Potential of using qFibrosis analysis to predict recurrent and survival outcome of patients with hepatocellular carcinoma after hepatic resection.

BACKGROUND: There remains a lack of studies addressing the stromal background and fibrosis features and its prognostic value in liver cancer. qFibrosis can identify, quantify and visualize the fibrosis features from biopsy samples. In this study, we aim to demonstrate the prognostic value of histological features by using qFibrosis analysis in liver cancer patients. METHODS: Liver specimen from 201 patients with hepatocellular carcinoma underwent curative resection were imaged and assessed using qFibrosis system, and generated a total of 33 and 156 collagen parameters from tumor part and non-tumor liver tissue, respectively. We used these collagen parameters on patients to build two combined indexes, RFS-index and OS-index, in order to differentiate patients with early recurrence and early death, respectively. The models were validated using leave-one-out method. RESULTS: Both combined indexes had significant prediction value of patients' outcome. The RFS-index of 0.52 well differentiates patients with early recurrence (p < 0.001), and the OS-index of 0.73 well differentiates patients with early death during follow-up (p = 0.02). CONCLUSIONS: Combined index calculated with qFibrosis from digital readout of fibrotic status of peri-tumor liver specimen in patients with HCC have prediction values for their disease and survival outcomes. These results demonstrated the potentials to transform histopathological features into quantifiable data that could be used to correlate with clinical outcome.

Unlocking the double-dividend: Evaluating the impact of SO2 emissions trading scheme on firm's environmental and economic performance.

The optimal design of environmental instruments demands a balance between environmental enhancement and economic growth. Utilizing microdata from the China Environmental Statistics Database and the China Industrial Firm Database, this study employs the difference-in-differences (DD) methodology to explore the dual effects of the SO2 Emissions Trading Scheme (ETS) on the environmental and economic performance of micro-firms. The findings suggest that: (1) The SO2 ETS not only induces emission reduction effects among firms in pilot areas but also improves their industrial added value. (2) The SO2 ETS exhibits heterogeneous impacts across firms of diverse ownership, export status, and size. (3) While the SO2 ETS prompts firms to advance technologically, boosting desulfurization capacities and subsequently enhancing total factor productivity, it also inadvertently results in companies offsetting some environmental compliance costs by curtailing employee wages.

The environmental effects of undertaking industrial transfer in developing countries: a quasi-natural experimental evidence in China.

The construction of National Industrial Relocation Demonstration Zones (NIRDZ) is important for China's industrial transfer, but its environmental influence cannot be neglected. This study explores the environmental effects of industrial transfers by studying China's NIRDZ. By employing panel data of 284 cities in China between 2005 and 2019, we compare environmental quality changes over time in areas with and without demonstration zones based on the staggered difference-in-differences (DD) technique. The results demonstrate a 0.032 increase in the environmental quality level of industrial receivers after the implementation of demonstration zones. The effect of demonstration zones on environmental improvement is moderated by natural resources, capital accumulation, and technological innovation capabilities. This impact is more fully realized in cities with resource-based, low-capital accumulation, and high-tech innovation but is not statistically significant difference at various levels of human resources. The environmental improvement effect of the NIRDZ is powerful in central cities and small- and medium-sized cities instead of western regions and large-scale cities. Additionally, mediation analysis is adopted to assess the potential mechanism between the association of NIRDZ and the environment. The demonstration area negatively affects environmental quality through the economic scale effect while improving environmental quality through the technological innovation effect. We provide empirical evidence that the NIRDZ is positively correlated with the environment and identify the technology effect as one underlying driver of this correlation to help developing countries address its detrimental impacts.

Second-Harmonic Generated Quantifiable Fibrosis Parameters Provide Signatures for Disease Progression and Regression in Nonalcoholic Fatty Liver Disease.

