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Magnetic Resonance Imaging (MRI) and Ventilation Perfusion Scans are two radiological investigations that offer detailed diagnostic images of the body, particularly lung structures.
MRI
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Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
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Imaging Studies III: Computed Tomography01:27

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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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Radiomics feature robustness as measured using an MRI phantom.

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  • 1Department of Radiation Physics, Unit 1420, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX, 77030, USA.

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Magnetic resonance imaging (MRI) radiomics features show variability with different scanning protocols and scanners. Robust features with low variation and high repeatability are essential for reliable clinical decision-making in radiomics studies.

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Area of Science:

  • Medical Imaging
  • Radiomics
  • Quantitative Imaging

Background:

  • Radiomics extracts quantitative features from medical images for outcome prediction and clinical decision support.
  • Radiomics feature robustness is crucial, as they can be sensitive to imaging parameters and scanner variations.

Purpose of the Study:

  • To assess the robustness of magnetic resonance imaging (MRI) radiomics features against variations in scanning protocols and scanners.
  • To identify reliable radiomics features for future MRI-based radiomics research.

Main Methods:

  • Utilized an MRI radiomics phantom and healthy volunteer data.
  • Evaluated radiomics feature variability across different scanning parameters and scanners.
  • Assessed feature repeatability using a test-retest scheme.
  • Quantified variability using the coefficient of variation and repeatability using the intraclass correlation coefficient (ICC) for T1- and T2-weighted images.

Main Results:

  • Radiomics features exhibited varying degrees of sensitivity to different scanning parameters and scanners.
  • Phantom analysis showed high repeatability with average ICCs of 0.963 (T1w) and 0.959 (T2w).
  • Volunteer analysis yielded slightly lower repeatability with average ICCs of 0.856 (T1w) and 0.849 (T2w).

Conclusions:

  • MRI radiomics features are demonstrably dependent on scanning parameters and hardware.
  • Features with low coefficient of variation and high ICC are suitable for MRI radiomics studies.
  • Findings provide guidance for selecting robust features in future radiomics research.