Single-Photon Radionuclide Imaging and SPECT

1.02

Single-Photon Radionuclide Imaging and SPECT

RS Miyaoka, University of Washington, Seattle, WA, USA ã 2014 Elsevier B.V. All rights reserved.

1.02.1 1.02.1.1 1.02.2 1.02.2.1 1.02.2.2 1.02.2.3 1.02.3 1.02.4 1.02.4.1 1.02.4.2 1.02.4.3 1.02.4.4 1.02.4.5 References

Introduction Radioisotopes of Interest Instrumentation The Detector Assembly Collimators Detector Positioning and Corrections Acquisition Modes and Image Formation Imaging Procedures Whole-Body Bone Scan Brain Cardiac Renal Thyroid

Abbreviations CdTe CZT FWHM

1.02.1

Cadmium telluride Cadmium zinc telluride Full width at half maximum – a common metric used for spatial and energy resolution

Introduction

In this chapter, we will lay the foundations of basic physics associated with single-photon radionuclide imaging and single-photon emission computed tomography (SPECT). We will describe the basic instrumentation associated with nuclear medicine imaging, acquisition methods, the principles of tomographic image reconstruction, quality control procedures, clinical imaging protocols, and research applications. There are additional chapters in this book that will provide more detailed descriptions of dynamic SPECT, SPECT scatter correction, and Compton SPECT imaging. As described in the opening chapter of this book, singlephoton radionuclide imaging began in the late 1950s with the invention of the Anger camera (Anger, 1958, 1964). Soon after was the development of positron emission imaging, as common detectors could be used between the two imaging methodologies. With the growth of positron emission tomography (PET) imaging in the early 1970s, it was thought that PET would eventually replace planar gamma camera imaging and SPECT. This is because PET imaging provides better image resolution, has higher detection efficiency, and is easier to quantitate. However, this has not been the case. Planar gamma camera and SPECT imaging offer a lower cost alternative and in many instances provide the required diagnostic information. An added benefit of single-photon imaging is that there are at least thirty FDA-approved radiopharmaceuticals for human clinical imaging (see Table 1 and

Comprehensive Biomedical Physics

39 39 40 40 43 46 49 55 55 56 58 58 59 59

PMT SPECT

Photomultiplier tube Single-photon emission computed tomography

many more are being developed) compared to one FDAapproved pharmaceutical for PET, fluorodeoxyglucose (18FFDG). While time has proven that there is a role for both single-photon and PET imaging in nuclear medicine clinics, recent advances in computer processing power and advanced image reconstruction methodologies are reducing many of the imaging advantages that PET has over SPECT (e.g., quantitation and image resolution). While this chapter will focus mostly on the current clinical utilization of single-photon imaging, we will briefly discuss current methods to facilitate quantitative single-photon imaging, both planar and SPECT, in the section describing image reconstruction.

1.02.1.1

Radioisotopes of Interest

One of the features of nuclear medicine imaging is that the cameras are used to image a variety of radionuclides that produce different gammas of different energies. These radioisotopes include 99mTc, 123I, 131I, 67Ga, 201Tl, and 111In. The characteristics of each are listed in Table 2. Some of the radioisotopes listed produce more than one gamma that may be used for imaging purposes. Others also produce beta particles that can be used for therapy (e.g., 131I). While gamma cameras image a variety of radionuclides, clinical systems have been optimized for imaging 99m Tc that emits a 140.5 keV gamma. This is because of the approximately 30 million nuclear medicine procedures conducted worldwide each year, about 80% of them use 99mTc (http://www.world-nuclear.org/info/inf55.html).

http://dx.doi.org/10.1016/B978-0-444-53632-7.00103-9

39

40

Table 1

Single-Photon Radionuclide Imaging and SPECT

FDA-approved SPECT radiopharmaceuticals

Radionuclide

Pharmaceutical

Gallium-67 Indium-111 Indium-111 Indium-111 Indium-111 Indium-111 Iodine-123 Iodine-123 Iodine-123 Iodine-131 Iodine-131 Iodine-131 Technetium-99m Technetium-99m Technetium-99m Technetium-99m Technetium-99m Technetium-99m Technetium-99m Technetium-99m Technetium-99m Technetium-99m Technetium-99m Technetium-99m Technetium-99m Technetium-99m Technetium-99m Technetium-99m Thallium-201 Xenon-133

Citrate Capromab pendetide (ProstaScint™) Ibritumomab tiuxetan (ZevalinW) Pentetate (DTPA) Oxyquinoline (OxineW) – leukocyte/platelet labeling Pentetreotide (OctreoScan™) Iobenguane (AdreView™) Ioflupane (DaTscan™) NaI capsules/solution NaI capsules/solution Human serum albumin (Megatope) Tositumomab (BEXXARW) Bicisate (NeuroliteW) Disofenin (HepatoliteW) Exametazime (Ceretec™) Macroaggregated albumin (MAA) Mebrofenin (CholetecW) Medronate (MDP) Mertiatide (MAG3™) Oxidronate (HDP™) Pentetate (DTPA) Pyrophosphate (PYP) Red blood cells Sestamibi Pertechnetate Succimer (DMSA™) Sulfur colloid Tetrofosmin (Myoview™) Chloride Gas

Table 2

Characteristics of nuclear medicine radioisotopes

Radionuclide

Half-life

Gammas

99m

6.04 h 13.3 h 8.05 days 78 h 73 h 2.81 days

140.5 keV 159 keVa 364 keV, 637 keV, 722 keVb 93 keV, 184.5 keV, 296 keV 167 keV, 71 keVc 173 keV, 247 keV

Tc I 131 I 67 Ga 201 Tl 111 In 123

a123 I produces additional higher-energy gammas with low branching ratios; however, some investigators recommend using medium-energy collimators to reduce collimator penetration due to higher-energy gammas. b131 I produces additional higher-energy gammas with low branching ratios. c201 Tl decays to 201Hg that produces 71 keV x-rays.

1.02.2

Instrumentation

As described in the opening chapter of this book, singlephoton radionuclide imaging began with the invention of the Anger camera (Anger, 1958, 1964). In many ways, little has changed with regard to the basic design of the very first nuclear medicine gamma cameras from 1957 till today. The main difference is that analog detector electronics have been replaced by digital electronics; however, the basic operation of the camera remains the same. A gamma camera consists of

three main components: (1) the detector (i.e., crystal and readout sensors and electronics), (2) a collimator, and (3) data acquisition and processing electronics.

