Computed Tomography for Radiation Treatment Planning

Motion Management in Positron Emission Tomography/Computed Tomography for Radiation Treatment Planning Valentino Bettinardi, MSc,*,† Maria Picchio, MD,*,† Nadia Di Muzio, MD,‡ and Maria Carla Gilardi, MSc*,†,§ Hybrid positron emission tomography (PET)/computed tomography (CT) scanners combine, in a unique gantry, 2 of the most important diagnostic imaging systems, a CT and a PET tomograph, enabling anatomical (CT) and functional (PET) studies to be performed in a single study session. Furthermore, as the 2 scanners use the same spatial coordinate system, the reconstructed CT and PET images are spatially co-registered, allowing an accurate localization of the functional signal over the corresponding anatomical structure. This peculiarity of the hybrid PET/CT system results in improved tumor characterization for oncological applications, and more recently, it was found to be also useful for target volume definition (TVD) and treatment planning in radiotherapy (RT) applications. In fact, the use of combined PET/CT information has been shown to improve the RT treatment plan when compared with that obtained by a CT alone. A limiting factor to the accuracy of TVD by PET/CT is organ and tumor motion, which is mainly due to patient respiration. In fact, respiratory motion has a degrading effect on PET/CT image quality, and this is also critical for TVD, as it can lead to possible tumor missing or undertreatment. Thus, the management of respiratory motion is becoming an increasingly essential component in RT treatment planning; indeed, it has been recognized that the use of personalized motion information can improve TVD and, consequently, permit increased tumor dosage while sparing surrounding healthy tissues and organs at risk. This review describes the methods used for motion management in PET/CT for radiation treatment planning. The article covers the following: (1) problems caused by organ and lesion motion owing to respiration, and the artifacts generated on CT, PET, and PET/CT images; (2) data acquisition and processing techniques used to manage respiratory motion in PET/CT studies; and (3) the use of personalized motion information for TVD and radiation treatment planning. Semin Nucl Med 42:289-307 © 2012 Elsevier Inc. All rights reserved.

H

ybrid positron emission tomography/computed tomography (PET/CT) imaging is nowadays well recognized as one of the most important diagnostic tool for oncological applications, particularly for staging and restaging the disease and for the assessment of therapy response. The possibility of *Department of Nuclear Medicine, Scientific Institute San Raffaele, Segrate, Milan, Italy. †IBFM-CNR, Institute for Molecular Bioimaging and Physiology, Segrate, Milan, Italy. ‡Department of Radiotherapy, Scientific Institute San Raffaele, Segrate, Milan, Italy. §Department of Surgical Sciences, University of Milano-Bicocca, TECNOMED Foundation, Monza, Italy. Address reprint requests to Valentino Bettinardi, MSc, Department of Nuclear Medicine, Scientific Institute San Raffaele Hospital, Via Olgettina 60, 20132 Milan, Italy. E-mail: [email protected]

0001-2998/12/$-see front matter © 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1053/j.semnuclmed.2012.04.001

performing both anatomical (CT) and functional (PET) studies in a single study session, without moving the patient from the scanner bed, has significantly contributed to a more accurate localization and characterization of the tumor.1-3 Furthermore, hybrid PET/CT has also been demonstrated to be valuable in improving target volume definition (TVD) in radiotherapy (RT) treatment planning, combining anatomical and functional information, provided by CT and PET, respectively, and taking advantages of their complementarity.4,5 Currently, the most common PET agent used for diagnostic and RT applications is 2-deoxy-2-[fluorine-18]fluoroD-glucose (FDG), a marker for tissue glucose metabolic activity. The utility of FDG-PET for TVD has been demonstrated by the fact that it can modify the RT treatment plan, compared with that of CT alone, either by reducing the dose distribution volume, in case the PET tracer uptake area is 289

290 smaller than the structural CT abnormal region, or by enlarging the dose distribution volume to PET hypermetabolic areas that appear normal on CT.6-8 Alternatively to FDG, other tracers, specific of metabolism (eg, 11C-choline), proliferation (eg, 18F-fluorothymidine), hypoxia (eg, 64Cu-diacetyl-bis [N4-methylthiosemicarbazone], 18F-fluoromisonidazole), apoptosis (eg, 2-(5-fluoro-pentyl)-2-methyl-malonic acid), gene expression (eg, 11C-PD153035 for epidermal growth factor receptors), and so forth, are being evaluated for their potential use in RT.9,10 By using different PET tracers as markers of specific pathways, it is possible to perform an accurate characterization of the tumor, mapped as a heterogeneous mixture of cell populations, which provides detailed information for a precise planning of the dose distribution for RT treatments. To take full advantage of such an accurate image of the tumor, radiation treatment systems require high precision in tailoring the dose distribution, according to the tumor shape and characteristics, and to spare surrounding healthy tissues from unnecessary radiation. In this respect, enormous progress has been made in the technological development of innovative radiation therapy systems, from 3-dimensional conformal radiotherapy (3D-CRT) to intensitymodulated radiotherapy (IMRT).11 In fact, 3D-CRT allows precise conformal radiation plans to be delivered, but with the constraint of a uniform beam strength. Conversely, IMRT allows a nonuniform radiation dose distribution to be delivered within the target volume, by modulating the intensity of the beam during the treatment, the beam composition being many small “beamlets” of different intensity. Furthermore, by generating steep dose gradients, IMRT can make the dose conform to complex target shapes, avoiding normal tissues to a much greater degree than with 3D-CRT. This leads to improvement in the therapeutic index by maximizing tumor coverage and sparing normal tissues. Based on the IMRT principle, several radiation therapy systems that adopt different approaches for dose delivery are now available (eg, TomoTherapy, RapidArc, and TrueBeam). As a consequence of the great potentialities of these RT systems, the trend in radiation treatment today is to reduce the irradiated volume and meanwhile increase the dose to the tumor, taking advantage of accurate target definition and precise dose deposition, guided by current imaging systems. In this scenario, a limiting factor for an accurate TVD by PET/CT is represented by physiological patient movement, well recognized as one of the most important artifact sources in diagnostic imaging, particularly in the thorax and abdomen. In fact, even when the patient is well positioned and immobilized on the scanner bed, heartbeat and breathing cause continuous movements of the internal organs.12,13 Heartbeat has a local effect on organs within a spatial range of approximately 2-3 cm, whereas the patient’s breathing leads to marked displacement of most of the internal organs, from the apical region of the lungs down to the abdominal organs (eg, liver, spleen, kidneys, stomach).14,15 Internal organ movement has a degrading effect on image quality in terms of spatial resolution and contrast, and can thus be critical in the definition of the target volume for RT planning. To account for the movement, as well as for positioning/repositioning setup errors, it is standard procedure to enlarge the volume to

V. Bettinardi et al be treated, by adding safety margins to the edges of the tumor as appearing on the diagnostic images used for TVD. However, a difficult and critical issue in the treatment planning design is just how large these margins should be, particularly if there is no available direct knowledge of organ and tumor motion. In fact, a conservative strategy requires the definition of large margins to ensure the encompassing of the whole volume of tumor motion. However, overestimated margins can result in an overdose to healthy tissues and organs at risk lying near the tumor, as well as in an underdose to the tumor. Conversely, if a more “aggressive” strategy is adopted using small margins with also the aim to increase the dose to the tumor, this could result in a higher probability of part of the tumor being missed, and thus in possible treatment failure. Finally, to further complicate the definition of the safety margins with respect to the organ motion, consideration must be given to the following: (1) organs characteristically have complex movements, including translation, rotation, and deformation; (2) organ movement differs from organ to organ; and (3) organ movement varies among patients.16 From the aforementioned considerations, it is clear that knowledge of organ and lesion motion is an important factor in compensating for effects seen on diagnostic images, as well as for an accurate definition of safety margins in RT treatment planning. Focusing on respiration and its effects in RT, much effort has been made over the years to investigate the type and magnitude of the motion due to breathing for organs such as lungs, liver, pancreas, adrenal glands, and kidneys. For this purpose, different imaging systems have been used (eg, fluoroscopy, ultrasonography, magnetic resonance imaging, and CT). Furthermore, as the evaluation of organ and lesion motion is usually not an easy task, the investigations were performed by tracking the movement of direct and indirect targets, which are assumed to correlate with the motion of the tumor (eg, the tumor itself, the host organ, radiographic fiducial markers embedded in or near the tumor, uptake of a radioactive tracer in the tumor, and even surrogate organs, such as the diaphragm).16 With regard to lung tumors, the magnitude of the motion depends on the dimension of the tumor (smaller tumor, high mobility) and on its location (mobility increases on passing from upper, to middle, down to lower lobe).16,17 Motion direction is mostly craniocaudal (CC), with a motion magnitude ranging from a few millimeters in the upper lobe to up to 1-3 cm in the lower lobe.14-16 Liver is also severely affected by respiratory motion: as in the case of lung tumors, motion mainly occurs in the CC direction, where displacements of 1.5-2.5 cm have been measured even during shallow breathing.16,18-20 Abdominal organs present complex motion.21,22 For example, pancreas has been observed to have not only a periodic displacement in the CC direction of approximately 1-2 cm, but also organ deformation. In addition to the CC displacement, respiratory motion is characterized by smaller anteroposterior and left–right movements, which, however, are usually ⬍1 cm.16 Besides this general information about organ motion, a common finding in most of the previous work was the high intra- and interpatient variability, which has led to the con-

