Nonalcoholic fatty liver disease/nonalcoholic steatohepatitis (NAFLD/NASH) is a major cause of liver fibrosis and cirrhosis. Accurate assessment of liver fibrosis is important for predicting disease ...outcomes and assessing therapeutic response in clinical practice and clinical trials. Although noninvasive tests such as transient elastography and magnetic resonance elastography are preferred where possible, histological assessment of liver fibrosis via semiquantitative scoring systems remains the current gold standard. Collagen proportionate area provides more granularity by measuring the percentage of fibrosis on a continuous scale, but is limited by the absence of architectural input. Although not yet used in routine clinical practice, advances in second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy imaging show great promise in characterising architectural features of fibrosis at the individual collagen fiber level. Quantification and calculation of different detailed variables of collagen fibers can be used to establish algorithm-based quantitative fibrosis scores (e.g., qFibrosis, q-FPs), which have been validated against fibrosis stage in NAFLD. Artificial intelligence is being explored to further refine and develop quantitative fibrosis scoring methods. SHG-microscopy shows promise as the new gold standard for the quantitative measurement of liver fibrosis. This has reaffirmed the pivotal role of the liver biopsy in fibrosis assessment in NAFLD, at least for the near-future. The ability of SHG-derived algorithms to intuitively detect subtle nuances in liver fibrosis changes over a continuous scale should be employed to redress the efficacy endpoint for fibrosis in NASH clinical trials; this approach may improve the outcomes of the trials evaluating therapeutic response to antifibrotic drugs.
Objectives
We measured the accuracy of magnetic resonance elastography (MRE) for the detection and staging of liver fibrosis in chronic hepatitis B (CHB) and compared it with serum fibrosis markers.
...Methods
Prospective comparison of MRE and routine serum fibrosis markers, namely serum alanine aminotransferase (ALT), serum aspartate aminotransferase (AST), ALT/AST ratio (AAR), AST to platelet ratio index (APRI) and prothrombin index (PI), was performed in 63 consecutive CHB patients who underwent MRE and histological confirmation of liver fibrosis within a 6-month interval. Diagnostic performance of MRE and serum markers for staging fibrosis (≥F1), significant fibrosis (≥F2), advanced fibrosis (≥F3) and cirrhosis (F4) was compared.
Results
The study group comprised 63 patients (19 female; mean age ± SD, 50 ± 11.9 years). MRE (ρ = 0.94,
P
< 0.0001), APRI (ρ = 0.42,
P
= 0.0006), PI (ρ = 0.42,
P
= 0.0006) and AST (ρ = 0.28,
P
= 0.028) results correlated significantly with fibrosis stage. MRE was significantly more accurate than serum fibrosis markers for the detection of significant fibrosis (0.99 vs. 0.55–0.73) and cirrhosis (0.98 vs. 0.53–0.77). Sensitivity, specificity, positive predictive and negative predictive values for MRE for significant fibrosis and cirrhosis were 97.4 %, 100 %, 100 % and 96 %, and 100 %, 95.2 %, 91.3 % and 100 %, respectively.
Conclusion
MRE is an accurate non-invasive technique for the detection and staging of liver fibrosis in CHB.
Key Points
• Magnetic resonance elastography is accurate for liver fibrosis detection and staging.
• MR elastography is more accurate than serum tests for staging liver fibrosis.
• MR elastography can potentially replace liver biopsy in chronic hepatitis B.
Histologically assessed hepatocyte ballooning is a key feature discriminating non-alcoholic steatohepatitis (NASH) from steatosis (NAFL). Reliable identification underpins patient inclusion in ...clinical trials and serves as a key regulatory-approved surrogate endpoint for drug efficacy. High inter/intra-observer variation in ballooning measured using the NASH CRN semi-quantitative score has been reported yet no actionable solutions have been proposed.
A focused evaluation of hepatocyte ballooning recognition was conducted. Digitized slides were evaluated by 9 internationally recognized expert liver pathologists on 2 separate occasions: each pathologist independently marked every ballooned hepatocyte and later provided an overall non-NASH NAFL/NASH assessment. Interobserver variation was assessed and a ‘concordance atlas’ of ballooned hepatocytes generated to train second harmonic generation/two-photon excitation fluorescence imaging-based artificial intelligence (AI).
