Ann Nucl Med DOI 10.1007/s12149-016-1144-1
ORIGINAL ARTICLE
Respiratory average CT for attenuation correction in myocardial perfusion SPECT/CT Duo Zhang1 • Bang-Hung Yang2,3 • Nien Yun Wu2,3 • Greta Seng Peng Mok1
Received: 27 September 2016 / Accepted: 29 November 2016 Ó The Japanese Society of Nuclear Medicine 2016
Abstract Objective Cine average CT (CACT) and interpolated average CT (IACT) have been proposed to improve attenuation correction (AC) for PET/CT in oncologic and cardiac studies. This study aims to evaluate their effectiveness on myocardial perfusion SPECT/CT using computer simulation and physical phantom experiments. Methods We first simulated normal male with 99mTc-sestamibi distribution using digital XCAT phantom with respiratory motion amplitudes of 2, 3, and 4 cm. Average activity and attenuation maps represented static SPECT and CACT, while the attenuation maps of end-inspiration and end-expiration represented two helical CTs (HCTs), respectively. Sixty noise-free and noisy projections were simulated over 180° using an analytical parallel-hole projector. We then filled 673 MBq 99mTc into an anthropomorphic torso phantom with normal heart or heart with a defect which placed on a programmable respiratory platform to model various respiratory amplitudes. Sixty projections were acquired over 180° using a clinical SPECT/ CT scanner. The CACT, standard HCT, and 2 HCTs at extreme phases were acquired. Interpolated CT phases were generated between them using affine plus b-spline
registration, and IACT was obtained by averaging the interpolated phases and the 2 original extreme phases for both simulation and phantom experiments. Projections were reconstructed with AC using CACT, IACT, and HCTs, respectively. Polar and 17-segment plots were analyzed by relative difference (RD) of the uptake. Two regions-of-interest (ROI) were drawn on the defect and background area to obtain the intensity ratio (IR). Results No substantial difference was observed on the polar plots generated from different AC methods, while the quantitative RD measurements showed that SPECTCACT were most similar to the original phantom, followed by SPECTIACT, with RDmax \8 and \10% in the simulation study. The RD of SPECTHCTs deviated from the original phantom and SPECTCACT in various segments, with RDmax of 19.76 and 16.68% in the simulation and phantom experiment, respectively. The IR of SPECTHCTs fluctuated more from the truth for higher motion amplitude. Conclusions Both CACT-AC and IACT-AC reduced respiratory artifacts and improved quantitation in myocardial perfusion SPECT as compared to HCT-AC. The use of IACT further reduced the radiation dose. Keywords SPECT/CT Myocardial perfusion Attenuation correction Respiratory artifacts
& Greta Seng Peng Mok
[email protected] 1
Biomedical Imaging Laboratory, Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Avenida da Universidade, Taipa, Macau SAR, China
2
Department of Biomedical Imaging and Radiological Sciences, National Yang Ming University, Taipei, Taiwan
3
Department of Nuclear Medicine, National PET/Cyclotron Center, Taipei Veterans General Hospital, Taipei, Taiwan
Introduction Currently, SPECT is still the primary imaging modality for myocardial perfusion imaging. Moreover, the combination of intrinsically registered SPECT and CT images in SPECT/CT scanners provides both functional and anatomical information in one single imaging session, which further enhances the diagnosis of substantial cardiac
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diseases [1], with calcium scoring feasible if diagnostic CT is used [2]. However, for the thorax region, the acquisition time of the conventional helical CT (HCT) is just a couple of seconds depending on the specifications of the CT and captures a specific respiratory phase, while free breathing SPECT takes a relatively long time (20–30 min). Thus, there are potential misalignments between HCT-based attenuation maps and SPECT data [3, 4]. For myocardial perfusion SPECT/CT, these misalignments can cause substantial artifacts in attenuation corrected SPECT images, and further affect the regional radiotracer distribution in the apex, anterior, and inferior wall of the heart [5]. Tonge et al. [6] found that a misregistration of only 1 pixel could create myocardial perfusion artifacts. Goetze et al. reported that 23 of 55 scans (42%) had moderate or severe misregistration between SPECT and CT [7], and the mean misregistration was 8.6 ± 3.8 mm in the heart [8]. Besides manual alignment and registration based on the