scholarly journals Ultrasound Stratification of Hepatic Steatosis Using Hepatorenal Index

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1443
Author(s):  
Stephen I. Johnson ◽  
Daniel Fort ◽  
Kenneth J. Shortt ◽  
George Therapondos ◽  
Gretchen E. Galliano ◽  
...  
Keyword(s):  
Liver Biopsy ◽  
Positive Predictive Value ◽  
Hepatic Steatosis ◽  
Retrospective Review ◽  
Predictive Value ◽  
Liver Steatosis ◽  
Liver Biopsies ◽  
Biopsy Methods

Hepatorenal index (HRI) has been shown to be an effective, noninvasive ultrasound tool to screen patients for those with or without >5% hepatic steatosis. Objective: The aim of this study was to further refine this HRI tool in order to stratify patients according to their degree of liver steatosis and give direction as to which patients should undergo random liver biopsy. Methods: We conducted a retrospective review of 267 consecutive patients from 2015 to 2017 who had abdominal ultrasounds and a subsequent random liver biopsy within one month. The HRI was calculated and compared with the percent steatosis as assessed by histology. Results: An HRI of ≤1.17 corresponds with >95% positive predictive value of ≤5% steatosis. Between HRI values 1.18 and 1.39, performance of steatosis prediction is mixed. However, for values <1.37 there is an increased likelihood of steatosis ≤5% and likewise the opposite for values >1.37. An HRI of ≥1.4 corresponds with >95% positive predictive value of ≥10% steatosis. Conclusion: HRI is an accurate noninvasive tool to quantify degree of steatosis and guide who should undergo random liver biopsy, potentially significantly reducing the total number of necessary liver biopsies.

The “Death Diamond”: Death beyond Trauma

2019 ◽  
Vol 85 (7) ◽  
pp. 757-760
Author(s):  
Michael Farrell ◽  
Thomas Marconi ◽  
John Getchell ◽  
Raymond Green ◽  
Mark Cipolle ◽  
...  
Keyword(s):  
Positive Predictive Value ◽  
Retrospective Review ◽  
Predictive Value ◽  
Median Survival Time ◽  
Trauma Patients ◽  
Invasive Procedures ◽  
Multicenter Studies ◽  
Trauma Population ◽  
Futile Care ◽  
Prognostic Implications

Thromboelastography (TEG) has become a critical tool for the diagnosis, assessment, and management of hyperfibrinolysis and coagulopathy in trauma. In 2015, Chapman et al. of the Denver group coined the term “Death Diamond” (DD) to describe a TEG tracing identified in a unique trauma population. The DD was associated with a 100 per cent positive predictive value for mortality. Given the potential prognostic implications and resource savings associated with validating the DD as a marker of futile care, we sought to further evaluate DD outcomes. A retrospective review of 6850 TEGs, 34 patients (24 trauma and 10 nontrauma), displayed a DD tracing. Through invasive procedures and transfusions, nine DD tracing “normalized,” but, ultimately, this did not impact the outcome because the DD had a positive predictive value of 100 per cent for mortality in both populations. The median survival time in trauma patients was two hours compared with seven hours in nontrauma patients. Overall, this study further validates the predictive value of the DD in a trauma population while also serving as an assessment of the DD in a nontrauma population. Given these findings, a DD may prove to be an indicator of futile care. Further multicenter studies should be conducted to confirm these results.

The role of prostatic urethral biopsies as a staging tool for bladder cancer

2016 ◽  
Vol 10 (4) ◽  
pp. 359-363
Author(s):  
Adam W Nelson ◽  
Richard A Parker ◽  
Karan Wadhwa ◽  
Alexandra J Colquhoun ◽  
William H Turner
Keyword(s):  
Bladder Cancer ◽  
Positive Predictive Value ◽  
Retrospective Review ◽  
Predictive Value ◽  
Frozen Section ◽  
Prostatic Urethra ◽  
Published Data ◽  
Apical Margin ◽  
Single Centre

Objective: To determine the incidence of prostatic urethral involvement in our patient population and how prostatic urethral biopsy correlates with final cystectomy pathology. Patients and methods: We conducted a retrospective review of prostatic urethral biopsies (PUB) performed between February 2008 and April 2012 in a single centre. PUB pathology was correlated with cystectomy pathology. Results: PUB was undergone by 172 patients with a median age of 70 years (range: 37–84 years): There were 35 (20%) patients having a positive PUB and 137 (80%) who were negative. Of the 94 patients who underwent cystectomy, we found that when the entire prostatic urethra was sectioned, 20 (21%) patients had cancer in the prostatic urethra. Cancer was found in 17 (77%) of 22 patients with a positive PUB and in three (4%) out of the 72 with a negative PUB (positive predictive value (PPV) 77%, negative predictive value (NPV) 96%, sensitivity 85% and specificity 93%). In all 94 patients, the prostatic apical margin was negative. Conclusion: Disease in the prostatic urethra affected 20% of patients, consistent with published data. Prostatic urethral apical margins were all negative. Intra-operative frozen section would have missed cancer in the 20 patients with prostatic urethral cancer, whereas PUB identified 17 (85%) of the 20 patients. These data confirm the value of using PUB before cystectomy, in our UK population.

