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(Radiology. 2001;218:163-171.)
© RSNA, 2001

Nuclear Medicine

Value of Iterative Reconstruction, Attenuation Correction, and Image Fusion in the Interpretation of FDG PET Images with an Integrated Dual-Head Coincidence Camera and X-Ray-based Attenuation Maps1

Dominique Delbeke, MD, PhD, William H. Martin, MD, James A. Patton, PhD and Martin P. Sandler, MD

1 From the Section of Nuclear Medicine, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, 21st Ave S and Garland, Nashville, TN 37232-2675. Received April 12, 2000; revision requested June 6; revision received June 29; accepted July 11. Supported by research grants from ELGEMS Ltd, Haifa, Israel, and GE Medical Systems, Milwaukee, Wis. Address correspondence to D.D. (e-mail: dominique.delbeke@mcmail.vanderbilt.edu).


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
PURPOSE: To compare lesion detectability on 2-[fluorine-18]fluoro-2-deoxy-D-glucose (FDG) positron emission tomographic (PET) images obtained with a dual-head coincidence (DHC) gamma camera equipped with an integrated x-ray tube–based transmission system (a) with images reconstructed with filtered back projection (FBP) and those reconstructed with an iterative reconstruction algorithm based on coincidence-ordered subsets expectation maximization (COSEM), (b) with images reconstructed without and with attenuation correction (AC), and (c) with images reconstructed without and with image fusion for anatomic mapping.

MATERIALS AND METHODS: Thirty-five patients known or suspected to have malignancy underwent initial imaging with a dedicated positron emission tomography (PET) unit after injection of 10 mCi (370 MBq) of FDG. Transmission computed tomographic (CT) scans and FDG emission images were then obtained with the DHC camera. The proportion of lesions detected on the various sets of FDG DHC images was determined by using FDG PET as the standard of reference. Imaging findings were correlated with those from histologic examination and clinical follow-up, in consultation with the respective referring physicians.

RESULTS: FDG PET depicted 78 lesions, 29 of which were equal to or less than 1.5 cm in diameter. FDG DHC depicted 52 of the 78 (67%), 59 of 78 (76%), and 61 of the 78 (78%) lesions, respectively, when image reconstruction was performed with FBP without AC, COSEM without AC, and both COSEM and AC. The detection rate of lesions 1.5 cm or smaller was better with COSEM and AC than with FBP (55% vs 34%, respectively). In addition, COSEM and AC allowed more confidence in the interpretation. None of these differences, however, were significant. Fusion of CT scans and FDG DHC images obtained with COSEM and AC allowed localization of lesions to the skeleton in three patients and to the liver versus adjacent bowel in three patients. Image fusion was especially helpful for localizing lesions in the neck in five patients. Anatomic mapping on fusion images was clinically relevant in 11 patients (31%).

CONCLUSION: The COSEM reconstruction algorithm should replace FBP when available. Functional anatomic mapping improved lesion localization in one-third of the patients studied.

Index terms: Fluorine, radioactive • Neoplasms, PET • Positron emission tomography (PET), comparative studies


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
The clinical utility of 2-[fluorine-18]fluoro-2-deoxy-D-glucose (FDG) imaging was first established by using dedicated positron emission tomography (PET) units equipped with multiple rings of bismuth germanate oxide detectors (1). More recently, hybrid gamma cameras capable of imaging conventional single-photon emitters and positron emitters such as FDG have become available. Improvement of the hybrid camera technology has been achieved by using dual-head coincidence (DHC) detection with multihead gamma cameras to improve resolution and by increasing the thickness of the NaI (Tl) crystals (2–10), which leads to an increase in sensitivity. Lesion detectability, however, remained inferior to that of images obtained with dedicated PET units (8–10). In these previous studies, images were reconstructed by using filtered back projection (FBP). Subsequently, iterative reconstruction algorithms became available, which further improved the image quality (11).

It has been demonstrated that attenuation effects are much more substantial in coincidence imaging than in single photon emission computed tomography (SPECT) because both photons from an annihilation process must pass through the region without interaction. Attenuation effects in coincidence imaging produce regional nonuniformities, distortions of intense structures, and edge effects. Correction for these attenuation artifacts should improve the quality of the images and increase image contrast. For the body, various methods have been developed with measured attenuation by using radioactive transmission sources. The quality of the image corrected for attenuation effects largely depends on registration of the transmission and emission scans. Recently, a commercial CT scanner and a commercial dedicated PET unit were integrated with a common imaging table for image correlation and fusion (12). Hasegawa et al (13) also described a CT system capable of a obtaining simultaneous emission-transmission scans.