Introduction: The current ordinal fibrosis staging system for nonalcoholic steatohepatitis (NASH) has a limited dynamic range. The goal of this study was to determine if second-harmonic generated (SHG) quantifiable collagen fibrillar properties (qFP) and their derived qFibrosis score capture changes in disease progression and regression in a murine model of NASH, in which disease progression can be induced by a high fat sugar water (HFSW) diet and regression by reversal to chow diet (CD). Methods: DIAMOND mice were fed a CD or HFSW diet for 40 to 52 weeks. Regression related changes were studied in mice with diet reversal for 4 weeks after 48 to 60 weeks of a HFSW diet. Results: As expected, mice on HFSW developed steatohepatitis with stage 2 to 3 fibrosis between weeks 40 and 44. Both the collagen proportionate area and the qFibrosis score based on 15 SHG-quantified collagen fibrillar properties in humans were significantly higher in mice on HFSW for 40 to 44 weeks compared to CD fed mice. These changes were greatest in the sinusoids (Zone 2) with further increase in septal and portal fibrosis related scores between weeks 44 and 48. Diet reversal led to decrease in qFibrosis, septal thickness, and cellularity with greatest changes in Zone 2. Specific qFPs associated with progression only, regression only, or both processes were identified and categorized based on direction of fibrosis change. Conclusion: Complementing recent human studies, these findings support the concept that changes of disease progression and regression can be assessed using SHG-based image quantification of fibrosis related parameters.

The Short- and Long-Run Impacts of Air Pollution on Human Health: New Evidence from China.

Under the background of the far-reaching impact of the COVID-19 epidemic on global economic development, the interactive effect of economic recovery and pollution rebound makes the research topic of air pollution and human health receive attention again. Matching a series of new datasets and employing thermal inversion as an instrumental variable, this study investigates the physical and mental health effect of air pollution jointly in China. We find that in the short run, the above inference holds for both physical and mental health. These short-run influences are credible after a series of robustness checks and vary with different individual characteristics and geographical locations. We also find that in the long run, air pollution only damages mental health. Finally, this study calculates the health cost of air pollution. The above findings indicate that in China, the effect of air pollution on physical and mental health cannot be ignored. The government needs to consider the heterogeneity and long-run and short-run differences in the health effects of air pollution when formulating corresponding environmental and medical policies.

Machine learning liver histology scores correlate with portal hypertension assessments in nonalcoholic steatohepatitis cirrhosis.

BACKGROUND AND AIMS: In cirrhotic nonalcoholic steatohepatitis (NASH) clinical trials, primary efficacy endpoints have been hepatic venous pressure gradient (HVPG), liver histology and clinical liver outcomes. Important histologic features, such as septa thickness, nodules features and fibrosis area have not been included in the histologic assessment and may have important clinical relevance. We assessed these features with a machine learning (ML) model. METHODS: NASH patients with compensated cirrhosis and HVPG ≥6 mm Hg (n = 143) from the Belapectin phase 2b trial were studied. Liver biopsies, HVPG measurements and upper endoscopies were performed at baseline and at end of treatment (EOT). A second harmonic generation/two-photon excitation fluorescence provided an automated quantitative assessment of septa, nodules and fibrosis (SNOF). We created ML scores and tested their association with HVPG, clinically significant HVPG (≥10 mm Hg) and the presence of varices (SNOF-V). RESULTS: We derived 448 histologic variables (243 related to septa, 21 related to nodules and 184 related to fibrosis). The SNOF score (≥11.78) reliably distinguished CSPH at baseline and in the validation cohort (baseline + EOT) [AUC = 0.85 and 0.74, respectively]. The SNOF-V score (≥0.57) distinguished the presence of varices at baseline and in the same validation cohort [AUC = 0.86 and 0.73, respectively]. Finally, the SNOF-C score differentiated those who had >20% change in HVPG against those who did not, with an AUROC of 0.89. CONCLUSION: The ML algorithm accurately predicted HVPG, CSPH, the development of varices and HVPG changes in patients with NASH cirrhosis. The use of ML histology model in NASH cirrhosis trials may improve the assessment of key outcome changes.

Efficacy and Safety of a Botanical Formula Fuzheng Huayu for Hepatic Fibrosis in Patients with CHC: Results of a Phase 2 Clinical Trial.