outline of the heart as suggested by Goetze et al. [8], several methods have been investigated to reduce the misalignment and corresponding artifacts in SPECT/CT. Acquiring CT at an optimal phase during respiration, such as breathing-hold at normal expiration, can reduce the occurrence of respiration motion and better improve the registration between SPECT and CT images [2, 9, 10]. Fricke et al. proposed to estimate the shift between SPECT and CT images and then applied the shift to the CT maps to reduce the image misregistration [5]. Chan et al. used gating device to acquire SPECT images only at end-expiration phase to match with the end-expiration CT [11, 12]. Similar investigation was also proposed by Suga et al. for acquiring SPECT at end-inspiration phase [13]. Segars et al. introduced 4D respiratory gating SPECT with phasematched gated CT to improve attenuation correction (AC) in each phase in a simulation study [14]. However, 4D CT scanning also suggests higher complexity of implementation and higher radiation dose. Thus, it is still not a common clinical protocol for SPECT/CT. In PET/CT, cine average CT (CACT) from a 4D CT acquisition has been demonstrated to remove misalignments artifacts and further improve the quantification results [15–19]. Its main concern is the increased radiation dose. Previously, we developed an interpolated average CT (IACT) method as a low dose alternate of CACT for AC to reduce misalignment in PET/CT [20], and demonstrated its effectiveness for artifacts reduction and improved quantitation in cardiac [21] and oncologic [22, 23] PET/CT studies. To the best of our knowledge, this is the first paper to investigate CACT and IACT on SPECT/CT. In this study, we aim to evaluate the effectiveness of CACT- and IACT- AC in reducing misalignment artifacts and improving quantitation in myocardial perfusion SPECT/ CT, using both simulation and physical phantom data.
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Materials and methods Simulation study We used the digital 4D Extended Cardiac Torso phantom (XCAT) [24] to simulate a male patient with 99mTc-sestamibi activity distribution. We modeled the normal cardiac motion and respiratory motion amplitudes of 2, 3, and 4 cm with a period of 5.9 s, where 2 cm was used to simulate the normal patient with shallow respiration, while 3 and 4 cm were used to simulate deep respiration [25]. The respiratory cycle was divided into 12 phases starting from the end-inspiration phase. The average activity and attenuation maps of the 12 phases were used to represent static SPECT with no respiratory gating and CACT, respectively (Fig. 1a, d). The attenuation maps of end-inspiration and end-expiration phases represented two different HCTs, i.e., HCT captured at end-expiration (HCTEX) and HCT captured at end-inspiration (HCT-IN), respectively (Fig. 1b, c). Other HCTs acquired at different respiratory phases were also modeled using attenuation maps of 6 respiratory phases placed with equal time interval between HCT-EX and HCT-IN. To generate IACT, an affine plus b-spline registration method based on the Insight Segmentation and Registration Toolkit [26] was used. The affine method was applied to first roughly align the 2 images to correct for the whole body movement, and the b-spline method was then used to calculate the non-rigid deformation vectors which include lateral, anterior–posterior, and inferior–superior displacement for each voxel between the two extreme HCTs, i.e., HCT-IN and HCT-EX. The forward deformation vector Vie was calculated from HCT-INto HCT-EX, whereas the backward deformation vector Vei was calculated from HCT-EX to HCT-IN. To acquire the interpolated phases, an empirical diaphragmatic movement function [27] was introduced: zðtÞ ¼ z0 b cos 2n ðpt=sÞ where z(t) is the position of diaphragm at time t, z0 is the diaphragm position at end-expiration, b is the amplitude of respiratory motion, s is the period of motion, and n means the degree of asymmetry which depends on the patient-specific respiratory signals, where 2n will lead to more phases near the end-expiration than the end-inspiration. Here, we used n = 2 in the simulation study and n = 3 in the physical phantom study to best fit the respiratory motion curves used in XCAT simulation and the physical phantom study. We used the deformation vectors combined with this empirical function to generate the interpolated phases between HCT-IN and HCT-EX. Finally, IACT can be acquired by averaging the ten interpolated phases plus the original two extreme phases (Fig. 1e).
