic resonance (MR) measurement offers potential, however ultrasound (US) has better accessibility than MR.PurposeThis study aims to suggest a multiparametric US approach which demonstrates better quantification and imaging performance than MR imaging‐based proton density fat fraction (MRI‐PDFF) for hepatic steatosis assessment.MethodsWe investigated early‐stage steatosis to evaluate our approach. An in vivo (within the living) animal study was performed. Fat inclusions were accumulated in the animal livers by feeding a methionine and choline deficient (MCD) diet for 2 weeks. The animals (n = 19) underwent US and MR imaging, and then their livers were excised for histological staining. From the US, MR, and histology images, fat accumulation levels were measured and compared: multiple US parameters; MRI‐PDFF; histology fat percentages. Seven individual US parameters were extracted using B‐mode measurement, Burr distribution estimation, attenuation estimation, H‐scan analysis, and shear wave elastography. Feature selection was performed, and the selected US features were combined, providing quantification of fat accumulation. The combined parameter was used for visualizing the localized probability of fat accumulation level in the liver; This procedure is known as disease‐specific imaging (DSI).ResultsThe combined US parameter can sensitively assess fat accumulation levels, which is highly correlated with histology fat percentage (R = 0.93, p‐value < 0.05) and outperforms the correlation between MRI‐PDFF and histology (R = 0.89, p‐value < 0.05). Although the seven individual US parameters showed lower correlation with histology compared to MRI‐PDFF, the multiparametric analysis enabled US to outperform MR. Furthermore, this approach allowed DSI to detect and display gradual increases in fat accumulation. From the imaging output, we measured the color‐highlighted area representing fatty tissues, and the fat fraction obtained from DSI and histology showed strong agreement (R = 0.93, p‐value < 0.05).ConclusionsWe demonstrated that fat quantification utilizing a combination of multiple US parameters achieved higher performance than MRI‐PDFF; therefore, our multiparametric analysis successfully combined selected features for hepatic steatosis characterization. We anticipate clinical use of our proposed multiparametric US analysis, which could be beneficial in assessing steatosis in humans.

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Novel Quantitative Liver Steatosis Assessment Method With Ultrasound Harmonic Imaging

Gong,

Zhang,

Huang

et al. 2024

J of Ultrasound Medicine

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ObjectivesMetabolic dysfunction‐associated steatotic liver disease (MASLD) is the most prevalent liver disorder in Western countries, with approximately 20%–30% of the MASLD patients progressing to severe stages. There is an urgent need for noninvasive, cost‐effective, widely accessible, and precise biomarkers to evaluate liver steatosis. This study aims to assess and compare the diagnostic performance of a novel reference frequency method‐based ultrasound attenuation coefficient estimation (ACE) in both fundamental (RFM‐ACE‐FI) and harmonic (RFM‐ACE‐HI) imaging for detecting and grading liver steatosis.MethodsAn Institutional Review Board‐approved prospective study was carried out between December 2018 and October 2022. A total number of 130 subjects were enrolled in the study. The correlation between RFM‐ACE‐HI values and magnetic resonance imaging proton density fat fraction (MRI‐PDFF), as well as between RFM‐ACE‐FI values and MRI‐PDFF were calculated. The diagnostic performance of RFM‐ACE‐FI and RFM‐ACE‐HI was evaluated using receiver operating characteristic (ROC) curve analysis, as compared to MRI‐PDFF. The reproducibility of RFM‐ACE‐HI was assessed by interobserver agreement between two sonographers.ResultsA strong correlation was observed between RFM‐ACE‐HI and MRI‐PDFF, with R = 0.88 (95% confidence interval [CI]: 0.83–0.92; P < .001), while the correlation between RFM‐ACE‐FI and MRI‐PDFF was R = 0.65 (95% CI: 0.50–0.76; P < .001). The area under the ROC (AUROC) curve for RFM‐ACE‐HI in staging liver steatosis grades of S ≥ 1 and S ≥ 2 was 0.97 (95% CI: 0.91–0.99; P < .001) and 0.98 (95% CI: 0.93–1.00; P < .001), respectively, and 0.76 (95% CI: 0.65–0.85) and 0.80 (95% CI: 0.70–0.88) for RFM‐ACE‐FI, respectively. Great reproducibility was achieved for RFM‐ACE‐HI, with an interobserver agreement of R = 0.97 (95% CI: 0.94–0.99; P < .001).ConclusionsThe novel RFM‐ACE‐HI method offered high liver steatosis diagnostic accuracy and reproducibility, which has important clinical implications for early disease intervention and treatment evaluation.

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Ultrasound Attenuation Estimation in Harmonic Imaging for Robust Fatty Liver Detection

Cited by 15 publications

References 35 publications

H‐scan trajectories indicate the progression of specific diseases

H‐scan trajectories indicate the progression of specific diseases

Multiparametric ultrasound imaging for early‐stage steatosis: Comparison with magnetic resonance imaging‐based proton density fat fraction

Novel Quantitative Liver Steatosis Assessment Method With Ultrasound Harmonic Imaging

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