Background: Hepatitis C virus (HCV) is a common cause of progressive hepatic fibrosis, cirrhosis, and hepatocellular carcinoma worldwide. Despite the availability of effective direct-acting antivirals, patients often have significant hepatic fibrosis at the time of diagnosis due to delay in diagnosis and comorbidities which promote fibrogenesis. Thus, antifibrotic agents represent an attractive adjunctive therapy. Fuzheng Huayu (FZHY), a traditional Chinese medicine botanical formulation, has been used as an antifibrotic agent in chronic HBV infection. Our aim was to assess FZHY in patients with HCV infection and active viremia. Method: We randomized 118 patients with active viremia from 8 liver centers in the U.S. to receive oral FZHY (n = 59) or placebo (n = 59) for 48 weeks. Efficacy was assessed by histopathologic changes at the end of therapy. A subset of biopsies was further analyzed using qFibrosis to detect subtle changes in fibrosis in different zones of the hepatic lobules. Results: FZHY was well tolerated and safe. Patients with baseline Ishak fibrosis stages F3 and F4 had better response rates to FZHY than patients with baseline F0-F2 (p=0.03). qFibrosis zonal analysis showed significant improvement in fibrosis in all zones in patients with regression of the fibrosis stage. Conclusions: FZHY produced antifibrotic effects in patients with baseline Ishak F3 and F4 fibrosis stages. Reduction in fibrosis severity was zonal and correlated with the severity of inflammation. Based on its tolerability, safety, and efficacy, FZHY should be further investigated as a therapy in chronic liver diseases because of its dual anti-inflammatory and antiibrotic properties. Lay Summary. This is the first US-based, multicenter and placebo-controlled clinical trial that shows statistically significant reduction in fibrosis in patients with active HCV using an antifibrotic botanical formula. This has important implications as there is an immediate need for effective antifibrotic agents in treating many chronic diseases including NASH that lead to scarring of the liver. With artificial intelligence-based methodology, qFibrosis, we may provide a more reliable way to assess the FZHY as a therapy in chronic liver diseases because of its dual anti-inflammatory and antifibrotic properties.

Digital pathology with artificial intelligence analyses provides greater insights into treatment-induced fibrosis regression in NASH.

BACKGROUND & AIMS: Liver fibrosis is a key prognostic determinant for clinical outcomes in non-alcoholic steatohepatitis (NASH). Current scoring systems have limitations, especially in assessing fibrosis regression. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy with artificial intelligence analyses provides standardized evaluation of NASH features, especially liver fibrosis and collagen fiber quantitation on a continuous scale. This approach was applied to gain in-depth understanding of fibrosis dynamics after treatment with tropifexor (TXR), a non-bile acid farnesoid X receptor agonist in patients participating in the FLIGHT-FXR study (NCT02855164). METHOD: Unstained sections from 198 liver biopsies (paired: baseline and end-of-treatment) from 99 patients with NASH (fibrosis stage F2 or F3) who received placebo (n = 34), TXR 140 µg (n = 37), or TXR 200 µg (n = 28) for 48 weeks were examined. Liver fibrosis (qFibrosis®), hepatic fat (qSteatosis®), and ballooned hepatocytes (qBallooning®) were quantitated using SHG/TPEF microscopy. Changes in septa morphology, collagen fiber parameters, and zonal distribution within liver lobules were also quantitatively assessed. RESULTS: Digital analyses revealed treatment-associated reductions in overall liver fibrosis (qFibrosis®), unlike conventional microscopy, as well as marked regression in perisinusoidal fibrosis in patients who had either F2 or F3 fibrosis at baseline. Concomitant zonal quantitation of fibrosis and steatosis revealed that patients with greater qSteatosis reduction also have the greatest reduction in perisinusoidal fibrosis. Regressive changes in septa morphology and reduction in septa parameters were observed almost exclusively in F3 patients, who were adjudged as 'unchanged' with conventional scoring. CONCLUSION: Fibrosis regression following hepatic fat reduction occurs initially in the perisinusoidal regions, around areas of steatosis reduction. Digital pathology provides new insights into treatment-induced fibrosis regression in NASH, which are not captured by current staging systems. LAY SUMMARY: The degree of liver fibrosis (tissue scarring) in non-alcoholic steatohepatitis (NASH) is the main predictor of negative clinical outcomes. Accurate assessment of the quantity and architecture of liver fibrosis is fundamental for patient enrolment in NASH clinical trials and for determining treatment efficacy. Using digital microscopy with artificial intelligence analyses, the present study demonstrates that this novel approach has greater sensitivity in demonstrating treatment-induced reversal of fibrosis in the liver than current systems. Furthermore, additional details are obtained regarding the pathogenesis of NASH disease and the effects of therapy.