In this study, we used a commercially available dual-head gamma camera equipped with an integrated x-ray transmission system for attenuation correction (AC), anatomic mapping, and image fusion (14). The purpose of the study was to compare lesion detectability (a) on images reconstructed with FBP versus those reconstructed with an iterative reconstruction algorithm, (b) on images obtained without and with AC, and (c) without and with fusion images for anatomic mapping.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Patient Population
Thirty-five patients referred to undergo FDG PET between June 1999 and February 2000 (18 men, 17 women; age range, 20–79 years; mean age, 55 years ± 13 [SD]) were included in the study. All 35 patients were known to have or suspected of having malignancy. The clinical diagnosis in these patients was indeterminate pulmonary nodules (n = 4), lung carcinoma (n = 3), colorectal carcinoma (n = 5), lymphoma (n = 3), melanoma (n = 1), head and neck carcinoma (n = 8), breast carcinoma (n = 3), esophageal carcinoma (n = 1), brain tumor (n = 1), testicular cancer (n = 1), bladder carcinoma (n = 1), and carcinoma of unknown primary (n = 4). Three patients underwent FDG PET twice, once for staging purposes and again after neoadjuvant chemoradiation therapy. All patients fasted for a minimum of 4 hours before imaging, and both PET and DHC imaging were performed after the same administration of FDG. The field of view for DHC imaging was determined with findings on CT or PET scans. The CT scans were obtained within 1 month of the FDG PET scans in most patients. The size of the lesions was measured on the CT scans, except for skeletal lesions. The uptake period between the injection of FDG and the beginning of emission PET scanning was 35–107 minutes (mean, 58 minutes ± 18). The uptake time between FDG injection and DHC imaging was 87–274 minutes (mean, 180 minutes ± 46). This protocol was approved by the institutional review board, and all patients gave their written informed consent.

FDG PET Imaging
FDG PET images were obtained by using an eight-ring tomograph (ECAT 933/08/16; Siemens, Iselin, NJ) with a 12.5-cm axial field of view that produced 15 transverse images. The section thickness was 8.0 mm, with a measured reconstructed resolution of 6.5 mm full width half maximum. The images were reconstructed by using photopeak/photopeak counts with an energy window of more than 350 keV.

After the intravenous administration of approximately 10 mCi (370 MBq) of FDG (mean, 10.35 mCi ± 0.35 [382.95 MBq ± 1.29]), transverse emission images were acquired for 15 minutes per bed position and reconstructed in a 128 x 128 matrix by using FBP and a Hamming filter with a cutoff frequency of 0.5 cycle per pixel. The pixel size was 0.38 cm. Images were reconstructed by using FBP. AC was not performed for FDG PET images.

FDG DHC Imaging
FDG DHC images were obtained with a dual-head gamma camera with coincidence imaging capability (Millennium VG; GE Medical Systems, Milwaukee, Wis) equipped with two rectangular detectors with a field of view of 38 x 50 cm positioned at 180°, with 5/8-inch-thick (15.9-mm) NaI (Tl) crystals and a slip ring gantry that permits data acquisition while the detectors are continually rotating around the patient. Electronic collimation (coincidence timing window) was used to simultaneously detect one annihilation photon in each detector, resulting from a positron decay (ie, 10 rotations for a 30-minute acquisition). A 15-nsec timing window was used to identify coincidence events, and an offset 45-nsec window was used to monitor random coincidence events. Slit collimators (septa of 70 x 4 mm spaced 10 mm apart) with graded absorbers (lead, tin, and copper) were used to reduce the singles rate from activity outside the field of view and the effects of low-energy scattered radiation. The acceptance angle was fixed at 8° in the transverse direction and 35° in the transaxial direction.

To provide attenuation maps and enable anatomic localization, an x-ray tube and linear detector array were mounted on the slip ring gantry of the dual-head gamma camera, which essentially functioned as a third-generation x-ray CT scanner. The x-ray tube operated in the continuous output mode during the acquisition of each transverse section, and the output was selectable up to a maximum of 140 kVp at 2.5 mA. The detector array consisted of 384 solid-state detectors, each measuring 1.8 x 28 mm. The x-ray tube was collimated to provide a fan beam of photons expanding to fill the field of view of the linear array in the transverse direction and a beam width of 1 cm at the center of the scanning field in the axial direction.

For data acquisition, the patient was first positioned for x-ray transmission scanning, and 40 transverse sections were obtained as the patient was indexed through the imaging field of the transmission device by using the computer-controlled imaging table. For transmission scanning, the system rotated at 2.6 revolutions per minute, with a single section being obtained in 13.8 seconds and requiring 0.6 rotation (0.5 rotation plus the width of the fan beam). Forty sections were acquired in 9.2 minutes. At the completion of transmission scanning, the patient was automatically repositioned so that the 40-cm axial field that was just scanned matched the 40-cm axial field of view of the dual-head scintillation camera. A 30-minute coincidence scan was then acquired in list mode with the detectors rotating at one revolution per 3 minutes.

Although the spatial resolution of the transmission scans was on the order of 1.0 mm, the scans were reconstructed into a 128 x 128 array of attenuation maps (pixel size, 4.2 mm) by using FBP to correspond to the array size of the reconstructed emission scan. The attenuation maps were displayed by using Hounsfield units to correspond to the displays routinely used in conventional CT.

