Optimization of Image Quality In A Radiotherapy Ct Simulator: Development of A Specific Protocol

Research output: Contribution to journalOriginal Articlepeer-review

Abstract

This study aimed to optimize the scan parameters of the Siemens Somatom Scope CT simulator to ensure optimal image quality for the detection of brain tumors. To achieve this, measurements were performed using the Catphan CTP 503 phantom, evaluating metrics such as the contrast-to-noise ratio (CNR), low-contrast visibility (LCV), signal-to-noise ratio (SNR), noise level, and uniformity index (UI). The optimization process involved adjusting scan parameters such as kilovoltage (kV), tube current (mA), and the automatic exposure control system (CareDose4D). The results showed that the optimized protocol (Protocol 2) achieved the highest CNR values—61.41 for polymethylpentene (PMP) and 47.9 for low-density polyethylene (LDPE)—as well as the best LCV and an SNR of 31.2. In addition, it exhibited the lowest noise level (0.3%) and the best uniformity index (0.03). These findings suggest that Protocol 2 may be an effective tool for improving the accuracy of brain structure delineation and other anatomical regions, thereby enhancing radiotherapy treatment planning.

Translated title of the contributionOptimizaci´n De La Calidad De Imagen En Un Tom´grafo Simulador Para Radioterapia: Desarrollo De Un Protocolo Espec´ıfico
Original languageAmerican English
Pages (from-to)81-97
Number of pages17
JournalMomento
Issue number72
DOIs
StateIndexed - 20 Jan 2026

Bibliographical note

Publisher Copyright:
© (2025). (Revista de F´ısica). All rights reserved.

Keywords

  • calidad de imagen
  • image optimization
  • image quality
  • optimizaci´on de imagen
  • planificaci´on del tratamiento
  • radioterapia
  • radiotherapy
  • simulator CT
  • tom´ografo simulador
  • treatment planning

Fingerprint

Dive into the research topics of 'Optimization of Image Quality In A Radiotherapy Ct Simulator: Development of A Specific Protocol'. Together they form a unique fingerprint.

Cite this