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DOI: 10.1148/radiol.2372041719
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(Radiology 2005;237:635-639.)
© RSNA, 2005

Nuclear Medicine

Comparison of Alignment of Computer-registered Data Sets: Combined PET/CT versus Independent PET and CT of the Thorax1

Vikram Krishnasetty, MD, Alan J. Fischman, MD, Elkan L. Halpern, PhD and Suzanne L. Aquino, MD

1 From the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, FND 202, Boston, MA 02114. From the 2004 RSNA Annual Meeting. Received October 5, 2004; revision requested December 13; revision received January 11, 2005; accepted February 16. Address correspondence to S.L.A. (e-mail: saquino{at}partners.org).


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
PURPOSE: To retrospectively determine whether alignment of registered positron emission tomographic (PET) and computed tomographic (CT) data sets obtained independently varies significantly from alignment of data sets acquired from a combined PET/CT scanner.

MATERIALS AND METHODS: The study was approved by the institution's Human Research Committee with a waiver of informed consent and complied with HIPAA. Whole-body combined PET/CT data sets and separate routinely positioned thoracic CT data sets were obtained from 12 patients (six men, six women; mean age, 48.6 years; range, 24–62 years). Separate PET and thoracic CT data sets matched for patient positioning and respiration were acquired on the same day for nine patients (four men, five women; mean age, 71 years; range, 51–90 years). Computer nonlinear registration was performed on PET and CT data sets from combined PET/CT (fusion group 1), PET data sets from combined PET/CT with unmatched thoracic CT (fusion group 2), and data sets from separate PET and CT matched for patient positioning and respiration (fusion group 3). Quality of alignment was assessed by two radiologists in consensus blinded to the source of registered data in each fusion group at the following anatomic locations: diaphragm, aortic arch, heart, thoracic spine, and lung apices. Results were compared by using the Wilcoxon paired signed rank and unpaired rank sum tests.

RESULTS: Quality of alignment did not significantly differ between fusion group 1 and fusion group 3. Fusion group 1 provided significantly better alignment in two of five anatomic locations (P = .008 for diaphragm and P = .031 for heart) than fusion group 2. Fusion group 3 provided significantly better alignment in two of five anatomic locations (P = .037 for diaphragm and P = .009 for heart) than fusion group 2.

CONCLUSION: Thoracic anatomic alignment does not significantly differ between registered PET and CT data sets acquired on a combined PET/CT scanner or from separate PET and CT scanners obtained on the same day when carefully matched for anatomic positioning and respiration.

© RSNA, 2005


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
In recent years, fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) has become an important diagnostic tool in oncologic imaging (1). The ability of PET imaging with FDG to depict increased metabolism in malignancies has greatly improved the accuracy in detecting and staging neoplasms (2). However, because of the lack of high-resolution anatomic detail, localization of abnormalities has been a challenge. With FDG PET, some anatomic detail is available from FDG uptake in muscles, soft tissue, and solid organs to aid in anatomic orientation. However, compared with other diagnostic imaging studies, such as computed tomography (CT) or magnetic resonance imaging, use of PET alone results in a lack of substantial detail (3,4). Thus, the combination of anatomic and functional imaging is clinically useful (5,6).

Until recently, CT and PET data sets were interpreted side by side for the diagnosis and follow-up of malignancy. Radiologists were required to "visually fuse" the images to combine the functional data of PET with the anatomic data of CT (7).

To help the interpreting physician more accurately localize abnormalities, many methods of software fusion that use sophisticated mathematical algorithms have been developed (8). Fusion software registers PET images to those of CT by transforming one data set to conform to the other. The major obstacles to software fusion, however, are the degree and the multiple directions of movement. One data set (eg, PET) may be substantially transformed to register with the other data set (eg, CT). This is particularly true with nonlinear software. There is the potential for distortion of the size of FDG uptake originally detected in a lesion. In this regard, registration could adversely affect patient care—for instance, by falsely increasing the size of a tumor.