The rebinning process was performed in the normal mode, which uses both photopeak-photopeak and photopeak-Compton interactions; the section thickness was usually 8.0 mm. The Compton scatter window was 100–350 keV. The images were first reconstructed by using FBP with a Metz filter (power of 3 and full width half maximum of 10 mm). The emission scan was then reconstructed by using an iterative reconstruction algorithm based on the ordered subsets expectation maximization, or OSEM, or algorithm but modified to handle list mode data as input and using a ray-tracing algorithm for image reconstruction. This algorithm, coincidence OSEM (COSEM), uses subsets of data ordered in time (a single 180° coincidence acquisition provides a complete set of image data) instead of space, as with the conventional OSEM algorithm. Typically, 10 subsets (each a 360° acquisition) with two iterations were used with COSEM. In addition, the attenuation maps were used for AC on each ray during reconstruction, and sensitivity profile corrections were performed in the process. The attenuation maps and emission images were also automatically reformatted into sagittal and coronal views from the transverse sections.

The emission images were then displayed with the corresponding registered attenuation maps. Because the emission images and the transmission scans were precisely registered during acquisition, obtained with the same acquisition system, and reconstructed into the same array dimensions and identical pixel sizes, the emission images can be superimposed (fused) with the attenuation maps to provide accurate anatomic locations of detected abnormalities.

Image and Data Analysis
FDG PET and DHC images were viewed on an interactive computer system with use of both a linear gray scale and a continuous linear rainbow color scale with varying degrees of background subtraction. One experienced nuclear medicine physician (D.D.) evaluated the FDG PET images, and two other experienced nuclear medicine physicians (W.H.M., M.P.S.) interpreted the FDG DHC images individually and separately, without knowledge of the FDG PET results. Clinical data and conventional radiographs were available when relevant for correlation at interpretation. The grading system used took into account the level of confidence in the interpretation, which was based on the degree of uptake in relation to surrounding tissues and the degree of confidence in the localization (physiologic vs pathologic uptake). Sites of suspected abnormal FDG uptake on both the FDG PET and FDG DHC images were visually scored by using a 4-point scoring system, as in a previous study performed in our laboratory (6,8,9): 0 = no uptake, 1 = equivocal uptake, 2 = mild uptake, and 3 = definitely increased uptake. Disagreement was resolved by consensus. As in our previous studies (6,8,9), an activity score of 2 or 3 was considered positive for pathologic uptake. Imaging findings were also correlated with those from histologic examination and/or clinical follow-up (2–7 months) in all patients, in consultation with the respective referring physicians.

Statistical Analysis
The {chi}2 test was used to compare proportions. For 1 df, the {chi}2 value should be greater than 3.84 for P < .05.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
DISCUSSION
 REFERENCES
 
A summary of the clinical data is shown in Table 1. FDG PET depicted 78 lesions, 29 (37%) of which were 1.5 cm in diameter or smaller. Lesion size was determined on CT scans. Table 2 summarizes the scores and number of lesions detected with each acquisition and reconstruction technique. Of the 78 lesions depicted with FDG PET, 52 (67%), 59 (76%), and 61 (78%) were depicted with FDG DHC when images were reconstructed with FBP without AC, COSEM without AC, and COSEM with AC, respectively. Among the 26 lesions not seen with FBP, 18 were 1.5 cm or smaller, four were adjacent to other lesions with marked activity, three were rib metastases, and one was in a patient who was undergoing chemotherapy. The use of COSEM without AC for image reconstruction enabled the detection of five more lesions 1.5 cm or smaller, one lesion adjacent to others lesions with marked activity, and one lesion in the abdomen. On images reconstructed with COSEM and AC, two additional axillary lesions became identifiable. Figure 1 shows examples of the quality of the different images.


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  		TABLE 1. Summary of Clinical Data
 

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  		TABLE 2. Uptake Score with Different Image-Generation Algorithms
 


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  		Figure 1a. Images in a 75-year-old man who presented with a palpable mass in the left side of his neck. (a, b) Transverse CT scans of the neck show (a) a 2.4-cm enhancing lesion (arrow) at the base of the tongue and (b) a 4-cm nodal mass in the left side of the neck (arrow). (c) Corresponding FDG PET scans obtained without AC demonstrate two additional lesions (arrows), one (diameter, 2.0 cm) in a separate but adjacent left node, and one (diameter, 1.0 cm) in a right node. At retrospective examination, the lesion in the right node is enhanced at CT. (d) Corresponding FDG DHC scans reconstructed with FBP without AC. (e) Corresponding FDG DHC scans reconstructed with COSEM and without AC. (f) Corresponding FDG DHC scans reconstructed with COSEM and AC. Squamous cell carcinoma was diagnosed at fine-needle biopsy. The tongue lesion and the nodal mass were demonstrated with all techniques. The large left node lesion is seen on the DHC images reconstructed with COSEM and without AC (e) and with COSEM and AC (f) but not on the images reconstructed with FBP (d). The lymph node on the right is not clearly seen on any of the FDG DHC images.