Motion management in PET/CT

291

Figure 1 CT images: Typical artifacts (white arrows) due to respiratory organ motion. Note how the respiratory motion can generate severe discontinuity in the liver anatomy (left image), which can result in a complete split of the organ into 2 pieces (right image).

clusion that respiratory organ motion should ideally be assessed for each patient, particularly in the case of RT applications. A better delineation of the target volume and the use of personalized motion information could, in fact, lead to a significant reduction in the volume to be irradiated (smaller safety margins), thus lowering the risk of treatment complications. Furthermore, more accurate tumor characterization and definition could allow a higher dose of radiation to be delivered to the tumor, thus leading to better tumor control. As a result of the aforementioned considerations, it is nowadays well accepted by the scientific community that the use of personalized motion information for TVD can improve radiation treatment results. Thus, the management of respiratory motion is becoming an increasingly essential component in the treatment planning process. This review aims at describing the approaches adopted for motion management in PET/CT for radiation treatment planning purposes. The present article covers the following: (1) the problems caused by organ and lesion motion owing to respiration, together with the artifacts generated on CT, PET, and PET/CT images; (2) the acquisition and data processing techniques used to manage respiratory motion in PET/CT studies; and (3) the way to use personalized motion information for TVD and radiation treatment planning purposes.

Image Artifacts Due to Respiratory Motion CT Artifacts Organ motion can generate different types of imaging artifacts, depending on the type of CT acquisition technique. In fact, Chen et al23 analyzed the distortion generated in the helical scanning of moving objects, and reported that such distortion depends on the relative movement of the object with respect to the CT scanning direction, that is, the object in the reconstructed images is shortened when the lesion moves toward the imaging plane and is lengthened when it

moves away from the advancing imaging plane. Thus, motion artifacts are generated as a consequence of the object’s “in and out” motion within the CT slice window during data acquisition, while CT reconstruction algorithms assume invariance of the imaged anatomy.24 The results of such in-and-out motion are distortions and discontinuities (eg, sawtooth, stair-step artifacts) of the scanned organ that, on the reconstructed images, appear in the most severe cases as split into 2 or even more parts (Fig. 1). When such artifacts are present in the diagnostic images used for TVD, they can cause severe distortion of the target volume and an incorrect positioning of its volumetric information. If inadequate safety margins are used to account for organ and lesion motion, this target misrepresentation could determine an underirradiation of the tumor and/or an unnecessary irradiation of normal structures.23 To avoid such artifacts, most diagnostic radiological protocols are performed with the breath held. Nowadays, this is feasible because the rotational and translational speed of modern CT systems is so fast that it is possible to scan wide axial portions of the patient’s body in a few seconds (eg, 10-30 s). However, in the case of clinical CT protocols for TVD and treatment planning, the acquisitions are usually performed in free-breathing mode to reproduce the same operating condition in which the patient will be treated during RT sessions.

PET and PET/CT Artifacts The respiratory artifacts seen in PET are connected to the long length of time required to complete a PET whole-body study (2-3 min/bed position ⫻ 6-7 bed positions), and to the patient’s free breathing during the scan. As a result of organ and lesion motion, the radioactive events from a small focal lesion appear spread throughout the volume of motion, resulting in an underestimation of the true tracer uptake in the lesion and in an overestimation of its volume (Fig. 2). In the case of hybrid PET/CT studies, in addition to such a smearing effect on the PET images, respiratory motion could

V. Bettinardi et al

292

This temporal mismatch can cause a spatial misalignment between PET and CT data. As in hybrid PET/CT systems CT images are used for the attenuation correction of the PET data, such a spatial mismatch can produce artifacts on the PET images.25-27 In this respect, much effort has been dedicated to evaluating a breathing protocol that allows PET/CT mismatches to be avoided, or at least to be reduced, particularly at the diaphragmatic level, where respiration-induced curvilinear artifacts are observed more often. Among the several proposed breathing protocols (eg, free breathing, shallow breathing, quiet breathing, held breath at the end of normal expiration, and held breath at mid of expiration), the optimal CT protocol seems to be that combining quiet breathing for most part of a whole-body scan, with held breath at the end of expiration when the CT scan is running over the diaphragmatic region. On the PET side, this CT breathing protocol should be matched with quiet free breathing to be performed throughout the time of the study.28,29 Figure 2 PET images and radioactivity profiles of a spherical target (diameter: 1 cm). Top: (A) Static image (no motion). (B) Image of the sphere when moving periodically with a displacement of 1 cm. (C) Image of the sphere when moving periodically with a displacement of 2 cm. Note how the radioactivity distribution of the moving sphere appears spread compared with that of the static image. Bottom: Profiles drawn through the radioactivity distributions of images (A), (B), and (C). Note how the radioactivity profiles of the moving spheres are lower and wider, as an effect of motion (spatial smearing of the radioactivity), than that of the stationary sphere.

also be responsible for a temporal and a spatial mismatch between CT and PET data (Fig. 3). In fact, as a result of the long scan time, PET images show a lesion as a blurred radioactivity distribution averaged over several breathing cycles (eg, 30-45). Conversely, multislice CT scanners allow wholebody studies to be performed in a few seconds (eg, 10-30 s), thus freezing, in the CT images, the anatomy of the patient at a specific moment of the respiratory cycle.

PET/CT: Tools for RT Applications and Respiratory Motion Detection Although the main goal in diagnostic PET/CT applications is to compensate for artifacts due to organ and lesion motion, so as to improve image quality and quantitative accuracy, when PET/CT images are used for TVD and treatment planning, it is also important to know the motion (trajectory) of the target and that of its surrounding organs. In fact, such information can be used to personalize the definition of the treatment plan, with the aim of delivering a higher radiation dose to the tumor while sparing healthy tissues and organs. Nowadays, motion management in PET/CT for radiation treatment planning can be achieved by 2 approaches: ●

Respiratory gating (RG) 4D-PET/CT acquisition techniques, which consist in the synchronization of the data acquisition systems (CT and PET) to the patient’s respi-

Figure 3 Fused PET/CT images of a lung tumor— coronal (left) and sagittal (right) views: Typical misalignment between CT and PET images, caused by the respiratory motion.

Motion management in PET/CT

●

ration, through the use of a real-time respiratory monitoring system.30-32 Breath-hold (BH) techniques, in which the patient is asked to hold his/her breath, with the aim to achieve tumor immobilization: (1) at a specific moment of the breathing cycle (eg, end inspiration, end expiration, mid inspiration, mid expiration, etc), (2) at a predefined breath level, and (3) for a predefined duration (eg, 10 s, 20 s, or as long as possible).33-37

Both approaches allow obtaining motion-free images and avoiding spatial mismatches between CT and PET data. RG 4D-PET/CT techniques also allow determining the magnitude and trajectory of the motion of the tumor, as well as of the surrounding organs. The following sections describe system characteristics and tools required to perform an RG 4D-PET/CT or a BH study for radiation treatment planning purposes.

293 the importance of maintaining the position and of avoiding any movement, and should fully understand the importance of his/her collaboration in this task.

Special Positioning and Immobilization Devices for Organ Motion Reduction Common positioning and immobilization devices used in RT allow the immobilization of the patient’s body, but usually have no effect on the motion of the internal organs. For this, special positioning and immobilization devices that use a compression system, usually applied at the abdominal level, are used for RT applications. With these devices, patient immobilization and a reduction of internal organ motion can be achieved. The aim of abdominal compression systems is, in fact, to reduce diaphragmatic motion, and thus breathinginduced motion of the tumor.42-44

External Lasers Hybrid PET/CT Systems An RG 4D-PET/CT study for RT applications should be performed by using an integrated PET/CT system with a wide bore (ⱖ70 cm), to accommodate the positioning and immobilization devices used in RT. Currently, big-bore (85 cm) CT and PET/CT systems are available, allowing scanning of extremely large patients and meeting the requirements of radiation oncology applications (flexibility in patient positioning and immobilization, and use of special devices).

