Review Article
The reliability of CT numbers as absolute values for diagnostic scanning, dental imaging, and radiation therapy simulation: A narrative review

https://doi.org/10.1016/j.jmir.2021.11.007Get rights and content

Abstract

Background and purpose

The purpose of this review was to examine the reported factors that affect the reliability of Computed Tomography (CT) numbers and their impact on clinical applications in diagnostic scanning, dental imaging, and radiation therapy dose calculation.

Methods

A comprehensive search of the literature was conducted using Medline (PubMed), Google Scholar, and Ovid databases which were searched using the keywords CT number variability, CT number accuracy and uniformity, tube voltage, patient positioning, patient off-centring, and size dependence. A narrative summary was used to compile the findings under the overarching theme.

Discussion

A total of 47 articles were identified to address the aim of this review. There is clear evidence that CT numbers are highly dependent on the energy level applied based on the effective atomic number of the scanned tissue. Furthermore, body size and anatomical location have also indicated an influence on measured CT numbers, especially for high-density materials such as bone tissue and dental implants. Patient off-centring was reported during CT imaging, affecting dose and CT number reliability, which was demonstrated to be dependent on the shaping filter size.

Conclusion

CT number accuracy for all energy levels, body sizes, anatomical locations, and degrees of patient off-centring is observed to be a variable under certain common conditions. This has significant implications for several clinical applications. It is crucial for those involved in CT imaging to understand the limitations of their CT system to ensure radiologists and operators avoid potential pitfalls associated with using CT numbers as absolute values for diagnostic scanning, dental imaging, and radiation therapy dose calculation.

Résumé

Contexte et objectif

L'objectif de cette étude était d'examiner les facteurs rapportés qui affectent la fiabilité des valeurs de tomodensitométrie, calculées en unités Hounsfield (valeurs UH), et leur impact sur les applications cliniques en matière de balayage diagnostique, d'imagerie dentaire et de calcul de la dose de radiothérapie.

Méthodologie

Une recherche exhaustive de la littérature a été menée dans les bases de données Medline (PubMed), Google Scholar et Ovid à l'aide des mots-clés variabilité des valeurs UH, précision et uniformité des valeurs UH, tension du tube, positionnement du patient, décentrage du patient et dépendance de la taille. Un résumé narratif a été utilisé pour compiler les résultats sous le thème principal.

Discussion

Au total, 47 articles ont été recensés pour répondre à l'objectif de cette étude. Il est clairement établi que la valeur UH dépend fortement du niveau d'énergie appliqué en fonction du numéro atomique effectif du tissu scanné. En outre, la taille du corps et la localisation anatomique ont également indiqué une influence sur les valeurs UH mesurées, en particulier pour les matériaux à haute densité tels que le tissu osseux et les implants dentaires. Un décentrage du patient a été rapporté pendant l'imagerie TDM, affectant la dose et la fiabilité de la valeur UH, dont il a été démontré qu'il dépendait de la taille du filtre de mise en forme.

Conclusion

La précision du nombre de tomographies pour tous les niveaux d'énergie, toutes les tailles de corps, tous les emplacements anatomiques et tous les degrés d'excentration du patient est variable dans certaines conditions courantes. Cela a des implications importantes pour plusieurs applications cliniques. Il est crucial pour les personnes impliquées dans l'imagerie TDM de comprendre les limites de leur système de TDM afin de s'assurer que les radiologues et les opérateurs évitent les pièges potentiels associés à l'utilisation des valeurs UH comme valeurs absolues pour le balayage diagnostique, l'imagerie dentaire et le calcul de la dose de radiothérapie.

Introduction

Computed Tomography (CT) is a vital imaging modality in medical imaging and has replaced many diagnostic radiographic procedures as well as being key in the simulation of radiation therapy treatment. In CT, all body tissues can be expressed in Hounsfield units (HU), also referred to as CT numbers, which reflect the value of the attenuation coefficient of any specified tissue relative to the attenuation coefficient of water, where vacuum is arbitrarily defined to be a -1000 HU and water as zero HU [1].

Several clinical outcomes rely on the accuracy of CT number values to identify internal structures and differentiate pathological tissue from adjacent healthy tissue [2]. The reliance on CT numbers for diagnosis underlines the importance of accurate performance for radiological diagnosis. Thus, variation within and between scanners and technical factors that impact accuracy should be taken into account when making quantitative measurements that depend on quantitative HU values for diagnosis; examples include adrenal and renal lesions [3], [4], [5], [6], renal stone composition [7], cerebral venous thrombosis [8], airway and parenchymal abnormalities [9], the extent of coronary atherosclerosis [10], 11, 12, and hepatic stenosis [13,14].

Cone beam CT (CBCT) also relies on CT numbers for diagnosis and treatment planning in several dentomaxillofacial clinical applications [15]. In fact, the accuracy of CT numbers can affect the assessment of bone mineralisation at potential implant sites using computer-aided automatic segmentation [15,16].

In radiation therapy, the dose calculation treatment planning systems (TPS) are highly dependent upon CT imaging data and are used to delineate body contour, shape, the density of internal organs and dose coverage for targeting tumours adjacent to critical organs [17]. The value of CT numbers represent tissue electron density (ED) and directly relate to the attenuation characteristic of the X-ray beam in the photon path length within a particular tissue [18]. Accurate dose calculation is possible only when the correct CT number, expressed in HU, and relative electron density (RED) is established in TPS [19]. Changes to the measured HU for a specific tissue, compared say to the HU value in the TPS calibration, can impact material assignment in CT pre-processing and influence therapeutic doses calculated by the TPS [20].

In brief, CT number accuracy is critical to achieving optimal efficiency of several imaging applications, dental treatment planning, and radiation therapy dose calculation. This review will discuss the current literature concerning four key factors (energy dependence, body size and anatomical location and patient centring) that influence the reliability of CT numbers as an absolute value.

Section snippets

Methodology

A review of the current literature was undertaken across Medline (PubMed), Google scholar, and Ovid databases to investigate this topic with the keywords. Broad search terms of CT number variability, CT number accuracy and uniformity, tube voltage, patient positioning, patient off-centring, and size dependence (including synonyms) were employed. Only studies with unrestricted access to their full text and written in English were included. The refined publications from the identified search

Discussion

The primary objective of the review was to highlight the importance of CT number accuracy in clinical practice. Furthermore, this review intended to explore the effect of applied energy, body size, anatomical location, and patient centring on CT number reliability.

Summary of evidence

Linearity is an important parameter of image quality that affects radiation dose calculation and quantitative diagnostic imaging. Various authorities are known to provide CT number tolerance and acceptance limits that are not the same. Generally, CT numbers for peripheral ROIs should not deviate by more than 4 HU compared to the central ROI [29,30]. A CT number is considered energy-dependent for any material other than air and water, based on the physical principles of photon interaction

Acknowledgments

The authors owe deep gratitude to Dr. Andrew Kilgour for his valuable discussions and consultations. I would like to give my special thanks to The Hashemite University for their generosity with my PhD scholarship.

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  • Contributors: All authors provided critical feedback, helped shape the research, and approved the manuscript's final version.

    Funding: This study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors (OR Disclose any funding here).

    Competing interests: The author(s) have no financial disclosures or conflicts of interest to declare.

    Ethical approval: Not required for this article type.

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