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Fat-Water Phantoms for Magnetic Resonance Imaging Validation: A Flexible and Scalable Protocol
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Pancreas fat quantification with quantitative CT: an MRI correlation analysis.

W J Yao1, Z Guo2, L Wang2

  • 1Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China; Department of Radiology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.

Clinical Radiology
|January 30, 2020
PubMed
Summary
This summary is machine-generated.

Quantitative computed tomography (QCT) shows good correlation with magnetic resonance imaging (MRI) for pancreatic fat assessment. While QCT measurements were slightly lower than MRI proton density fat fraction (PDFF), further research can improve numerical agreement.

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Area of Science:

  • Radiology
  • Medical Imaging
  • Gastroenterology

Background:

  • Pancreatic fat content is an important biomarker.
  • Accurate quantification methods are crucial for clinical applications.
  • Quantitative computed tomography (QCT) and chemical-shift-encoded magnetic resonance imaging (CSE-MRI) are advanced imaging techniques.

Purpose of the Study:

  • To evaluate pancreatic fat content using QCT.
  • To correlate QCT findings with CSE-MRI proton density fat fraction (PDFF).
  • To assess the agreement between QCT and CSE-MRI for pancreatic fat quantification.

Main Methods:

  • 52 participants from the Prospective Urban Rural Epidemiology (PURE) Study underwent both QCT and CSE-MRI.
  • Regions of interest were placed in the pancreatic head, body, and tail on both scans.
  • Pearson correlation and Bland-Altman analyses were used to compare measurements.

Main Results:

  • QCT and CSE-MRI measurements of pancreatic fat content demonstrated a strong correlation (r=0.805, p<0.0001).
  • Bland-Altman analysis indicated that QCT measurements were systematically lower by 6.3% compared to CSE-MRI PDFF.
  • The findings suggest good agreement between the two imaging modalities.

Conclusions:

  • QCT is a viable method for assessing pancreatic fat content with good correlation to CSE-MRI PDFF.
  • Further studies are needed to refine QCT protocols for improved numerical agreement with PDFF.
  • This research supports the potential of QCT in pancreatic fat quantification.