scholarly journals Application of artificial intelligence in chronic liver diseases: a systematic review and meta-analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Pakanat Decharatanachart ◽  
Roongruedee Chaiteerakij ◽  
Thodsawit Tiyarattanachai ◽  
Sombat Treeprasertsuk
Keyword(s):  
Artificial Intelligence ◽  
Liver Fibrosis ◽  
Liver Biopsy ◽  
Predictive Value ◽  
Characteristic Curve ◽  
Liver Steatosis ◽  
Diagnostic Tools ◽  
Summary Receiver Operating Characteristic ◽  
Subgroup Analyses ◽  
Sensitivity Specificity

Abstract Background The gold standard for the diagnosis of liver fibrosis and nonalcoholic fatty liver disease (NAFLD) is liver biopsy. Various noninvasive modalities, e.g., ultrasonography, elastography and clinical predictive scores, have been used as alternatives to liver biopsy, with limited performance. Recently, artificial intelligence (AI) models have been developed and integrated into noninvasive diagnostic tools to improve their performance. Methods We systematically searched for studies on AI-assisted diagnosis of liver fibrosis and NAFLD on MEDLINE, Scopus, Web of Science and Google Scholar. The pooled sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic odds ratio (DOR) with their 95% confidence intervals (95% CIs) were calculated using a random effects model. A summary receiver operating characteristic curve and the area under the curve was generated to determine the diagnostic accuracy of the AI-assisted system. Subgroup analyses by diagnostic modalities, population and AI classifiers were performed. Results We included 19 studies reporting the performances of AI-assisted ultrasonography, elastrography, computed tomography, magnetic resonance imaging and clinical parameters for the diagnosis of liver fibrosis and steatosis. For the diagnosis of liver fibrosis, the pooled sensitivity, specificity, PPV, NPV and DOR were 0.78 (0.71–0.85), 0.89 (0.81–0.94), 0.72 (0.58–0.83), 0.92 (0.88–0.94) and 31.58 (11.84–84.25), respectively, for cirrhosis; 0.86 (0.80–0.90), 0.87 (0.80–0.92), 0.85 (0.75–0.91), 0.88 (0.82–0.92) and 37.79 (16.01–89.19), respectively; for advanced fibrosis; and 0.86 (0.78–0.92), 0.81 (0.77–0.84), 0.88 (0.80–0.93), 0.77 (0.58–0.89) and 26.79 (14.47–49.62), respectively, for significant fibrosis. Subgroup analyses showed significant differences in performance for the diagnosis of fibrosis among different modalities. The pooled sensitivity, specificity, PPV, NPV and DOR were 0.97 (0.76–1.00), 0.91 (0.78–0.97), 0.95 (0.87–0.98), 0.93 (0.80–0.98) and 191.52 (38.82–944.81), respectively, for the diagnosis of liver steatosis. Conclusions AI-assisted systems have promising potential for the diagnosis of liver fibrosis and NAFLD. Validations of their performances are warranted before implementing these AI-assisted systems in clinical practice. Trial registration: The protocol was registered with PROSPERO (CRD42020183295).

scholarly journals Diagnostic Value of MRI Proton Density Fat Fraction for Assessing Liver Steatosis in Chronic Viral C Hepatitis

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Francesco Paparo ◽  
Giovanni Cenderello ◽  
Matteo Revelli ◽  
Lorenzo Bacigalupo ◽  
Mariangela Rutigliani ◽  
...  
Keyword(s):  
Liver Biopsy ◽  
Diagnostic Accuracy ◽  
Hepatic Steatosis ◽  
Transient Elastography ◽  
Liver Steatosis ◽  
Liver Stiffness ◽  
Diagnostic Value ◽  
Proton Density ◽  
Time Interval ◽  
Fat Fraction

