Truncation Artifact on PET/CT: Impact on Measurements of Activity Concentration and Assessment of a Correction Algorithm
Abstract
OBJECTIVE. Discrepancy between fields of view (FOVs) in a PET/CT scanner causes a truncation artifact when imaging extends beyond the CT FOV. The purposes of this study were to evaluate the impact of this artifact on measurements of 18F-FDG activity concentrations and to assess a truncation correction algorithm.
MATERIALS AND METHODS. Two phantoms and five patients were used in this study. In the first phantom, three inserts (water, air, bone equivalent) were placed in a water-filled cylinder containing 18F-FDG. In the second phantom study, a chest phantom and a 2-L bottle fitted with a bone insert were used to simulate a patient's torso and arm. Both phantoms were imaged while positioned centrally (baseline) and at the edge of the CT FOV to induce truncation. PET images were reconstructed using attenuation maps from truncated and truncation-corrected CT images. Regions of interest (ROIs) drawn on the inserts, simulated arm, and background water of the baseline truncated and truncation-corrected PET images were compared. In addition, extremity malignancies of five patients truncated on CT images were reconstructed with and without correction and the maximum standard uptake values (SUVs) of the malignancies were compared.
RESULTS. Truncation artifact manifests as a rim of high activity concentration at the edge of the truncated CT image with an adjacent low-concentration region peripherally. The correction algorithm minimizes these effects. Phantom studies showed a maximum variation of -5.4% in the truncation-corrected background water image compared with the baseline image. Activity concentration in the water insert was 6.3% higher while that of air and bone inserts was similar to baseline. Extremity malignancies showed a consistent increase in the maximum SUV after truncation correction.
CONCLUSION. Truncation affects measurements of 18F-FDG activity concentrations in PET/CT. A truncation-correction algorithm corrects truncation artifacts with small residual error.
Introduction
PET is increasingly being used in oncology patients to stage the primary malignancy, assess therapeutic response and prognosis, and detect recurrence [1-7]. More recently, integrated PET/CT has been used to evaluate oncology patients [2, 8-10]. A major advantage of integrated PET/CT over dedicated PET is that it allows the use of CT for attenuation correction [11] and for anatomic localization [12]. Directly combining functional and morphologic information has been shown to improve the accuracy and efficiency of PET [13]. However, the use of CT for attenuation correction of PET images has introduced artifacts that can affect the interpretation of the PET scan. In this regard, a truncation artifact can occur when the acquisition field of view (FOV) of the CT data is smaller than the PET FOV.
Current commercially available PET/CT scanners have a CT FOV of 45-50 cm whereas that of PET scanners is 60-70 cm. When large patients undergo imaging, the small CT FOV causes some CT projection views to be truncated, and this manifests on the CT image as a rim of high-attenuation values combined with characteristic streaking (Fig. 1A). Furthermore, the discrepancy between the two FOVs causes some sections of the PET emission data not to have any corresponding attenuation-correction factors. The net result of this artifact is an overestimation of the activity concentration corresponding to the image rim and an underestimation corresponding to the region without attenuation-correction factors (Fig. 1B).
Several techniques have been proposed to correct for this truncation artifact [14-17]. One of the proposed techniques is that the missing data can be estimated by extrapolation of the missing detector data using the fact that the total attenuation of the slice should be the same in all parallel beam projections [14, 17]. In this article, we evaluate how truncation affects measurements of 18F-FDG activity concentrations in PET/CT and the impact of a new truncation-correction algorithm, as implemented on the Discovery ST PET/CT scanner (GE Healthcare), on the measurement of standard uptake values (SUVs) using two phantoms and five patient studies.
Materials and Methods
Integrated PET/CT Scanner
Data acquisition for this study was performed on a Discovery ST Integrated PET/CT scanner. The CT component of this scanner has a 50-cm transaxial FOV and can acquire 8 slices per X-ray tube rotation. The CT slice thickness can range from 1.25 to 10 mm. The X-ray tube current can be varied between 10 and 440 mA, and the peak tube voltage setting can be 80, 100, 120, or 140 kVp. The table feed rate of the CT scanner ranges from 1.25 to 30 mm per 360° rotation of the X-ray tube. The minimum and maximum scanning times per gantry rotation are 0.5 and 4 sec, respectively, with highest in-plane spatial resolution of 0.32 mm.