Combined PET/CT devices offer a hardware solution to this problem. These instruments permit sequential acquisition of anatomic CT and functional PET images in a single scanning session. Since the patient is not moved from the bed between examinations, spatial and temporal differences between the two studies are minimized. Theoretically this would provide easier fusion of the PET and CT data sets. Currently, however, the availability and cost of the actual imaging hardware are major obstacles.

The combination of anatomic and functional imaging has become a useful tool in oncologic imaging (9,10). Because of this, it is necessary to compare the two leading approaches of CT and PET image fusion. Both software and hardware fusion have obstacles and advantages; however, the most important point of comparison between the two methods of image fusion is the quality of the result. Since a large portion of oncologic imaging is the diagnosis and follow-up of chest malignancies, it is important to compare methods of image registration and fusion by using PET and CT data sets of the thorax. The purpose of our study, therefore, was to retrospectively determine whether alignment of registered PET and CT data sets obtained independently varies significantly from alignment of data sets acquired with a combined PET/CT scanner.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 References
 
Patient Population
This study was approved by the institution's Human Research Committee and complied with the Health Insurance Portability and Accountability Act. Waiver of informed consent was granted. Our study population consisted of two groups. The first group comprised 12 sequentially selected patients (six men and six women; mean age, 48.6 years; range, 24–62 years) who underwent combined PET/CT and a thoracic CT performed with a separate scanner. Indications for PET/CT were lymphoma staging (six patients), gastrointestinal cancer staging (three patients), non–small cell lung cancer staging (two patients), and pancreatic cancer restaging (one patient). In the month before their FDG PET study, these patients had undergone a diagnostic thoracic CT at our institution by using a newly installed combined PET/CT scanner. In these situations, the referring physicians deemed that both studies were clinically indicated. The second group comprised nine sequentially selected patients (four men and five women; mean age, 71 years; range, 51–90 years) who underwent CT and PET separately on the same day. Indication for PET was staging of lung carcinoma for all patients.

Image Acquisition
Combined FDG PET/CT studies were performed in patient group 1 with a Biograph Sensation 16 (Siemens Molecular Imaging, Knoxville, Tenn) scanner. The PET image spatial resolution was 5.0 mm full width at half maximum, with a section thickness of 3.5 mm. The patients fasted for at least 6 hours before scanning, and blood glucose levels were measured just before injection of FDG. Fifteen to 20 mCi (740 MBq) of FDG was administered intravenously as a bolus, and static emission images were obtained 60 minutes later. Patients were imaged in an average of six bed positions with arms up in midrespiration. Images were reconstructed with Fourier rebinning and attenuation-weighted ordered-subsets expectation maximization. Subsequent diagnostic CT scans were obtained during the same scanning session (without moving the patient) with 100 mL of intravenous contrast material (Isovue 300; Bracco Diagnostics, Princeton, NJ) at an injection rate of 2 mL/sec and 5-mm sections. CT examinations were performed during suspended expiration.

Separate thoracic CT scans were obtained in this same patient group with a LightSpeed scanner (GE Medical Systems, Milwaukee, Wis) within 11 days (mean, 4.4 days) before combined PET/CT was performed. Scans were obtained at 5-mm section thickness during full inspiration with arms positioned overhead. All CT scans were obtained with intravenous contrast material at an injection rate of 2 mL/sec.

The FDG PET scans were obtained in patient group 2 with an ECAT ACCEL scanner (CTI Molecular Imaging, Knoxville, Tenn). Image spatial resolution was 5.0 mm full width at half maximum, with a section thickness of 2.5 mm. The patients fasted for at least 6 hours before scanning, and blood glucose levels were measured just before injection of FDG. Fifteen to 20 mCi (740 MBq) of FDG was administered intravenously as a bolus, and static emission images were obtained 60 minutes later. Patients were imaged in an average of six bed positions with arms up in midrespiration. Transmission images were obtained by using rotating germanium 68 rod sources. Images were reconstructed with ordered-subset expectation maximization algorithms.