1.02.2.1

The Detector Assembly

The detector assembly consists of a large area scintillator crystal, a light guide, and an array of photosensors, usually photomultiplier tubes (PMTs) as illustrated in Figure 1. The scintillator crystals are usually
60 cm by
45 cm in area and 9.5 mm thick. They are viewed by a hexagonal array of 55–61 hexagonal PMTs. A majority of the tubes are 3 in. in diameter with smaller diameter tubes used along the edges of the crystal. A general packing scheme of tubes is illustrated in Figure 2. Event positioning along the edges of the crystal is very distorted due to truncation of the light response spread within the crystal, and therefore, a band along the edge of the crystal is not used for imaging. That area is masked both mechanically through lead shielding and electronically during event positioning. Therefore, the effective imaging area of a 60 cm by 45 cm crystal is around 54 cm by 40 cm. The detector has three main functions. The first is detection of the gamma photons being emitted from the patient. The second is to determine the energy of the detected photon. The third is to localize where the gamma photon was detected in

Single-Photon Radionuclide Imaging and SPECT

the detector assembly and thereby assisting in the localization of the source of the gamma photon. Radioactive decay is a stochastic process and therefore there is noise associated with any measurement. The impact of noise can be reduced by acquiring more counts. Therefore, in nuclear medicine imaging, the quality of the image can typically be improved by acquiring more events. This can be achieved by administering higher levels of radioactivity to the patient or by imaging longer. However, there are set limits on how much radioactivity can be given to a patient to avoid effects of radiation toxicity and imaging longer lowers patient throughput and increases the possibility of image blurring or artifacts due to patient motion during the procedure. Thus, a key component of any nuclear medicine detector is its efficiency at stopping the emitted gamma photons. When a single-photon-emitting radionuclide undergoes decay in the patient, it emits a gamma photon. In the ideal situation, that photon will exit the patient without interacting in the patient and then be fully absorbed (i.e., photoelectric interaction) by the detector. However, most of the time, the photon will interact via Compton scatter before exiting the patient. In the case of Compton scatter, the photon is deflected from its original path and loses spatial information regarding the origination point of the photon. Photons that have Compton scattered in the patient are undesirable as they reduce

PMT LG

Crystal

Collimator

Figure 1 Gamma camera detector assembly consisting of a collimator, scintillator crystal, light guide (LG), and array of photomultiplier tubes (PMTs).

41

contrast and resolution of an image. Compton scattered events have lost energy, so one way to reject Compton scattered events at the detector level is to use an energy acceptance window during data acquisition. The energy window is set to reject Compton scattered photons and to accept gamma photons that have not Compton scattered in the patient. Just as radioactive decay is a random process, the conversion of deposited photon energy to light in a scintillator is a stochastic process, and the variability of the estimate of the energy deposited in a crystal is defined by the full width at half maximum (FWHM) of the photopeak energy spectrum divided by the photopeak energy. This is illustrated in Figure 3. The better the energy resolution of the detector, the narrower the energy acceptance window that can be used that translates to better scatter photon rejection. The ability to localize the gamma interaction point in a detector depends mostly on the amount of light produced by the scintillator, the geometry of the light sensors, and the decoding methods used for event positioning. Event positioning is characterized by the intrinsic spatial resolution of the detector. More light typically translates to better intrinsic spatial resolution, as does the use of more compact light sensors that allow finer sampling of the light response function of the detector. Besides the amount of light a scintillator produces, a second physical characteristic of the scintillator that can affect the intrinsic spatial resolution is the photoelectric cross section of the material at the energy of the photon being imaged. Ideally, the gamma photon will be photoelectrically absorbed in a single interaction in the detector. In this situation, all of the energy is deposited at a single site. When there are multiple interactions in a detector (e.g., Compton scatter followed by photoelectric absorption), light is produced at multiple points in the detector, and most detector systems will position the event to a location close to the energy-weighted mean between the two interaction points. Therefore, the ideal scintillator would produce a lot of light and also have a very high photoelectric cross section for the energy of the radioisotope being imaged.

Energy resolution vs. Energy window

Number of interactions

A

C B 20

40

60

80

100

120

140

160

Energy (keV) Figure 2 Photomultiplier tubes are generally packed in a hexagonal arrangement. Tubes that may be circular or have hexagonal packaging are illustrated in drawing. Special half-size tubes are often used along the edge of the detector to improve light collection efficiency and packing of the detector assembly.

Figure 3 The energy resolution of a detector system is given by the full width at half maximum of the collected energy spectrum divided by the energy of the photopeak times 100%. In the plot above, the energy of the photopeak is 140.5 keV, the full width half maximum of the energy spectrum is
13 keV, and energy resolution is
9.3%.

42

Single-Photon Radionuclide Imaging and SPECT

The main scintillator material for use in gamma cameras is NaI(Tl). NaI(Tl) was used in the original camera developed by Anger and is still used in almost all gamma cameras today. Some of the properties of NaI(Tl) are listed in Table 3. As can be seen in the table, NaI(Tl) has outstanding physical characteristics for the detection of 140.5 keV photons produced by 99m Tc. Most clinical gamma cameras use a 3/8 in. or 9.5 mm thick NaI(Tl) crystal detector. This provides 90% detection efficiency for 140.5 keV photons. The detection efficiency of different thicknesses of NaI(Tl) versus photon energy is plotted in Figure 4. As can be seen in the plot, NaI(Tl) is very efficient at detecting 140.5 keV photons; however, its efficiency drops dramatically for higher-energy photons, such as 511 keV photons as produced in PET. In addition, NaI(Tl) has a high photoelectric cross section at 140.5 keV. Therefore, the intrinsic positioning capability of the detector is not limited by Compton scattering within the crystal. In addition to its outstanding photon-detection characteristics at 140.5 keV, NaI(Tl) is relatively inexpensive to grow and can be grown into large area detectors (e.g., as large as 1 m in diameter). The other two important physical characteristics of NaI(Tl) are that it is very efficient at converting deposited energy into light and that it has a relatively fast decay time. The light conversion efficiency of NaI(Tl) translates into excellent energy resolution that is very important for human imaging because energy windowing is the main method used to discriminate good events from photons that have Compton scattered in the patient. Compton scattered events lose their spatial information and therefore are undesirable as they reduce image resolution and contrast. The typical energy resolution of a modern gamma camera is <10%. In addition to providing excellent Table 3

Physical properties of NaI(Tl) 3.67 g cm3 2.64 cm1
80% 40 K MeV1 230 ns 410 nm

Photopeak detection efficiency (%)

Density Attenuation coefficient (@140 keV) PE fraction Light output Decay time Wavelength

energy resolution, the high light output of NaI(Tl) leads to excellent intrinsic spatial resolution of the detectors while using relatively large 3 in. diameter PMTs. Light guides are used to spread the light from the relatively thin scintillator to a group of PMTs for position decoding. Modern-day gamma cameras have intrinsic spatial resolution of better than 4 mm FWHM for a 3/8 in. thick NaI(Tl) detector. The decay time of NaI(Tl) is important because the detectors are single, monolithic crystals and therefore in principle if multiple gamma photons strike the detector during the decay time of an event, pulse pileup will occur. In most cases, both piled-up photons will be lost due to energy discrimination; however, in some situations, a mispositioned event will be collected if the combined energies of the two photons fall within the photopeak energy window. Therefore, pulse pileup leads to both loss of counts in an image and also the potential of artifacts if there are a few very hot structures in an object being imaged. Vendors have implemented two main techniques to improve the count rate characteristics of gamma cameras. The first class of strategies is pulse clipping methods (Leo, 1987; Lewellen et al., 1989; Mankoff et al., 1989; Miyaoka et al., 1996). These include both analog and digital implementations of techniques to shorten the effective pulse duration. The second strategy is zone triggering and processing methods (Karp et al., 1998; Wong et al., 1998). Zone triggering effectively partitions a monolithic crystal into multiple pseudo discrete zones. This technique works because a vast majority of light produced from a given photon interaction is collected by 7–14 PMTs. Since most gamma camera detectors use 55–61 PMTs for any given two events, there is a reasonable probability that the light produced by each of the events will be viewed by a nonoverlapping set of PMTs. For most single-photon imaging studies, count rates are relatively moderate (e.g., <50 kcps) due to the use of physical collimation and count losses due to pileup are modest. For this reason, in general, gamma cameras currently do not correct for dead time losses. However, dead time corrections are important for any type of quantitative imaging procedure. Besides inorganic scintillators, room-temperature semiconductor detectors, such as cadmium zinc telluride (CZT) and

Nal(TI) thickness (cm) 100

5.08 2.54

1.27

10 0.64 1 0

100

200

300 400 500 g-Ray energy (keV)

600

700

Figure 4 Detection efficiency of different thickness NaI(Tl) crystals versus gamma photon energy. The dotted red lines represent 140.5 and 511 keV.

