|Year : 2016 | Volume
| Issue : 3 | Page : 167-172
Quantitative assessment of radionuclide uptake and positron emission tomography-computed tomography image contrast
Hasford Francis1, John Humphrey Amuasi2, Kyere Augustine Kwame2, Mboyo Di Tamba Vangu3
1 Department of Medical Physics, School of Nuclear and Allied Sciences, University of Ghana; Medical Radiation Physics Centre, Radiological and Medical Sciences Research Institute, Ghana Atomic Energy Commission, Accra, Ghana; Department of Nuclear Medicine, Charlotte Maxeke Johannesburg Academic Hospital, University of the Witwatersrand, Johannesburg, South Africa
2 Department of Medical Physics, School of Nuclear and Allied Sciences, University of Ghana, Accra, Ghana
3 Department of Nuclear Medicine, Charlotte Maxeke Johannesburg Academic Hospital, University of the Witwatersrand, Johannesburg, South Africa
|Date of Web Publication||31-Aug-2016|
Medical Radiation Physics Centre, Radiological and Medical Sciences Research Institute, Ghana Atomic Energy Commission, PO Box LG 80, Legon, Accra
| Abstract|| |
Radionuclide uptake and contrast for positron emission tomography-computed tomography (PET-CT) images have been assessed in this study using NEMA image quality phantom filled with background activity concentration of 5.3 kBq/mL fluorodeoxyglucose (F-18 FDG). Spheres in the phantom were filled in turns with water to mimic cold lesions and FDG of higher activity concentrations to mimic tumor sites. Transaxial image slices were acquired on the PET-CT system and used for the evaluation of mean standard uptake value (SUV mean ) and contrasts for varying sphere sizes at different activity concentrations of 10.6 kBq/mL, 21.2 kBq/mL, and 42.4 kBq/mL. For spheres of same sizes, SUV mean increased with increase in activity concentration. SUV mean was increased by 80.6%, 83.5%, 63.2%, 87.4%, and 63.2% when activity concentrations of spheres with a diameter of 1.3 cm, 1.7 cm, 2.2 cm, 2.8 cm, and 3.7 cm, respectively, were increased from 10.6 kBq/mL to 42.4 kBq/mL. Average percentage contrast between cold spheres (cold lesions) and background activity concentration was estimated to be 89.96% for the spheres. Average contrast for the spheres containing 10.6 kBq/mL, 21.2 kBq/mL, and 42.4 kBq/mL were found to be 110.92%, 134.48%, and 150.52%, respectively. The average background contrast variability was estimated to be 2.97% at 95% confidence interval (P < 0.05).
Keywords: Hot lesion, image contrast, image quality phantom, radionuclide activity
|How to cite this article:|
Francis H, Amuasi JH, Kwame KA, Vangu MD. Quantitative assessment of radionuclide uptake and positron emission tomography-computed tomography image contrast. World J Nucl Med 2016;15:167-72
|How to cite this URL:|
Francis H, Amuasi JH, Kwame KA, Vangu MD. Quantitative assessment of radionuclide uptake and positron emission tomography-computed tomography image contrast. World J Nucl Med [serial online] 2016 [cited 2020 Aug 13];15:167-72. Available from: http://www.wjnm.org/text.asp?2016/15/3/167/174702
| Introduction|| |
Imaging of tumors with integrated positron emission tomography-computed tomography (PET-CT) system has become a standard component of diagnosis, staging and therapy response evaluation in oncology. ,,,, The use of fluorine fluorodeoxyglucose (F-18 FDG) for oncology imaging accounts for the majority of all PET-CT imaging procedures since the increased accumulation of FDG relative to normal tissue is a useful marker for many cancers.  Several methods exist for measuring the rate and/or total amount of FDG accumulation in tumors. PET scanners are designed to measure in vivo radioactivity concentration (kBq/mL), which is directly linked to the FDG concentration. Typically, however, it is the relative tissue uptake of FDG that is of interest. The two most significant sources of variation that occur in practice are the amount of injected FDG and the patient size. 
The practice of using standard uptake value (SUV) thresholds for diagnosis is known to be affected by a number of factors, which does not make it wholistically acceptable worldwide. These factors have been discussed extensively by a number of researchers. ,,,,,,,,, Two common reasons for the inconsistent use of SUVs in practice are: (i) Accurate staging and diagnostic information do not have to depend upon accurate image quantification, since the relative image content or appearance is often sufficient for such purposes,  and (ii) measured SUVs have large degree of variability due to physical and biological sources of error, as well as inconsistent and non-optimized image acquisition, processing and analysis. ,,,,, However, the use of SUV as a measurement of relative tissue/organ uptake facilitates comparisons between patients, and has been suggested as a basis for diagnosis. ,, Standard uptake value, which is a simplified measure of radionuclide uptake, is until date thought to be the most widely used method for the quantification of F-18 FDG PET studies, although other methods have been developed as well. ,
Tomographic image quality of PET-CT images is determined by a number of different performance parameters, primarily the contrast and spatial resolution, scanner sensitivity, tomographic uniformity, and the process that is used to reconstruct the images.  Due to the complexity of variation in uptake of radiopharmaceuticals and the large range of patient sizes and shapes, the characteristics of radioactivity distributions often vary greatly and a single study with a phantom cannot simulate all clinical imaging conditions. However, such studies give some indications of image quality for a particular imaging situation that could be reproduced on different scanners at different times. The study of image quality (contrast) follows closely the NEMA NU2-2007 recommendations.  Image contrast is assessed to produce images simulating those obtained in a total body imaging study involving both hot and cold lesions. Radioactivity is present outside the PET scanner to mimic out-of-field radioactivity, and spheres of different diameters are imaged in a simulated body phantom with nonuniform attenuation. Image quality is assessed by calculating image contrast and background variability ratios for both hot and cold spheres.