Separate thoracic CT scans were obtained in the same patient group with a GE LightSpeed scanner (GE Medical Systems) on the same day. Scans were obtained at 5-mm section thickness and without intravenous or oral contrast material. Since the studies for patient group 2 were performed before the availability of a combined PET/CT scanner, these studies were performed on the same day with patients matched for positioning and respiration in anticipation of image fusion for clinical practice. The clinical protocols in place during that time were not changed for the purposes of this study. The patients were matched for positioning with regard to PET scanning in the supine position with arms up. Special care was taken to minimize any differences in rotation or flexion of the patient on the gantry table, although no specialized alignment equipment was used. The CT images were acquired at expiration to optimize matching to PET scans. Before CT image acquisition, patients practiced the breathing method after careful instruction by the technologist.

Image Registration
Registration and fusion were performed on the following three pairs of fusion data sets: (a) PET and CT data sets from combined PET/CT with intravenous contrast material (fusion group 1), (b) PET data sets from the combined PET/CT and unmatched separately acquired thoracic CT (fusion group 2), and (a) data sets from separate PET and CT matched for patient positioning and respiration (fusion group 3).

Image registration was performed in the following manner for all three fusion groups: Computer linear registration and fusion on PET and CT data sets were performed with the REVEAL-MVS (Mirada Solutions, Oxford, UK) workstation for each patient. By using the workstation, CT data were loaded as source data and PET data were loaded as target data. Automatic rigid linear registration and transformation were performed by using these two data sets to grossly align images. Subsequently, automatic deformable nonlinear registration and transformation were performed on the same data sets. The resulting fusion data were displayed on the workstation as overlays.

Fusion Analysis
Registered and fused data sets for each patient from each fusion group were analyzed for quality of alignment at five key anatomic locations: (a) diaphragm, (b) aortic arch, (c) heart, (d) thoracic spine, and (e) lung apices. The quality of alignment at each of these anatomic locations was rated on a scale of 1–5 as follows: score of 5, exact alignment; score of 4, alignment differs by less than 5 mm; score of 3, alignment differs by more than 5 mm but less than 25 mm; score of 2, alignment differs by more than 25 mm; and score of 1, anatomic alignment completely lacking. Within each region, the greatest measure of discrepancy was used for rating the quality of alignment for that region. Analysis was performed by two radiologists (S.L.A. and A.J.F.), and a score was obtained by consensus. Evaluators were blinded to the source of the fused image data. Both radiologists had more than 6 years of experience analyzing PET and CT images.

Statistical Analysis
A Wilcoxon paired signed rank test was used to compare the quality of registration between fusion groups 1 and 2 and between fusion groups 1 and 3. The quality of registration between fusion groups 2 and 3 was compared by using a Wilcoxon unpaired rank sum test. P < .05 was considered to indicate a significant difference.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 References
 
For fusion group 1, the quality of alignment in all five anatomic locations scored an average of 4.97 (range, 4–5) on the 1-to-5 scoring system (Fig 1). The average scores were as follows: for the diaphragm, 4.92; for the aortic arch, 5; for the heart, 4.92; for the spine, 5; and for the lung apices, 5 (Table 1).



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  		Figure 1. Transverse (left), coronal (middle), and sagittal (right) views from fusion of PET and CT data sets from combined PET/CT. The quality of fusion for both the heart and diaphragm was rated as 5. Arrow = exact alignment of the heart, arrowhead = exact alignment of the diaphragm.

 

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  		TABLE 1. Average Quality Scores for Each PET/CT Fusion Group by Anatomic Location

 
For fusion group 2, the quality of alignment in all five anatomic locations scored an average of 4.37 (range, 4–5) (Fig 2). The average scores were as follows: for the diaphragm, 4.08; for the aortic arch, 4.58; for the heart, 3.5; for the spine, 4.75; and for the lung apices, 4.92 (Table 1).