Single-Photon Radionuclide Imaging and SPECT

cadmium telluride (CdTe), have long been proposed for nuclear medicine imaging. Semiconductor detectors directly convert the energy signal to an electric signal. This conversion process is more efficient than the light conversion process associated with scintillator crystals. The main advantages that semiconductor detectors have over scintillators are extremely good energy resolution and they can be easily pixilated into very fine arrays. Thus, semiconductor detectors have the potential to provide both better energy resolution and spatial resolution than scintillation crystal cameras. The main drawback to these detectors is cost. The high cost is mainly associated with low yield in the manufacturing process. While process improvements have occurred, it is unlikely that semiconductor detectors will replace NaI(Tl) in the near future. Part of the reason for this, as will be explained in the succeeding text, is the fact that the NaI(Tl) detector is not the performance-limiting component of clinical gamma camera imaging systems. The component that limits general imaging performance is the collimator. With that said, there have recently been some organ-specific nuclear medicine imaging cameras built using semiconductor detectors. There are a few research CdTe detector scinti-mammo devices (Eisen et al., 2004; Yin et al., 2002), and there are also dedicated cardiac imaging cameras using semiconductor detectors. The key to these devices is that the volume of detector material required to make the cameras is much less than that of a standard dual-headed gamma camera. For scinti-mammography, the need for better image resolution and a very compact imaging detector offsets the increased cost of using a semiconductor detector. For the dedicated cardiac imaging cameras, the CZT detectors offer better intrinsic spatial resolution, better energy resolution, and a much more compact detector design (Ben-Haim et al., 2010; Buechel et al., 2010; Esteves et al., 2009; Garcia et al., 2011; Sharir et al., 2008).

1.02.2.2

Collimators

Collimators are what their names imply, a device to collimate photons so that one can know the line along which a detected photon originates. One characteristic of collimators is that they have a depth-dependent spatial response function. This and their efficiency are the two main design parameters for collimator optimization. There are four main types of collimators used with nuclear medicine imaging. They are illustrated in Figure 5. The different types of collimators are the parallel hole

43

collimator, the pinhole collimator, the converging hole collimator, and the diverging hole collimator. In addition to these types of collimator, other collimator designs that have been proposed but have not found wide use clinically are coded-aperture collimators (Accorsi et al., 2001; Barrett, 1972; Budinger and Gullberg, 1979; Rangarajan et al., 1998) and slit-slat collimators (Mahmood et al., 2010; Metzler et al., 2006; Wang et al., 2004). While collimators appear to be a very simple device, essentially a matrix of holes placed in front of the detector, they actually are of critical importance to the overall imaging characteristics of a gamma camera. In general, the collimator determines the effective spatial resolution in an image and also the detection efficiency of the camera. The geometric intrinsic spatial resolution versus distance from the front face of the collimator for the different style designs is illustrated in Figure 6(a). One of the key points to derive from this plot is that the spatial resolution of a collimator worsens with distance. Thus, one of the most important principles of nuclear medicine imaging is to bring the detectors as close to the patient as possible. The detection efficiency versus distance from the face of the collimator for the different style designs is plotted in Figure 6(b). The two most common collimator styles that are found in nuclear medicine clinics are parallel hole and pinhole collimators. Converging hole and diverging hole collimators, respectively, magnify and minify the object being imaged. Converging hole collimators can have application for neuroimaging or cardiac imaging where the object being imaged is significantly smaller than the imaging detector. Diverging hole collimators have not been used extensively, but would have application with high-resolution, small area, portable detectors where the compactness of the instrument is more critical than the resolution of the final image. Due to the vast majority of nuclear medicine imaging procedures being conducted with parallel hole and pinhole collimators, the rest of the discussion on collimators will focus on understanding these designs. For a parallel hole collimator, the most important design trade-off is spatial resolution versus detection efficiency. As can be seen in Figure 5, the intrinsic spatial resolution of a collimator is dependent upon the source distance from the collimator. Basically, the collimator resolution (Rcol) can be geometrically calculated from the septa spacing (d), the length of the collimator (l),

Figure 5 Different collimator designs: (a) parallel hole collimator, (b) diverging hole collimator, (c) converging hole collimator, and (d) pinhole collimator. Note that the converging and diverging collimators are often flipped versions of each other and have a focus spot above the detector for a converging hole collimator and behind the detector in the case of the diverging hole collimator.

44

Single-Photon Radionuclide Imaging and SPECT

20

250 Diverging 200 Parallel hole

12

8 Pinhole Converging

4

Relative geometric efficiency

System resolution (mm)

16

Converging

150 Parallel hole 100

50

Diverging Pinhole

(a)

0

0

(b)

5

10

0 15 20 0 5 Source-to-collimator distance (cm)

10

15

20

Figure 6 (a) Gamma camera collimator–detector spatial resolution versus source to collimator distance. Intrinsic spatial resolution of detector is equal to collimator–detector spatial resolution as distance equals 0. (b) Relative gamma camera geometric efficiency versus source to collimator distance. For parallel hole collimator, geometric efficiency is relatively independent of source to collimator distance.

Detector

Collimator septa

l

d

t

Figure 7 Diagram illustrating photon penetration in collimator.

and the distance the source is from the collimator (D). An example of a one-dimensional collimator design is illustrated in Figure 7. The geometric collimator resolution is given by eqn [1]:
 l þ 2D 2D ¼d 1þ Rcol ¼ d [1] l l The sensitivity of a parallel hole collimator is given by eqn [2] (Rangarajan et al., 1998): !
2 d d2 [2] g  K2 l ðd þ t Þ2 where K is a constant that depends upon the shape of the collimator holes (e.g.,
0.24 for round holes in a hexagonal array pattern and
0.26 for hexagonal holes in a hexagonal array; Cherry et al., 2003). As one can see from eqn [2], the collimator efficiency is independent of source distance from the collimator. This is because the efficiency is mostly related to the ratio of the open surface area of the collimator versus the total surface area of the collimator, which is independent of

source to collimator distance. As one examines eqns [1] and [2], one sees that to improve collimator spatial resolution, the septa hole diameter must decrease or the length of the collimator septa must increase. Both of these changes lead to a decrease in geometric efficiency. In fact, while spatial resolution varies linearly with septa hole diameter and less than linearly for collimator length, it varies as the square of both the septa diameter and collimator length. Most gamma camera manufacturers make two types of low-energy collimators for imaging 99m Tc, a low-energy general purpose (LEGP) and a low-energy high-resolution (LEHR) collimator. The third critical design parameter for parallel hole collimators is septa thickness (t). The septa thickness is designed to limit the amount of septal penetration from gamma photons impinging on the collimator at oblique angles. Collimator septal penetration is illustrated in Figure 7. As a general rule of thumb, septa penetration should be less than 5% (Rangarajan et al., 1998). To achieve this, one can calculate the minimum septa thickness to achieve this for a given collimator geometry using eqn [3]: t

6d=m 1  ð3=mÞ

[3]

where m is the linear attenuation coefficient of the collimator material. Since m depends upon the energy of the photons, the minimal thickness of the septa in a collimator is energydependent. Therefore, nuclear medicine instrumentation vendors produce both medium- and high-energy versions of their collimators for imaging radioisotopes such as 111In, 67Ga, and 131 I. In general, higher-energy collimators have longer and thicker septa, larger hole diameters, and lower geometric efficiency. In addition to understanding the basic numeric equations that determine collimator intrinsic spatial resolution and