| Materials and Methods|| |
Image quality phantom (IEC/NEMA 2001 body phantom, Middleton, Wisconsin, USA)  was used for the study. The phantom container was filled with 5.3 kBq/mL F-18 FDG to serve as background activity. This activity concentration is an approximation of the typical background uptake observed on clinical data and hence, is recommended for the use of NEMA phantom devices. ,
Five spheres in the phantom (with diameters 1.3 cm, 1.7 cm, 2.2 cm, 2.8 cm, and 3.7 cm) were filled with tap water to mimic cold lesion imaging. The phantom was set up and aligned in a supine position on PET-CT system (Biograph 40, Siemens, Memphis, Tennessee, USA) for imaging as shown in [Figure 1]a. PET-CT images of the phantom were acquired in 3 min (one bed position) and displayed in 512 × 512 matrix. Transaxial image slice centering on the spheres as shown in [Figure 1]b was selected for the analysis.
|Figure 1: (a) NEMA image quality phantom under scanning (b) PET-CT image showing cold spheres (lesions) (c) PET-CT image showing hot spheres (lesions)|
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The spheres were emptied and refilled with F-18 FDG of concentration 10.6 kBq/mL such that the ratio of concentration between spheres and background was 2:1. Images were acquired in the same setup and acquisition conditions as in step 1.
The procedure was repeated for activity concentrations of 21.2 kBq/mL and 42.4 kBq/mL such that the ratios of concentration between sphere and background were 4:1 and 8:1, respectively. [Figure 1]c indicates hot spots from the higher activity concentration in spheres.
Standard uptake values (SUVs) and image contrasts (Q) for the different activity concentrations in the spheres were assessed by drawing regions of interest (ROIs) over the respective target areas, and employing equations 1-4. Four transaxial image slices (one from each of the four steps) centering on all spheres were used for the analysis.
Percentage contrasts for hot and cold spheres were estimated by equations (2) and (3), respectively. 
where C H denotes the counts of activity in ROI for hot sphere and C B denotes average counts of activity in corresponding background ROIs; a H is activity concentration in the hot sphere and a B is activity concentration in the background; C C denotes the counts of activity in ROI for cold sphere.
Percentage background contrast variability (N) was estimated from equation 4. 
where K is the number of background ROIs (i.e. 48).
| Results|| |
The study was performed to assess the quality of PET-CT images by simulating those obtained in total body imaging involving hot and cold lesions. Four transaxial image slices corresponding to cold sphere (water) and hot spheres (10.6 kBq/mL, 21.2 kBq/mL, and 42.4 kBq/mL) were used in examining the trends of radionuclide uptake and image contrasts in the study. SUV, which indirectly characterizes the level of radionuclide uptake in tissues, was used as a measure to analyze the quantities of radionuclide activity in spheres of different sizes in the image quality phantom. The image quality phantom mimics a human being with varying tumor sites and sizes. For uniform activity distribution with no excretion, SUV = 1 assuming tissue density of 1 g/cm 3 . Mean SUV (SUV mean ) was used as quantity for measurement in this study because its value does not change significantly with image reconstruction factors such as matrix size, number of subsets, and iterations, compared to maximum SUV (SUV max ). 
Uptake values (SUV mean ) for the different activity concentrations and respective sphere sizes are presented in [Table 1] and graphically shown in [Figure 2]. Pixel intensity plot from image J, along the central point of a hot spot in the transaxial images is indicated in [Figure 3]. The percentage contrast estimates are presented in [Table 2]. Variation of percentage contrast with the sphere's activity concentrations is presented in [Figure 4] while the variation of percentage contrast with spherical sizes is presented in [Figure 5]. The background contrast variability estimates for different ROI sizes are presented in [Table 3] and graphically presented in [Figure 6].