Flat Table A rigid flat table must be used to ensure a spatial reference flat surface, guaranteeing accurate and reproducible patient positioning in both PET/CT study and RT treatment sessions. The flat table can be locked in place over the PET/CT and RT scanning bed. It is marked on both sides with position numerical indicators, allowing different immobilization devices to be fixed in specific codified and recordable positions.38,39

Positioning and Immobilization Devices The same positioning and immobilization device must be used during the PET/CT study and the radiation treatment sessions, to allow the accurate positioning and repositioning of the patient. The use of these devices guarantees the following: (1) a certain level of immobilization, which is a mandatory condition for the quality of the PET/CT study and a correct dose delivery in RT; (2) consistency and reproducibility of the patient position, important for an accurate dose delivery coherent with the treatment plan. Positioning and immobilization devices change depending on the anatomical district to be treated and are often personalized to the patient (eg, wing board, combi-fix, breast board, belly board, and vacuum pillows).38-41 In this respect, the operator appointed to prepare and position the patient for treatment must always pay particular attention to avoid conditions that cause discomfort or pain to the patient. In fact, if in a suffering situation, the patient, in searching for a less painful and more comfortable position, might be unable to maintain the required immobility. The patient should also be informed of

During an RT simulation session, tattoos are marked on the patient’s skin to allow subsequent alignment of the patient to the isocenter of the RT system. The same tattoos are used to guarantee alignment consistency of PET/CT. The final (fine) positioning of the patient in PET/CT is thus performed, aligning the patient, using the tattoos, by means of a set of external laser cross beams defining the isocenter of the PET/CT system. Two lasers, usually fixed on the walls, provide lateral lights to align transaxial and coronal planes, whereas the third one, usually mounted on the ceiling, allows the alignment of the sagittal plane.

Respiratory Monitoring Systems As soon as the patient is properly positioned and immobilized, a respiratory monitoring system (RMS) is switched “ON” to synchronize the patient’s respiratory cycle with the (CT–PET) acquisition system in RG 4D studies. Several devices have been proposed for use as RMS, for example, optoelectronic systems, pressure sensors, spirometry systems, strain-gauge belts, temperature sensors, and laser sensors; these differ in the sensors used and in the detected physical effects associated with breathing motion. Most of these devices are based on the detection of an external surrogate signal of the patient’s respiration (eg, abdominal displacement, chest expansion, etc), relying on the assumption of a good correlation between the internal tumor and the external body motions induced by respiration.31,45 Despite the high number of RMS described in the literature, or available as system prototypes, only a few have been approved for use in the clinical environment of the Nuclear Medicine Department (synchronization to PET/CT scanners) and Radiation Oncology Department (synchronization to the linear accelerator’s delivery system, to control the ON/OFF beam state during RT treatment sessions). Two of the most used RMS, which can be interfaced to both diagnostic PET/CT and RT systems, are the RPM (Real Time Position Management by Varian Medical Systems, Palo Alto, CA) and the AZ-733V system (Anzai MEDICAL Shinagawa, Tokyo).46,47

V. Bettinardi et al

294

Figure 4 Respiratory Monitoring Systems Top: Components of the RPM system. Infrared video camera and plastic box (left); patient in place with the RPM box positioned on his abdomen (right). Bottom: Components of the AZ-733V system. PC, analog to digital converter (Wave Deck), pressure sensors, and belt (left). Belt in place over the abdomen of the patient (right).

RPM (Fig. 4) is an optoelectronic device based on an infrared video camera, which can be firmly attached to the end of the PET/CT flat table. The infrared video camera illuminates a light plastic box, positioned on the abdomen of the patient. On the surface of the plastic box, facing the video camera, there are 2 infrared reflective dots. During patient respiration, the box moves up and down, following the motion of the abdomen. The video camera detects in real time the light reflected by the 2 infrared reflective dots, generating a monodimensional signal, as surrogate of the patient’s respiratory signal. The signal is then processed and presented in real time, as a time curve, on the display screen of a personal computer. Differently from the RPM, the AZ-733V system is based on the activation of a pressure sensor, inserted into a belt fastened around the chest or the abdomen of the patient (Fig. 4). The system detects pressure changes caused by patient respiration, and as for the RPM, the signal is converted and displayed in real time on the screen of a personal computer as the patient’s respiratory curve. Similar to most of the other RMS, both RPM and AZ-733V can also be used to monitor the respiratory conditions of the patient during BH. In such cases, the RMS is used to ensure that the patient is performing the BH following the requested conditions (eg, at the end inspiration, for at least 20 s). Furthermore, by using the RMS, it is possible to verify the reproducibility of each BH when more than one has to be performed by the patient during the study. Also in case of BH, it is assumed that a good correlation exists between the re-

spiratory signal, produced by the sensor of the RMS (eg, RPM and AZ-733V), and the internal tumor position. Finally, it is important to note that when an RMS based on an external sensor (eg, RPM or AZ733V) is used in a PET/CT simulation session, the position of the sensor on the patient must be recorded (usually marking its position on the patient’s skin), to be reproduced in the following RT sessions. This is an important factor that must be taken into account to reproduce the same breathing pattern (or the same BH), assuming the same respiratory condition by the patient. Correlation Between External Surrogate of the Respiratory Signal and Internal Tumor Motion A critical issue for RMS based on an external surrogate of the patient’s breathing signal is how well such a surrogate signal correlates with the internal motion of the tumor. This is an important point for the use of such RMS, as they rely on the assumption that the internal tumor motion is well correlated with the external respiratory-induced motion and that this correlation is constant in time.48 In this regard, several studies have evaluated such internal– external correlations. Some, using fluoroscopic or 4D-CT images, evaluated the correlation between radio-opaque fiducial clips implanted in or near the tumor and external markers positioned on the patient’s skin in the abdominal region. The results of these studies have shown that, in general, tumor motion correlates well with the external markers, particularly for the CC motion direction and during the expiration phase.49,50 However, Ionascu et al48 reported rela-

Motion management in PET/CT

295

tively large underlying tumor motion compared with external marker motion, as well as tumor position variation for a given marker position. Based on these results, the authors recommended caution in the use of motion information, particularly in defining treatment margins when relying only on external markers’ information. A similar recommendation has been recently suggested by Hunjan et al,51 who evaluated, in lung cancer studies, the correlation between external fiducial positions and internal tumor positions during BH CT. The results of this work showed that external surrogates for tumor position are not an accurate metric of BH accuracy for lung cancer patients. Thus, the authors suggested that care should be taken when using such an approach for TVD and RT treatment planning because an incorrect internal margin could be generated.

RG 4D-PET/CT Protocols For radiation treatment planning purposes, an RG 4DPET/CT study is usually performed, focusing on tumor location, to cover a portion of the body corresponding to a 1 or 2 PET axial field of views (approximately 15-30 cm). The RG 4D-PET/CT study can be acquired as a specific examination, or it can be integrated as a part of a whole-body PET/CT study (from head to lower limbs), if the patient is able to tolerate immobilization for the time required for a whole-body study.38 RG 4D-PET/CT acquisition techniques that can take the motion of respiratory organs into account can be implemented according to 2 different approaches: prospective or retrospective gating.

RG 4D-CT Acquisition Techniques When CT gating is performed in the prospective mode (axial step and shoot or helical), data are recorded in a specific time window (gate or phase) of the patient’s respiratory cycle (eg, end inspiration, end expiration); 2 triggers turn the x-ray tube ON and OFF and also set the start and stop of data acquisition. The 2 triggers are activated when the patient’s breathing curve crosses a selected threshold, establishing the gating window (respiratory phase) during which the CT data are acquired (Fig. 5A). In the CT image, the organs and tumor appear frozen at a specific moment of the patient’s breathing cycle, and the shorter the time window, the less the motion artifacts appear in the image. In the case of gated treatment, the same time window is selected to deliver the dose to the target. The advantages of a prospective 4D-CT technique are as follows: ● ● ●

●

Nearly full compensation for motion artifacts; An accurate representation of the target volume; A relatively low dose delivered to the patient, as the x-ray beam is ON for only a fraction of the full breathing cycle; Direct CT image generation; no postreconstruction processing is needed. Indeed, once reconstructed, the CT images directly represent the patient’s anatomy in the respiratory phase selected for data acquisition (eg, end expiration).

Figure 5 (A) Schematic representation of a prospective (axial) 4D-CT scan. Note how data acquisition is performed only during a specific time window (in this case, end of the expiration phase). (B) Schematic representation of a retrospective (axial) 4D-CT scan. Note how data acquisition is performed during the whole breathing cycle for each axial position.

