Home › Cell Biology › Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research
Cell Biology JoVE (Open Access) Citable · DOI

Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research

DOI: 10.3791/50238-v
What you'll learn
  • ✓ Adapt optical projection tomography to near-infrared imaging for larger specimens
  • ✓ Prepare pancreatic tissue samples and acquire NIR-OPT scan data
  • ✓ Process and reconstruct 3D tomographic images to quantify β-cell mass distribution
  • ✓ Apply computational tools to enhance multichannel imaging quality and analysis
Protocol

We describe the adaptation of optical projection tomography (OPT)1 to imaging in the near infrared spectrum, and the implementation of a number of computational tools. These protocols enable assessments of pancreatic β-cell mass (BCM) in larger specimens, increase the multichannel capacity of the technique and increase the quality of OPT data.

Difficulty
advanced
Total time
~3–5 days per specimen (including tissue preparation, scanning, and computational reconstruction)
Model organism
Mouse
Biosafety
BSL-1

Steps

1
Understand near infrared OPT technology and applications

Review the principles of optical projection tomography adapted to near-infrared spectrum, its advantages for imaging larger pancreatic specimens, and multichannel imaging capacity compared to standard OPT.

▶ 01:18
2
Set up near infrared OPT imaging apparatus

Configure the NIR-OPT hardware setup, including light source, optical components, and detector alignment for pancreatic β-cell mass imaging.

▶ 02:02
3
Prepare pancreatic tissue and acquire scan data

Perform sample preparation steps, including tissue clearing and mounting, then execute NIR-OPT scanning protocols to acquire multichannel volumetric data from pancreatic specimens.

▶ 03:31
4
Process and reconstruct three-dimensional tomographic images

Apply computational algorithms to process raw scan data, perform image reconstruction, and generate 3D volumetric datasets for quantitative analysis of β-cell mass distribution.

▶ 10:31
5
Analyze representative results and validate protocol

Review example reconstructed images and quantitative outputs demonstrating successful β-cell mass assessment across pancreatic tissue using the NIR-OPT workflow.

▶ 12:38
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