 


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  		Figure 1b. Images in a 75-year-old man who presented with a palpable mass in the left side of his neck. (a, b) Transverse CT scans of the neck show (a) a 2.4-cm enhancing lesion (arrow) at the base of the tongue and (b) a 4-cm nodal mass in the left side of the neck (arrow). (c) Corresponding FDG PET scans obtained without AC demonstrate two additional lesions (arrows), one (diameter, 2.0 cm) in a separate but adjacent left node, and one (diameter, 1.0 cm) in a right node. At retrospective examination, the lesion in the right node is enhanced at CT. (d) Corresponding FDG DHC scans reconstructed with FBP without AC. (e) Corresponding FDG DHC scans reconstructed with COSEM and without AC. (f) Corresponding FDG DHC scans reconstructed with COSEM and AC. Squamous cell carcinoma was diagnosed at fine-needle biopsy. The tongue lesion and the nodal mass were demonstrated with all techniques. The large left node lesion is seen on the DHC images reconstructed with COSEM and without AC (e) and with COSEM and AC (f) but not on the images reconstructed with FBP (d). The lymph node on the right is not clearly seen on any of the FDG DHC images.

 


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  		Figure 1c. Images in a 75-year-old man who presented with a palpable mass in the left side of his neck. (a, b) Transverse CT scans of the neck show (a) a 2.4-cm enhancing lesion (arrow) at the base of the tongue and (b) a 4-cm nodal mass in the left side of the neck (arrow). (c) Corresponding FDG PET scans obtained without AC demonstrate two additional lesions (arrows), one (diameter, 2.0 cm) in a separate but adjacent left node, and one (diameter, 1.0 cm) in a right node. At retrospective examination, the lesion in the right node is enhanced at CT. (d) Corresponding FDG DHC scans reconstructed with FBP without AC. (e) Corresponding FDG DHC scans reconstructed with COSEM and without AC. (f) Corresponding FDG DHC scans reconstructed with COSEM and AC. Squamous cell carcinoma was diagnosed at fine-needle biopsy. The tongue lesion and the nodal mass were demonstrated with all techniques. The large left node lesion is seen on the DHC images reconstructed with COSEM and without AC (e) and with COSEM and AC (f) but not on the images reconstructed with FBP (d). The lymph node on the right is not clearly seen on any of the FDG DHC images.

 


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  		Figure 1d. Images in a 75-year-old man who presented with a palpable mass in the left side of his neck. (a, b) Transverse CT scans of the neck show (a) a 2.4-cm enhancing lesion (arrow) at the base of the tongue and (b) a 4-cm nodal mass in the left side of the neck (arrow). (c) Corresponding FDG PET scans obtained without AC demonstrate two additional lesions (arrows), one (diameter, 2.0 cm) in a separate but adjacent left node, and one (diameter, 1.0 cm) in a right node. At retrospective examination, the lesion in the right node is enhanced at CT. (d) Corresponding FDG DHC scans reconstructed with FBP without AC. (e) Corresponding FDG DHC scans reconstructed with COSEM and without AC. (f) Corresponding FDG DHC scans reconstructed with COSEM and AC. Squamous cell carcinoma was diagnosed at fine-needle biopsy. The tongue lesion and the nodal mass were demonstrated with all techniques. The large left node lesion is seen on the DHC images reconstructed with COSEM and without AC (e) and with COSEM and AC (f) but not on the images reconstructed with FBP (d). The lymph node on the right is not clearly seen on any of the FDG DHC images.

 


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  		Figure 1e. Images in a 75-year-old man who presented with a palpable mass in the left side of his neck. (a, b) Transverse CT scans of the neck show (a) a 2.4-cm enhancing lesion (arrow) at the base of the tongue and (b) a 4-cm nodal mass in the left side of the neck (arrow). (c) Corresponding FDG PET scans obtained without AC demonstrate two additional lesions (arrows), one (diameter, 2.0 cm) in a separate but adjacent left node, and one (diameter, 1.0 cm) in a right node. At retrospective examination, the lesion in the right node is enhanced at CT. (d) Corresponding FDG DHC scans reconstructed with FBP without AC. (e) Corresponding FDG DHC scans reconstructed with COSEM and without AC. (f) Corresponding FDG DHC scans reconstructed with COSEM and AC. Squamous cell carcinoma was diagnosed at fine-needle biopsy. The tongue lesion and the nodal mass were demonstrated with all techniques. The large left node lesion is seen on the DHC images reconstructed with COSEM and without AC (e) and with COSEM and AC (f) but not on the images reconstructed with FBP (d). The lymph node on the right is not clearly seen on any of the FDG DHC images.