Developing a New qFIBS Model Assessing Histological Features in Pediatric Patients With Non-alcoholic Steatohepatitis.

Background: The evolution of pediatric non-alcoholic fatty liver disease (NAFLD) to non-alcoholic steatohepatitis (NASH) is associated with unique histological features. Pathological evaluation of liver specimen is often hindered by observer variability and diagnostic consensus is not always attainable. We investigated whether the qFIBS technique derived from adult NASH could be applied to pediatric NASH. Materials and Methods: 102 pediatric patients (<18 years old) with liver biopsy-proven NASH were included. The liver biopsies were serially sectioned for hematoxylin-eosin and Masson trichrome staining for histological scoring, and for second harmonic generation (SHG) imaging. qFIBS-automated measure of fibrosis, inflammation, hepatocyte ballooning, and steatosis was estabilshed by using the NASH CRN scoring system as the reference standard. Results: qFIBS showed the best correlation with steatosis (r = 0.84, P < 0.001); with ability to distinguish different grades of steatosis (AUROCs 0.90 and 0.98, sensitivity 0.71 and 0.93, and specificity 0.90 and 0.90). qFIBS correlation with fibrosis (r = 0.72, P < 0.001) was good with high AUROC values [qFibrosis (AUC) > 0.85 (0.85-0.95)] and ability to distinguish different stages of fibrosis. qFIBS showed weak correlation with ballooning (r = 0.38, P = 0.028) and inflammation (r = 0.46, P = 0.005); however, it could distinguish different grades of ballooning (AUROCs 0.73, sensitivity 0.36, and specificity 0.92) and inflammation (AUROCs 0.77, sensitivity 0.83, and specificity 0.53). Conclusion: It was demonstrated that when qFIBS derived from adult NASH was performed on pediatric NASH, it could best distinguish the various histological grades of steatosis and fibrosis.

Complexity of ballooned hepatocyte feature recognition: Defining a training atlas for artificial intelligence-based imaging in NAFLD.

BACKGROUND & AIMS: 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. METHODS: 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). RESULTS: 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. CONCLUSIONS: 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. LAY SUMMARY: 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".

An Improved qFibrosis Algorithm for Precise Screening and Enrollment into Non-Alcoholic Steatohepatitis (NASH) Clinical Trials.

BACKGROUND: Many clinical trials with potential drug treatment options for non-alcoholic fatty liver disease (NAFLD) are focused on patients with non-alcoholic steatohepatitis (NASH) stages 2 and 3 fibrosis. As the histological features differentiating stage 1 (F1) from stage 2 (F2) NASH fibrosis are subtle, some patients may be wrongly staged by the in-house pathologist and miss the opportunity for enrollment into clinical trials. We hypothesized that our refined artificial intelligence (AI)-based algorithm (qFibrosis) can identify these subtle differences and serve as an assistive tool for in-house pathologists. METHODS: Liver tissue from 160 adult patients with biopsy-proven NASH from Singapore General Hospital (SGH) and Peking University People's Hospital (PKUH) were used. A consensus read by two expert hepatopathologists was organized. The refined qFibrosis algorithm incorporated the creation of a periportal region that allowed for the increased detection of periportal fibrosis. Consequently, an additional 28 periportal parameters were added, and 28 pre-existing perisinusoidal parameters had altered definitions. RESULTS: Twenty-eight parameters (20 periportal and 8 perisinusoidal) were significantly different between the F1 and F2 cases that prompted a change of stage after a careful consensus read. The discriminatory ability of these parameters was further demonstrated in a comparison between the true F1 and true F2 cases as 26 out of the 28 parameters showed significant differences. These 26 parameters constitute a novel sub-algorithm that could accurately stratify F1 and F2 cases. CONCLUSION: The refined qFibrosis algorithm incorporated 26 novel parameters that showed a good discriminatory ability for NASH fibrosis stage 1 and 2 cases, representing an invaluable assistive tool for in-house pathologists when screening patients for NASH clinical trials.

