Learning curve of liver stiffness measurement using a new hybrid machine composed of transient elastography interfaced with ultrasound

Inter-platform Variability of Liver Elastography: Pairwise Comparisons of Four Devices

This study was aimed at determining whether liver stiffness measurements by 2-D shear wave elastography using GE's (2D-SWE-GE) and Canon's (2D-SWE-Canon) newest apparatus and vibration-controlled transient elastography (VCTE) share the same distribution of values compared with Hologic Supersonic Imagine (2D-SWE-SSI). In participants with chronic liver disease recruited in two university centers from August 2020 to February 2021, liver stiffness was measured the same day by the same operator with 2D-SWE-SSI plus one of the following devices: 2D-SWE-GE (n = 314), 2D-SWE-Canon (n = 311), and VCTE-M probe (n = 812). VCTE-M and 2D-SWE-SSI values shared the highest correlation and concordance coefficients (0.933 and 0.920, respectively) and a coefficient of variation below 20%, whatever the range of values. 2D-SWE-GE had the lowest variations, with 2D-SWE-SSI values below 13 kPa. However, both 2D-SWE-GE and 2D-SWE-Canon exhibited a frank underestimation of the high percentiles' 2D-SWE-SSI values with coefficients of variation of -21.7% and -25.8% from 13- to 17-kPa values, and -44.3% and -32.4% from 17-kPa values, respectively. In conclusion, knowledge of the vendor-specific distribution of values is mandatory for interpreting results obtained with different machines. If all four techniques behave closely in low values allowing excluding advanced chronic liver diseases in larger populations, discrepancies are observed in high percentile values.

Diagnostic Performance of Attenuation to Stage Liver Steatosis with MRI Proton Density Fat Fraction as Reference: A Prospective Comparison of Three US Machines

Background US tools to quantify liver fat content have recently been made clinically available by different vendors, but comparative data on their accuracy are lacking. Purpose To compare the diagnostic performances of the attenuation parameters of US machines from three different manufacturers (vendors 1, 2, and 3) in participants who underwent liver fat quantification with the MRI-derived proton density fat fraction (PDFF). Materials and Methods From July 2020 to June 2021, consecutive participants with chronic liver disease were enrolled in this prospective single-center study and underwent MRI PDFF quantification (reference standard) and US on the same day. US was performed with two different machines from among three vendors assessed. Areas under the receiver operating characteristic curve (AUCs) for the staging of liver steatosis (MRI PDFF: ≥5.5% for grade ≥S1 and ≥15.5% for grade ≥S2) were calculated in test and validation samples and then compared between vendors in the study sample. Results A total of 534 participants (mean age, 60 years ± 13 [SD]; 320 men) were evaluated. Failure of measurements occurred in less than 1% of participants for all vendors. Correlation coefficients with the MRI PDFF were 0.71, 0.73, and 0.54 for the attenuation coefficients of vendors 1, 2, and 3, respectively. In the test sample, AUCs for diagnosis of steatosis grade S1 and higher and grade S2 and higher were 0.89 and 0.93 for vendor 1 attenuation, 0.88 and 0.92 for vendor 2 attenuation, and 0.79 and 0.79 for vendor 3 attenuation, respectively. In the validation sample, a threshold value of 0.65 for vendor 1 and 0.66 for vendor 2 yielded sensitivity of 77% and 84% and specificity of 78% and 85%, respectively, for diagnosis of grade S1 and higher. Vendor 2 attenuation had greater AUCs than vendor 3 attenuation (P = .001 and P = .003) for diagnosis of grade S1 and higher and grade S2 and higher, respectively, and vender 2 had greater AUCs for attenuation than vendor 1 for diagnosis of grade S2 and higher (P = .04). For all vendors, attenuation was not associated with liver stiffness (correlation coefficients <0.05). Conclusion To stage liver steatosis, attenuation coefficient accuracy varied among US devices across vendors when using MRI proton density fat fraction quantification as the reference standard, with some demonstrating excellent diagnostic performance and similar cutoff values. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Dubinsky in this issue.

The Future Role of Machine Learning in Clinical Transplantation

The use of artificial intelligence and machine learning (ML) has revolutionized our daily lives and will soon be instrumental in healthcare delivery. The rise of ML is due to multiple factors: increasing access to massive datasets, exponential increases in processing power, and key algorithmic developments that allow ML models to tackle increasingly challenging questions. Progressively more transplantation research is exploring the potential utility of ML models throughout the patient journey, although this has not yet widely transitioned into the clinical domain. In this review, we explore common approaches used in ML in solid organ clinical transplantation and consider opportunities for ML to help clinicians and patients. We discuss ways in which ML can aid leverage of large complex datasets, generate cutting-edge prediction models, perform clinical image analysis, discover novel markers in molecular data, and fuse datasets to generate novel insights in modern transplantation practice. We focus on key areas in transplantation in which ML is driving progress, explore the future potential roles of ML, and discuss the challenges and limitations of these powerful tools.

Trends of Liver Stiffness in Inflammatory Bowel Disease with Chronic Hepatitis C

Concomitant inflammatory bowel disease (IBD) and hepatitis C virus (HCV) infection is a relevant comorbidity since IBD itself exposes to a high risk of liver damage. We aimed to evaluate liver stiffness (LS) in IBD-HCV after antiviral treatment. We enrolled IBD patients with HCV. All patients at baseline underwent LS measurement by elastography. Patients who were eligible for antiviral therapy received direct antiviral agents (DAAs) and sustained viral response was evaluated at the 12th week. A control group was selected within IBD patients without HCV. One year later, all IBD-HCV patients and controls repeated LS measurement. Twenty-four IBD-HCV patients and 24 IBD controls entered the study. Only twelve out of 24 received DAAs and all achieved sustained viral response (SVR). All IBD subjects were in remission at enrollment and maintained remission for one year. After one year, IBD patients who eradicated HCV passed from a liver stiffness of 8.5 ± 6.2 kPa to 7.1 ± 3.9, p = 0.13. IBD patients who did not eradicate HCV worsened liver stiffness: from 7.6 ± 4.4 to 8.6 ± 4.6, p = 0.01. In the IBD control group, stiffness decreased from 7.8 ± 4.4 to 6.0 ± 3.1, p < 0.001. In conclusion, HCV eradication is able to stop the evolution of liver fibrosis in IBD, while failure to treat may lead to its progression. A stable IBD remission may improve LS even in non-infected subjects.