 


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  		Figure 1f. Images in a 75-year-old man who presented with a palpable mass in the left side of his neck. (a, b) Transverse CT scans of the neck show (a) a 2.4-cm enhancing lesion (arrow) at the base of the tongue and (b) a 4-cm nodal mass in the left side of the neck (arrow). (c) Corresponding FDG PET scans obtained without AC demonstrate two additional lesions (arrows), one (diameter, 2.0 cm) in a separate but adjacent left node, and one (diameter, 1.0 cm) in a right node. At retrospective examination, the lesion in the right node is enhanced at CT. (d) Corresponding FDG DHC scans reconstructed with FBP without AC. (e) Corresponding FDG DHC scans reconstructed with COSEM and without AC. (f) Corresponding FDG DHC scans reconstructed with COSEM and AC. Squamous cell carcinoma was diagnosed at fine-needle biopsy. The tongue lesion and the nodal mass were demonstrated with all techniques. The large left node lesion is seen on the DHC images reconstructed with COSEM and without AC (e) and with COSEM and AC (f) but not on the images reconstructed with FBP (d). The lymph node on the right is not clearly seen on any of the FDG DHC images.

 
Table 2 also demonstrates the improvement in image quality, as shown with the increase in the confidence level in interpretation, obtained by using COSEM instead of FBP for image reconstruction. Seven lesions were detected with more confidence (score, 3) with COSEM without AC than with FBP without AC (score, 2).

The 19 lesions missed on FDG DHC images reconstructed with COSEM and AC were located in 11 patients. Detection of 15 of the 19 lesions would not have altered treatment because other lesions were identified in these eight patients. In two patients, the undetected lesion was a contralateral neck lymph node that would not have been included in the radiation field if undetected (Fig 1). In one patient, residual activity was not detected in a residual mass at CT performed after the end of chemotherapy, which would have prevented additional, more aggressive therapy. Nine of the 19 undetected lesions were graded as equivocal (score, 1) because they could be retrospectively identified after correlation with FDG PET images. Five of the 19 undetected lesions had only mild uptake (score, 2) at FDG PET.

Thirty of the 78 lesions detected with PET were confirmed to be malignant at biopsy or surgery. These 30 lesions were located in 20 patients, and nine of the 30 lesions (30%) were 1.5 cm or smaller. Only four of these lesions in four patients were not detected on DHC images reconstructed with COSEM and AC. Three were 1.5 cm or smaller, and the detection of these lesions would not have altered the treatment of these patients. The fourth undetected lesion was in the patient with the residual mass who had finished chemotherapy.

Table 3 gives the percentage of lesions detected with FDG DHC imaging with respect to size and location of lesions; FDG PET is used as the standard of reference. The size of the lesions could not be measured in the skeleton. Although none of the differences in percentages were significant with regard to location and size, there is a trend toward better lesion detectability for small and large lesions with sequential technical improvement going from FBP without AC to COSEM without AC to COSEM with AC. Of the 29 lesions 1.5 cm or smaller (excluding those in the skeleton), 10 (34%) were seen with FBP without AC, 15 (52%) with COSEM without AC, and 16 (55%) with COSEM with AC. Of the 40 lesions larger than 1.5 cm (excluding those in the skeleton), 36 (90%), were detected with FBP without AC, 38 (95%) with COSEM without AC, and 39 (98%) with COSEM with AC.


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  		TABLE 3. Number of Lesions Detected with FDG DHC Imaging with Use of Different Algorithms for Image Generation
 
Anatomic mapping on fusion images was clinically relevant in 11 of the 35 patients (31%). Image fusion allowed localization of lesions to the skeleton in three patients. One patient with testicular cancer (patient 16) had elevated tumor markers and a normal CT scan. Both the PET and DHC images demonstrated a focus of uptake in the abdomen, but the exact location was equivocal. Bone marrow uptake, which is often a useful landmark to outline the spine, was virtually absent in this patient. Therefore, it was difficult to evaluate whether the focus of uptake was in a vertebral body or the soft tissue anterior to the spine. The fusion image (CT and DHC) enabled exact localization in the vertebral body, and this was confirmed with magnetic resonance imaging. In two other patients, the fusion image allowed localization of a focus of uptake in the inferior tip of the liver versus adjacent bowel, a common problem in the interpretation of FDG images. In that regard, images with AC can be helpful as well because the outline of the liver is better delineated. Figure 2 shows images obtained in such a patient (patient 17 in Table 1). Image fusion was especially helpful for localizing lesions in the neck in five patients. For example, patient 20 (Table 1) had previously undergone a total thyroidectomy for thyroid carcinoma, right-side neck exploration for resection of metastases on three separate occasions, and placement of a right vocal cord implant-each followed by high-dose iodine 131 therapy-even though the whole-body diagnostic 31I scans were always negative. She presented again with elevated thyroglobulin levels, and the CT–FDG DHC fusion images were crucial for diagnosing a new metastasis in the right side of the neck and excluding a possible active granuloma in the region of the vocal cord implant.