The PET component of the Discovery ST PET/CT scanner is composed of 24 rings of bismuth-germanate (BGO) detectors. The dimensions of each detector element are 6.3 × 6.3 × 30 mm in the tangential, axial, and radial directions, respectively. The scanner has a transaxial FOV of 70 cm and an axial FOV of 15.7 cm. The scanner is also capable of acquiring data in 2D and in 3D modes by retracting tungsten septa (54 mm long and 0.8 mm thick) from the FOV. The performance characterization of this scanner has been described elsewhere [18].
Phantom Studies
Two phantom studies were conducted. In the first study, a cylindric phantom (depth = 20 cm, length = 20 cm) fitted with three inserts (water, air, and bone equivalent) was filled with water having an activity concentration of 3.2 kBq/mL of 18F-FDG. The water and air inserts were 4.3 cm in diameter, and the bone equivalent insert was 2.5 cm in diameter. The water insert was filled with water at an 18F-FDG activity concentration of 7.8 kBq/mL giving an insert-to-background ratio of 2.4:1. The three inserts were positioned in the cylindric phantom around the circumference of a 12.5-cm-diameter circle. The phantom was then placed centrally in the FOV of the scanner and a CT scan (Fig. 2A), followed by a PET scan, was acquired. This acquisition was then repeated with the phantom placed at the edge of the CT FOV in such a way as to cause truncation along the center of the three inserts (Fig. 2B). The CT data of the second acquisition were then processed with and without the new truncation-correction algorithm. The two resulting CT image sets were then used to generate two attenuation maps to correct the corresponding PET emission data.
In the second study, a thorax phantom (Alderson, Radiology Support Devices) and a 2-L cylindric plastic bottle fitted with a bone insert were used to simulate a patient's torso and arm (Fig. 3A). The phantom and plastic bottle were filled with 18F-FDG and water having activity concentrations of 11.5 and 7.4 kBq/mL, respectively. The phantom was then placed centrally inside the FOV of the scanner, and a CT scan and then a PET scan were acquired. The phantom was then repositioned in a way to cause truncation in the simulated arm along the bone insert (Fig. 3B), and a second CT and PET acquisition was performed. The CT data of the second acquisition were processed in a similar manner to that in the first phantom study, thus generating two attenuation maps to correct the corresponding PET emission data.
The phantom designs that were used in both studies were selected to evaluate whether the algorithm can correct truncated tissues of different densities (phantom 1: air, water, bone) and geometries that mimic a real clinical setting (phantom 2: chest with simulated arm). In both phantom studies, the central positioning of the phantom in the FOV on the scanner will be referred to from here onward as the “baseline scan” because it represents the acquired data without truncation artifacts. The CT acquisition parameters of all phantom studies were as follows: 120 kVp, 180 mAs, helical mode, and a pitch of 1.35 with a detector configuration of 8 × 1.25 mm. Images were then reconstructed using a soft filter with a slice thickness of 3.75 mm. The PET emission data were acquired for 3 min in the 2D mode and were corrected for attenuation using the CT images. PET image reconstruction was performed using the weighted least-squares ordered subset expectation maximization (OSEM) iterative techniques [19] with two iterations and 30 subsets using a post filter and a loop filter of 6 and 5.47 mm, respectively.
To evaluate the impact of the truncation-correction algorithm on quantitative measurements, several regions of interest (ROIs) of 1.5 cm in diameter were drawn on the two different attenuation-corrected PET image sets of both phantom studies and their corresponding baseline scans. The ROIs were drawn in the three inserts and background water of the first phantom study and the background water and bone insert of the simulated arm in the second phantom study. The mean and SD of the activity concentration in all these ROI measurements were then recorded, and the percentage error between the baseline and truncation-corrected images was calculated.