The Fleiss kappa statistic for overall interobserver agreement for presence/absence of ballooning was 0.197 (95% CI 0.094–0.300), rising to 0.362 (0.258–0.465) with a ≥5-cell threshold. However, the intraclass correlation coefficient for consistency was higher (0.718 0.511–0.900), indicating ‘moderate’ agreement on ballooning burden. 133 ballooned cells were identified using a ≥5/9 majority to train AI ballooning detection (AI-pathologist pairwise concordance 19–42%, comparable to inter-pathologist pairwise concordance of between 8–75%). AI quantified change in ballooned cell burden in response to therapy in a separate slide set.
The substantial divergence in hepatocyte ballooning identified amongst expert hepatopathologists suggests that ballooning is a spectrum, too subjective for its presence or complete absence to be unequivocally determined as a trial endpoint. A concordance atlas may be used to train AI assistive technologies to reproducibly quantify ballooned hepatocytes that standardize assessment of therapeutic efficacy. This atlas serves as a reference standard for ongoing work to refine how ballooning is classified by both pathologists and AI.
For the first time, we show that, even amongst expert hepatopathologists, there is poor agreement regarding the number of ballooned hepatocytes seen on the same digitized histology images. This has important implications as the presence of ballooning is needed to establish the diagnosis of non-alcoholic steatohepatitis (NASH), and its unequivocal absence is one of the key requirements to show ‘NASH resolution’ to support drug efficacy in clinical trials. Artificial intelligence-based approaches may provide a more reliable way to assess the range of injury recorded as “hepatocyte ballooning”.
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•Hepatocyte ballooning identification underpins regulatory-approved drug efficacy endpoints in clinical trials.•We report substantial variation in ballooned cell identification by expert hepatopathologists.•Our data suggest that ballooning is too subjective for its presence or complete absence to be used as a trial endpoint.•A ‘concordance atlas’ of cells identified as ballooned by multiple pathologists can be used to train AI-based image analysis.•AI-based approaches may provide a more reliable way to assess the range of injury recorded as hepatocyte ballooning.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Liver fibrosis is the net result of dynamic changes between fibrogenesis and fibrolysis. Evidence has shown that antiviral therapy can reverse liver fibrosis or even early cirrhosis caused by ...hepatitis B virus. However, current evaluation systems mainly focus on the severity of, but not the dynamic changes in, fibrosis. Here, we propose a new classification to evaluate the dynamic changes in the quality of fibrosis, namely: predominantly progressive (thick/broad/loose/pale septa with inflammation); predominately regressive (delicate/thin/dense/splitting septa); and indeterminate, which displayed an overall balance between progressive and regressive scarring. Then, we used this classification to evaluate 71 paired liver biopsies of chronic hepatitis B patients before and after entecavir‐based therapy for 78 weeks. Progressive, indeterminate, and regressive were observed in 58%, 29%, and 13% of patients before treatment versus in 11%, 11%, and 78% after treatment. Of the 55 patients who showed predominantly regressive changes on posttreatment liver biopsy, 29 cases (53%) had fibrosis improvement of at least one Ishak stage, and, more interestingly, 25 cases (45%) had significant improvement in terms of Laennec substage, collagen percentage area, and liver stiffness despite remaining in the same Ishak stage. Conclusion: This new classification highlights the importance of assessing and identifying the dynamic changes in the quality of fibrosis, especially relevant in the era of antiviral therapy.(Hepatology 2017;65:1438‐1450)
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Current liver fibrosis scoring by computer-assisted image analytics is not fully automated as it requires manual preprocessing (segmentation and feature extraction) typically based on domain ...knowledge in liver pathology. Deep learning-based algorithms can potentially classify these images without the need for preprocessing through learning from a large dataset of images. We investigated the performance of classification models built using a deep learning-based algorithm pre-trained using multiple sources of images to score liver fibrosis and compared them against conventional non-deep learning-based algorithms - artificial neural networks (ANN), multinomial logistic regression (MLR), support vector machines (SVM) and random forests (RF). Automated feature classification and fibrosis scoring were achieved by using a transfer learning-based deep learning network, AlexNet-Convolutional Neural Networks (CNN), with balanced area under receiver operating characteristic (AUROC) values of up to 0.85-0.95 versus ANN (AUROC of up to 0.87-1.00), MLR (AUROC of up to 0.73-1.00), SVM (AUROC of up to 0.69-0.99) and RF (AUROC of up to 0.94-0.99). Results indicate that a deep learning-based algorithm with transfer learning enables the construction of a fully automated and accurate prediction model for scoring liver fibrosis stages that is comparable to other conventional non-deep learning-based algorithms that are not fully automated.