Single-Photon Radionuclide Imaging and SPECT

Table 4 Type

LEGP LEHR CHR MEGP HEGP HEPH HEPH HEPH

45

Physical properties of collimators Hole shape

Hex Hex Hex Hex Hex Round Round Round

Size (mm)

1.40 1.22 2.03 3.4 3.81 3.0 4.0 5.0

Septa (mm)

0.180 0.152 0.152 0.86 1.73 25.4 25.4 25.4

Length (mm)

24.7 27 48 58.4 58.4 220.0 220.0 220.0

Construction

Foil Foil Foil Cast Cast Cast Cast Cast

Septa (%)

2.1 1.7 1.1 6.1 4.2 – – –

sensitivity, it is also important to have a feel of how they translate into imaging performance. Table 4 lists the specifications for a series of collimators produced by one manufacturer. The key numbers here are the intrinsic collimator resolution at 10 cm and the sensitivity of the collimator. One notices that the collimator resolution at 10 cm dominates the overall image resolution versus the intrinsic spatial resolution of the detector. However, the most striking characteristic of collimators is their efficiency. For a low-energy, high-resolution collimator, the sensitivity for 99mTc with a 20% window and a 9.5 mm thick NaI(Tl) crystal is <1 count per 10 000 decays. This extremely low collimator efficiency is the main physical-limiting property of single-photon imaging. Researchers have proposed many solutions to this problem. The simplest solution has been to develop systems with multiple detector heads. Dual- and triple-headed systems are commercially available with dualheaded systems being the mainstay for clinical imaging. There have also been many attempts to do single-photon imaging without the use of collimators. The main method is referred to as Compton camera imaging (Kamae et al., 1988; LeBlanc et al., 1998; Singh and Doria, 1983). The way a Compton camera works is that a detector with a very low photoelectric cross section but a very good Compton cross section and excellent energy and spatial resolution is placed between the object being imaged and a second high detection efficiency detector. The aim of the design is to have photons Compton scatter in the first detector and then get photoelectrically absorbed in the second detector, as illustrated in Figure 8. The energy of the original photon can be determined by summing the energy deposited in the Compton detector and the second imaging detector. It is very important that the Compton detector has very good energy and spatial resolution, because the location of the interaction and the energy deposited at the site in the Compton detector have a critical role in the determination of the origination of the photon. Using the formula for Compton kinematics, if one knows the amount of energy deposited in an interaction, one then knows the scattering angle of the photon. Since the photon is detected in the second detector, one can trace back the interaction location in the second detector to the interaction location of the first detector and that will define a cone from which the photon must have originated. This is different from imaging with a collimator, where the collimator defines a line from which the photon must have originated. Because a Compton camera identifies a

Penetration (keV)

140 140 140 300 364 –(4) –(4) –(4)

Sensitivity (cpm mCi1)

277 168 165 212 106 83 139 222

Spatial resolution system @ 0 cm

@ 10 cm

3.9 3.7 4.2 5.3 5.7 – – –

8.9 7.4 7.8 10.9 12.1 – – –

Standard detector

Compton detector

Figure 8 Diagrams illustrate operation of a Compton imaging camera. In the upper diagram, an incoming photon interacts in the Compton detector depositing a portion of its energy. The scattered photon is then detected in the standard detector. Based upon the energy deposited in the Compton detector, one can calculate the scattering angle between the interaction in the Compton detector and the interaction in the standard detector. Based on this information, a cone of response is defined as illustrated in the lower diagram.

cone of response versus a line of response, each individual event does not contain as much information; however, because the collimator has been eliminated, the sensitivity of a Compton camera can be orders of magnitude higher than a parallel hole collimator. The Compton camera is a clever idea; however, in practice, it has been difficult to implement mainly because an ideal material for the Compton detector has not been found. Silicon detectors have been used as well as CZT or CdTe; however, CZT and CdTe are expensive and silicon

46

Single-Photon Radionuclide Imaging and SPECT

detectors have not had the energy resolution and detection efficiency to make these systems outperform standard gamma cameras. Again, it has been difficult to find a material with a very high Compton cross section, a very low photoelectric cross section, and outstanding energy and intrinsic spatial resolution characteristics. The second most common collimator found in nuclear medicine clinics is the pinhole collimator. The pinhole collimator operates much like the aperture of a camera lens. The important imaging characteristic of the pinhole collimator is that it produces a magnified picture of the object being imaged on the detector assembly. This is illustrated in Figure 9. The amount of magnification is based upon the geometry of the object being imaged and its distance from the pinhole. Thus, images produced using pinhole collimation can have a much better intrinsic spatial resolution. For many imaging geometries, the intrinsic spatial resolution will be limited by the size of the pinhole. The main drawback to pinhole collimators is that they only work well for imaging small objects located relatively close to the pinhole. Therefore, they work very well for imaging the thyroid but are not effective for doing whole-body imaging. The two methods to improve the detection efficiency are to use multiple pinholes in the collimator and to use multiple detectors. Using multipinhole collimators also can help improve the size of the imaging field of view (Meng et al., 2003; Vogel et al., 1978; Wilson et al., 2000). Multipinhole collimators were originally proposed back in the 1970s along with coded-aperture techniques for decoding of the superimposed images on the detector; however, they have not made it into clinical practice. The main issue with codedaperture systems for nuclear medicine imaging is the violation of the far-field assumption that all the photons from the source are parallel. For nuclear medicine imaging, this geometry is not feasible and it leads to severe imaging restrictions or artifacts in

d

D

Figure 9 Example of magnification effect of a pinhole collimator. Magnification is equal to D/d.

the images. However, one application area where multipinhole imaging is being used is in small animal and preclinical imaging systems (Bastenhouw and Beekman, 2007; Beekman and van der Have, 2007; Meng et al., 2003; Peterson et al., 2003; Schramm et al., 2003; Vogel et al., 1978; Wilson et al., 2000). In addition to using multipinhole collimation, most of the commercial small animal single-photon imaging systems also use multiple detectors (Bastenhouw and Beekman, 2007; Forrer et al., 2006). A research human head imaging system using multiple detectors was constructed (Rogers et al., 1988); however, this design was never translated to a clinical imaging system.

1.02.2.3

Detector Positioning and Corrections

As stated in the preceding text, a gamma camera detector consists of a large-area scintillation crystal coupled to an array of PMTs via a light guide. An example of this arrangement is illustrated in Figure 2. Round or hexagonal PMTs are packed in a hexagonal pattern to optimize the light collection efficiency of the detector. Traditionally, the outputs from the individual PMTs were fed into a resistor network that weights and sums the signals. The weighting applied to each signal is associated with the spatial position of the PMT in the array structure. An example of how an event is positioned in one dimension is illustrated in Figure 10. In addition to a weighted summed signal, the individual PMT signals are summed to provide an estimate of the total amount of energy deposited in the crystal for a given detected event and to normalize the summed position signals. Equation [4] is used for positioning an event: X ðxi Ei Þ x^ ¼ X [4] Ei This positioning method goes back to the original work of Anger and is referred to as Anger positioning or Anger logic. In modern gamma cameras, most of the analog detector electronics have been replaced with digital electronics. Instead of using resistor weighting networks to sum PMT signals, the PMT signals are amplified and digitized for processing. Using standard Anger logic, event positioning is biased. This bias is related to the shape of the light response function, as illustrated in Figure 10. In general, 3-in. diameter PMTs are used in gamma cameras, whereas the NaI(Tl) crystal is 3/8 in. thick. A little guide is used to spread the light among the array of PMTs; however, even with the use of a light guide, a majority of the light from an event may be collected from the PMT right over where the photon was detected. Thus, a single PMT can have a disproportionate weight on the positioning of an event and the positioning of the event gets pulled toward the center of the PMT. If an event occurs at a location between two PMTs, a majority of the light may be shared between the two devices and the ratio of the light collected between the two PMT channels will be more sensitive to the spatial position of the detected event. Further, if an event occurs at the location between three PMTs, the ratio of light collected between the channels will be even more sensitive to changes in the photondetection position. Therefore, the intrinsic spatial resolution of a detector is best in the areas between PMTs and not over PMTs.

