Quantitative digital pathology enables automated and quantitative assessment of inflammatory activity in patients with autoimmune hepatitis
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ABSTRACT:
SUBMITTER: Socha P
PROVIDER: S-EPMC10959696 | biostudies-literature | 2024 Mar
REPOSITORIES: biostudies-literature
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Project description:Historically, the safety of live attenuated vaccine candidates against neurotropic viruses was assessed by semi-quantitative analysis of virus-induced histopathology in the central nervous system of monkeys. We have developed a high-throughput automated image analysis (AIA) for the quantitative assessment of virus-induced neuroinflammation and neurodegeneration. Evaluation of the results generated by AIA showed that quantitative estimates of lymphocytic infiltration, microglial activation, and neurodegeneration strongly and significantly correlated with results of traditional histopathological scoring. In addition, we show that AIA is a targeted, objective, accurate, and time-efficient approach that provides reliable differentiation of virus neurovirulence. As such, it may become a useful tool in establishing consistent analytical standards across research and development laboratories and regulatory agencies, and may improve the safety evaluation of live virus vaccines. The implementation of this high-throughput AIA will markedly advance many fields of research including virology, neuroinflammation, neuroscience, and vaccinology.
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Project description:Adjunction of immune response into the TNM classification system improves the prediction of colon cancer (CC) prognosis. However, immune response measurements have not been used as robust biomarkers of pathology in clinical practice until the introduction of Immunoscore (IS), a standardized assay based on automated artificial intelligence assisted digital pathology. The strong prognostic impact of the immune response, as assessed by IS, has been widely validated and IS can help to refine treatment decision making in early CC. In this study, we compared pathologist visual scoring to IS. Four pathologists evaluated tumor specimens from 50 early-stage CC patients and classified the CD3+ and CD8+ T-cell densities at the tumor site (T-score) into 2 (High/Low) categories. Individual and overall pathologist scoring of immune response (before and after training for immune response assessment) were compared to the reference IS (High/Low). Pathologists' disagreement with the reference IS was observed in almost half of the cases (48%) and training only slightly improved the accuracy of pathologists' classification. Agreement among pathologists was minimal with a Kappa of 0.34 and 0.57 before and after training, respectively. The standardized IS assay outperformed expert pathologist assessment in the clinical setting.
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Project description:Quantitative neuropathologic methods provide information that is important for both research and clinical applications. The technologic advancement of digital pathology and image analysis offers new solutions to enable valid quantification of pathologic severity that is reproducible between raters regardless of experience. Using an Aperio ScanScope XT and its accompanying image analysis software, we designed algorithms for quantitation of amyloid and tau pathologies on 65 ?-amyloid (6F/3D antibody) and 48 phospho-tau (PHF-1)-immunostained sections of human temporal neocortex. Quantitative digital pathologic data were compared with manual pathology counts. There were excellent correlations between manually counted and digitally analyzed neuropathologic parameters (R² = 0.56-0.72). Data were highly reproducible among 3 participants with varying degrees of expertise in neuropathology (intraclass correlation coefficient values, >0.910). Digital quantification also provided additional parameters, including average plaque area, which shows statistically significant differences when samples are stratified according to apolipoprotein E allele status (average plaque area, 380.9 ?m² in apolipoprotein E [Latin Small Letter Open E]4 carriers vs 274.4 ?m² for noncarriers; p < 0.001). Thus, digital pathology offers a rigorous and reproducible method for quantifying Alzheimer disease neuropathologic changes and may provide additional insights into morphologic characteristics that were previously more challenging to assess because of technical limitations.
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Project description:Background & aimsThe I148M variant (rs738409) in patatin-like phospholipase domain-containing protein 3 (PNPLA3) is by far the most important genetic determinant of non-alcoholic fatty liver disease (NAFLD). However, in the context of NAFLD, the transcriptional regulation of PNPLA3 in human liver cells is not known. In this study, we aimed to define the relationship between PNPLA3 transcription and disease characteristics of human NAFLD.MethodsThe abundance of PNPLA3 and collagen 1α (COL1α) transcripts was quantified in situ at single-cell resolution using RNAscope® in 87 patients with NAFLD. We examined the association of PNPLA3 and COL1α transcript levels with NAFLD disease severity, defined by histology.ResultsWhile the majority of PNPLA3 transcripts were found in hepatocytes, approximately 7% of PNPLA3-positive cells co-express COL1α, representing activated myofibroblasts. There is no association between the rs738409 genotype and the level of PNPLA3 transcript. The overall PNPLA3 transcript abundance is lower in zone 1 hepatocytes, patients with higher body mass index, and those with advanced liver fibrosis. The negative association between the PNPLA3 transcript levels and liver fibrosis is largely driven by COL1α-positive cells. A significant proportion of PNPLA3 mRNA is seen in the nucleus. The cytoplasmic-to-nuclear PNPLA3 mRNA ratio is inversely associated with NAFLD disease activity.ConclusionsPNPLA3 transcript abundance and nuclear-to-cytoplasmic translocation are negatively associated with hepatic steatosis and NAFLD disease activity, while its abundance in activated myofibroblasts is inversely associated with the stage of liver fibrosis.Lay summaryA genetic variant in patatin-like phospholipase domain-containing protein 3 (or PNPLA3) is the most important genetic determinant of non-alcoholic fatty liver disease (NAFLD). However, it is not known how transcriptional regulation of the PNPLA3 gene contributes to the disease characteristics of human NAFLD. Herein, we show that the mRNA levels of PNPLA3, particularly in the cytoplasm, are negatively associated with the severity of NAFLD in humans.
