Non-alcoholic fatty liver disease (NAFLD) prevalence is estimated at >25% in the U.S., makingit the most common cause of chronic liver disease. Non-alcoholic steatohepatitis (NASH), theprogressive form of NAFLD, affects 1-3% of the U.S. population and is expected to double by2030. Currently, there is no effective pharmacotherapy for NAFLD, but there are numerouspromising drug candidates being evaluated in clinical trials. However, the primary endpoint forthese trials, histologic fibrosis, has shortcomings including sampling error and use of asubjective five category scale to quantify a continuous variable. Our team has pioneered the useof 3D open-top light-sheet (OTLS) microscopy, which enables rapid, high-throughput imaging oflarge clinical samples. In combination with cutting-edge machine learning techniques, wehypothesize that 3D OTLS microscopy can provide more accurate and consistent assessmentof fibrosis in liver biopsies from NASH patients. We will test this hypothesis by developing amultiplex staining protocol and machine learning analysis pipeline, which will be piloted on 20archived FFPE liver biopsies. Results from our assay will be correlated with currently usedprimary and secondary outcome measures to motivate further studies with sing archivedsamples from clinical trials with responsivity and outcomes data.
Public Health Relevance Statement: Narrative
Non-alcoholic steatohepatitis (NASH) affects 1-3% of the U.S. population and is expected to
double by 2030. There are many promising therapeutic agents to treat NASH, but the primary
outcome, histologic fibrosis assessment, is plagued by sampling error and use of a subjective
five category scale to quantify a continuous variable. We propose an assay to visualize and
quantify liver fibrosis in 3D for more accurate and consistent NASH diagnostics.
Project Terms: Affect ; Aftercare ; After Care ; After-Treatment ; post treatment ; Archives ; Biological Assay ; Assay ; Bioassay ; Biologic Assays ; Biopsy ; Cell Nucleus ; Nucleus ; Clinical Trials ; Collagen ; Cytoplasm ; Pharmacotherapy ; Drug Therapy ; drug treatment ; Esters ; Fibrosis ; Future ; Gold ; Primary carcinoma of the liver cells ; Hepatocarcinoma ; Hepatocellular Carcinoma ; Hepatocellular cancer ; Hepatoma ; Liver Cells Carcinoma ; liver carcinoma ; Human ; Modern Man ; Light ; Photoradiation ; Liver ; hepatic body system ; hepatic organ system ; Magnetic Resonance Imaging ; MR Imaging ; MR Tomography ; MRI ; Medical Imaging, Magnetic Resonance / Nuclear Magnetic Resonance ; NMR Imaging ; NMR Tomography ; Nuclear Magnetic Resonance Imaging ; Zeugmatography ; Manuals ; Methods ; Microscopy ; mortality ; Pathology ; Patients ; Research ; Sampling Errors ; Computer software ; Software ; Stains ; Staining method ; Technology ; Testing ; Tissues ; Body Tissues ; Translating ; United States ; Universities ; Washington ; Work ; Diagnostic radiologic examination ; Conventional X-Ray ; Diagnostic Radiology ; Diagnostic X-Ray ; Diagnostic X-Ray Radiology ; Radiography ; Roentgenography ; X-Ray Imaging ; X-Ray Medical Imaging ; Xray imaging ; Xray medical imaging ; conventional Xray ; diagnostic Xray ; diagnostic Xray radiology ; Sirius Red F3B ; picrosirius red ; sirius red F 3B ; Trichrome stain ; Imaging Techniques ; Imaging Procedures ; Imaging Technics ; Outcome Measure ; Data Set ; Dataset ; Custom ; Microscope ; improved ; liver biopsy ; Liver lesion biopsy ; Clinical ; Phase ; Histologic ; Histologically ; Evaluation ; Training ; Failure ; Liver Fibrosis ; fibrotic liver ; hepatic fibrosis ; Therapeutic Agents ; chronic hepatic disease ; chronic hepatic disorder ; chronic liver disorder ; chronic liver disease ; Diagnostic ; machine learned ; Machine Learning ; Malignant Tumor of the Prostate ; Malignant prostatic tumor ; Prostate CA ; Prostate Cancer ; Prostatic Cancer ; Malignant neoplasm of prostate ; Complex ; human tissue ; Protocol ; Protocols documentation ; Techniques ; 3-D ; 3D ; three dimensional ; 3-Dimensional ; Services ; drug efficacy ; Disease Outcome ; Categories ; Position ; Positioning Attribute ; Sampling ; 3-D Imaging ; 3D imaging ; Three-Dimensional Imaging ; Formalin ; Preparedness ; Readiness ; Data ; Detection ; Clinical Data ; Small Business Innovation Research Grant ; SBIR ; Small Business Innovation Research ; Pathologic ; Preparation ; Process ; Cirrhosis ; cirrhotic ; Image ; imaging ; Three-dimensional analysis ; 3-D analysis ; 3-dimensional analysis ; 3D analysis ; Outcome ; three dimensional structure ; 3-D structure ; 3-dimensional structure ; 3D structure ; Population ; Prevalence ; nonalcoholic steatohepatitis ; NASH ; non-alcohol induced steatohepatitis ; non-alcoholic steato-hepatitis ; non-alcoholic steatohepatitis ; nonalcoholic steato-hepatitis ; high risk ; primary outcome ; secondary outcome ; drug candidate ; elastography ; elastic imaging ; elasticity imaging ; lightspeed ; light speed ; speed of light ; CLIA certified ; CLIA accredited ; CLIA approved ; CLIA compliant ; CLIA licensed ; non-alcoholic fatty liver disease ; NAFLD ; non-alcohol fatty liver disease ; non-alcoholic liver disease ; nonalcoholic fatty liver disease ; primary endpoint ; primary end point ; machine learning algorithm ; machine learned algorithm ; analysis pipeline ; three-dimensional visualization ; 3-D visualization ; 3-dimensional visualization ; 3D visualization ; algorithm training ; antifibrotic treatment ; antifibrotic therapy ; sample archive ;