Single-Photon Radionuclide Imaging and SPECT

47

E Ù x=

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Figure 11 (a) Uncorrected uniform flood. (b) Uniform flood corrected for linearity but not energy. (c) Uniform flood with both energy and linearity correction applied.

To better visualize this, if one were to flood the detector with a uniform photon flux, the ‘flood’ image without any corrections for the nonlinear positioning characteristics of a gamma camera detector would look as illustrated in Figure 11(a). Events occurring over a PMT are pulled toward the center of

the PMT. This leads to a ‘pincushion’ distortion as illustrated in Figure 12(a). Therefore, linearity corrections are required to linearize the spatial positioning characteristics of a gamma camera detector. After linearity correction, the flood map looks like Figure 11(b).

48

Single-Photon Radionuclide Imaging and SPECT

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Figure 12 (a) Diagram illustrating the reason for nonlinear behavior of spatial positioning. When an event occurs directly over a PMT, a majority of the light is collected by that PMT. Using standard Anger positioning, events tend to get pulled toward the center of PMTs. When an event occurs at a location between two PMTs, the light tends to get shared evenly between the two PMTs. Since two þ PMTs each get a relatively large signal, the positioning algorithm is very sensitive to small spatial displacements occurring between the two sensors. This leads to the ‘barrel’ distortion illustrated in the drawing. (b) Diagram illustrating need for energy correction. When events happen right over a PMT, a higher percentage of the light produced by the event is collected than when an event occurs at the edges between a group of PMTs. Therefore, for the same amount of energy deposited, the light signal collected varies with position. The energy correction normalizes the energy signal so that the photopeak positions are aligned for all interaction positions in the detector.

Even after linearity correction, PMT tube patterns are visible in the uniform flood image. This is because gamma cameras also require energy corrections. There are two levels of energy corrections. First, the camera is tuned so that each of the PMTs is operating with the same gain. This is required because the gains of PMTs drift over time and there is also a wide variability of gain between devices. This type of gain calibration should be part of a daily quality control check. In addition to balancing the gains between individual PMTs, a second energy correction is required for optimal performance of a gamma camera. Again, as described earlier, when a photon interacts in the detector directly above a single PMT, that PMT receives a majority of the light produced. In addition, for that type of event, a higher percentage of the light produced in the crystal is collected than when an interaction event occurs between two or three PMT centers as illustrated in Figure 12(b). The reason for the differences in the fractional amount of light collected is that PMTs are housed in a glass structure, and therefore, the edges of the devices are inactive, so the light collection efficiency of the detector system is somewhat heterogeneous and

depends upon the interaction location of the detected event. In Figure 12(b), we also illustrate how the photopeak position in the energy histogram varies for different locations in the detector. The purpose of the energy corrections is to align all of the photopeaks to the same relative signal channel for the full detector. This allows a narrower energy window to be used during imaging, which in turn leads to the collection of less Compton scatter events. A thorough discussion of scatter events and how to correct for them is provided in Chapter 1.04. A final correction that is used by some vendors is a uniformity correction. This correction is an extrinsic correction meaning that it is taken with the collimators on. Therefore, it is collimator-dependent. This correction is used to correct for any small sensitivity differences due to the collimator and any small nonuniformities associated with the crystal. The uniformity correction is implemented by taking a long extrinsic flood image. From the high statistics extrinsic flood image, a multiplicative correction is calculated to make the flood uniform. It is important to note that since this is a multiplicative correction, it should only be used to correct for small

Single-Photon Radionuclide Imaging and SPECT

inconsistencies. Since the correction matrix is derived from a uniform flood source (i.e., the same phantom that is used for daily quality assurance), if it is used to correct for large errors in the linearity and/or energy corrections, the problems will not be picked up by the daily flood testing.

1.02.3

Acquisition Modes and Image Formation

There are a number of different data acquisition modes that are used with gamma camera imaging. These include static planar, planar whole-body, SPECT, gated, and dynamic imaging protocols. Gated and dynamic acquisition methods can be for either planar or SPECT imaging procedures; however, gated is usually used with cardiac SPECT procedures and most clinical dynamic imaging are associated with planar protocols. Static planar protocols acquire a two-dimensional projection image of the radiotracer distribution in the patient. A projection image is representative of the total activity along a line of response through the patient. An important userselected parameter is the number of picture elements (or pixels) in the created image. While gamma camera detectors are usually rectangular or circular, planar images are usually binned into square matrices. Standard matrix dimensions for planar images are 64 by 64, 128 by 128, and 256 by 256. Most systems allow planar images to be formed to matrix dimensions up to 1024 by 1024. The size of the pixel element is equal to the long axis of the useful imaging field of view divided by the number of bins. So a planar detector with X, Y dimensions of 54 cm by 40 cm, respectively, when binned into a 128 by 128 array will have pixel elements of 4.22 mm by 4.22 mm. Pixels are square and therefore pixels beyond the 40 cm field of view in Y will be set to zero. In general, most modern-day gamma camera detectors have an intrinsic spatial resolution of less than 4 mm full with at half maximum. Further, unlike some other imaging modalities (e.g., magnetic resonance imaging (MRI)) where the pixel size determines the image resolution, for gamma camera, imaging pixels can be smaller or larger than the intrinsic spatial resolution of the detector. If the pixel size is larger than the intrinsic spatial resolution, the pixel size will reduce image resolution. The positioning algorithms used allow for binning the data to arbitrarily small pixel dimensions. However, once the pixel dimension is less than about one-third of the intrinsic spatial resolution of the detector, going smaller will not improve image resolution. While using larger dimension images requires more storage, the main reason for restricting the pixel size in planar images is to limit the statistical noise in the image. Going to higher dimension image arrays means there are less counts per pixel and a corresponding increase in the relative noise in each pixel. As previously stated, radioactive decay is a random process that follows Poisson statistics, and therefore, for planar images, the noise in each pixel will also follow Poisson statistics. Each pixel in the projection image corresponds to a line of response through the patient. The value of the pixel is the integrated activity along the line of response reduced by the effects of attenuation. Planar images are formed from collected data and do not require any additional processing. Because of the effects of attenuation and depth-dependent spatial resolution, anterior and posterior views of the patient can produce very