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  		Figure 2a. Images in a 59-year-old man with rectal carcinoma. (a) Transverse CT scan of the abdomen obtained through the inferior border of the liver to help plan radiation therapy shows a 2.0-cm lesion (arrow) in the inferior tip of the liver on the uppermost section of the field of view. (b) Corresponding transverse (upper left), sagittal (upper right), and coronal (bottom) FDG PET scans through the inferior border of the liver. (c) Corresponding FDG DHC scans reconstructed with COSEM and without AC. The scans were obtained through the inferior border of the liver (right) and another selected transverse section at a upper level (left). (d) Corresponding FDG DHC scans reconstructed with COSEM and AC. The scans were obtained through the inferior border of the liver (right) and another selected transverse section at an upper level (left). (e) Transverse CT transmission image (left) and FDG DHC-transmission CT fusion images, which were both obtained through the inferior border of the liver (right). The FDG images obtained with the PET scanner and the hybrid gamma camera show a focus of uptake (arrow in b, arrows in c and d), but the location is equivocal (tip of the liver vs adjacent bowel). Although the lesion is not clearly seen on the transmission CT scans (left image in e), the location in the liver (arrow in e) is unequivocally determined with the help of the fusion image (right image in e). Another liver metastasis was found posteriorly on an uppermost section (left images in c and d).

 


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  		Figure 2b. Images in a 59-year-old man with rectal carcinoma. (a) Transverse CT scan of the abdomen obtained through the inferior border of the liver to help plan radiation therapy shows a 2.0-cm lesion (arrow) in the inferior tip of the liver on the uppermost section of the field of view. (b) Corresponding transverse (upper left), sagittal (upper right), and coronal (bottom) FDG PET scans through the inferior border of the liver. (c) Corresponding FDG DHC scans reconstructed with COSEM and without AC. The scans were obtained through the inferior border of the liver (right) and another selected transverse section at a upper level (left). (d) Corresponding FDG DHC scans reconstructed with COSEM and AC. The scans were obtained through the inferior border of the liver (right) and another selected transverse section at an upper level (left). (e) Transverse CT transmission image (left) and FDG DHC-transmission CT fusion images, which were both obtained through the inferior border of the liver (right). The FDG images obtained with the PET scanner and the hybrid gamma camera show a focus of uptake (arrow in b, arrows in c and d), but the location is equivocal (tip of the liver vs adjacent bowel). Although the lesion is not clearly seen on the transmission CT scans (left image in e), the location in the liver (arrow in e) is unequivocally determined with the help of the fusion image (right image in e). Another liver metastasis was found posteriorly on an uppermost section (left images in c and d).

 


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  		Figure 2c. Images in a 59-year-old man with rectal carcinoma. (a) Transverse CT scan of the abdomen obtained through the inferior border of the liver to help plan radiation therapy shows a 2.0-cm lesion (arrow) in the inferior tip of the liver on the uppermost section of the field of view. (b) Corresponding transverse (upper left), sagittal (upper right), and coronal (bottom) FDG PET scans through the inferior border of the liver. (c) Corresponding FDG DHC scans reconstructed with COSEM and without AC. The scans were obtained through the inferior border of the liver (right) and another selected transverse section at a upper level (left). (d) Corresponding FDG DHC scans reconstructed with COSEM and AC. The scans were obtained through the inferior border of the liver (right) and another selected transverse section at an upper level (left). (e) Transverse CT transmission image (left) and FDG DHC-transmission CT fusion images, which were both obtained through the inferior border of the liver (right). The FDG images obtained with the PET scanner and the hybrid gamma camera show a focus of uptake (arrow in b, arrows in c and d), but the location is equivocal (tip of the liver vs adjacent bowel). Although the lesion is not clearly seen on the transmission CT scans (left image in e), the location in the liver (arrow in e) is unequivocally determined with the help of the fusion image (right image in e). Another liver metastasis was found posteriorly on an uppermost section (left images in c and d).

 


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  		Figure 2d. Images in a 59-year-old man with rectal carcinoma. (a) Transverse CT scan of the abdomen obtained through the inferior border of the liver to help plan radiation therapy shows a 2.0-cm lesion (arrow) in the inferior tip of the liver on the uppermost section of the field of view. (b) Corresponding transverse (upper left), sagittal (upper right), and coronal (bottom) FDG PET scans through the inferior border of the liver. (c) Corresponding FDG DHC scans reconstructed with COSEM and without AC. The scans were obtained through the inferior border of the liver (right) and another selected transverse section at a upper level (left). (d) Corresponding FDG DHC scans reconstructed with COSEM and AC. The scans were obtained through the inferior border of the liver (right) and another selected transverse section at an upper level (left). (e) Transverse CT transmission image (left) and FDG DHC-transmission CT fusion images, which were both obtained through the inferior border of the liver (right). The FDG images obtained with the PET scanner and the hybrid gamma camera show a focus of uptake (arrow in b, arrows in c and d), but the location is equivocal (tip of the liver vs adjacent bowel). Although the lesion is not clearly seen on the transmission CT scans (left image in e), the location in the liver (arrow in e) is unequivocally determined with the help of the fusion image (right image in e). Another liver metastasis was found posteriorly on an uppermost section (left images in c and d).

