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

C. Ryan Oliver; Trisha  M. Westerhof; Maria  G. Castro; Sofia  D. Merajver

doi:10.3791/61654

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

JoVE Journal
Cancer Research

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JoVE Journal Cancer Research

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

7,249 Views

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09:53 min

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August 16, 2020

DOI:

10.3791/61654-v

DOI:

10.3791/61654-v

•

09:53 min

August 16, 2020

•

7233 Views

C. Ryan Oliver*^1,2, Trisha M. Westerhof*^1,2, Maria G. Castro^2,3,4, Sofia D. Merajver^1,2

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

Summary

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).

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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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