49

different looking images. Besides anterior and posterior imaging, left anterior oblique (LAO) and right anterior oblique (RAO) views are often acquired for static imaging protocols. For static planar imaging, it is important to get the detector as close to the object of interest as possible. Whole-body planar imaging is usually associated with bone scans; however, it is also often used for whole-body counting for dosimetry purposes. Whole-body scans are similar to static planar protocols, only the patient is translated through the imaging field of view during the study. The scanning rate is usually
10 cm min1. For whole-body bone scans, both anterior and posterior views are acquired. As can be seen in Figure 13, there is significantly different information provided by the different views. The main reason for the differences is attenuation, although depth-dependent attenuation also contributes. Again, the key to obtaining good bone scans is to make sure the detectors are brought as close to the patient as possible. For single-headed gamma cameras, this can lead to long acquisition times. The advent of dual-headed gamma cameras is especially helpful for these protocols. In addition to standard static acquisition protocols, gated and dynamic imaging protocols can be supported. Gated acquisition protocols are used to capture images for processes that undergo periodic motion such as a beating heart or respiratory patterns. In a gated protocol, data are collected into a series of time bins that span the time cycle associated with the periodic motion being imaged. For cardiac imaging, an electrocardiogram (EKG) signal is used for the gating signal to the camera. Data are usually binned into 8 (to 16 bins), as illustrated in Figure 14. Gated acquisition only works when the periodic motion is regular; thus, it will not work well for an irregularly beating heart. An advantage of gated imaging is that it significantly reduces image blurring caused by motion and can be used to quantify physiological function, such as ventricular ejection fraction. The disadvantage is that the counts in each image are reduced by the number of gating bins and therefore each individual image is much noisier. Dynamic image acquisition mode allows one to visualize time-varying processes through imaging. An example of a clinical imaging procedure that uses dynamic image acquisition is renal flow (emptying) studies. For dynamic image acquisition, a series of images is collected over time. In general, the time binning has to be determined before the start of the imaging procedure. For dynamic imaging series, often a region of interest is drawn encompassing the structure of interest, and time– activity curves are plotted as shown in Figure 15 to analyze flow or uptake or emptying of an organ. In addition to planar imaging, nuclear medicine gamma cameras also support three-dimensional imaging via SPECT. SPECT images are produced by acquiring a number of projection views around the patient as illustrated in Figure 16. SPECT image formation is based on the principles of computed tomography. Once the angular projection data are collected, the image reconstruction methods are similar to that used for PET or CT. For image reconstruction, the SPECT angular projection data are formed into sinograms as illustrated in Figure 16. The axes of a two-dimensional sinogram are distance and angle. The angle refers to the view angle of the gamma camera detector as it traverses around the patient. The distance bin is

50

Single-Photon Radionuclide Imaging and SPECT

Figure 13 Whole-body bone scan. The main reasons for the significantly different looking images between the anterior and posterior views are the effects of attenuation and depth-dependent image resolution.

Figure 14 In this dynamic binning example, the EKG wave is divided into 8 equal time bins. Dynamic or gated imaging of the heart is used to reduce motion blurring of images and also to assess cardiac function, such as ventricular ejection fraction.

associated with pixel binning in the projection image. Each bin in the sinogram corresponds to a line of response in image space. A sinogram gets its name because a point source in image space maps out a sine wave in a sinogram. Once the data have been binned into a sinogram, there are two main methods by which images are reconstructed. The first method is an analytic method called filtered back projection.

There are a number of good references that give detailed explanations of filtered back projection (Brooks and DiChiro, 1975; Bruyant, 2002; Ter-Pogossian, 1977; Zeng, 2001). Here, we provide a brief overview of the technique. To understand filtered back projection, let us first look at the process of back projection. Imagine a point source object is first imaged with two view angles. When the projection data are back projected, it appears as in Figure 17(a). If the object is imaged from more view angles, after back projection, it will look like Figure 17(b), and if even more view angles are used, it will look like Figure 17 (c). Using more view angles removes the apparent streaks in the tails of the back projected image; however, even with continuous sampling of view angles, the back projection process leads to blurring of the point response from the fact that the data are projected along the full line of response since the source location along the line is not known. This blurring smoothes the image data by the inverse of the distance from the center of the point source. This is equivalent to convolving the point source by a 1/r function, where r is a radial distance. The solution to remove the image tails is to apply a filter to the

Single-Photon Radionuclide Imaging and SPECT

Age: 51.9 years Weight:(Ib): 240 Radiopharmaceutical: TcMAC3 Diuretic: Yes Diuretic dose (mg): 40 Diuretic time (min): 13

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Figure 15 Example of dynamic renal emptying study. Regions of interest are drawn over the kidney, collecting system, aorta, and bladder regions. Time–activity curves are plotted to determine kidney perfusion (first phase, 0–60 s), parenchymal transit (second phase, 1–5 min), and excretion (third phase, 5–30 min). Reproduced from Mettler FA and Guiberteau MJ (2006) Essentials of Nuclear Medicine Imaging, 5th edn. Philadelphia, PA: Saunders/Elsevier.

projection data to cancel the impact of the tails before back projection. The appropriate filter is the ramp filter. The ramp filter is illustrated in frequency and image space in Figure 18. Applying the ramp filter and back projecting provides the following images (Figure 19) in comparison to the back projection images (Figure 17). Even with filtered back projection, there are residual tailing artifacts if too few angular projections are used. In general, for clinical SPECT filter back projection, the number of angular projections that needs to be acquired can be approximated by N ¼ pD=ðdx=2Þ where D is the field of view size and dx is the resolution distance (Bieszk and Hawman, 1987; Brooks et al., 1978;

Budinger et al., 1977). Therefore, for a brain imaging study with an expected image resolution of
8 mm and a 128 by 128 matrix on an effective 400 mm field of view camera, the number of projection angles N should be N ¼ p  160=ð8=2Þ ¼
125 This is in line with what is normally used, that is, 128 views over 360 . The other main method for image reconstruction is iterative image reconstruction. Again, there are a number of excellent references for iterative image reconstruction (Gordon, 1974; Herbert and Leahy, 1989; Hudson and Larkin, 1994; Liang and Hart, 1988; Liang et al., 1992; Shepp and Vardi, 1982), and we will only go over the basic principles in this chapter. The basic

52

Single-Photon Radionuclide Imaging and SPECT

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Single-Photon Radionuclide Imaging and SPECT

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Figure 20 Block diagram illustrating the iterative image reconstruction process. An initial estimate is forward projected through a model of the imaging system. This model can include just the basic system geometry or could include all physical effects such as attenuation, scatter, and collimator– detector response. The projected data are then compared to the collected data. An error term is determined and the image is updated based on the differences between the measured and estimated projection data.

components of an iterative image reconstruction are illustrated in Figure 20. One begins with an initial image estimate. This estimate can be a uniform activity object or it can be a filtered back projected or back projected image from the collected projection data. The initial image estimate is then forward projected using a model of the imaging system. This model

can include collimator–detector response, attenuation, scatter, and basic system geometry. The projected data are then compared to the measured data. An error term is determined between the projection of the initial image estimate and the collected projection data. The initial image estimate is updated during a ‘back’ projection of the update term. The new image