Ann Nucl Med
Fig. 1 a Average 99mTc-sestamibi activity map with cardiac motion and respiratory motion of 2 cm; b attenuation map of respiratory phase #1 to represent HCT-IN; c attenuation map of respiratory phase
To simulate realistic noisy CT data, Gaussian noise with the standard deviation r = 0.0002 was added on different CT projections which were then reconstructed to represent realistic noisy CT images. The noise measurement was based on the standard deviation of an ROI drawn on the uniform liver region in different clinical CT data, i.e., CACT, HCT, and IACT. We used a homemade analytical projector to model a lowenergy high-resolution parallel-hole collimator. Sixty noisefree and realistic noisy projections were generated with attenuation modeling from right anterior oblique position (RAO) to left posterior oblique position (LPO) positions. The radius-of-rotation was kept to 24 cm. Poisson noise was generated on the projections based on the realistic clinical count level, i.e., *34 M counts for acquisition time of 28 min and *987 MBq 99mTc-sestamibi injection. The noise-free and noisy projections were reconstructed with different AC maps, i.e., CACT, IACT, and HCTs using OSEM algorithm for 200 (20 iterations 9 10 subsets) and 30 (5 iterations 9 6 subsets) updates, respectively. Physical phantom study We placed the anthropomorphic torso phantom (Data Spectrum Corporation, Durham, NC, USA) with cardiac insert on a QUASAR programmable respiratory motion platform (Modus Medical Devices Inc., London, Ontario, Canada) (Fig. 2), to simulate a patient with a realistic normal respiratory trace and maximum respiratory motion amplitude of 2 and 3 cm, respectively. Normal heart without defects and abnormal heart with a myocardial defect were modeled, respectively, leading to a total of four sets of experiment. The solid defect was located at mid-lateral region with thickness of 1 cm. A total activity of *673 MBq 99mTc-pertechnetate was injected into the phantom, with activity concentration ratios of 4:3:1:1:0:0 for myocardium:liver:cardiac chamber:background:lungs:defect. The lungs were filled with Styrofoam beads with no activity uptake. For each set of experiment, four imaging sessions were acquired: 1.
SPECT: 60 projections of 25 s/projection from RAO to LPO, with automatic body contouring, primary energy
#8 to represent HCT-EX; d average of the attenuation maps to represent CACT; e IACT
Fig. 2 Data Spectrum anthropomorphic torso phantom with cardiac insert placed on top of the QUASAR programmable respiratory motion platform
2. 3. 4.
window of 126.45–154.55 keV, and scatter window of 114–126 keV, with free platform moving; CACT: 120 kV, 10 mA, 5.9 s duration with free platform moving; Standard HCT: 120 kV, smart mA (15–120 mA), 1.375:1 pitch, with free platform moving; Two low dose HCTs: 120 kV, 10 mA, 1.375:1 pitch, acquired when phantom stopped at ±9.5 mm for maximum motion amplitude of 2 cm and ±13.5 mm for maximum motion amplitude of 3 cm, to represent patients breath-holding at end-inspiration and endexpiration phases.
All scans were acquired on a clinical SPECT/CT scanner (Discovery NM/CT 670, GE Medical Systems, Milwaukee, WI). The IACT was generated using the same procedure as mentioned in the simulation study with the 2 HCTs acquired at extreme phases. Projection data were reconstructed on the scanner workstation using
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Fig. 3 Polar plots generated from the noise-free SPECT short-axis reconstructed images for a normal heart simulation with respiratory motion amplitude of a 2 cm, b 3 cm, and c 4 cm
Fig. 4 Polar plots generated from the noisy SPECT short-axis reconstructed images for a normal heart simulation with respiratory motion amplitude of a 2 cm, b 3 cm, and c 4 cm
the 3D OS-EM method with dual-energy-window scatter correction and AC using different AC maps, i.e., CACT, IACT, and HCTs. No post filtering was applied on the reconstructed images.