 


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  		Figure 2e. Images in a 59-year-old man with rectal carcinoma. (a) Transverse CT scan of the abdomen obtained through the inferior border of the liver to help plan radiation therapy shows a 2.0-cm lesion (arrow) in the inferior tip of the liver on the uppermost section of the field of view. (b) Corresponding transverse (upper left), sagittal (upper right), and coronal (bottom) FDG PET scans through the inferior border of the liver. (c) Corresponding FDG DHC scans reconstructed with COSEM and without AC. The scans were obtained through the inferior border of the liver (right) and another selected transverse section at a upper level (left). (d) Corresponding FDG DHC scans reconstructed with COSEM and AC. The scans were obtained through the inferior border of the liver (right) and another selected transverse section at an upper level (left). (e) Transverse CT transmission image (left) and FDG DHC-transmission CT fusion images, which were both obtained through the inferior border of the liver (right). The FDG images obtained with the PET scanner and the hybrid gamma camera show a focus of uptake (arrow in b, arrows in c and d), but the location is equivocal (tip of the liver vs adjacent bowel). Although the lesion is not clearly seen on the transmission CT scans (left image in e), the location in the liver (arrow in e) is unequivocally determined with the help of the fusion image (right image in e). Another liver metastasis was found posteriorly on an uppermost section (left images in c and d).

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
REFERENCES
 
Table 4 summarizes data from studies performed with sequential technical modifications to improve the performance of FDG imaging with one type of hybrid gamma camera. In our first study (6), we demonstrated that, despite the limited spatial resolution of collimated 511-keV SPECT with 17.0-mm resolution, FDG SPECT can adequately depict primary and metastatic lesions larger than 1.8 cm. The hybrid gamma camera was then modified to perform coincidence detection, which improved resolution, and then equipped with thicker NaI (Tl) crystals (5/8 inch), which approximately doubled sensitivity. The detection rate for malignant lesions, however, appears to be similar despite these improvements (6,8,9). This is most probably related to the limited sensitivity of the DHC system, which is still approximately 10 times less than that of the dedicated PET system. The limited detection rate obtained with DHC in patients with oncologic disease has also been reported by other investigators with a system developed by a different manufacturer also using 5/8-inch crystals and dynamic segmentation (15). These investigators reported difficulty in detecting lesions smaller than 1.5 cm in both the abdomen and pelvis, as compared with PET.


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  		TABLE 4. Summary of Vanderbilt Experience with 511-KeV Imaging Performed with a Dual-Head Gamma Camera
 
In the current study, we demonstrated that (a) the use of an iterative reconstruction algorithm allowed detection of more lesions and a higher level of confidence in the interpretation, (b) there was no significant difference in lesion detection between images obtained without or with AC (76% vs 78%, respectively), and (c) image fusion allowed precise localization of lesions in the skeleton, liver versus adjacent bowel, and specific structures of the neck. Anatomic mapping on fusion images was clinically relevant in 11 of the 35 patients (31%).

The signal-to-noise ratio can be improved by using iterative reconstruction instead of the FBP algorithm to reconstruct PET images (16). To our knowledge, however, no studies have shown improvement of lesion detection in patients. Bleckmann et al (17) compared, with visual analysis, lesion detection on PET images obtained in 28 patients with breast cancer. They found no improvement in lesion detection when the FDG images (which were corrected for attenuation) were reconstructed by using iterative reconstruction, as compared with FBP. Farquhar and colleagues (18) studied the effect of acquisition modes (two-dimensional and three-dimensional), reconstruction algorithms (FBP and iterative reconstruction), and AC on lesion detection with FDG PET. In their study, they added simulated lung cancer lesions to two- and three-dimensional PET data acquired in healthy volunteers. Using receiver operating characteristic analysis, they found that lesion detection with iterative reconstruction was better than that with FBP. The improvement in lesion detection, however, was not significant.

The topic of AC has been recently discussed in an editorial by Wahl (19). The most important advantage of AC is improved anatomic delineation (mediastinum from lungs, lungs from liver). Therefore, images with AC are easier to interpret than images without AC, especially for the inexperienced interpreter, allowing lesions to be more accurately localized. The second advantage of AC is the possibility of semiquantitative measurement, which may be helpful in some clinical settings (eg, when monitoring therapy for malignant lesions). In addition, on images with AC, lesions are not distorted, and lesions located deeply should have intensity similar to that of superficial lesions. Images obtained with AC are often noisier than those obtained without AC, however, and the degree of noise in images is dependent on the method used to perform AC. Results of several studies (including this one) (17, 18,20–22) have indicated that lesion detection is comparable on FDG images with and without AC. In our study, AC was performed by using x-ray attenuation maps obtained with an x-ray tube attached to the gantry of the hybrid gamma camera. Therefore, attenuation maps can be obtained just before the FDG images without repositioning the patient, and the registration of transmission and emission images is optimal. In addition, the high photon flux inherent with this technique produces high-quality images with AC. Zimny et al (23) reported improved lesion detection on images with AC, as compared with those without AC. The use of AC resulted in a significant increase in the detection rate of lesions 20.0 mm or smaller, from 60% to 80%. The controversy between our study and those mentioned in this paragraph is probably related to differences in equipment, techniques, and data analysis.