Single-Photon Radionuclide Imaging and SPECT

estimate is then forward projected through the system model and the new projection data compared to the acquired data. This process continues until the error between the estimated and measured projection data has converged or the predefined number of iterations has been reached. In most instances, iterative image reconstructions are not run to convergence because the images become very noisy. Within the general framework of iterative image reconstruction, there are different statistical models that can be used (e.g., Poisson, scaled Poisson, and Gaussian) and also different objective functions defining the best image estimate (e.g., log-likelihood, weighted least square, and maximum a posteriori). An example of an ordered subset expectation maximization image reconstruction for a 2 2 pixel object is provided in Chapter 1.06 (PET). Traditionally, planar gamma camera and SPECT imaging have been qualitative not quantitative. The main reason for this has been difficulty in attenuation correction of the images, and as previously stated, for many nuclear medicine imaging procedures, absolute image quantitation is not necessary. One of the imaging applications that have required quantitative assessment of drug delivery has been in the area of radioimmunotherapy. In these studies, pretherapy doses are given to patients to determine uptake in critical organs. Therapy doses are usually extremely high and are limited by dose toxicity to critical organs. For these patients, quantitative imaging is critical that they receive optimum and safe treatments. The radioisotope that is often used for treatment is iodine-131. It is used because it emits both a beta particle for therapy and gamma photons for imaging. The main gamma that it emits is at 364 keV. Unfortunately, it also emits other higher-energy gammas with gammas at 637 and 722 keV being the most abundant. These high-energy photons significantly complicate trying to quantitate the uptake of 131I in these patients as they are highly penetrating through the collimator and make it into the 364 keV energy window via Compton scatter in the patient or the detector system. We will describe techniques that have been used to quantitate 131I uptake as a means to discuss what is needed to achieve quantitative nuclear medicine imaging. The largest physical effect that must be accounted for is attenuation. Attenuation in single-photon imaging is complicated by the fact that it is depth-dependent. In PET, attenuation is constant for any specific line through the patient. This is not the case for single-photon imaging. This concept is illustrated in Figure 21. The fact that attenuation is depth-dependent means that even if one has an accurate attenuation image of the patient being imaged and knows the location of the activity, it is nontrivial to do attenuation correction. The three main methods that have been used for attenuation correction are calculation of the geometric mean from two opposing views, Chang’s attenuation correction method and modeling attenuation in an iterative image reconstruction method. The geometric mean method can be used in the context of both planar and SPECT imaging but is more common for planar imaging. Chang’s method is for SPECT images. Modeling attenuation in an iterative image reconstruction again can work for both planar and SPECT data; however, it has usually been used in the context of SPECT iterative image reconstruction. Figure 22 illustrates how taking the geometric mean of the attenuation of a point source can be used for accurate

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Figure 22 The geometric mean has often been used as a simple method to correct for attenuation in single-photon imaging. The method works well for single point source in an object (i.e., top equation); however, the methodology breaks down when multiple point sources are in line with one another (i.e., bottom equation).

attenuation correction if the attenuation of the object being imaged is known. For a single point source object, this method works well. However, as soon as there is more than one object along the line of response, the geometric mean correction method breaks down. It can still be used to approximate the effects of attenuation; however, it is no longer quantitative. Nevertheless, because it is easy to use and because it can be used in the context of planar imaging, the geometric mean method for attenuation compensation is often used when doing radioimmunotherapy planning. The second method for attenuation correction is known as Chang’s algorithm (Chang, 1978). Chang’s algorithm works on SPECT image data. In order to implement the algorithm, the attenuation object must be known. In cases where an accurate attenuation map does not exist, one often assumes

Single-Photon Radionuclide Imaging and SPECT

that the object has uniform attenuation, with an attenuation coefficient equivalent to water. The basic algorithm is described in Figure 23. First, the average attenuation correction factor over all projection angles is calculated for each pixel in the image. Then each pixel in the initial nonattenuationcorrected image is multiplied by its average attenuation correction factor. The ‘attenuation’-corrected image is then forward projected including the effects of attenuation and the results compared to the collected data. The difference between the acquired data and the forward-projected data is then reconstructed and subtracted from the attenuation-corrected image estimate. This is the new estimate of the attenuation-corrected image. One can iterate on this process; however, usually, the iteration number is one. Chang’s method is a simple method that works using the principles of iterative image reconstruction; however, the only physical process that is included in the forward projection of the data is attenuation (i.e., it neglects resolution blurring and scatter). The third method for attenuation correction is to use iterative image reconstruction. The basic methodology of iterative image reconstruction was explained earlier in this chapter, so we will not repeat those details here. However, we will mention one interesting implementation of iterative image reconstruction for quantitative planar imaging (He and Frey, 2006). This method requires planar images and a three-dimensional attenuation map and has been applied to radioimmunotherapy dosimetry planning where the activity distribution in an organ of interest is assumed to be homogeneous. By making this assumption, the principles of iterative image reconstruction can be used for projection data limited to two angular bins. In addition to using the three-dimensional attenuation map for attenuation correction, it is also used to segment and determine the location of organs of interest. For many radioimmunotherapy drugs, there are only a few organs that take up or process the drug (i.e., liver, spleen, kidney, heart, lung, bone marrow). Besides these organs of interest, one can assume uniform distribution of activity in the rest of the body. If one assumes that activity is taken up homogeneously within each of the organs of interest, the number of regions of interest that must be determined for a given patient data set may only be four to five. If the regions of interest are treated as super voxels, the iterative image reconstruction becomes fairly straightforward even with only two projection angles. The key is only solving for a small number of activity concentration levels in the patient. Again, using the principles of iterative image reconstruction, one first provides an initial guess of the activity distribution. The three-dimensional activity distribution is forward projected through the three-dimensional attenuation

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Determine average ACF over all projection angles for each pixel Multiply initial image by ACFs to get initial guess of real distribution Forward project f(x,y) including atten and subtract from acq data

Reconstruct error image then f(x,y) = f(x,y)  ACF(x,y) + ferror(x,y)  ACF(x,y) subtract from initial image

Figure 23 Description of Chang’s attenuation correction algorithm.

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object. The forward-projected data are compared to the collected data. An error term is calculated and back projected to the image estimate. A new image estimate is formed and the process iterates. To improve the accuracy of this technique, the forward projector can include models for the collimator– detector response function and also scatter. In order to do attenuation correction, one must have an attenuation map or image. Traditional methods to measure attenuation are illustrated in Figure 24. The simplest method is to use a flood sheet source. Drawbacks to this method is that it must be done before the patient is injected with activity, and this method is very susceptible to accepting a lot of Compton scattered events, thereby underestimating the true attenuation factor. A method to reduce the collection of scattered events is to use a scanning line source. In this situation, one can effectively use collimation on both sides of the patient and it is even feasible to implement this method with activity in the patient. The drawback to this method is that it significantly lengthens an imaging procedure. To reduce the length of imaging time, multiple scanning line sources have been used with dualheaded systems, and for triple-headed systems, one head could be dedicated for just collecting data for attenuation correction as illustrated in Figure 24 (right). Note in this situation, a converging fan-beam collimator is used, so the transmission line source does not have to move relative to the detector during acquisition. While scanning line sources have been used clinically, they have not been deployed extensively because they require a lot of activity (e.g., on the order of 100 mCi) and extend the length of time of already long procedures. The introduction of SPECT/CT systems is changing the landscape for attenuation correction for SPECT, and these new systems along with increases in computer power to implement iterative image reconstruction are leading to the widespread use of attenuation correction in SPECT.

1.02.4

Imaging Procedures

As previously mentioned, while over 90% of clinical PET imaging is whole-body, oncological imaging studies, there are over 50 clinical gamma camera and SPECT imaging protocols that cover almost all organ systems in the body. A list of imaging protocols is provided in Table 5. In the succeeding text, we describe five of the most common nuclear medicine imaging procedures that also demonstrate the wide range of imaging applications covered by nuclear medicine.