The major disadvantage of 4D-CT imaging is that it does not provide information about the motion of the tumor. When CT gating is performed in the retrospective mode (axial cine or helical), CT data are acquired throughout the patient’s whole respiratory cycle (Fig. 5B). During an axial cine CT scan, data are recorded continuously, over the same axial position for a time corresponding to the average duration of the patient’s breathing cycle (period). Usually 0.5 or 1 seconds are added to the calculated mean period to account for possible variations (longer breathing cycles) that could occur during the scan. When retrospective CT gating is performed in the helical acquisition mode, the selection of correct acquisition parameters (translation speed, gantry rotation time, pitch factor) is particularly important, to guarantee that each portion of the body is imaged throughout the whole breathing cycle (complete sampling) and no anatomical slice is missed in the final reconstructed volume.52 Retrospectively RG 4D-CT protocols can be applied in a relatively straightforward way in case of studies not requiring

V. Bettinardi et al

296 the use of contrast agent. In fact, in this case, the only specific acquisition parameter that needs to be set is the duration of the patient’s breathing cycle (period), as previously described. Conversely, when a contrast agent is needed to enhance the visualization of the tumor (eg, liver, pancreas), the following parameters have to be considered: (1) the amount of contrast agent and the time of administration, (2) the CT scan time, and (3) the peak time of contrast enhancement curve, which is dependent on the organ and tumor under study. Knowledge of such information allows the operator to set the acquisition parameters to obtain the highest enhancement with respect to the surrounding tissues.53,54 The advantages of a retrospective RG 4D-CT study are as follows: ● ●

●

Nearly complete compensation for motion artifacts; Accurate representation of the target volume, for each single 4D-CT phase obtained after processing of the RG 4D-CT data (see section: RG 4D-PET/CT: data processing techniques); Knowledge of the movement (trajectory) of the tumor and of the surrounding organs.

The major disadvantage of a retrospective RG 4D-CT scan is the higher radiation dose delivered to the patient, compared with that of a conventional helical CT scan. This is because of the longer scan time needed to perform a RG 4D-CT study, which, as previously described, depends on the patient’s respiratory cycle. In this respect, Nehmeh et al55 reported a dose 4 times higher than that delivered during a conventional helical CT scan using the same acquisition parameters. Whatever the acquisition mode used for an RG 4D-CT study (prospective/retrospective, axial/helical), the rotation speed of the x-ray tube has to be fast (eg, 0.5 s/rot), so that the motion of the target can be adequately sampled both temporally and spatially.

Slow CT Acquisition Technique Before the advent of the RG 4D-CT techniques, slow CT scans were used to capture the volume of space encompassing tumor motion due to the patient’s respiration in CT lung studies. In fact, a slow CT scan consists in a conventional axial (step and shoot) acquisition protocol characterized by slow rotational speed (ie, 4 s/rot).56 The rationale behind a slow CT scan is that, as a consequence of the slow rotation of the x-ray tube, the CT projections are formed, with data recorded when the tumor is in different positions during its motion trajectory. As a result of this inconsistent data acquisition, reconstructed CT images show an image of the tumor spread over the volume of motion. In this respect, it is noteworthy that the inconsistency of the acquired data can generate artifacts (distortions) in the reconstructed CT images, resulting in an incorrect evaluation of the target volume and of its spatial position. Furthermore, as the tumor is imaged while moving, its edges are blurred, and this loss of resolution and contrast could result in an underrepresentation of the volume of motion.57-59 To overcome such limitations, some authors

suggested repeating the slow CT scans twice or more times over the same axial positions.60,61 Notwithstanding such known limitations, slow CT imaging has been successfully used for TVD and treatment planning. In fact, different authors have reported that target volumes defined on slow CT images were larger and more reproducible than those derived from conventional fast helical CT scans, indicating that slow CT imaging allows: (1) a better capture of tumor movement, and (2) a reduction of the intra- and interoperator variability in the TVD. Furthermore, the use of personalized motion information, like that obtained by a slow CT scan, also enabled the application of tighter margins compared with those defined by using a conventional approach.60,62,63

RG 4D-PET Acquisition Techniques As for RG 4D-CT, an RG 4D-PET study can be performed in both prospective and retrospective modes. However, the retrospective method is currently the only method used in clinical practice. RG 4D-PET studies are generally acquired in 3D list mode and synchronized to the patient’s respiratory cycle. During an RG 4D-PET scan, each new breathing cycle is recognized by a trigger sent by the RMS to the PET scanner. To acquire enough counts, an RG 4D-PET scan usually requires acquisition times longer than in conventional PET studies, to the order of 8-12 versus 2-3 min/bed position.

Retrospective RG 4D-PET/CT: Data Processing Techniques Once acquired, retrospective RG 4D-CT and RG 4D-PET data have to be processed and sorted into a selected (operator-defined) number of gates (also named: phases, bins, or partitions) (Fig. 6). The sorting process involves dividing the data acquired during a whole breathing cycle into a predefined number of gates (eg, 10 gates), each gate corresponding to a specific phase of the respiratory cycle. Two sorting methods can be used: (1) by time or (2) by amplitude.64 When sorted by time, the breathing curve is analyzed considering only the timing information, regardless of the magnitude of the corresponding breathing signal. A fixed or a proportional timing division can be used. Conversely, sorting by amplitude is performed by sampling the magnitude of signal recorded in each breathing cycle, after the global amplitude (global maximum and global minimum) has been determined over the whole breathing curve recorded during the 4D scan. Equal or variable heights can be used. Amplitude-based sorting techniques have been shown to produce better results than time-based techniques, showing a significant reduction of artifacts due to irregularities in the patient’s breathing cycle.64-66 This notwithstanding, the 4D data sorting techniques generally available in commercial diagnostic PET/CT systems use time-based techniques, these being more simple to implement. After sorting (by time or by amplitude), data from corresponding gates are combined to generate a set of images, each representing the body anatomy (CT) or function

Motion management in PET/CT

297

Figure 6 Respiratory curves. Top: Free breathing (black curve): Note the irregularity (amplitude and frequency) of the breathing signal. Free breathing with audio prompting (white curve): Note the more regular frequency and the increased amplitude of the signal, compared with the free-breathing condition. Middle: Free breathing (black curve, see aforementioned comment). Free breathing with visual prompting (white curve): Note how the amplitude of the breathing signal is well controlled by the patient, guided by the 2 reference lines (white dotted lines). Bottom: Example of a deep inspiration breath-hold test. After a few free-breathing cycles, the patient is instructed to reach the established threshold (within the two white dotted lines), and then to keep his/her breath held for an established period.

(PET) in a specific moment of the patient’s respiratory cycle. The higher the number of phases into which the breathing cycle is divided, the better the sampling of the respiratory signal, and therefore the better the description of the tumor motion. In this respect, it is noteworthy that CT data sorting is performed on the reconstructed images by extracting, from the large number of CT images, those representing the CT volume at each specific phase of the breathing cycle. Thus, the number of phases used to represent the whole breathing cycle does not affect the quality of the sorted 4D-CT images. Conversely, PET data sorting is performed on raw data before reconstruction, thus the number of phases used to sample the patient’s breathing cycle must be carefully evaluated to balance motion compensation and image quality. In fact, the higher the number of phases, the better motion compensation can be achieved, but at the expense of counting statistics in each image phase and thus of the quality of the recon-

structed images in terms of signal-to-noise ratio. The optimization of the number of phases in an RG 4D-PET study, to achieve nearly motion-free images of good quality, has been the topic for several investigations.67-69 Another relevant issue in processing an RG 4D-PET/CT study is the possibility of correcting each 4D-PET phase (raw data) for attenuation using the corresponding phase of the 4D-CT study, by the so-called phase-matched reconstruction method. The qualitative and quantitative improvement of PET images in an RG 4D-PET/CT study, resulting from phase-matched reconstruction, has been demonstrated in several works on phantom studies as well as on patient data.55,70-73

BH PET/CT Protocols As previously described, RG 4D-PET/CT acquisition techniques allow compensation for respiratory motion artifacts,

V. Bettinardi et al

298 also providing personalized information about the motion of the tumor. Nevertheless, the use and diffusion of RG 4DPET/CT studies is still quite limited owing to: (1) the more general complexity of the RG 4D-PET/CT protocol compared with the conventional nongated one; (2) the longer time needed to perform the acquisitions and the postprocessing of the 4D data (particularly for 4D-PET); and (3) the higher radiation dose delivered to the patient (during the 4D-CT scan). To overcome these more demanding clinical conditions compared with that of a conventional PET/CT protocol, BH techniques were recently proposed for PET/CT oncological applications, the aim being to compensate for respiratory organ and lesion motion, as an alternative approach to the use of RG 4D-PET/CT techniques.33-37 In this respect, Nehmeh et al33 proposed a PET/CT deepinspiration breath-hold (DIBH) technique for thorax studies; in the study, the patients were verbally coached to perform a reproducible DIBH level during both CT and PET studies. The first DIBH was performed during the CT scan and was used as the reference, and this was followed by 9 independent DIBH PET scans of 20 seconds each. In 8 patients (10 lesions), the results showed an improved spatial matching between PET and CT images; reduced motion artifacts, especially in the diaphragmatic region; and a mean standard uptake value increase of 32.5% compared with the corresponding conventional nongated PET images. The authors concluded that the DIBH PET/CT technique accurately compensates for respiratory motion artifacts, with a consequent improvement of data quantification and tumor localization. From this initial experience, several variations of the aforementioned protocol have been proposed, in which different BH times (eg, 10 s, 20 s, as long as possible, etc.) and different numbers of PET BH repetitions were used.33,35,36 In an attempt to establish the optimal acquisition protocol for BH PET/CT studies for the diagnosis of thoracic lesions, Mitsumoto et al74 recently evaluated different protocol configurations. The authors studied 32 thoracic lesions in 21 patients. Each patient underwent a whole body PET/CT study in freebreathing mode, followed by a BH-CT and 5 BH-PET scans of 20 seconds each. The summed BH-PET images, corresponding to total acquisition times of 40, 60, 80, and 100 seconds, were then evaluated. From this analysis, the authors recommended that ⱖ3 BH-PET images, each of 20-second acquisition time, be summed. Although none of the aforementioned work specifically proposes the use of a PET/CT BH protocol for TVD and radiation treatment planning, BH techniques are normally used in RT applications (planning and treatment). Indeed, BH protocols are used to obtain target immobilization and to determine anatomical conditions that allow the protection of normal tissues.75-77 In this respect, several studies have demonstrated that the most reproducible organ position is obtained on deep inspiration or deep/end expiration. From physiological respiration studies, it is known that during deep inspiration, the diaphragm pulls the heart posteriorly and inferiorly away from the anterior chest wall. Thus, this protocol is particu-

