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Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography
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Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

DOI:
10.3791/61654-v

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09:53 min

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August 16, 2020

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, , ,
1Department of Internal Medicine,University of Michigan Ann Arbor, 2Rogel Cancer Center,University of Michigan Ann Arbor, 3Department of Neurosurgery,University of Michigan Ann Arbor, 4Department of Cell and Developmental Biology,University of Michigan Ann Arbor

Capítulos

  • 00:04Introduciton
  • 00:49Form and Assemble the Microfluidic BBN Device
  • 03:24Cancer Cell Seeding
  • 04:023D Model Imaging Data Conversion
  • 05:06Plane Fitting
  • 06:04Individual Cancer Cell Analysis
  • 07:05Results: Representative Brain Metastatic Tumor Micro-Environment Analyses
  • 08:56Conclusion

Summary

Tadução automática

Tadução automática

Here, we present a protocol for preparing and culturing a blood brain barrier metastatic tumor micro-environment and then quantifying its state using confocal imaging and artificial intelligence (machine learning).

Tags

Keywords: Confocal TomographyMachine LearningOrgan-on-a-chipBrain MetastasisTumor MicroenvironmentCell BehaviorDiagnostic ToolMicrofluidic DeviceCollagenAstrocyteEndothelial CellsCell Culture

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