1.02.4.1

Whole-Body Bone Scan

The whole-body bone scan is a routine nuclear medicine procedure. It can be used for a variety of diagnostic applications including malignant metastases staging, primary bone neoplasm evaluation, early skeletal inflammatory disease, undetermined skeletal pain etiology evaluation, painful total joint prosthesis evaluation, stress fracture, heterotopic ossification, reflex sympathetic dystrophy, elevated alkaline phosphatase of unknown etiology, bone graft viability, avascular necrosis, and pseudarthrosis and to determine osteoblastic distribution before palliative bone pain radiotherapy (Mettler and Guiberteau, 2006). The most commonly used radiopharmaceuticals

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Single-Photon Radionuclide Imaging and SPECT

Flood source, uniform flux

Triple head gamma camera with fixed line source

Scanning line source Figure 24 Traditional single-photon gamma camera attenuation correction methods. Upper left, flood source; lower left, scanning line source; and right, line source with dedicated detector head for transmission line source imaging. These methodologies are being replaced with SPECT/CT systems. Table 5

Nuclear medicine protocol list

Bone Cardiac Neuro Gastrointestinal

Lung Thyroid Renal Tumor and inflammation

Scintigraphy, flow, marrow, tomography Dual isotope, myoview and MIBI stress study, resting LV study, cardiac sarcoidosis, thallium REST and DELAY Brain cerebral blood flow, brain scan tomo, cerebral shunt, cisternography, CSF leak, Diamox brain scan, DaTscan Gastric empty, abdominal patency, cardiac shunt, esophageal function, gastro reflux, GI bleed, hemangioma, hepatic pump, hepatobiliary, hepatobiliary gallbladder ejection fraction, peritoneovenous shunt, liver spleen, Meckel’s diverticulum, salivary gland Lung perfusion, lung ventilation and perfusion Treatment of hyperthyroidism, thyroid scan, thyroid uptake, thyroid cancer survey Cystography, diuretic renography, renal bilateral, renal captopril (stenosis), renal DMSA, renal donor, renal transplant Gallium inflammation, gallium tumor, lymphangiography, lymphoscintigraphy for breast cancer, lymphoscintigraphy for melanoma, octreotide, parathyroid, ProstaScint, white blood cell scan

are technetium-labeled disphosphonates, most often methylene diphosphonate (99mTc MDP). The tracer is injected a minimum of 2.5 h before imaging. A typical imaging session will include an anterior and posterior whole-body sweep with the patient table traveling at a rate of 10 cm min1. Most studies will last about 20–23 min. In addition to the wholebody bone scan, static projection views are often collected. In the whole-body bone scan example shown in Figure 13, left and right lateral views of the head, neck, and upper shoulders were also collected. Other views often collected include the LAO and RAO. In the sample image, one can see significant differences between the anterior and posterior views of the patient. The two main reasons for the differences are the effects

of attenuation and the depth-dependent spatial resolution characteristics of the collimator. A key to high-resolution bone scan imaging is to get the detector as close to the patient as possible.

1.02.4.2

Brain

Nuclear medicine brain imaging can use both planar and SPECT techniques. Common diagnostic procedures include cerebral blood flow (brain death), evaluation of dementia, evaluation of vasospasm, suspected trauma, epilepsy, and cerebral vascular disease (Mettler and Guiberteau, 2006). Examples of neuro-SPECT imaging are shown in Figure 25. In this

Single-Photon Radionuclide Imaging and SPECT

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Figure 25 DaTscans showing patient with Parkinson’s disease (bottom panel) and patient negative for Parkinson’s disease (top panel).

Figure 26 Splash screen of stress–rest cardiac scan. An anterior-septal defect in the apex of the heart in the stress image largely goes away in the rest image indicative of ischemia. In addition, there is an anterior-septal defect that is seen in both the rest and stress images.

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example, an imaging agent called DaTscan is used to differentiate between Parkinsonian syndromes (PS) and essential tremor. The ‘comma’ image is for a patient without PS (upper panel), while the abnormal ‘period’ scan is for a patient with PS (lower panel). DaTscan is a radiopharmaceutical indicated for striatal dopamine transporter visualization. The data were collected using 128 view angles and a high-resolution, low-energy collimator. Because neuroimaging only utilizes a portion of the imaging area of the detector, a zoom factor is used to improve image resolution (by reducing voxel size) and more efficiently utilizing system memory. Just as in bone imaging, a key to achieving the best image spatial resolution is to make sure the detectors are as close to the patient’s head as possible.

exhibiting myocardial ischemia is presented in Figure 26. One can see an anterior-septal defect in the apex of the heart in the stress image that largely goes away in the rest image. In addition, there is an anterior-septal defect that is seen in both the rest and stress images. Gated acquisition procedures are often used to reduce motion blurring associated with a beating heart. Due to the number of cardiac nuclear medicine imaging procedures and the unique requirement of imaging a smaller fixed object within a patient, manufacturers have produced optimized cardiac-specific imaging systems (Ben-Haim et al., 2010; Buechel et al., 2010; Esteves et al., 2009; Garcia and Faber, 2009; Garcia et al., 2011; Maddahi et al., 2009; Sharir et al., 2008).

1.02.4.3

1.02.4.4

Cardiac

Along with bone scans, cardiac exams are among the most practiced nuclear medicine procedures. A common protocol is a stress–rest perfusion imaging procedure to look for infarction or ischemia. The study is conducted in two phases, a rest phase and a stress phase. The rest phase is used as a baseline to compare myocardial perfusion during stress. For the stress phase, the patient is usually asked to walk on a treadmill or pedal a stationary bicycle and the radiotracer is injected during exercise. For patients that cannot exercise, stress is induced pharmacologically. An example of a stress–rest protocol

Renal

An example of a dynamic nuclear medicine imaging protocol is a renogram. A renogram provides a time–activity curve of the uptake and excretion of a radiotracer by the kidneys. It is used to evaluate both renal function and if there are any bilateral differences between the kidneys. There is often a perfusion phase and a functional phase of the exam. A standard protocol is 80 one-second frames to visualize kidney perfusion and 120 twenty-second frames to evaluate function. As illustrated in Figure 15, regions of interest are drawn on the kidneys and time–activity curves are generated. A renogram is an example

Figure 27 These thyroid images had uptake values higher than normal. The image shows diffusely increased radiotracer uptake in the gland that is larger in size. The inferior portion of the left thyroid gland is mildly heterogeneous. The findings of the study are consistent with Graves’ disease.

Single-Photon Radionuclide Imaging and SPECT

of using imaging to quantify kidney function. Functional metrics that are often determined are time-to-peak activity, relative renal uptake at 2–3 min, half-time excretion, differential cortical retention at 15 min, and the 20 min-to-peak count ratio (Mettler and Guiberteau, 2006). The tracer that is usually used for renograms is 99mTc mercaptoacetyltriglycine or MAG3. Due to the posterior position of the kidneys in the body, renogram data are derived from the posterior view image (i.e., the anterior view image is not used).

1.02.4.5

Thyroid

Another organ routinely imaged in nuclear medicine is the thyroid. There are imaging procedures to access function and also to image for thyroid cancer. From the physics perspective, one unique aspect of thyroid imaging is that the organ is reasonably small and also located close to the surface of the neck. Therefore, thyroid imaging is done with a pinhole collimator. As previously described, images collected using a pinhole collimator can have better image resolution due to the magnification effect associated with using a pinhole. The drawbacks of using a pinhole collimator are a reduced imaging field of view and a limited imaging field depth. However, thyroid imaging is not susceptible to either of these limitations. Thyroid imaging is done using 99mTc-labeled pharmaceuticals (e.g., pertechnetate), 131I, or 123I. 131I is the radionuclide of choice for therapeutic procedures because it is a beta emitter (for therapy) and a gamma emitter for imaging. Sample nuclear medicine thyroid images are shown in Figure 27. The main characteristics used for interpretation of the images are size of the thyroids and whether there is uniform uptake between the left and right thyroids.

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