Cellular imaging at 3 T: Detecting Cells in Inflammation

using Active Labeling with Super paramagnetic Iron oxide

Azhar Hosein FarazMedical Biophysics Western University

Robarts Research Institute Under supervision of: Dr. Paula Foster

4th April 2012

Immune Response and Inflammation

• Tissue injury caused by bacteria, trauma, chemicals, or any other phenomenon –Inflammation.

• Walling- off

• Within minutes after inflammation occurs macrophages already present in the tissues (microglia, Kupffer cells,..) begins their phagocytic action.

• The second line of defence within the first hours of inflammation begins are the large number of neutrophils that invade the inflamed area.

• In Vivo Labeling of Cells with Iron Particles

Imaging Immune Cells with MRI

Iron oxide contrast agent

Intravenous (i.v) administration Phagocytosis

Labeled cells

Iron oxide-based MRI contrast agents

Adapted from Modo, M. et al. Mol. Imag, 2004 Effect of iron is tocause signal loss inMRI images

Iron-labeled cells In gel

Aim of study

• To detect inflammatory cells in the mouse brain by in vivo 3T MRI in a model of neuroinflammation.

MRI Pre-Scan of body

Normal Healthy Mouse (C57/Bl6, n=2)

Iron Oxide (Fe) injected Intravenously (IV) to Mice

MRI Body 24 hours Post-injection (Fe)

Fe - Bone marrow- Liver - Spleen

Monocytes

Inject mice with :LPS (lipopolysaccharide) 48 hours Post-injection (Fe)

MRI Body 6 days Post-injection (Fe)

Model of Neuroinflammation- Neurotoxic

- Over activation of microglia

MRI Brain 9 days Post-injection (Fe)

Methods

3T clinical system

Solenoid radio frequency coil

Custom-built high performance gradient

Imaging Cells (3T cellular MRI) at Robarts

- Only lab in the world- research imaging

experiments at clinical magnetic strength

- pulse sequence known as, bSSFP.

Image Analysis: Body Images

• Measuring mean signal intensity of different image slices in Liver, Bone marrow, and Spleen.

• Standard deviation (SD) of Noise present in each slice.

• SNR Signal to Noise ratio Mean signal intensity / SD of Noise Present in each scan slice

• No. of Voids present in Brain MRI scan • Mean signal intensity of each discrete region of

signal void• Fractional signal loss in %

=

• Clear canvas software used for analyze of MRI scan images.

Image Analysis: Brain Images

Results

Whole Mouse Body BSSFP Images

Head Tail Sagittal view of mouse

Before Iron Injection

Post Injection Iron

• In vivo labelling of liver, spleen and bone marrow macrophages

Results: SNR

• Liver > Spleen > Bone marrow

MRI Brain • Voids present in brain

Results: FSL

• FSL is related to the amount of Iron in discrete reigns of signal void.

• Can be related to the number of iron-labeled cells.

SUMMARY

• Changes in SNR suggests that cells take up iron in the liver, spleen and bone marrow - the numbers of iron-labeled cells is different for each organ and varies in mice.

• This work indicates that pre-labeling immune cells with iron allows us to track their involvement in inflammation in the brain

• This study has been done for first time

Future directions

• To prove that signal loss in the brain is due to the accumulation of immune cells

• To determine which kind of cells are presenting in brain, using histology and experiments with transgenic mice.

• To obtain body images over a prolonged time period, to better understand the time course of cell uptake and retention of iron.

Acknowledgment

• Supervisor : Dr. Paula Foster

• Research funding : MS society

• Thanking Jonatan Snir, for imaging

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