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  		Figure 2. Transverse (left), coronal (middle), and sagittal (right) views from fusion of PET data sets from combined PET/CT and unmatched, separately acquired thoracic CT. The quality of alignment for both the diaphragm and heart was rated as 3 since alignment differed by more than 5 but less than 25 mm. Arrow = poor alignment of the heart, arrowhead = poor alignment of the diaphragm.

 
For fusion group 3, the quality of alignment in all five anatomic locations scored an average of 4.96 (range, 4–5) (Fig 3). The average scores were as follows: for the diaphragm, 5; for the aortic arch, 4.78; for the heart, 5; for the spine, 5; and for the lung apices, 5 (Table 1).



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  		Figure 3. Transverse (left), coronal (middle), and sagittal (right) views from fusion of separate PET and CT data sets matched for patient positioning and breath hold. The quality of fusion for both the heart and diaphragm was rated as 5. Arrow = exact alignment of the heart, arrowhead = exact alignment of the diaphragm.

 
The quality of alignment of the diaphragm and the heart was significantly better in fusion group 1 than in fusion group 2 (P = .008 and .031, respectively) (Table 2) and in fusion group 3 than in fusion group 2 (P = .037 and .009, respectively). Alignment quality in any anatomic location did not significantly differ between fusion group 1 and fusion group 3.


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  		TABLE 2. Comparison of Quality of Alignment between Combined PET/CT and Independently Registered PET and CT Data Sets

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
References
 
Image registration is the process of finding a geometric transformation between two image-coordinate sets to map a specific patient-based location in one image-coordinate set (eg, PET) to the same patient-based location in the second image-coordinate set (eg, CT) (8). The application of geometric transformation and registration of such data sets has been termed translation and fusion. Several approaches have been used to register radiologic and nuclear medicine image data sets to provide combined anatomic and functional information. On the basis of the type of computer algorithm used, these approaches can be classified as linear and nonlinear (11). Linear methods of image registration are limited to scaling, translation, and rotation. Nonlinear algorithms involve more complex geometric transformations that include image deformation or warping. Linear algorithms can be manual or automatic, while nonlinear algorithms tend to be automatic. Manual registration relies on the viewer's identification of equivalent patient-based anatomic locations, whereas automatic algorithms can be independent of user input. Automatic nonlinear registration algorithms use complex image interpolation programs to account for patient breathing, body positioning, or movement of internal organs (9,12).

Image registration to fuse functional and anatomic data has long been used in neurologic imaging (13,14). Moreover, the combination of functional and anatomic data has also proved to be useful in thoracic imaging. Study findings have shown that the combination of CT and PET imaging has improved the diagnosis and staging of lung cancers (9,10,15,16). Specifically, PET and CT image registration improved sensitivity and specificity for detecting metastatic nodal disease when compared with either PET or CT scans interpreted alone or side by side (16). The improved detection of nodal disease over PET was mainly due to the lack of fine anatomic detail in PET imaging alone. At CT alone, small lymph nodes may be wrongly interpreted as benign and enlarged lymph nodes may be erroneously interpreted as malignant; this has been shown to be less likely with combined PET/CT data sets (16). In addition, anatomic correlation with increased radionuclide uptake at PET leads to more precise localization of the primary tumor and detection of any chest wall or mediastinal invasion (15). Unlike neurologic images, however, the registration of thoracic images is more susceptible to error because of voluntary patient motion, as well as cardiac and respiratory motion (17,18).

