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Optimisation of CT scan parameters to increase the accuracy of gross tumour volume identification in brain radiotherapy

Published online by Cambridge University Press:  15 June 2020

Kosar Estak ,
Mohammad Mohammadzadeh ,
Nahideh Gharehaghaji ,
Tohid Mortezazadeh Open the ORCID record for Tohid Mortezazadeh [Opens in a new window] ,
Rahim Khatyal  and
Davood Khezerloo
Kosar Estak
Affiliation:
Department of Radiology, School of Paramedicine, Tabriz University of Medical Sciences, Tabriz, Iran
Mohammad Mohammadzadeh
Affiliation:
Department of Radiology and Radiotherapy, School of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
Nahideh Gharehaghaji
Affiliation:
Department of Radiology, School of Paramedicine, Tabriz University of Medical Sciences, Tabriz, Iran
Tohid Mortezazadeh
Affiliation:
Department of Medical Physics, School of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
Rahim Khatyal
Affiliation:
Department of Radiology, School of Paramedicine, Tabriz University of Medical Sciences, Tabriz, Iran
Davood Khezerloo*
Affiliation:
Department of Radiology, School of Paramedicine, Tabriz University of Medical Sciences, Tabriz, Iran
*
Author for correspondence: Davood Khezerloo, Assistant Professor of Medical Physics, Department of Radiology, School of Paramedicine, Tabriz University of Medical Sciences, Tabriz, Iran. Tel/Fax: +984133356911. E-mail: D.khezerloo@gmail.com.
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Abstract

Aim:

This study aimed to optimise computed tomography (CT) simulation scan parameters to increase the accuracy for gross tumour volume identification in brain radiotherapy. For this purpose, high-contrast scan protocols were assessed.

Materials and methods:

A CT accreditation phantom (ACR Gammex 464) was used to optimise brain CT scan parameters on a Toshiba Alexion 16-row multislice CT scanner. Dose, tube voltage, tube current–time and CT dose index (CTDI) were varied to create five image quality enhancement (IQE) protocols. They were assessed in terms of contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR) and noise level and compared with a standard clinical protocol. Finally, the ability of the selected protocols to identify low-contrast objects was examined based on a subjective method.

Results:

Among the five IQE protocols, the one with the highest tube current–time product (250 mA) and lowest tube voltage (100 kVp) showed higher CNR, while another with a tube current–time product of 150 mA and a tube voltage of 135 kVp had improved SNR and lower noise level compared to the standard protocol. In contouring low-contrast objects, the protocol with the highest milliampere and lowest peak kilovoltage exhibited the lowest error rate (1%) compared to the standard protocol (25%).

Findings:

CT image quality should be optimised using the high-dose parameters created in this study to provide better soft tissue contrast. This could lead to an accurate identification of gross tumour volume recognition in the planning of radiotherapy treatment.

Keywords

brain radiotherapyCT image qualityCT simulationtumour contouring
Type
Original Article
Information
Journal of Radiotherapy in Practice , Volume 20 , Issue 3 , September 2021 , pp. 340 - 344
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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