Diagnostic performance of ultrasound attenuation imaging for assessing low-grade hepatic steatosis

Abstract Background As part of a prospective clinical study, the degree of hepatic fatty degeneration was quantified in a patient population with nonalcoholic fatty liver disease and sonographically diagnosed with hepatic steatosis using attenuation imaging. Methods A total of 113 patients with hepatic steatosis were examined, of whom 35 showed focal fatty sparing. Patients with the condition after right nephrectomy, other known liver diseases, and relevant alcohol consumption were excluded from the evaluation. B-scan sonography and sonographic quantification of steatosis content using attenuation imaging (Aplio i800 Canon Medical Systems) were performed. Attenuation imaging is a new ultrasound-based measurement technique that allows objective detection and quantification of hepatic steatosis. Results The prevalence of focal fatty sparing was 31.0% in the patient population examined. Patients with focal fatty sparing showed a statistically significantly higher attenuation coefficient in contrast to patients without focal fatty sparing (0.79 ± 0.10 vs. 0.66 ± 0.09 dB/cm/MHz, p < 0.0001). Conclusion Detection of focal fatty sparing is associated with an increased attenuation coefficient and is thus an expression of higher-grade hepatic fatty degeneration. Patients with focal fatty sparing are more often male and have a higher BMI and a larger liver than patients with nonalcoholic fatty liver disease without focal fatty sparing.

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Value of Ultrasound Attenuation Index in Noninvasive Quantitative Estimation of Hepatic Steatosis

Ultrasound in Medicine & Biology ◽

10.1016/j.ultrasmedbio.2013.02.380 ◽

2013 ◽

Vol 39 (5) ◽

pp. S80-S81 ◽

Cited By ~ 1

Author(s):

K.W. Kim ◽

H.J. Kwon ◽

S.J. Lee ◽

S.Y. Kim ◽

J.S. Lee ◽

...

Keyword(s):

Hepatic Steatosis ◽

Quantitative Estimation ◽

Ultrasound Attenuation ◽

Attenuation Index

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Diagnostic Performance of Oncuria™, a Urinalysis Test for Bladder Cancer

10.21203/rs.3.rs-253377/v1 ◽

2021 ◽

Author(s):

Yosuke Hirasawa ◽

Ian Pagano ◽

Runpu Chen ◽

Yijun Sun ◽

Yunfeng Dai ◽

...

Keyword(s):

Bladder Cancer ◽

Diagnostic Performance ◽

Clinical Laboratory ◽

Demographic Data ◽

Roc Curves ◽

Low Grade ◽

Linear Discriminant ◽

Non Invasive ◽

Diagnostic Panel ◽

Parallel Measurement

Abstract Background: Due to insufficient accuracy, urine-based assays currently have a limited role in the management of patients with bladder cancer. The identification of multiplex molecular signatures associated with disease has the potential to address this deficiency and to assist with accurate, non-invasive diagnosis and monitoring. Methods: To evaluate the performance of Oncuria™, a multiplex immunoassay for bladder detection in voided urine samples. The test was evaluated in a multi-institutional cohort of 362 prospectively collected subjects presenting for bladder cancer evaluation. The parallel measurement of 10 biomarkers (A1AT, APOE, ANG, CA9, IL8, MMP9, MMP10, PAI1, SDC1 and VEGFA) was performed in an independent clinical laboratory. The ability of the test to identify patients harboring bladder cancer was assessed. Bladder cancer status was confirmed by cystoscopy and tissue biopsy. The association of biomarkers and demographic factors was evaluated using linear discriminant analysis (LDA) and predictive models were derived using supervised learning and cross-validation analyses. Diagnostic performance was assessed using ROC curves.Results: The combination of the 10 biomarkers provided an AUROC 0.93 [95% CI: 0.87 – 0.98], outperforming any single biomarker. The addition of demographic data (age, sex, and race) into a hybrid signature improved the diagnostic performance AUROC 0.95 [95% CI: 0.90 – 1.00]. The hybrid signature achieved an overall sensitivity of 0.93, specificity of 0.93, PPV of 0.65 and NPV of 0.99 for bladder cancer classification. Sensitivity values of the diagnostic panel for high-grade bladder cancer, low-grade bladder cancer, MIBC and NMIBC were 0.94, 0.89, 0.97 and 0.93, respectively. Conclusions: Urinary levels of a biomarker panel enabled the accurate discrimination of bladder cancer patients and controls. The multiplex Oncuria™ test can achieve the efficient and accurate detection and monitoring of bladder cancer in a non-invasive patient setting.