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Data analysis For both simulation and phantom studies, reconstructed images were re-oriented to short-axis images which were
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Fig. 5 Seventeen-segment analysis based on the noise-free polar plots for a normal heart simulation using original phantom as the reference with motion amplitude of a 2 cm, b 3 cm, and c 4 cm. Dark red indicates RD value of 20% and light yellow indicates 0%
Fig. 6 Seventeen-segment analysis based on the noisy polar plots for a normal heart simulation using original phantom as the reference with motion amplitude of a 2 cm, b 3 cm, and c 4 cm. Dark red indicates RD value of 20% and light yellow indicates 0%
perpendicular to the long axis of the left ventricle. Polar plots were generated from the short-axis images and 17 segments were drawn on the plots based on the American Heart Association guidelines [28]. Average intensity values were
calculated for each segment and their relative differences (RD) as compared to the references, i.e., original phantom in simulation or SPECTCACT data in phantom study, to quantify the recovery of the activity concentration:
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Ann Nucl Med Table 1 Maximum RD values for the 17-segment analysis of the simulation study SPECTCACT (%)
SPECTIACT (%)
Noise-free heart with 2 cm motion
1.41
2.96
5.89
7.44
Noise-free heart with 3 cm motion
1.14
2.65
8.44
12.42
9.07
Noise-free heart with 4 cm motion
1.32
5.37
11.32
17.44
11.85
Noisy heart with 2 cm motion
6.17
5.30
8.13
7.97
6.93
Noisy heart with 3 cm motion
7.63
9.95
12.12
17.27
9.95
Noisy heart with 4 cm motion
6.22
8.02
14.25
19.76
13.75
Fig. 7 Polar plots generated from the noisy short-axis reconstructed images of the physical phantom study for a normal heart phantom with respiratory motion amplitude of 2 cm; b heart phantom with
RD ¼
Intensityrecon Intensityreference : Intensityreference
The mean of the RD values in each segment for the 8 different HCTs was also calculated in the simulation study. For the phantom with defect, two regions-of-interest (ROIs) were drawn on the polar plots to cover the defect and normal background region. Average intensity in each ROI was measured and the corresponding intensity ratio (IR) was calculated:
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SPECTHCT-IN (%)
SPECTHCT-EX (%)
SPECTHCT-mean (%) 6.65
defect and respiratory motion amplitude of 2 cm; c normal heart phantom with respiratory motion amplitude of 3 cm; and d heart phantom with defect and respiratory motion amplitude of 3 cm
IR ¼
Meandefect : Meanbackground
Results In the simulation study, there is no substantial difference among the polar plots using different AC maps from visual assessment (Figs. 3, 4). From the RD analysis on the
Ann Nucl Med
Fig. 8 Seventeen-segment analysis based on the noisy polar plots of physical phantom study using SPECTCACT as the reference for a normal heart phantom with respiratory motion amplitude of 2 cm; b heart phantom with defect and respiratory motion amplitude of
2 cm; c normal heart phantom with respiratory motion amplitude of 3 cm; and d heart phantom with defect and respiratory motion amplitude of 3 cm. Dark red indicates RD value of 20% and light yellow indicates 0%
Table 2 Maximum RD values for the 17-segment analysis of the physical phantom study SPECTIACT (%)
SPECTHCT (%)
SPECTHCT-IN (%)
Normal heart with 2 cm motion
3.27
1.67
7.03
Heart with defect and 2 cm motion
1.94
6.95
3.12
3.58
Normal heart with 3 cm motion
7.80
4.29
5.95
16.68
Heart with defect and 3 cm motion
2.67
9.56
2.68
5.70
17-segment plots (Figs. 5, 6), SPECTCACT was most similar to the original phantom, followed by SPECTIACT and SPECTHCTs. The RD of the SPECTHCTs notably deviated from the phantom in the basal inferolateral and anterolateral regions, especially for higher motion amplitudes. The deviation was more significant for SPECTHCT-EX, with the RDmax value of 7.44, 12.42, and 17.44% for noise-free images with 2, 3, and 4 motions and 7.97, 17.27, and 19.76% for noisy images, respectively (Table 1).