larly used in the case of breast tumor RT, reducing both cardiac and lung exposure during dose delivery.78-80 Another dosimetric advantage of the DIBH protocol is related to the increase in lung volume, which in turn determines a reduction in lung density, thus allowing the fraction of normal irradiated tissue to be reduced. These 2 conditions (volume increase and lung density decrease) associated with the immobilization of the target make, in the case of DIBH, such a breathing condition particularly suitable in lung cancer RT.81-84 Although the DIBH procedure has been reported by several authors as the one most commonly used for RT treatment, it is not feasible for the majority of patients affected by respiratory complications. In these cases, a BH performed at the end of expiration represents a more natural and relaxed condition, which could also guarantee better reproducibility of the tumor position at each new breathing cycle.74,76,85,86

Patient Training Whatever the technique used to manage respiratory organ and lesion motion (eg, RG 4D-PET/CT, BH PET/CT), active patient collaboration is essential for the success of the study. In fact, the quality of the results obtained with an RG 4DPET/CT or a DIBH PET/CT study depends more on the patient’s compliance and capability to perform a regular and reproducible breathing condition (free breathing or DIBH), than on the technique used for data acquisition and processing. In this respect, it is important to motivate the patient by giving him/her the proper information concerning the aims of the RG 4D-PET/CT or DIBH study, stressing the importance of his/her active collaboration. Furthermore, a training session is also useful, allowing the patient to become acquainted with: (1) the tools used to monitor his/her breath, (2) the different possible coaching techniques to help him/ her perform a regular breathing pattern, and (3) the technical staff who assist the patients during the test. Operatively, the training session can be performed either before the diagnostic session, in a dedicated room where diagnostic and treatment conditions can be simulated (eg, flat table, devices for positioning and immobilizing the patient, respiratory monitoring system), or with the patient on the PET/CT scanner bed, before beginning the PET/CT simulation session. Our experience has shown that the training session performed in a dedicated room before the PET/CT study offers the best conditions to the patient; this is a more relaxed situation to experiment the different coaching techniques, for example, audio, visual feedback, and simultaneous audiovisual, to help maintain a regular breathing pattern. As reported by Kini et al,46 a training session generally improves the reproducibility of the patient’s breathing performance, both in amplitude and frequency. However, different coaching techniques have been shown to have specific advantages and disadvantages, which have to be evaluated for each patient. The audio-coaching method, with verbal instructions, in which the patient is guided to “breath in” and “breath out,” usually result in a more reproducible frequency; however, the variability and the amplitude of the breathing signal increases (Fig. 6). Thus, it is noteworthy that amplifi-

Motion management in PET/CT cation of the breathing signal will correspond to amplification in the tumor displacement, leading to a further qualitative and quantitative degradation of the PET/CT images. Furthermore, the resulting TVD also requires wider safety margins to cover the corresponding wider volume of motion. Considering these effects, the use of audio-coaching methods must be evaluated carefully, patient by patient, to balance the advantages and disadvantages of the technique. Another type of coaching technique is visual feedback. During visual feedback, using goggles or a mini-screen, the patient can see his/her respiratory signal moving up and down according to the respiration cycle. The patient is asked to maintain a constant amplitude of respiratory motion, and is guided by 2 indicators, usually 2 horizontal lines, that should be approached, but not exceeded, by the moving signal (Fig. 6). Kini et al46 reported that visual feedback gave a better control over the amplitude of the respiratory signal, but, in contrast, also showed more variations in frequency. Aiming at a further improvement in the coaching techniques, a simultaneous audiovisual prompting method has also been proposed.87 The simultaneous audiovisual prompting method usually provides the best results in terms of the regularization and reproducibility of the patient’s breathing pattern, but the complexity of the task is such that only a small percentage of the patients performs successfully.88 Less demanding in terms of patient concentration is the training session aiming at teaching the patient to perform a reproducible BH condition (eg, deep inspiration, deep/end expiration). In this case, it is particularly important to establish an active collaboration between the patient and the technical staff, as it is the operator who usually guides the patient, also during the clinical sessions, to reach and to maintain a predefined level of inspiration or expiration. Furthermore, to help the patient in performing the required task well, goggles or a mini-screen are commonly used, as in the visual feedback coaching technique. In this case, the patient can see, in a double check with the operator, his/her breathing curve and the threshold to be reached to reproduce the established respiratory condition (Fig. 6). Finally, as during the training session the operator can verify the compliance and the performance of the patient, the training session can be used to address the patient to the proper breathing protocol (free breathing or BH). Conversely, in case of poor performance, the patient should be addressed to a conventional free-breathing protocol, without motion management.

Workflow for Using Motion Information in TVD and Treatment Planning This section describes the steps of the procedure to use personalized motion information obtained from an RG 4D-PET/CT or BH PET/CT study for TVD and treatment planning.

Contouring Techniques for TVD Having co-registered the available PET/CT images, the first step in the definition of the target volume is to contour: (1)

299 the gross tumor volume (GTV) on the anatomical CT images, and (2) the biological target volume (BTV) on the functional PET images.89,90 Target definition, for both CT and PET, is generally based on an initial qualitative visual assessment of the tumor, followed by a manual contouring of the target. To perform this task, physicians rely on guidelines and on personal clinical experience. This qualitative approach is in contrast to the high precision in radiation delivery achievable by current-generation RT systems, which, to fully exploit their potentialities, would require a corresponding high precision in the target definition. Whereas radiation oncologists can take advantage of the high spatial resolution and high contrast among different tissue types in the definition of GTV on CT images, this is not the case in PET, which is characterized by a limited spatial resolution (approximately 4-5 mm) and often also by low contrast between the tumor and the surrounding active background. These conditions, combined with the smearing effect caused by respiratory motion in cases of freebreathing acquisition, make it difficult to accurately and precisely define the target because of the blurred tumor edges. These difficulties in GTV and BTV contouring also result in a high intra- and interoperator variability. To minimize this variability, a standardized protocol should be established at each RT center, codifying the contouring parameters (eg, display window, threshold level, color scale, etc.), which all physicians should use for GTV and BTV definition. To overcome these difficulties in the TVD, several automatic and semiautomatic classification/segmentation methods have been proposed, the aim being: (1) to improve TVD, (2) to reduce intra- and interoperator variability, and (3) to reduce the physician’s workload in the contouring process.91-96 Unfortunately, the complexity of the problem is such that, although some techniques are promising, they have not yet entered clinical practice or been accepted as reference standard methods for GTV and/or BTV definition. Despite all the difficulties and the criticalness of the previously described contouring process, there is also evidence that the combined use of PET and CT images allows for a more accurate and reproducible definition of the target compared with the use of a single imaging modality (eg, CT).6,7,97,98

Definition of the Planning Target Volume GTV and BTV are used to define the planning target volume (PTV) on which to perform the treatment.90,99,100 How to combine GTV and BTV to define PTV depends on which PET/CT acquisition protocol has been used, as described in the following text. Conventional PET/CT Acquisition Protocol (free breathing) In the case of a conventional acquisition protocol, in which CT and PET data have been acquired in free-breathing conditions, GTV represents the CT target at a certain moment (position) of the breathing cycle, whereas BTV represents the PET functional volume encompassing the motion of the active part of the tumor. In such a case, the following steps are then performed:

V. Bettinardi et al

300 ●

●

Expansion of GTV and BTV to clinical target volumes (CTVCT and CTVPET), to account for possible microscopic disease infiltration; Expansion of the CTVCT to internal target volume (ITVCT), to account for intrafraction (due to respiration) and interfraction (due to repositioning) motion of the target. The ITV expansion has to be applied only to CTVCT, as the CTVPET (ITVPET) intrinsically accounts for the target motion (at least for the respiratory intrafraction motion).

ITV definition is a critical step in treatment planning. If motion information is not available, standardized ITV expansions are derived from statistical data on patient population, accounting for tumor size and anatomical location: ● ●

Convolution of ITVCT and ITVPET to generate an “integrated” ITVCT-PET. Finally, expansion of ITVCT-PET to PTV by accounting for setup uncertainties.

