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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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Phantom-based radiomics feature test-retest stability analysis on photon-counting detector CT.

Alexander Hertel1, Hishan Tharmaseelan1, Lukas T Rotkopf1,2

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Radiomics analysis using photon-counting CT shows high feature stability in phantom studies. This stability may enable the clinical application of radiomics in routine practice.

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Area of Science:

  • Medical Imaging
  • Radiology
  • Computational Pathology

Background:

  • Radiomics analysis shows promise for research applications in medical imaging.
  • Clinical implementation of radiomics is hindered by parameter instability.
  • Photon-counting detector CT (PCCT) is an emerging imaging technology.

Purpose of the Study:

  • To evaluate the stability of radiomics features derived from PCCT scans.
  • To assess the impact of varying exposure levels (mAs) on radiomics stability.
  • To identify stable and important radiomics parameters for potential clinical use.

Main Methods:

  • PCCT scans of organic phantoms (apples, kiwis, limes, onions) were acquired at different mAs settings.
  • Semi-automatic segmentation and extraction of radiomics parameters were performed.
  • Statistical analyses including CCC, ICC, random forest, and cluster analysis were employed.

Main Results:

  • 70% of features demonstrated excellent stability (CCC > 0.9) in test-retest analysis.
  • 65.4% of features remained stable after repositioning.
  • 75% of features showed excellent stability across different mAs values.
  • Random forest analysis identified key features for distinguishing phantom groups.

Conclusions:

  • Radiomics analysis using PCCT exhibits high feature stability on organic phantoms.
  • This stability supports the potential integration of PCCT-based radiomics into clinical workflows.
  • PCCT may facilitate the routine clinical application of radiomics.