Patient Studies
In addition to the phantom experiments, integrated PET/CT scans of five patients that exhibited a truncation artifact were also evaluated. Permission to perform this study was obtained through the institutional retrospective chart review process, according to the ethics requirement of our institution. Two of the patients had melanoma and lymphoma and, according to standard institutional protocol, were imaged with their arms adjacent to their bodies. Both of these patients had a forearm lesion that was truncated. The third patient had a mid thigh osteosarcoma. Because the patient could not straighten his leg, the tumor was truncated in the CT image. The remaining two patients were large and extended beyond the 50-cm CT FOV of the Discovery ST Integrated PET/CT scanner.
The CT scans of all five patients were processed with and without the truncation-correction algorithm, and the resulting CT attenuation maps were used to correct the emission PET data. ROIs were then drawn in the lesion or truncated area on the truncation-corrected and uncorrected PET attenuation-corrected images, and the maximum SUVs of the lesions were evaluated.
All patients had fasted for 4 hr before injection of approximately 555 MBq of 18F-FDG. Patients were scanned 75 ± 10 min (mean ± SD) after injection. All PET data were acquired in the 2D mode with 3 min for each bed position and were reconstructed using the same parameters as those used for the phantom studies.
Truncation-Correction Algorithm
The method for extending the CT reconstruction FOV has been described by Hsieh et al. [14]. Briefly, the method extends the truncated projections by relying on the fact that the total attenuation of each ideal projection remains constant over all views. By comparing the total measured attenuation in each view, the truncated projections can be identified and the amount of truncation can be quantified. The truncated projection can then be corrected by assuming that the missing attenuation is made of a partial cylindric water object that is fitted to match the slope and intercept of the measured attenuation values at the edge of the detector.
Consider a projection view p(i, k), where i is the distance from the isocenter and k is the projection angle. The projection sum function ξ(k) is then obtained byA projection is considered to be truncated if ξ(k) is less than a preset percentage of the maximum attenuation, ξm. The value of ξm is determined by averaging projections that do not exhibit truncation that are identified by determining if the boundary samples of these projections are constrained to a predetermined threshold (rather than zero to account for nonideal calibration). The missing attenuation is then equal to:λ(k) is then modeled as two partial cylindric water objects fitted to match the slope and intercept at both ends of the truncated projection ξ(k). The total area of the added cylinders for the k-th projection is given by η(k):where pl and pr are the magnitude of the left and right intercepts, respectively, and xl, Rl, xr, and Rr are the location and radius of the left and right fitted cylinders.
\[{\xi}(k)={{\sum}_{i=1}^{N}}p(i,k)\]
\[{\lambda}(k)={\xi}_{m}-{\xi}(k),\]
\[{\eta}(k)=\frac{{\pi}}{2}R_{1}^{2}(k)-\frac{x_{1}(k)p_{1}(k)}{2}-R_{1}^{2}(k)arcsin\left(\frac{x_{1}(k)}{R_{1}(k)}\right)+\frac{{\pi}}{2}R_{r}^{2}(k)-\frac{x_{r}(k)p_{r}(k)}{2}-R_{r}^{2}(k)arcsin\left(\frac{x_{r}(k)}{R_{r}(k)}\right)\]
Ideally the ratio ϵ(k) = η(k)μw / λ(k), where μw is the attenuation coefficient of water, should be equal to unity. If ϵ(k) ≠ 1, then additional adjustments to the estimated missing projections are performed [14].
Although the extended region of the projection does not contain any fine structure, this information is supplied by other views that pass through the region, and the reconstructed image can reveal anatomic detail in the extended FOV. These extended reconstructions are then used to create attenuation maps for correction of the PET emission activity.