Objective.To assess the diagnostic performance of a T1-independent, T2*-corrected multiecho magnetic resonance imaging (MRI) technique for the quantification of hepatic steatosis in a cohort of patients affected by chronic viral C hepatitis, using liver biopsy as gold standard.Methods.Eighty-one untreated patients with chronic viral C hepatitis were prospectively enrolled. All included patients underwent MRI, transient elastography, and liver biopsy within a time interval <10 days.Results.Our cohort of 77 patients included 43/77 (55.8%) males and 34/77 (44.2%) females with a mean age of 51.31 ± 11.27 (18–81) years. The median MRI PDFF showed a strong correlation with the histological fat fraction (FF) (r=0.754, 95% CI 0.637 to 0.836,P<0.0001), and the correlation was influenced by neither the liver stiffness nor the T2*decay. The median MRI PDFF result was significantly lower in the F4 subgroup (P<0.05). The diagnostic accuracy of MRI PDFF evaluated by AUC-ROC analysis was 0.926 (95% CI 0.843 to 0.973) forS≥1and 0.929 (95% CI 0.847 to 0.975) forS=2.Conclusions.Our MRI technique of PDFF estimation allowed discriminating with a good diagnostic accuracy between different grades of hepatic steatosis.

The value of transabdominal ultrasound for assessment of the severity of liver steatosis as compared to liver biopsy

Open Medicine ◽  
2009 ◽  
Vol 4 (4) ◽  
pp. 490-495 ◽  
Author(s):  
Ioan Sporea ◽  
Roxana Şirli ◽  
Elena Başa ◽  
Maria Cornianu ◽  
Alina Popescu ◽  
...  
Keyword(s):  
Chronic Hepatitis ◽  
Liver Biopsy ◽  
Predictive Value ◽  
Gold Standard ◽  
Liver Steatosis ◽  
Pathological Examination ◽  
Transabdominal Ultrasound ◽  
Moderate Severity ◽  
Ultrasound Evaluation ◽  
The Us

AbstractThe purpose of our paper was to evaluate the performance of ultrasound (US) for assessment of the severity of liver steatosis as compared to a pathological examination, which is presently considered to be the gold standard, in patients that have undergone liver biopsy for various reasons. We performed echo-assisted liver biopsy in 161 patients with chronic hepatitis with the US aspect of “bright liver” with “posterior attenuation”, using modified Menghini needles. Following the US examination, the severity of liver steatosis was estimated as minimal, mild, moderate. or severe according to the Hepburn classification: absent (affecting 0% to 2% of the hepatocytes), minimal (2% to 10%), mild (10% to 30%), moderate (30% to 60%), and severe (more than 60% of the hepatocytes). The results of this study showed that the sensitivity of US for the prediction of histological steatosis of at least moderate severity was 0.64, with 0.77 specificity, 0.55 positive predictive value, and 0.94 negative predictive value. The overall accuracy was 0.75. This study showed that the transabdominal ultrasound evaluation of the fatty liver is a quite good predictor, perhaps sufficient for most purposes, for the estimation of the severity of liver steatosis in the moderate to severe range.

scholarly journals Role of tissue C4d in differentiation between acute rejection and HCV recurrence after living donor liver transplantation

2020 ◽  
Vol 7 (8) ◽  
pp. 1196
Author(s):  
Zeinab Salah Eldin Hamza Khalil ◽  
Waleed Gad Dandarawy Hassan
Keyword(s):  
Liver Transplantation ◽  
Liver Biopsy ◽  
Acute Rejection ◽  
Positive Predictive Value ◽  
Portal Vein ◽  
Predictive Value ◽  
Pathological Finding ◽  
Specific Marker ◽  
C4d Staining

Background: Liver biopsy represents the gold standard for diagnosis of acute rejection and HCV recurrence after liver transplantation; never the less discrimination can be difficult due to similar display of alterations in liver specimen. Therefore, a specific marker expressed only in rejection but not in HCV recurrence would be a great asset to differentiate between both conditions. The aim of this study was to assess the role of tissue C4d complement fragments in liver biopsy as a marker for differentiating between acute rejection and HCV recurrence in recipients post LDLT.Methods: A case control study on 25 recipients after liver transplantation with the suspicion of either acute rejection or HCV disease recurrence, patients were classified according to pathological finding into two groups, Group 1: patients with acute rejection (n=13), Group 2: patients with HCV recurrence (n=12), The C4d was evaluated by immunohistochemical staining of the formalin-fixed, paraffin-embedded tissue in different liver compartments.Results: C4D staining of all the studied tissue compartments (Sinusoids, portal vein endothelium, hepatic vein endothelium, arterial internal elastic lining, portal stroma, bile ducts) had high specificity (100%) and positive predictive value (100%) in diagnosis of rejection cases except portal vein endothelium. (Specificity 91.7%, positive predictive value 88.9%).Conclusions: Tissue C4d staining was almost present in rejection cases only; further studies on larger cohort are required to stand on standard diagnostic criteria for C4d to be included in diagnosis of acute rejection after liver transplantation as its role in other organ transplantation.