Notwithstanding the described procedure for target and treatment volumes’ definition, it is also common practice to unify the expansions from GTV/BTV directly to ITV in a unique step accounting for both disease infiltration (CTV) and motion (ITV). RG 4D-PET/CT Acquisition Protocol When GTV and BTV are defined in the respiratory phases of 4D-CT and 4D-PET studies (4D-GTVs and 4D-BTVs, respectively), the expansion to CTV for the microscopic subclinical disease must be applied to each 4D-GTV and 4D-BTV, resulting in a set of 4D-CTVsCT and 4D-CTVsPET. ITVCT and ITVPET can then be generated by the convolution of the corresponding 4D-CTVsCT and 4D-CTVsPET. The procedure just described is formally correct, but it is also a cumbersome procedure, considering the number of phases in which the breathing cycle has been divided (eg, 10). To make the procedure clinically feasible by reducing the contouring working time for the radiation oncologists, a possible alternative strategy is to define the target on 2 selected phases only, corresponding to the end of inspiration and the end of expiration,101 and by convolving the resulting 2 contours. The radiation oncologist can then verify whether all phases are included within the volume delimited by the convolved contour. If this is not the case, the nonincluded phases have to be contoured and convolved with the others to fully cover the volume of tumor motion. CT Maximum Intensity Pixel To further reduce the workload of the radiation oncologist, another opportunity, valid in the case of lung tumors well surrounded by the lower density of lung parenchyma, is to contour the target using a maximum intensity pixel (MIP) image set instead of the original 4D-CT phases. In an MIP image, by definition, each pixel contains the maximum of the CT numbers (for that pixel) among the sorted 4D-CT phases, and the target visible on an MIP image represents the volume of space encompassing the motion of the tumor caused by the patient’s respiration (GTVMIP).102-105

An MIP image set can be generated using a defined number of phases (eg, 10 phases), or using all the images acquired during a cine 4D-CT scan, regardless of the synchronization with the patient’s breathing cycle. To assess the value of MIP in TVD, target volumes generated by the convolution of 10 GTVs (GTV4DCT-phases), drawn on each 4D-CT phase, have been compared with the GTVMIP obtained by contouring the target on the corresponding MIP image set. In particular, Underberg et al102 compared data from a mobile phantom and from 12 patients with stage I lung cancer, finding good agreement with a ratio of 1.07 between GTV4DCT-phases and GTVMIP target volumes, leading to the conclusion that MIP is a reliable clinical tool for the generation of ITVs from 4D-CT data sets, and that it allows rapid assessment of tumor mobility for both gated and nongated RT in lung cancer (Fig. 7). In another study, Muirhead et al103 evaluated 10 patients with stage I-III non-small-cell lung cancer, reporting median differences of 19% between the GTV4DCT-phases and GTVMIP target volumes. In agreement with Underberg et al,102 the authors suggested that MIP images should be used only for the delineation of stage I tumors, to prevent undertreatment of disease, whereas the delineation of the 10 4D-CT phases is preferable for stage II and III disease. More recently, Zamora et al105 demonstrated that MIP generated from a 4D-CT sorting process (even with a relatively high number of phases: 10) could in some cases underestimate the volume of motion by even more than 10%, when compared with the corresponding one drawn on the MIP image set generated using all the images acquired during the cine 4D-CT scan. The difference was attributed to errors in the sorting procedure associated to irregularities in the breathing signal. Using the MIP image set obtained using all the acquired images, such sorting irregularities were shown to be not so relevant with respect to the final result. Thus, the authors suggested, for RT applications, the use of an MIP image generated from the full cine CT data set, to ensure maximum inclusive tumor extent. Finally, in the case of lung tumors not well surrounded by lower-density lung parenchyma, particular attention should be paid to the use of MIP images for TVD. In fact, in such cases, parts of the tumor margins could appear as not well defined, should nearby anatomical regions (structures or organs) have comparable or higher density than the tumor (eg, liver).106 CT Average Image Alternatively to the MIP, the creation of an average (AVE) image set has also been proposed for TVD. In an AVE image, each pixel is calculated as the mean of the CT numbers among all the 4D-CT phases or the acquired CT images. Similar to an MIP, the target seen in an AVE image represents the volume of space encompassing the tumor motion. However, significant differences between MIP and AVE images can be seen on the tumor edges owing to the motion. While MIP images have sharp edges, AVE image edges are blurred. For this reason the target volume outlined on AVE images tends to underestimate the true volume of motion (Fig. 8).106-108 Conversely, AVE images can be successfully used for attenu-

Motion management in PET/CT

301

Figure 7 Lung tumor—Upper left: Coronal view of a 4D-CT phase; the target is well defined, as it is represented in a specific moment of the patient’s breathing cycle. Upper right: Coronal view of the corresponding MIP image obtained by combining 10 4D-CT phases. Bottom left: Zoomed image of the 4D-CT phase; the target has been contoured, generating the GTV. Bottom right: Zoomed image of the MIP image; the contour of the “target” accounts for the tumor respiratory motion (ITV). Note how the GTV drawn on the single 4D-CT phase is well contained within the ITV drawn on the MIP image.

ation correction of PET data to reduce, as reported in the article by Chi et al,107 the probability of mismatch between CT and PET data. In this study, the authors demonstrated the

importance of an accurate attenuation correction (by using AVE images), particularly when PET images are used for TVD, to avoid or reduce PET image artifacts, which may

Figure 8 Lung tumor—Coronal (top) and sagittal (bottom) views of a lung tumor (white arrows). Left column: Single 4D-CT phase; the target is well defined, as it is frozen at a specific moment of the patient’s breathing cycle. Center column: MIP image; the target is larger than in the single 4D-CT phase, as it accounts for tumor motion (tumor edges are sharp). Right column: AVE image; the target is larger than in a single 4D-CT phase, as it accounts for tumor motion (edges are blurred). Note the different representation of the target in the 3 different image sets.

302 increase uncertainty in the lesion volume definition, as well as in its centroid location. PET: Sum and MIP To reduce the workload in the TVD on 4D-PET images, similar to the CT MIP and AVE strategies, a PET procedure involves summing all the 4D-PET phases (4D-PETsum) and then contouring the target only on the resulting 4D-PETsum image set. Besides the workload reduction, another advantage of this procedure is related to the lower statistical noise present in the 4D-PETsum images, compared with that in each of the 4D-PET phases, which allows a more accurate definition of the target. Alternatively to the sum of the 4D-PET phases, Lamb et al109 recently proposed the generation of an MIPPET image in a similar way to CT (MIPCT), with the aim to quantitatively and efficiently incorporate respiratory-correlated PET information into the RT treatment planning, particularly for the generation of lung tumor ITV. In this article, the authors reported (on 4 lower-lobe lung tumors) that MIPPET images better match MIPCT images compared with nongated PET images, based on volume overlap, relative volumes, and visual interpretation. BH PET/CT Acquisition Protocol When CT and PET studies are acquired in BH, both GTV and BTV represent a snapshot of the target volume at a specific moment of the breathing cycle (eg, end of expiration), but no information on target motion is available. In such a case, target definition proceeds as described in the previous section, but the ITV expansion has to be applied to both CTVCT and CTVPET to account for possible residual motion.

Motion Information and Type of Radiation Treatment The way of radiation dose delivery during RT sessions (conventional–nongated or gated modality) depends on how motion information has been accounted for in the definition of PTV. If the whole volume of the target motion (as can be obtained from a MIP image or from the whole set of 4D-CT and 4D-PET phases) is used to define ITV, the treatment plan can be delivered in the conventional way, without gating. The advantage of this approach consists in the use of personalized motion information to improve the TVD, by reducing the volume of treatment (Fig. 9).108,110-113 In particular, knowledge of the target motion allows for a more accurate definition of ITV by the use of anisotropic margins. Better target coverage can thus be obtained, compared with the use of conventional isotropic expansions, that are applied to an unknown tumor position with respect to its full motion trajectory. In a recent work, Hof et al114 reported that in a population of 14 lung cancer patients, treatment planning using personalized motion information obtained from a 4D-CT study significantly reduced the PTV (31%), compared with the corresponding PTV conventionally generated using isotropic expansions. This result confirmed the

V. Bettinardi et al findings previously reported by Rietzel et al,112 who found an average 23% reduction of the internal margins when 4D-CT personalized motion information was used for the definition of the target volume instead of population-based expansion. Conversely, if the target volume is defined using only a few selected 4D-CT and 4D-PET phases, radiation dose has to be then delivered in gated mode during the corresponding breathing windows (eg, few phases covering the end inspiration). By this approach, the treatment volume can be reduced, as only a residual percentage of motion should be present in the selected phases.115-117 Finally, if PET/CT images are obtained using a BH technique (eg, DIBH), then the treatment has to be performed in the same BH condition. Considering that, during a BH, the target is supposed to not move, this technique allows for a significant reduction of the volume to treat.75

RG 4D-PET/CT and BH Techniques for Monitoring the Response to Therapy and Efficacy of the Treatment Besides the importance of a well-designed treatment plan, another important step for accurate patient management is the assessment of therapy response.118-123 Actually, the most effective follow-up strategy for monitoring patients after RT treatment, with or without chemotherapy, is still not fully established. However, in general, FDG-PET/CT is reported to present additional benefit, compared with morphologic conventional evaluation, in the assessment of response to treatment as well as in outcome prediction.124,125 When treatment monitoring is clinically performed, a conventional PET/CT acquisition protocol is currently used. Even though, to the best of our knowledge, only one single paper has been published up to date on this topic (Aristophanous et al126), RG 4D-PET/CT or BH techniques could also be useful in the evaluation of response to treatment. In fact, these techniques, accounting for important effects (ie, respiratory organ motion, spatial mismatch between CT and PET data) that can bias imaging results (qualitatively and quantitatively), should provide a more accurate evaluation of the changes in metabolic activity during and after therapy, compared with that obtained by a conventional PET/CT study.

