Counting small hypointense spots confounds the quantification of functional islet mass based on islet MRI

J H Kim1, S M Jin, S H Oh

  • 1Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.

Insights

Excluding small spots on MRI scans improves the assessment of transplanted islet function. This method helps accurately quantify functioning islet mass after islet transplantation for better diabetes management.

Area of Science:

  • Biomedical Imaging
  • Transplantation Biology
  • Metabolic Disease Research

Background:

  • Magnetic Resonance Imaging (MRI) using iron nanoparticles is used to monitor islet grafts.
  • Artifacts from free iron or fragmented islets can hinder accurate interpretation of MRI scans.
  • Improving the quantification of functioning islet mass is crucial for assessing transplant success.

Purpose of the Study:

  • To evaluate if excluding small hypointense spots on MRI improves the estimation of functioning islet mass post-transplantation.
  • To investigate the relationship between MRI findings and glycemic control in islet transplant recipients.

Main Methods:

  • Utilized a rat syngeneic intraportal islet transplantation model.
  • Quantitatively assessed MRI hypointense spots (total area, number per quartile) and correlated with recipient glycemic control.
  • Performed ex-vivo imaging and histology to identify the source of small hypointense spots.

Main Results:

  • Total area of hypointense spots was significantly larger in recipients with diabetes reversal (p = 0.002).
  • Excluding small hypointense spots significantly improved the correlation between the number of spots and blood glucose levels (p < 0.001).
  • Histology confirmed that small hypointense spots can represent phagocytosed free iron, an artifact.

Conclusions:

  • Excluding small hypointense spots enhances the accuracy of quantifying functional islet mass using MRI.
  • This strategy offers a valuable principle for developing algorithms to estimate islet graft function.
  • Improved MRI interpretation can lead to better monitoring and management of islet transplantation outcomes.

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