scholarly journals The Positive Predictive Value of Onconeural Antibody Testing: A Retrospective Review

2018 ◽  
Vol 45 (5) ◽  
pp. 577-579 ◽  
Author(s):  
Adrian Budhram ◽  
Michael W. Nicolle ◽  
Liju Yang
Keyword(s):  
Positive Predictive Value ◽  
Retrospective Review ◽  
Predictive Value ◽  
Test Interpretation ◽  
Antibody Testing ◽  
Single Centre ◽  
Neurologic Diseases ◽  
Onconeural Antibodies ◽  
Onconeural Antibody ◽  
Immune Mediated

AbstractParaneoplastic syndromes (PNS) are immune-mediated neurologic diseases that occur as an indirect effect of malignancy, and can be challenging to diagnose. Onconeural antibodies have a greater than 95% association with cancer, and their presence in a patient with neurologic symptoms is reportedly highly indicative of PNS. However, we performed a single-centre retrospective review to determine the positive predictive value of onconeural antibody testing, and found it to be concerningly low (39%). Recognising the limitations of onconeural antibody testing is critical to ensure accurate test interpretation, avoid unnecessary repeated malignancy screening and prevent the use of potentially hazardous immunotherapy.

scholarly journals Application of Artificial Intelligence in Chronic Liver Diseases: A Systematic Review and Meta-analysis

2020 ◽  
Author(s):  
Pakanat Decharatanachart ◽  
Roongruedee Chaiteerakij ◽  
Thodsawit Tiyarattanachai ◽  
Sombat Treeprasertsuk
Keyword(s):  
Artificial Intelligence ◽  
Liver Fibrosis ◽  
Liver Biopsy ◽  
Predictive Value ◽  
Characteristic Curve ◽  
Liver Steatosis ◽  
Diagnostic Tools ◽  
Summary Receiver Operating Characteristic ◽  
Subgroup Analyses ◽  
Sensitivity Specificity

Abstract Background: The gold standard for the diagnosis of liver fibrosis and nonalcoholic fatty liver disease (NAFLD) is liver biopsy. Various noninvasive modalities, e.g., ultrasonography, elastography and clinical predictive scores, have been used as alternatives to liver biopsy, with limited performance. Recently, artificial intelligence (AI) models have been developed and integrated into noninvasive diagnostic tools to improve their performance. Methods: We systematically searched for studies on AI-assisted diagnosis of liver fibrosis and NAFLD on MEDLINE, Scopus, Web of Science and Google Scholar. The pooled sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic odds ratio (DOR) with their 95% confidence intervals (95%CIs) were calculated using a random effects model. A summary receiver operating characteristic curve and the area under the curve was generated to determine the diagnostic accuracy of the AI-assisted system. Subgroup analyses by diagnostic modalities were performed.Results: We included 17 studies reporting the performances of AI-assisted ultrasonography, elastrography, computed tomography (CT), magnetic resonance imaging (MRI) and clinical parameters for the diagnosis of liver fibrosis and steatosis. For the diagnosis of liver fibrosis, the pooled sensitivity, specificity, PPV, NPV and DOR were 0.78 (0.70 – 0.84), 0.88 (0.79 – 0.94), 0.73 (0.58 – 0.84), 0.91 (0.88 – 0.94) and 29.57 (10.65 – 82.10), respectively, for cirrhosis; 0.86 (0.80 – 0.91), 0.87 (0.79 – 0.92), 0.85 (0.74 – 0.91), 0.88 (0.82 – 0.92) and 37.95 (15.52 – 92.77), respectively; for advanced fibrosis; and 0.86 (0.78 – 0.92), 0.81 (0.77 – 0.84), 0.88 (0.80 – 0.93), 0.77 (0.58 – 0.89) and 26.79 (14.47 – 49.62), respectively, for significant fibrosis. Subgroup analyses showed significant differences in performance for the diagnosis of fibrosis among different modalities. The pooled sensitivity, specificity, PPV, NPV and DOR were 0.97 (0.76 – 1.00), 0.91 (0.78 – 0.97), 0.95 (0.87 – 0.98), 0.93 (0.80 – 0.98) and 191.52 (38.82 – 944.81), respectively, for the diagnosis of liver steatosis. Conclusions: AI-assisted systems have promising potential for the diagnosis of liver fibrosis and NAFLD. Validations of their performances are warranted before implementing these AI-assisted systems in clinical practice.Trial registration: The protocol was registered with PROSPERO (CRD42020183295).

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