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Role of the spleen in the development of steatohepatitis in high-fat-diet-induced obese rats

Experimental Biology and Medicine ◽

10.1258/ebm.2011.011230 ◽

2012 ◽

Vol 237 (4) ◽

pp. 461-470 ◽

Cited By ~ 4

Author(s):

Megumi Inoue ◽

Koro Gotoh ◽

Masataka Seike ◽

Takayuki Masaki ◽

Koichi Honda ◽

...

Keyword(s):

Fatty Liver ◽

Hepatic Steatosis ◽

Liver Tissue ◽

Sham Operation ◽

Low Grade ◽

Sprague Dawley ◽

High Fat ◽

Obese Rats ◽

Inflammatory State

Obesity is considered a systemic low-grade inflammatory state. Although the spleen is the main immune organ with a close anatomical relationship with the liver, its role in the progression of fatty liver disease remains uncertain. Therefore, we sought to clarify the functional role of the spleen in the development of steatohepatitis in high-fat (HF)-diet-induced obese rats. Male Sprague-Dawley rats were fed HF food and divided into two groups, a splenectomy (SPX) group and a sham-operation (Sham) group. The liver and abdominal white adipose tissue (WAT) were removed one and six months after surgery, and we evaluated the effects of SPX on WAT and HF-induced fatty liver. SPX rats exhibited worse dyslipidemia and inflammatory changes in WAT one month after surgery. Hepatic steatosis and inflammation were accelerated by SPX, based on the time after surgery. At one month after surgery, the tissue triglyceride content increased in SPX rats, compared with Sham controls ( P < 0.05). The liver histology also showed a worsening of steatosis in those rats. At six months after SPX, dramatic inflammatory and fibrotic changes were observed in liver tissue sections. Hepatic carnitine palmitoyltransferase-1 was suppressed at one and six months after SPX ( P < 0.05 for each). WAT and liver tissue levels of inflammatory markers such as tumor necrosis factor- α, and the expression of Kupffer cells were all increased at six months in SPX rats, compared with Sham controls ( P < 0.05 for each). Our results indicate that the preservation of the spleen contributes to the prevention of the progression of hepatic steatosis to steatohepatitis in obese rats.

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Vanishing washout of hepatocellular carcinoma according to the presence of hepatic steatosis: diagnostic performance of CT and MRI

European Radiology ◽

10.1007/s00330-020-07438-9 ◽

2020 ◽

Author(s):

Ji Hye Min ◽

Tae Wook Kang ◽

Yeon-Yoon Kim ◽

Dong Ik Cha ◽

Young Kon Kim ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Hepatic Steatosis ◽

Diagnostic Performance ◽

Ct And Mri

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Diagnostic Accuracy of Machine Learning-Based Radiomics in Grading Gliomas: Systematic Review and Meta-Analysis

Contrast Media & Molecular Imaging ◽

10.1155/2020/2127062 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Curtis K. Sohn ◽

Sotirios Bisdas

Keyword(s):

Machine Learning ◽

Diagnostic Accuracy ◽

Diagnostic Performance ◽

Meta Analysis ◽

Total Sample ◽

Low Grade ◽

Sample Sizes ◽

Summary Receiver Operating Characteristic ◽

Pubmed Database ◽

Sensitivity Specificity

Purpose. This study aimed to estimate the diagnostic accuracy of machine learning- (ML-) based radiomics in differentiating high-grade gliomas (HGG) from low-grade gliomas (LGG) and to identify potential covariates that could affect the diagnostic accuracy of ML-based radiomic analysis in classifying gliomas. Method. A primary literature search of the PubMed database was conducted to find all related literatures in English between January 1, 2009, and May 1, 2020, with combining synonyms for “machine learning,” “glioma,” and “radiomics.” Five retrospective designed original articles including LGG and HGG subjects were chosen. Pooled sensitivity, specificity, their 95% confidence interval, area under curve (AUC), and hierarchical summary receiver-operating characteristic (HSROC) models were obtained. Result. The pooled sensitivity when diagnosing HGG was higher (96% (95% CI: 0.93, 0.98)) than the specificity when diagnosing LGG (90% (95% CI 0.85, 0.93)). Heterogeneity was observed in both sensitivity and specificity. Metaregression confirmed the heterogeneity in sample sizes ( p = 0.05 ), imaging sequence types ( p = 0.02 ), and data sources ( p = 0.01 ), but not for the inclusion of the testing set ( p = 0.19 ), feature extraction number ( p = 0.36 ), and selection of feature number ( p = 0.18 ). The results of subgroup analysis indicate that sample sizes of more than 100 and feature selection numbers less than the total sample size positively affected the diagnostic performance in differentiating HGG from LGG. Conclusion. This study demonstrates the excellent diagnostic performance of ML-based radiomics in differentiating HGG from LGG.

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