SPECTHCT-EX (%) 3.77
Similarly, polar plots from the physical phantom study did not show obvious difference among different AC maps (Fig. 7). The 17-segment result showed that SPECTIACT is more close to SPECTCACT as compared to SPECTHCTs (Fig. 8). The RDmax values of SPECTIACT, SPECTHCT, SPECTHCT-IN, and SPECTHCT-EX as compared to SPECTCACT are shown in Table 2. The IR values for the defect and the background using different CT AC maps are shown in Fig. 9, indicating the IRs for
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Fig. 9 Intensity ratios between the defect and the background for the heart phantom with respiratory motion of a 2 cm and b 3 cm
HCT-AC deviated more from the truth for higher motion amplitude.
Discussion There is generally no significant difference for visual assessment among different polar plots generated from different AC methods in both simulations and physical phantom studies. However, for further quantitative analysis in simulations (Figs. 5, 6; Table 1), SPECTCACT demonstrated the best performance, followed by SPECTIACT and SPECTHCTs, similar to our previous PET/CT study [21]. In the physical phantom study, SPECTHCT occasionally showed good results (Fig. 8; Table 2). This might be due to the fact that the HCT of free breathing motion could coincidently be acquired at a position that matched with the emission data. Our simulation result showed that HCT acquired at mid-respiration demonstrated better quantitation result as compared to other phases and inferior results for those acquired close to the extreme phases (data not shown). This indicated that mid-respiratory HCT could be a good alternate of CACT with lower radiation dose. However, it is difficult for patients to breath-hold at this phase unless an active breathing controller is used [22]. Notably, the general performance of HCT as indicated by the mean RD of HCTs acquired at various phases is still inferior to CACT and IACT (Figs. 5, 6; Table 1). The IR values also indicated similar results, while their variations among different AC maps are larger for higher motion amplitude (Fig. 9). Another observation is that the IRs deviated more from the truth, i.e., showing higher values, for 3 cm as compared to 2 cm motion, probably due to the more severe ‘‘spill in’’ effects for increased motion blur. There were slight differences in the RD values in some segments for with and without defects in the physical phantom study. It was possibly caused by the different parameters used to reorient the
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heart to short-axis images for generating the polar plots. The reorientation parameters were the same in the same row for different AC methods, thus the results in the same row were comparable. The simulation and physical phantom results are generally accordant. In our previous PET/CT study, the visual and RD value differences among polar plots generated with different CT maps were more prominent than those shown in this study. The higher resolution and higher contrast of PET could be one justification for this observation. Fricke et al. also mentioned that the lower resolution of SPECT system can lead to inferior result when using CT for AC [29], concealing the potential mismatch problem. Our results indicate that if no quantitation is needed, using standard HCT could be sufficient for common defect detection. However, CACT and IACT are preferred for more stable performance and accurate quantitation, especially for larger respiratory motion, with the cost of higher radiation dose from CACT or additional experimental setup and data processing time from IACT. We used one respiratory trace in simulation study and another trace from a real patient data was used in the physical phantom study. Their results are consistent. Evaluations with a population of phantoms with various normal and abnormal traces, and clinical study with various patients are warranted to demonstrate the full feasibility of IACT and CACT. Besides, respiratory gated SPECT can be used to further improve the image quality with motion blurring reduction [14, 30], and its appropriate choice of AC map is also critical for improved quantitation, which is also under investigation in our laboratory. In conclusion, our study showed that both CACT and IACT have the potential to reduce respiratory artifacts and to improve quantitation in myocardial perfusion SPECT/CT. The performance of IACT was comparable to CACT with reduced radiation dose. However, the improvement of image quality and quantitation using CACT and IACT is less obvious in SPECT/CT as compared to our previous PET/CT studies.
Ann Nucl Med Acknowledgements This work was supported by research grants from University of Macau (MYRG2016-00091-FST), Science and Technology Development Fund (FDCT) (079/2011/A3), Macau, and Natural Science Foundation of China (81601525).
14.
Compliance with ethical standards
15.
Conflict of interest The authors declare that they have no conflict of interest.
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