Free automatic software for quality assurance of computed tomography calibration, edges and radiomics metrics reproducibility.

Fecha de publicación: 29/09/2023 Fecha Ahead of Print: 30/09/2023

Autores de IIS La Fe

• Matías Fernández Patón

  Autor

• Natalia Tejedor Aguilar

  Autor

• Irene Torres Espallardo

  Autor

• José Pérez Calatayud

  Autor

• 

  Luis Martí Bonmatí

  Autor

• Montserrat Carles Fariña

  Autor

Participantes ajenos a IIS La Fe

• Saborido-Moral, Juan D.
• Cristian-Marin, Andrei
• Campayo-Esteban, Juan M.
• Baltas, Dimos

Grupos

• Investigacion Biomédica en Imagen (GIBI 2-30)

  Investigador Principal

  Leonor Cerdá Alberich

• Investigación Clínica y Traslacional en Cáncer

  

  Leader

  José Gómez Codina

• Núcleo de investigación traslacional integrado Urológico de Valencia (NITIUV)

  

  Leader

  César David Vera Donoso

• Unidad Mixta de Investigación en Radiofísica e Instrumentación nuclear en medicina

  Leader

  Facundo Ballester Pallares

Abstract

PURPOSE: To develop a QA procedure, easy to use, reproducible and based on open-source code, to automatically evaluate the stability of different metrics extracted from CT images: Hounsfield Unit (HU) calibration, edge characterization metrics (contrast and drop range) and radiomic features. METHODS: The QA protocol was based on electron density phantom imaging. Home-made open-source Python code was developed for the automatic computation of the metrics and their reproducibility analysis. The impact on reproducibility was evaluated for different radiation therapy protocols, and phantom positions within the field of view and systems, in terms of variability (Shapiro-Wilk test for 15 repeated measurements carried out over three days) and comparability (Bland-Altman analysis and Wilcoxon Rank Sum Test or Kendall Rank Correlation Coefficient). RESULTS: Regarding intrinsic variability, most metrics followed a normal distribution (88% of HU, 63% of edge parameters and 82% of radiomic features). Regarding comparability, HU and contrast were comparable in all conditions, and drop range only in the same CT scanner and phantom position. The percentages of comparable radiomic features independent of protocol, position and system were 59%, 78% and 54%, respectively. The non-significantly differences in HU calibration curves obtained for two different institutions (7%) translated in comparable Gamma Index G (1mm, 1%, >99%). CONCLUSIONS: An automated software to assess the reproducibility of different CT metrics was successfully created and validated. A QA routine proposal is suggested.

Copyright © 2023 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.

Keywords

• Computed tomography; Automatic quality assurance; Radiomics; Reproducibility