|Figure 2: Mean standard uptake values for ROIs of different activity concentrations|
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|Figure 4: Percentage contrast variability with activity concentration in sphere|
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|Figure 5: Percentage contrast for spheres of different sizes and activities|
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|Table 1: Standard uptake values (mean) for ROIs of different activity concentrations |
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| Discussion|| |
For spheres of same sizes, SUV mean increased with increase in activity concentration [Figure 2]. Between 10.6 kBq/mL and 42.4 kBq/mL F-18 FDG solution, SUV mean increased by 80.6%, 83.5%, 63.2%, 87.4%, and 63.2% for spheres of diameters 1.3 cm, 1.7 cm, 2.2 cm, 2.8 cm, and 3.7 cm, respectively. Radionuclide uptake values correspond proportionally to the concentration of activity in organs or tissues; hence, higher concentration is associated with higher SUV mean as established in this study. For any particular activity concentration, the differences in SUV mean among the different spherical sizes were relatively minimal. Activity concentrations of 10.6 kBq/mL, 21.2 kBq/mL, and 42.4 kBq/mL produced deviations of 19.4%, 13.4%, and 11.4%, respectively, between the highest and least recorded SUV mean . [Table 1] presents detailed SUV data for the study.
From [Figure 3], in the region around the central point in the hot spot, pixels have intensities of approximately 250 units, and background activity has pixel intensities of less than 100 units. Image pixel intensities have a linear relation with activity concentration; hence, the uneven nature at the peak of the curve implies imperfect uniformity of activity distribution in the sphere. Deviations of pixel values at the peak of the pixel plots for hot spots in the study were all within 10%, signifying a relatively uniform concentration.
Image contrast evaluation between hot or cold spots (lesions) and background radionuclide activity in acquired images reveal to some extent the level of image quality produced on PET-CT systems. [Figure 4] and [Figure 5] show the percentage contrast variabilities with the sphere's activity concentrations and sizes, respectively [Table 2]. Percentage contrast for the cold spots ranged from 85.2% to 92% for the different sized water-filled spheres, with mean contrast estimated to be 89.96 ± 2.76%. Average contrast for the spheres containing 10.6 kBq/mL, 21.2 kBq/mL, and 42.4 kBq/mL were found to be 110.92 ± 1.60%, 134.48 ± 2.15%, and 150.52 ± 1.58%, respectively, in reference to the background activity. From the smallest to the biggest sphere, percentage contrast fairly remained constant in the case of water and the three activity concentrations, implying that tumor size may not directly have a significant influence on image contrast at constant activity concentration. By doubling the concentration from 10.6 kBq/mL to 21.2 kBq/mL, the contrast increased by 21% while doubling from 21.4 kBq/mL to 42.4 kBq/mL resulted in 12% increase in contrast. The contrast curve in [Figure 4] is projected to assume a plateau shape beyond 42.4 kBq/mL where the radionuclide activity concentration ratio between sphere and background is 8:1.
For spheres of diameter 1.3 cm, 1.7 cm, 2.2 cm, 2.8 cm, and 3.7 cm, contrast increased by 79.7%, 65.8%, 64.3%, 63.9%, and 63.8% between a cold lesion (water) of no radionuclide activity and a hot lesion of 42.4 kBq/mL, as depicted in [Figure 5]. By increasing the activity concentration, bigger sized spheres recorded relatively less increase in contrast compared to smaller spheres. This observation could be a result of the count density being high for smaller volumes compared to larger volumes. At constant activity concentration, contrast remains relatively the same for hot spheres of different sizes, an indication that tumors of different sizes but containing similar activity concentrations may likely record similar contrast values.
Background contrast variability (N) estimation allows assessment of the accuracy of absolute quantification of radioactivity concentration in the uniform volume of interest inside the phantom. Contrast within the background activity distribution varied by approximately 3% as shown in [Figure 6]. Using ROIs of different sizes (1.3 cm, 1.7 cm, 2.2 cm, 2.8 cm, and 3.7 cm), the average background contrast variability was estimated to be 2.97 ± 0.1% (2.85-3.08%) at 95% confidence interval with P < 0.05 [Table 3]. The tolerance level of ±5% relative to baseline estimates for contrast and background variability recommended by the IAEA Human Health Series 1  could not be assessed due to unavailable baseline data.
| Conclusion|| |
The study has analyzed SUVs and contrast of PET-CT images with the use of NEMA image quality phantom. For same sized spheres, SUV mean increases with increase in activity concentration, affirming that radionuclide uptake values correspond proportionally to the concentration of activity in organs or tissues. Radionuclide activity concentration was also shown to have linear relation with image pixel intensities. Contrast between tumor sites (hot lesions) and background activity distribution increases with increasing activity concentration in the tumor but the contrast is likely to plateau beyond certain concentration ratios between the tumor and background activity. At constant activity concentration, contrast remains relatively the same for tumors (hot lesions) of different sizes. Background contrast variability has also been determined to be approximately 3%, indicating a very good uniformity within the background activity concentration.
This research serves as a part of the Doctor of Philosophy (Ph.D.) study of Francis Hasford. The author acknowledges with thanks the support of the International Atomic Energy Agency, Ghana Atomic Energy Commission, University of Ghana, and the Nuclear Medicine Department of CM Johannesburg Academic Hospital/University of Witwatersrand.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of intrest.
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[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
[Table 1], [Table 2], [Table 3]