Image-Guided Radiation Therapy: Management of Motion and Treatment Plan The use of RG 4D-PET/CT techniques has certainly been shown to be effective and useful to improve TVD and RT treatment planning, providing objective and personalized information about tumor motion due to the patient’s respiration. However, it must be noted that motion information measured in RG 4D-PET/CT studies may not be representative of motion during RT treatment sessions. First, because of intrasubject variability: the pattern of organ and lesion mo-

Motion management in PET/CT

303

Figure 9 Pancreatic tumor—TVD and PTV by 4D-PET/CT. Top images: Two selected 4D-CT phases with GTV (red) and BTV (blue) contours. Bottom image: Organ and target contours overlapped on a 4D-CT phase. ITV1 (yellow contour) accounts for the whole tumor motion, whereas ITV2 (red contour) accounts for motion in a specific region of the pancreas tumor, involved by vessel infiltration. 4D-PTV1 (yellow expansion) represents the whole planned treatment volume, whereas the 4D-PTV2 (orange expansion) represents a subvolume of 4D-PTV1, where a boost of dose has to be delivered. Planned treatment volume (STD-PTV1) obtained by using a conventional approach (expansions based on statistical population data). Note how the use of personalized motion information allows the treatment volume to be reduced.

tion during the RG 4D-PET/CT scan time may be different from that during the RT sessions. Second, for CT, because of intrafraction variability: a 4D-CT (axial cine) study records lesion motion during a single specific breathing cycle for each axial position, thus missing breathing cycle irregularities, which may occur during treatment sessions. Furthermore, the respiratory breathing pattern (and thus internal organ and lesion motion) can show not only intrafraction but also interfraction variability, from 1 RT session to the other. It is thus important to verify that the breathing pattern during RT reproduces well the one performed during the PET/CT study. Moreover, anatomical changes produced by the treatment itself can modify the type and magnitude of organ and tumor motion. To account for these variations, an image should be produced before each treatment session, to verify that the target is well covered by the designed PTV. To fulfill this requirement, state-of-the-art RT systems, known as image-guided radiation therapy (IGRT), are equipped with on-board imag-

ing systems (OBIs), enabling the radiation oncologist to take diagnostic high-quality radiographs (mega voltage portal images) or 3D-CT images (mega voltage CT [MVCT], cone beam CT), while the patients are immobilized on the RT bed, immediately before, during, or just after the treatment.127-129 The images obtained by OBIs can be compared with those used for the definition of the treatment plan, to minimize daily changes in patient position and to correct, in real time, setup errors. Furthermore, OBIs can show changes of the tumor volume on a daily basis, which can thus be monitored and accounted for, to properly adjust the radiation delivery to target the tumor precisely. Advanced OBIs also allow 4D imaging or slow acquisitions to be performed, thus providing not only the image of the tumor but also motion information. Both intrafraction position changes (during a treatment session because of normal respiratory organ and tumor motion) and interfraction changes (caused by day-to-day changes of setup conditions) can thus be managed. As an example, the TomoTherapy sys-

V. Bettinardi et al

304

imaging. Furthermore, it also represents one of the most critical factors to be accounted for, in RT applications. Motion management is thus becoming an important issue in both diagnostic and RT applications, particularly when PET/CT images are used for GTV and BTV definition. Focusing on PET/CT, RG 4D-PET/CT, and BH protocols allows compensation for image degradation (loss of spatial resolution and contrast) and artifacts induced by respiratory movements. In addition, RG 4D-PET/CT techniques provide information on the target motion, which can be used to personalize and improve TVD and treatment planning. Within this context, molecular PET/CT imaging combined with RG motion management techniques can play an important role in the advances of RT treatment, considering also the potentiality of IGRT and of the adaptive RT approach. The synergic use of all these powerful imaging and treatment techniques is thus expected to produce a significant improvement in the efficacy of RT treatment, aiming at improving local tumor control rates with lower toxicity.

References Figure 10 TomoTherapy system—MVCT image acquired before the third treatment session. As the MVCT scan is slow, the representation of the tumor also accounts for its motion. The contour of the tumor falls well within the PTV.

tem allows verification of the patient position to be performed using a MVCT scan before each treatment session. As the MVCT scan involves a very slow acquisition (eg, 9 s/rot), the resulting reconstructed images show an image of the tumor also accounting for its volume of motion. In the case of high contrast between target and surrounding tissues (eg, lung tumor), the radiation oncologist can thus verify, by assessing the MVCT images, the correctness of patient position as well as that of the target and its volume of motion with respect to the defined PTV (Fig. 10).128,130,131 Furthermore, in the case of tumor changes (eg, position, shape, motion), which could result in a suboptimal dose delivery, by using IGRT and OBIs, it is nowadays possible to properly adjust the RT treatment planning, implementing those modifications required to account for such variations. In fact, the aim of this adaptive RT approach is to systematically improve the treatment plan, accounting for temporal variations concerning the patient and the tumor during the course of the therapy. An adaptive RT approach, although implying a higher degree of complexity, could thus significantly improve the outcome of the treatment by allowing: (1) more precise patient repositioning, (2) intra- and intertarget motion management, (3) redefinition of the safety margins to spare healthy tissues and organs at risk, and (4) easier implementation of dose escalation protocols.

Conclusions Organ and lesion motion is well known to be one of the most important sources of image degradation in both CT and PET

1. Townsend DW: Dual-modality imaging: Combining anatomy and function. J Nucl Med 2008;49:938-955 2. Townsend DW, Beyer T, Blodgett TM: PET/CT scanners: A hardware approach to image fusion. Semin Nucl Med 2003;33:193-204 3. Almuhaideb A, Papathanasiou N, Bomanji J: 18F-FDG PET/CT imaging in oncology. Ann Saudi Med 2011;31:3-13 4. MacManus M, Nestle U, Rosenzweig KE, et al: U, Rosenzweig KE, et al: Use of PET and PET/CT for radiation therapy planning: IAEA expert report 2006-2007. Radiother Oncol 2009;91:85-94 5. Thorwarth D, Geets X, Paiusco M: Physical radiotherapy treatment planning based on functional PET/CT data. Radiother Oncol 2010;96: 317-324 6. Ashamalla H, Rafla S, Parikh K, et al: The contribution of integrated PET/CT to the evolving definition of treatment volumes in radiation treatment planning in lung cancer. Int J Radiat Oncol Biol Phys 2005; 63:1016-1023 7. Greco C, Rosenzweig K, Cascini GL, et al: Current status of PET/CT for tumour volume definition in radiotherapy treatment planning for non-small cell lung cancer (NSCLC). Lung Cancer 2007;57:125-134 8. Spratt DE, Diaz R, McElmurray J, et al: Impact of FDG PET/CT on delineation of the gross tumor volume for radiation planning in nonsmall-cell lung cancer. Clin Nucl Med 2010;35:237-243 9. Zaidi H, Vees H, Wissmeyer M: Molecular PET/CT imaging-guided radiation therapy treatment planning. Acad Radiol 2009;16:11081133 10. Bentzen SM, Gregoire V: Molecular imaging-based dose painting: A novel paradigm for radiation therapy prescription. Semin Radiat Oncol 2011;21:101-110 11. Bhide SA, Nutting CM: Recent advances in radiotherapy. BMC Med 2010;8:25 12. Langen KM, Jones DT: Organ motion and its management. Int J Radiat Oncol Biol Phys 2001;50:265-278 13. Goitein M: Organ and tumor motion: An overview. Semin Radiat Oncol 2004;14:2-9 14. Shirato H, Seppenwoolde Y, Kitamura K, et al: Intrafractional tumor motion: Lung and liver. Semin Radiat Oncol 2004;14:10-18 15. Seppenwoolde Y, Shirato H, Kitamura K, et al: Precise and real-time measurement of 3D tumor motion in lung due to breathing and heartbeat, measured during radiotherapy. Int J Radiat Oncol Biol Phys 2002;53:822-834 16. Keall PJ, Mageras GS, Balter JM, et al: The management of respiratory motion in radiation oncology report of AAPM Task Group 76. Med Phys 2006;33:3874-3900 17. Plathow C, Fink C, Ley S, et al: Measurement of tumor diameter-

Motion management in PET/CT

18.