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Background & Aims A broad range of hepatocellular nodules has been reported in hepatic vascular disorders. It is not clear whether hepatocellular adenoma (HCA) in this context share the same ...characteristics as conventional HCA. The aim of this study was to carry out a retrospective multicenter survey of hepatocellular nodules associated with hepatic vascular disorders. Methods Forty-five cases were reviewed, including 32 Budd-Chiari syndrome (BCS). Benign nodules were subtyped using the HCA immunohistochemical panel. Results Nodules with a HCA morphology were observed in 11 cases. Six originated in BCS: two were liver fatty acid binding protein (LFABP) negative (one with malignant transformation); two expressed glutamine synthetase (GS) and nuclear b-catenin, two expressed C reactive protein (CRP). Among three cases with portal vein agenesis, one nodule was LFABP negative, two expressed GS and nuclear b-catenin, both with malignant transformation. In a Fallot tetralogy case, there were multiple LFABP negative nodules with borderline features and in a hepatoportal sclerosis case, the nodule looked like an inflammatory HCA. Two additional cases had nodules expressing CRP, without typical characteristics of inflammatory HCA. Conclusion HCA of different immunohistochemical phenotype can develop in hepatic vascular disorders; they may have a different behavior compared to conventional HCA and be more at risk of malignant transformation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
There is increasing need for accurate assessment of liver fibrosis/cirrhosis. We aimed to develop qFibrosis, a fully-automated assessment method combining quantification of histopathological ...architectural features, to address unmet needs in core biopsy evaluation of fibrosis in chronic hepatitis B (CHB) patients.
qFibrosis was established as a combined index based on 87 parameters of architectural features. Images acquired from 25 Thioacetamide-treated rat samples and 162 CHB core biopsies were used to train and test qFibrosis and to demonstrate its reproducibility. qFibrosis scoring was analyzed employing Metavir and Ishak fibrosis staging as standard references, and collagen proportionate area (CPA) measurement for comparison.
qFibrosis faithfully and reliably recapitulates Metavir fibrosis scores, as it can identify differences between all stages in both animal samples (p<0.001) and human biopsies (p<0.05). It is robust to sampling size, allowing for discrimination of different stages in samples of different sizes (area under the curve (AUC): 0.93–0.99 for animal samples: 1–16mm2; AUC: 0.84–0.97 for biopsies: 10–44mm in length). qFibrosis can significantly predict staging underestimation in suboptimal biopsies (<15mm) and under- and over-scoring by different pathologists (p<0.001). qFibrosis can also differentiate between Ishak stages 5 and 6 (AUC: 0.73, p=0.008), suggesting the possibility of monitoring intra-stage cirrhosis changes. Best of all, qFibrosis demonstrates superior performance to CPA on all counts.
qFibrosis can improve fibrosis scoring accuracy and throughput, thus allowing for reproducible and reliable analysis of efficacies of anti-fibrotic therapies in clinical research and practice.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
With the rapid development of various coronavirus disease 2019 (COVID-19) vaccines in a bid to counter and contain the COVID-19 pandemic, unusual and uncommon side effects of COVID-19 vaccination ...have been increasingly reported in the literature. Ipsilateral lymphadenopathy is a fairly common side effect of vaccination of any kind, with its etiology most commonly related to reactive lymphadenopathy. However, Kikuchi–Fujimoto Disease (KFD) or necrotizing histiocytic lymphadenitis is rarely observed post-vaccination, with only one other case of KFD post COVID-19 vaccination reported to date. We report two more cases of KFD post COVID-19 vaccination in the Asian population, highlighting the clinical course and salient clinical, radiological and histologic findings. In addition, we provide a literature review of the existing cases of lymphadenopathy post COVID-19 vaccination with cytologic and/or histologic correlation.