SHG/TPEF-based image technology improves liver fibrosis assessment of minimally sized needle biopsies.

BACKGROUND AND AIMS: Sampling size variability of liver biopsy remains a major limitation in the assessment of liver fibrosis. We aimed to evaluate the diagnostic value of a fully quantitative method (second harmonic generation/two-photon excitation fluorescence, SHG/TPEF based) in "short" liver biopsy samples. METHODS: Liver biopsy samples from chronic hepatitis B (CHB) patients were constructed into "virtual" biopsies with different lengths. The original and "virtual" samples were measured by SHG/TPEF-based technology to obtain qFibrosis score, respectively. Here, ΔqFibrosis was defined as difference of qFibrosis between original biopsy and "virtual" biopsy. Equivalence test was used to compare ΔqFibrosis with the clinically acceptable error (deviation of 0.50) in each group. RESULTS: In real-world practice, qFibrosis score increased significantly with fibrosis progression in ≥ 1.5-cm-, 1.0-1.5-cm-, and 0.5-1.0-cm-long specimens (p < 0.05), compared with ≤ 0.5-cm-long specimens (p > 0.05). In virtual biopsy samples with specified length, the equivalence was confirmed in 0.5-1.0-cm- and 1.0-1.5-cm-long specimens (0.27 vs. 0.22, p < 0.001), whereas not in ≤ 0.5-cm-long specimens (0.53, p > 0.05). The number of cross-linked collagen fibers, the total and aggregated collagen proportionate area, and the collagen strings in number, length, width and perimeter showed excellent consistency with original biopsy samples in 0.5-1.0-cm- and 1.0-1.5-cm-long specimens (ICC > 0.90). CONCLUSIONS: The use of SHG/TPEF-based image technology may give useful suggestive information in evaluation of CHB-related liver fibrosis for the short sample (biopsy length > 0.5 cm).

Automated evaluation of liver fibrosis in thioacetamide, carbon tetrachloride, and bile duct ligation rodent models using second-harmonic generation/two-photon excited fluorescence microscopy.

Animal models provide a useful platform for developing and testing new drugs to treat liver fibrosis. Accordingly, we developed a novel automated system to evaluate liver fibrosis in rodent models. This system uses second-harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy to assess a total of four mouse and rat models, using chemical treatment with either thioacetamide (TAA) or carbon tetrachloride (CCl4), and a surgical method, bile duct ligation (BDL). The results obtained by the new technique were compared with that using Ishak fibrosis scores and two currently used quantitative methods for determining liver fibrosis: the collagen proportionate area (CPA) and measurement of hydroxyproline (HYP) content. We show that 11 shared morphological parameters faithfully recapitulate Ishak fibrosis scores in the models, with high area under the receiver operating characteristic (ROC) curve (AUC) performance. The AUC values of 11 shared parameters were greater than that of the CPA (TAA: 0.758-0.922 vs 0.752-0.908; BDL: 0.874-0.989 vs 0.678-0.966) in the TAA mice and BDL rat models and similar to that of the CPA in the TAA rat and CCl4 mouse models. Similarly, based on the trends in these parameters at different time points, 9, 10, 7, and 2 model-specific parameters were selected for the TAA rats, TAA mice, CCl4 mice, and BDL rats, respectively. These parameters identified differences among the time points in the four models, with high AUC accuracy, and the corresponding AUC values of these parameters were greater compared with those of the CPA in the TAA rat and mouse models (rats: 0.769-0.894 vs 0.64-0.799; mice: 0.87-0.93 vs 0.739-0.836) and similar to those of the CPA in the CCl4 mouse and BDL rat models. Similarly, the AUC values of 11 shared parameters and model-specific parameters were greater than those of HYP in the TAA rats, TAA mice, and CCl4 mouse models and were similar to those of HYP in the BDL rat models. The automated evaluation system, combined with 11 shared parameters and model-specific parameters, could specifically, accurately, and quantitatively stage liver fibrosis in animal models.