Results
Truncation artifacts appear in PET images as a rim of high activity concentration due to the elevated CT pixel intensity at the edge of the truncated CT image, and an adjacent region of low activity concentration due to attenuation losses beyond the edge of the CT FOV. ROI measurements of 18F-FDG activity concentration on the truncated PET images confirmed visual assessment, showing increased activity concentration in the rim region and decreased activity concentration peripherally. The truncation-correction algorithm minimizes these effects and restores the shape of the imaged object. Both truncation-corrected phantom studies showed a maximum variation of 5.4% in the truncation-corrected background water when compared with baseline. Activity concentration in the water insert was higher by 6.3%, whereas that of the air and bone inserts was similar to baseline. The ROI measurements before and after correction are shown in Table 1. The percentage error between the corrected and the baseline measurements is also shown in Table 1.
| Mean (SD) ROI Values (Bq/mL) | ||||
|---|---|---|---|---|
| Insert | Baseline | Truncated | Truncation-Corrected | Error (%) |
| Phantom 1 | ||||
| Background water | 3,150 (302) | 486 (141) | 3,321 (316) | –5.4 |
| Air | 241 (27) | 1,162 (559) | 263 (35) | –9.1 |
| Bone | 537 (283) | 27 (61) | 550 (300) | –2.4 |
| Water | 7,634 (586) | 3,633 (1,784) | 7,155 (527) | 6.3 |
| Phantom 2 | ||||
| Background water | 5,825 (552) | 2,022 (1,323) | 5,927 (451) | –1.8 |
| Bone | 1,697 (381) | 646 (508) | 1,762 (376) | –3.8 |
Analysis of the patient data sets showed a consistent increase in maximum SUV after truncation correction for malignancies and normal tissue located in the truncated regions (Figs. 4A, 4B, 5A, 5B, 6A, 6B, 7A, and 7B and Table 2). In the three patients with peripherally located malignancies, six measurements of maximum SUVs after truncation correction showed an increase of 43-520% (average, 279%). In the two patients with truncation artifact involving the extremities and normal tissues in these regions, measurements of the maximum SUVs of the soft tissues after truncation correction showed an increase of 147% and 98%, respectively.
| SUVmax of Lesions | |||
|---|---|---|---|
| Location of Lesion | Truncated | Truncation-Corrected | % Difference |
| Patient 1 | |||
| Right extremity | 3.25 | 6.05 | 86 |
| Left extremity (1) | 2.51 | 3.59 | 43 |
| Left extremity (2) | 1.28 | 7.94 | 520 |
| Patient 2 | |||
| Left extremity (3) | 1.31 | 7.13 | 444 |
| Left extremity (4) | 2.74 | 11.12 | 306 |
| Patient 3 | |||
| Left thigh | 3.37 | 12.74 | 278 |
| Patient 4 | |||
| Left arm soft tissue | 0.32 | 0.79 | 147 |
| Patient 5 | |||
| Right arm soft tissue | 0.45 | 0.89 | 98 |
Note–SUVmax = maximum standard uptake value.
Discussion
Integrated PET/CT improves lesion localization and the accuracy of tumor staging when compared with PET and CT performed independently [8-10]. However, dual-technique PET/CT has also introduced artifacts that can affect the interpretation of the PET scan [12, 20-22]. These artifacts are mainly due to the use of CT rather than a transmission source for the attenuation correction of PET images. One of these artifacts is truncation; this artifact is seen more frequently in large patients or when patients are imaged with their arms at their sides and is due to the difference in the size of the data acquisition FOV of the CT and PET scanners.
Current commercially available integrated PET/CT scanners have a CT FOV of 45-50 cm, whereas that of PET is 60-70 cm. When imaging large patients, the small CT FOV causes some CT projection views to be truncated and this can manifest on the CT image as a rim of high attenuation values combined with characteristic streaking. Furthermore, the discrepancy between the two FOVs results in the absence of attenuation-correction factors in some sections of the PET emission data. The net result of this artifact is an overestimation of the activity concentration corresponding to the image rim and an underestimation corresponding to the region without attenuation-correction factors.
Several techniques have been proposed to correct for the truncation artifact [14-17]. In this study, we evaluated the CT truncation-correction algorithm that was developed and characterized by Hsieh et al. [14] and implemented by GE Healthcare on the Discovery ST Integrated PET/CT scanner to study its impact on SUV measurements using phantom and patient data. The correction technique extends the CT FOV based on information obtained from nontruncated projections of the object and the knowledge that the total attenuation of an object should be the same independent of the projection angle. It is also important to note that the correction algorithm is not dependent on the extent of truncation, as was shown by Hsieh et al. [14].