The novel targeted therapeutics for hepatitis C virus (HCV) in last decade solved most of the clinical needs for this disease. However, despite antiviral therapies resulting in sustained virologic ...response (SVR), a challenge remains where the stage of liver fibrosis in some patients remains unchanged or even worsens, with a higher risk of cirrhosis, known as the irreversible group. In this study, we provided novel tissue level collagen structural insight into early prediction of irreversible cases via image based computational analysis with a paired data cohort (of pre- and post-SVR) following direct-acting-antiviral (DAA)-based treatment. Two Photon Excitation and Second Harmonic Generation microscopy was used to image paired biopsies from 57 HCV patients and a fully automated digital collagen profiling platform was developed. In total, 41 digital image-based features were profiled where four key features were discovered to be strongly associated with fibrosis reversibility. The data was validated for prognostic value by prototyping predictive models based on two selected features: Collagen Area Ratio and Collagen Fiber Straightness. We concluded that collagen aggregation pattern and collagen thickness are strong indicators of liver fibrosis reversibility. These findings provide the potential implications of collagen structural features from DAA-based treatment and paves the way for a more comprehensive early prediction of reversibility using pre-SVR biopsy samples to enhance timely medical interventions and therapeutic strategies. Our findings on DAA-based treatment further contribute to the understanding of underline governing mechanism and knowledge base of structural morphology in which the future non-invasive prediction solution can be built upon.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Objectives
Comparison of magnetic resonance elastography (MRE) and diffusion-weighted imaging (DWI) for differentiating malignant and benign focal liver lesions (FLLs).
Methods
Seventy-nine subjects ...with 124 FLLs (44 benign and 80 malignant) underwent both MRE and DWI. MRE was performed with a modified gradient-echo sequence and DWI with a free breathing technique (b = 0.500). Apparent diffusion coefficient (ADC) maps and stiffness maps were generated. FLL mean stiffness and ADC values were obtained by placing regions of interest over the FLLs on stiffness and ADC maps. The accuracy of MRE and DWI for differentiation of benign and malignant FLL was compared using receiver operating curve (ROC) analysis.
Results
There was a significant negative correlation between stiffness and ADC (r = −0.54, p < 0.0001) of FLLs. Malignant FLLs had significantly higher mean stiffness (7.9kPa vs. 3.1kPa, p < 0.001) and lower mean ADC (129 vs. 200 × 10
−3
mm
2
/s, p < 0.001) than benign FLLs. The sensitivity/specificity/positive predictive value/negative predictive value for differentiating malignant from benign FLLs with MRE (cut-off, >4.54kPa) and DWI (cut-off, <151 × 10
−3
mm
2
/s) were 96.3/95.5/97.5/93.3 % (p < 0.001) and 85/81.8/88.3/75 % (p < 0.001), respectively. ROC analysis showed significantly higher accuracy for MRE than DWI (0.986 vs. 0.82, p = 0.0016).
Conclusion
MRE is significantly more accurate than DWI for differentiating benign and malignant FLLs.
Key points
•
MRE is superior to DWI for differentiating benign and malignant focal liver lesions
.
•
Benign lesions with large fibrous
components may have higher stiffness with MRE
.
•
Cholangiocarcinomas tend to have higher stiffness than hepatocellular carcinomas
.
•
Hepatocellular adenomas tend to have lower stiffness than focal nodular hyperplasia
.
•
MRE is superior to conventional MRI in differentiating benign and malignant liver lesions
.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, VSZLJ, ZAGLJ
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