Despite the improvement of image quality with COSEM and AC, users must be aware of the limitations of imaging FDG with hybrid cameras instead of dedicated PET scanners. In this study, DHC imaging, which was performed with a state-of-the-art hybrid gamma camera, depicted only approximately half of the lesions 1.5 cm or smaller that were depicted with an older-model dedicated PET scanner. This may be a major limitation for staging some types of tumors or detecting small amounts of viable tissue in residual masses after therapy. Three of the 35 patients (8%) would have been undertreated if FDG DHC imaging alone was performed.

There may be some argument that the sensitivity of FDG DHC in the detection of malignant lesions (especially small lesions) is not superior to that of CT. In this study, we did not directly compare FDG DHC with CT; therefore, it is difficult to make speculations in that regard. In addition, it is now well accepted that FDG imaging does not replace but complements CT, as demonstrated by anatomic mapping on fusion images in this study.

Although numerous studies have shown that the sensitivity and specificity of FDG PET imaging is superior to that of CT in many clinical settings, the inability of FDG imaging to provide anatomic localization remains a substantial impairment in maximizing its clinical utility (24,25). The availability of the x-ray transmission scan is an added benefit, providing an anatomic map for correlation and/or fusion with the emission scan. In our study, the fusion images helped precisely locate the lesion in 31% of the patients.

Limitations of the Study
One limitation of our study is the use of FDG images obtained with an older-model PET scanner as a standard of reference. The technology of dedicated PET scanners has improved substantially during the past 10 years. The resolution of state-of-the-art PET scanners is superior to that of the scanner used in this study. In addition, iterative reconstruction algorithms are now available for state-of-the-art dedicated PET scanners, and the transmission scan used for AC can be obtained after the emission scan, which avoids repositioning the patient in the gantry and associated registration errors. The use of an outdated PET scanner as the standard of reference may have caused us to overestimate the performance of the state-of-the-art hybrid gamma camera. The same PET unit, however, was used for comparison in previous studies in which we evaluated sequential technical improvements of the hybrid gamma camera (6,8,9) (Table 4).

Another limitation of our study is the potential bias introduced because dedicated FDG PET images were interpreted by only one reviewer, whereas two reviewers interpreted the FDG DHC images.

In conclusion, DHC imaging with use of a hybrid gamma camera equipped with 5/8-inch NaI (Tl) crystals provides spatial resolution in the same range as and a sensitivity 10 times less than that of a dedicated PET scanner with bismuth germanate oxide crystals. The iterative reconstruction algorithm (COSEM) definitely improved the quality of the images and confidence in the interpretation, although the improvement in lesion detection was not significant. Optimal AC with x-ray–based transmission scanning did not increase the lesion detection rate but enabled better visualization of the anatomic landmarks.

Fusion of anatomic and functional images (CT and FDG PET images) sequentially in time and registered in an integrated system without patient movement was extremely helpful for precise anatomic localization of lesions with increased metabolism and was clinically relevant in 31% of the patients. This technology, however, does not challenge the need for a high-resolution diagnostic CT scan obtained with oral and intravenous contrast material, which is necessary to evaluate the extent of the lesions and their relationship to vascular structures. In patients in whom there is insufficient information to localize a lesion, the data may be used to precisely select the appropriate section for review from a diagnostic-quality CT scan that matches up with the area of increased metabolism. The combined approach of x-ray AC and image fusion with FDG imaging is a new and powerful diagnostic tool for nuclear medicine imaging, intensity-modulated radiation therapy, and surgical planning.

Users must be familiar with the rapid developments of this technology and aware of the range of options currently available for FDG imaging.


   ACKNOWLEDGMENTS
 
The authors thank Dawn Shone, CNMT, for her technical support and John Bobbitt and Heather Day for preparing the illustrations. The authors also acknowledge the expert help and advice of Irene Feurer, PhD, with the statistical analysis.


   FOOTNOTES
 
Abbreviations: AC = attenuation correction, COSEM = coincidence-ordered subsets expectation maximization, FBP = filtered back projection, FDG = 2-[fluorine-18]fluoro-2-deoxy-D-glucose

Author contributions: Guarantor of integrity of entire study, D.D.; study concepts, all authors; study design, all authors; definition of intellectual content, D.D.; literature research, D.D.; clinical studies, D.D.; data acquisition, J.A.P.; data analysis, W.H.M., M.P.S.; statistical analysis, D.D.; manuscript preparation, D.D.; manuscript editing, M.P.S.; manuscript review, D.D.


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RESULTS
 DISCUSSION
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