Both of our phantom studies showed that after correction the activity concentration in the water insert was 97% higher than those measurements without any correction. Furthermore, the patient data obtained using the correction algorithm showed that the SUV measurements corresponding to the truncated regions increased as would be expected. In some cases, this increase was as high as 278% and would significantly have affected interpretation regarding treatment response and could potentially have had a major impact on the patient's clinical management.
The effect of the truncation artifact on SUV measurements and the changes that occur when a correction algorithm is used can potentially have significant clinical ramifications. In this regard, besides being used for the diagnosis, staging, and restaging of a wide range of tumors, 18F-FDG PET is being increasingly used clinically to determine the response to therapy and to predict prognosis. This assessment requires an objective measurement of 18F-FDG uptake in the tumor, and SUV measurements are the most commonly used parameter to quantify this uptake. Because these measurements can have a major impact on the clinical management of oncology patients, their accuracy and reproducibility are important. However, in malignancies with a propensity to be located peripherally, such as soft-tissue sarcomas, melanomas, and osteosarcomas, detection of locoregional metastases and accurate determination of SUV measurements can be compromised by the presence of the truncation artifact associated with integrated PET/CT. Fortunately, correction of SUV measurements for tumors located in a truncated region improves the accuracy of these measurements. Consequently, knowledge and recognition of this artifact are important so that the correction algorithm can be applied to prevent misinterpretation and inappropriate assessment of tumor grade, staging, and response to therapy.
Although our results show an improvement in the semiquantitative SUV measurements in the truncated region, a close evaluation of the CT images shows that the shape of the truncated object is not fully recovered. This is mainly due to an error in the estimation of the boundary of the truncated projection. The correction algorithm estimates the missing attenuation in a projection based on the difference between the maximum attenuation and the projection under consideration. This difference is then modeled as a partial water cylinder with an area equivalent to the missing region. The only information available for the fitting process is the intercept and the slope at the truncated edge of the projection. No information about the natural boundary of the projection is available. Such information is important for more accurate fitting of the missing attenuation. An extension of the current truncation-correction technique, which is currently under investigation, is to provide the missing boundary information from the nonattenuated corrected PET data. It is well known that reconstruction of the emission PET data without attenuation correction results in an enhancement of the boundaries of the patient's body. This information could then be incorporated during the fitting process of the partial water cylinder to more accurately define the distal boundary of the missing attenuation in a truncated projection.
Other limitations of the algorithm that will cause the correction technique to fail occur whenever all projection views are truncated, such as in the case of a large patient who has been malpositioned in the FOV of the scanner. In this case, the algorithm cannot estimate the maximum attenuation of the object and hence fails to extend the truncated projection accurately. Another limitation occurs whenever the truncated portion of the object cannot be modeled as a smooth rolloff, which is a characteristic of a water phantom. This situation occurs when there is a discontinuity between the patient and the truncated object, such as scanning patients who do not put their arms close to their body. If the truncation occurs within the patient's body boundary, then the smooth water phantom cannot appropriately model the air gap between the patient and the arms. In this case, a modification of the reconstruction algorithm that is based on iterative reconstruction techniques combined with information about the shape of the truncated object obtained from the nonattenuated PET images would be of great interest to further improve the CT reconstruction
In conclusion, the discrepancy between PET and CT FOVs in an integrated PET/CT scanner when imaging extends beyond the CT FOV can cause a truncation artifact that affects SUV measurements. Because these measurements can have a major impact on the clinical management of oncology patients, recognition of this artifact is important so that the correction algorithm can be applied to prevent an inappropriate assessment of tumor grade, staging, and response to therapy. The new truncation-correction algorithm used in this study is capable of correcting PET/CT truncation artifacts in tissues with different densities and activity concentrations with small residual error.
Footnotes
Presented in part at the 2005 meeting of the American Roentgen Ray Society, New Orleans, LA.
Address correspondence to O. Mawlawi ([email protected]).
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Submitted: February 14, 2005
Accepted: April 6, 2005
First published: November 23, 2012
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