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Project description:Multispectral optoacoustic tomography (MSOT) allows non-invasive molecular disease activity assessment in adults with inflammatory bowel disease (IBD). In this prospective pilot-study, we investigated, whether increased levels of MSOT haemoglobin parameters corresponded to inflammatory activity in paediatric IBD patients, too. 23 children with suspected IBD underwent MSOT of the terminal ileum and sigmoid colon with standard validation (e.g. endoscopy). In Crohn`s disease (CD) and ulcerative colitis (UC) patients with endoscopically confirmed disease activity, MSOT total haemoglobin (HbT) signals were increased in the terminal ileum of CD (72.1 ± 13.0 a.u. vs. 32.9 ± 15.4 a.u., p = 0.0049) and in the sigmoid colon of UC patients (62.9 ± 13.8 a.u. vs. 35.1 ± 16.3 a.u., p = 0.0311) as compared to controls, respectively. Furthermore, MSOT haemoglobin parameters correlated well with standard disease activity assessment (e.g. SES-CD and MSOT HbT (rs =0.69, p = 0.0075). Summarizing, MSOT is a novel technology for non-invasive molecular disease activity assessment in paediatric patients with inflammatory bowel disease.
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Project description:IntroductionPrevious research identified AIH as linked to unfavorable obstetrical outcomes in a US nationwide retrospective study from 2012-2016. Our aim is to update the literature and strengthen the AIH-pregnancy outcomes relationship.MethodsUsing the National Inpatient Sample database in the US, from 2016 to 2020, we compared pregnant females with a diagnosis of AIH to those with and without other chronic liver diseases (CLD), using ICD-10-CM codes. Baseline characteristics were analyzed using T-test and Chi-Square, and multivariate regression was used to estimate the differences in maternal outcomes adjusted for age, race, insurance status, geographical location, hospital characteristics, and comorbid conditions.ResultsOut of 19,392,328 hospitalizations for pregnant females ≥ 18 years old from 2016 to 2020, 1095 had AIH, 179,655 had CLD, and 19,206,696 had no CLD. No mortality was observed among individuals with AIH. When compared to individuals without CLD, AIH was associated with an 82% increase in the odds of preterm delivery (AIH: 8% vs. Without CLD: 5%, adjusted Odds Ratio = 1.82, 95% CI 1.06-3.14), with no significant differences in gestational diabetes mellitus, hypertensive complications, and postpartum hemorrhage, and a 0.6 day longer hospital stay. Furthermore, there were no significant differences in outcomes between AIH and CLD.ConclusionsOur study reinforces the association of AIH with adverse obstetrical outcomes (e.g., preterm delivery), however, we found that there is no difference in GDM and hypertensive complications, as suggested in prior studies. Therefore, further investigations are needed to clarify the association between AIH and these obstetrical complications.
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Project description:Automatic and accurate detection of positive and negative nuclei from images of immunostained tissue biopsies is critical to the success of digital pathology. The evaluation of most nuclei detection algorithms relies on manually generated ground truth prepared by pathologists, which is unfortunately time-consuming and suffers from inter-pathologist variability. In this work, we developed a digital immunohistochemistry (IHC) phantom that can be used for evaluating computer algorithms for enumeration of IHC positive cells. Our phantom development consists of two main steps, 1) extraction of the individual as well as nuclei clumps of both positive and negative nuclei from real WSI images, and 2) systematic placement of the extracted nuclei clumps on an image canvas. The resulting images are visually similar to the original tissue images. We created a set of 42 images with different concentrations of positive and negative nuclei. These images were evaluated by four board certified pathologists in the task of estimating the ratio of positive to total number of nuclei. The resulting concordance correlation coefficients (CCC) between the pathologist and the true ratio range from 0.86 to 0.95 (point estimates). The same ratio was also computed by an automated computer algorithm, which yielded a CCC value of 0.99. Reading the phantom data with known ground truth, the human readers show substantial variability and lower average performance than the computer algorithm in terms of CCC. This shows the limitation of using a human reader panel to establish a reference standard for the evaluation of computer algorithms, thereby highlighting the usefulness of the phantom developed in this work. Using our phantom images, we further developed a function that can approximate the true ratio from the area of the positive and negative nuclei, hence avoiding the need to detect individual nuclei. The predicted ratios of 10 held-out images using the function (trained on 32 images) are within ±2.68% of the true ratio. Moreover, we also report the evaluation of a computerized image analysis method on the synthetic tissue dataset.
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Project description:Conventional histopathology is the gold standard for allograft monitoring, but its value proposition is increasingly questioned. "-Omics" analysis of tissues, peripheral blood and fluids and targeted serologic studies provide mechanistic insights into allograft injury not currently provided by conventional histology. Microscopic biopsy analysis, however, provides valuable and unique information: (a) spatial-temporal relationships; (b) rare events/cells; (c) complex structural context; and (d) integration into a "systems" model. Nevertheless, except for immunostaining, no transformative advancements have "modernized" routine microscopy in over 100 years. Pathologists now team with hardware and software engineers to exploit remarkable developments in digital imaging, nanoparticle multiplex staining, and computational image analysis software to bridge the traditional histology-global "-omic" analyses gap. Included are side-by-side comparisons, objective biopsy finding quantification, multiplexing, automated image analysis, and electronic data and resource sharing. Current utilization for teaching, quality assurance, conferencing, consultations, research and clinical trials is evolving toward implementation for low-volume, high-complexity clinical services like transplantation pathology. Cost, complexities of implementation, fluid/evolving standards, and unsettled medical/legal and regulatory issues remain as challenges. Regardless, challenges will be overcome and these technologies will enable transplant pathologists to increase information extraction from tissue specimens and contribute to cross-platform biomarker discovery for improved outcomes.
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