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Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
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Protocol optimization for quantitative MRI studies in radiation oncology: II. Diffusion MRI.

Yves De Deene1,2,3,4, Morgan J Wheatley2,3, Robba Rai1,2

  • 1Cancer Therapy Centre, SWSLHD, Liverpool, 2170 NSW, Australia.

Physics in Medicine and Biology
|May 15, 2026
PubMed
Summary
This summary is machine-generated.

Diffusion-weighted MRI (DWI) is crucial for radiation therapy, but quantitative accuracy is hampered by inconsistent methods. Robust quality assurance and advanced diffusion models are essential for reliable diffusion-weighted imaging in clinical practice.

Keywords:
anthropomorphic imaging phantomsbiofunctional imagingdiffusion-weighted imaging (DWI)imaging biomarkersquality assurancequantitative MRI

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Radiotherapy
  • Biomedical Engineering

Background:

  • Diffusion-weighted MRI (DWI) is widely used in radiation therapy for gross target volume (GTV) delineation and treatment response assessment.
  • Quantitative accuracy of apparent diffusion coefficient (ADC) maps is critical but often compromised by suboptimal scanning and simplified diffusion models.
  • Discrepancies in published ADC maps highlight the need for improved quality assurance (QA) and fitting models in clinical DWI.

Purpose of the Study:

  • To address the discrepancies in quantitative ADC maps derived from diffusion-weighted MRI (DWI) in radiation therapy.
  • To emphasize the importance of robust quality assurance (QA) and appropriate diffusion models for accurate quantitative DWI.
  • To discuss common pitfalls and methodological errors in clinical DWI studies.

Main Methods:

  • Review and discussion of various quality assurance (QA) methods for clinical DWI.
  • Analysis of deviations from the mono-exponential diffusion model, including diffusion time and directional dependence in human tissues.
  • Illustration of how organ motion can compromise quantitative parametric diffusion maps.

Main Results:

  • Standard commercial QA phantoms may not detect all methodological errors in quantitative DWI.
  • Significant deviations from the mono-exponential diffusion model are observed in human tissues.
  • Organ motion can introduce substantial, often unrecognized, artifacts in quantitative diffusion parametric maps.

Conclusions:

  • Robust QA protocols and advanced diffusion models are essential for accurate quantitative DWI in radiation therapy.
  • Oversimplified diffusion models and inadequate QA can lead to unreliable ADC measurements.
  • Awareness of potential artifacts, such as those caused by organ motion, is crucial for accurate interpretation of quantitative DWI data.