To overcome problems associated with software image registration in areas of the body susceptible to large degrees of motion, combined PET/CT hardware systems have been developed (3). Although still susceptible to artifacts from voluntary and respiratory motion, the combined PET/CT hardware solution minimizes misregistration by reducing spatial and temporal differences between scan acquisitions. In addition, the CT data set is used to correct attenuation of the PET images, obviating germanium 68–based attenuation correction, which is more time consuming (15). Acquisition of this transmission CT data set during expiration rather than inspiration (as is performed at conventional CT imaging) optimizes the alignment of the diaphragm and lung bases for improved attenuation correction and anatomic fusion (19).

Cost is an important limitation of combined PET/CT imaging. The initial capital cost of owning and operating a PET/CT machine is much greater than that of owning a software image registration system. Therefore, some practices use software registration programs rather than dual scanning. As of yet, no standard of practice has been established for the acquisition of data sets from separate scanners that will optimize computer-based registration. In addition, to our knowledge, no previous studies have compared combined PET/CT hardware fusion with software image fusion to determine whether any method is superior. Our study was designed to address these issues.

In our study, the spine and lung apices registered well in all groups despite variations in patient positioning or respiration. Conversely, misregistration of data occurred most commonly at the diaphragm and along the heart border. Combined PET/CT had the overall best registration at these locations, although the difference in quality of alignment on matched PET and CT (fusion group 3) for these same areas was not significant. These anatomic areas are also the locations where the unmatched PET and CT images misregistered most frequently. The quality of registration in these areas is essential not only for better detection of the lung bases, pleural, and chest wall disease but also for better detection and localization of upper abdominal abnormalities.

One limitation of this study was the relatively small number of patients. The number of patients in group 2 was limited to nine. This group was unusual because the patients underwent a separate diagnostic thoracic CT during a transition when our department installed a new combined PET/CT scanner. They subsequently underwent FDG PET by using the new PET/CT scanner. Because of the radiation risks, acquiring a separate thoracic CT scan apart from a combined PET/CT scan in more patients for the sole purpose of research would not have been warranted. Although our study demonstrated significant differences in the quality of alignment in two key anatomic locations (heart and diaphragm), a larger study may have been able to reveal smaller differences in the other anatomic locations. It should be noted that fusion of abdominal studies was not evaluated, although this is not truly a limitation of the study. Although the study focuses on thoracic imaging, it is still relevant to clinical practice since the leading indication for combined PET/CT imaging is the staging of lung carcinoma.

Our results demonstrate that the quality of computer-based fusion of data sets acquired on a combined PET/CT is superior to the quality of fusion of data sets acquired on separate PET and separate CT hardware when the scans are not matched for patient positioning and respiration. More important, these results show that if separate PET and CT scans are matched for patient positioning and respiration, these scans can yield anatomic fusion results that are equal to those from scans acquired with a combined PET/CT scanner. Our results indicate that by acquiring CT and PET images with careful patient positioning in each scanner, performing CT during expiration, and minimizing the interval between scans, software registration can be optimized to approximate the quality of a combined PET/CT scanner.

In conclusion, for our study involving the thorax, matching patient positioning and performing consecutive examinations on the same day by using separate PET and CT scanners improve the quality of registration compared with registration of separate scans acquired without purposeful alignment and breathing instructions. Registration of PET and CT data sets acquired with the intention of fusion for interpretation can approximate the anatomic alignment in fusion of a combined PET/CT scan. Fusion software is useful for anatomic alignment; however, for optimal registration, patients should be scheduled for imaging on the same day with specific attention to matching positioning and respiration.


   FOOTNOTES
 

Abbreviations: FDG = fluorine 18 fluorodeoxyglucose

Authors stated no financial relationship to disclose.

Author contributions: Guarantors of integrity of entire study, V.K., A.J.F., S.L.A.; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, all authors; approval of final version of submitted manuscript, all authors; literature research, V.K., A.J.F., S.L.A.; clinical studies, V.K., A.J.F., S.L.A.; statistical analysis, all authors; and manuscript editing, V.K., A.J.F., S.L.A.


   References
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

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