19. 20. 21.

22.

23. 24. 25.

26.

27. 28. 29.

30. 31.

32.

33. 34.

35.

36.

37.

38.

39. 40.

41.

42.

dependent mobility of lung tumors by dynamic MRI. Radiother Oncol 2004;73:349-354 Kirilova A, Lockwood G, Choi P, et al: Three-dimensional motion of liver tumors using cine-magnetic resonance imaging. Int J Radiat Oncol Biol Phys 2008;71:1189-1195 Xi M, Liu MZ, Li QQ, et al: Analysis of abdominal organ motion using four-dimensional CT. Ai Zheng 2009;28:989-993 Wagman R, Yorke E, Ford E, et al: Respiratory gating for liver tumors: Use in dose escalation. Int J Radiat Oncol Biol Phys 2003;55:659-668 Bussels B, Goethals L, Feron M, et al: Respiration-induced movement of the upper abdominal organs: A pitfall for the three-dimensional conformal radiation treatment of pancreatic cancer. Radiother Oncol 2003;68:69-74 Mori S, Hara R, Yanagi T, et al: Four-dimensional measurement of intrafractional respiratory motion of pancreatic tumors using a 256 multi-slice CT scanner. Radiother Oncol 2009;92:231-237 Chen GT, Kung JH, Beaudette KP: Artifacts in computed tomography scanning of moving objects. Semin Radiat Oncol 2004;14:19-26 Keall P: 4-dimensional computed tomography imaging and treatment planning. Semin Radiat Oncol 2004;14:81-90 Beyer T, Antoch G, Blodgett T, et al: Dual-modality PET/CT imaging: The effect of respiratory motion on combined image quality in clinical oncology. Eur J Nucl Med Mol Imaging 2003;30:588-596 Osman MM, Cohade C, Nakamoto Y, et al: Respiratory motion artifacts on PET emission images obtained using CT attenuation correction on PET-CT. Eur J Nucl Med Mol Imaging 2003;30:603-606 Mawlawi O, Pan T, Macapinlac HA: PET/CT imaging techniques, considerations, and artifacts. J Thorac Imaging 2006;21:99-110 de Juan R, Seifert B, Berthold T, et al: Clinical evaluation of a breathing protocol for PET/CT. Eur Radiol 2004;14:1118-1123 Gilman MD, Fischman AJ, Krishnasetty V, et al: Optimal CT breathing protocol for combined thoracic PET/CT. AJR Am J Roentgenol 2006; 187:1357-1360 Nehmeh SA, Erdi YE, Pan T, et al: Four-dimensional (4D) PET/CT imaging of the thorax. Med Phys 2004;31:3179-3186 Nehmeh SA, Erdi YE: Respiratory motion in positron emission tomography/computed tomography: A review. Semin Nucl Med 2008;38: 167-176 Bettinardi V, Picchio M, Di Muzio N, et al: PET/CT for radiotherapy: Image acquisition and data processing. Q J Nucl Med Mol Imaging 2010;54:455-475 Nehmeh SA, Erdi YE, Meirelles GS, et al: Deep-inspiration breathhold PET/CT of the thorax. J Nucl Med 2007;48:22-26 Fin L, Daouk J, Morvan J, et al: Initial clinical results for breath-hold CT-based processing of respiratory-gated PET acquisitions. Eur J Nucl Med Mol 2008;35:1971-1980 Kawano T, Ohtake E, Inoue T: Deep-inspiration breath-hold PET/CT of lung cancer: Maximum standardized uptake value analysis of 108 patients. J Nucl Med 2008;49:1223-1231 Torizuka T, Tanizaki Y, Kanno T, et al: Single 20-second acquisition of deep-inspiration breath-hold PET/CT: Clinical feasibility for lung cancer. J Nucl Med 2009;50:1579-1584 Nagamachi S, Wakamatsu H, Kiyohara S, et al: The reproducibility of deep-inspiration breath-hold (18)F-FDG PET/CT technique in diagnosing various cancers affected by respiratory motion. Ann Nucl Med 2010;24:171-178 Brunetti J, Caggiano A, Rosenbluth B, et al: Technical aspects of positron emission tomography/computed tomography fusion planning. Semin Nucl Med 2008;38:129-136 Coffey M, Vaandering A: Patient setup for PET/CT acquisition in radiotherapy planning. Radiother Oncol 2010;96:298-301 Levitt SH, Prudy JA, Perez CA, et al: Technical Basis of Radiation Therapy: Practical Clinical Applications. (Medical Radiology/Radiation Oncology) (ed 4). Netherlands, Springer, 2006 Metcalfe P, Kron T, Hoban P: The Physics of Radiotherapy X-rays and Electrons. Madison, WI. Netherlands, Medical Physics Publishing, Springer, 2007 Eccles CL, Dawson LA, Moseley JL, et al: Interfraction liver shape variability and impact on GTV position during liver stereotactic radio-

305

43.

44.

45. 46. 47.

48.

49.

50.

51.

52. 53.

54.

55. 56.

57. 58.

59.

60.

61.

62.

63.

64.

65.

therapy using abdominal compression. Int J Radiat Oncol Biol Phys 2011;80:938-946 Eccles CL, Patel R, Simeonov AK, et al: Comparison of liver tumor motion with and without abdominal compression using cine-magnetic resonance imaging. Int J Radiat Oncol Biol Phys 2011;79:602608 Han K, Cheung P, Basran PS, et al: A comparison of two immobilization systems for stereotactic body radiation therapy of lung tumors. Radiother Oncol 2010;95:103-108 Jiang SB: Radiotherapy of mobile tumors. Semin Radiat Oncol 2006; 16:239-248 Kini VR, Vedam SS, Keall PJ, et al: Patient training in respiratory-gated radiotherapy. Med Dosim 2003;28:7-11 Otani Y, Fukuda I, Tsukamoto N, et al: A comparison of the respiratory signals acquired by different respiratory monitoring systems used in respiratory gated radiotherapy. Med Phys 2010;37:6178-6186 Ionascu D, Jiang SB, Nishioka S, et al: Internal-external correlation investigations of respiratory induced motion of lung tumors. Med Phys 2007;34:3893-3903 Gierga DP, Brewer J, Sharp GC, et al: The correlation between internal and external markers for abdominal tumors: Implications for respiratory gating. Int J Radiat Oncol Biol Phys 2005;61:1551-1558 Beddar AS, Kainz K, Briere TM, et al: Correlation between internal fiducial tumor motion and external marker motion for liver tumors imaged with 4D-CT. Int J Radiat Oncol Biol Phys 2007;67:630-638 Hunjan S, Starkschall G, Prado K, et al: Lack of correlation between external fiducial positions and internal tumor positions during breathhold CT. Int J Radiat Oncol Biol Phys 2010;76:1586-1591 Pan T, Sun X, Luo D: Improvement of the cine-CT based 4D-CT imaging. Med Phys 2007;34:4499-4503 Beddar AS, Briere TM, Balter P, et al: 4D-CT imaging with synchronized intravenous contrast injection to improve delineation of liver tumors for treatment planning. Radiother Oncol 2008;87:445-448 Mancosu P, Bettinardi V, Passoni P, et al: Contrast enhanced 4D-CT imaging for target volume definition in pancreatic ductal adenocarcinoma. Radiother Oncol 2008;87:339-342 Nehmeh SA, Erdi YE, Ling CC, et al: Effect of respiratory gating on quantifying PET images of lung cancer. J Nucl Med 2002;43:876-881 van Sörnsen de Koste JR, Lagerwaard FJ, Schuchhard-Schipper RH, et al: Dosimetric consequences of tumor mobility in radiotherapy of stage I non-small cell lung cancer-an analysis of data generated using “slow” CT scans. Radiother Oncol 2001;61:93-99 Gagné IM, Robinson DM: The impact of tumor motion upon CT image integrity and target delineation. Med Phys 2004;31:3378-3392 Zeng R, Fessler JA, Balter JM: Respiratory motion estimation from slowly rotating x-ray projections: Theory and simulation. Med Phys 2005;32:984-991 Mori S, Kanematsu N, Mizuno H, et al: Physical evaluation of CT scan methods for radiation therapy planning: Comparison of fast, slow and gating scan using the 256-detector row CT scanner. Phys Med Biol 2006;51:587-600 Lagerwaard FJ, Van Sornsen de Koste JR, Nijssen-Visser MR, et al: Multiple “slow” CT scans for incorporating lung tumor mobility in radiotherapy planning. Int J Radiat Oncol Biol Phys 2001;51:932-937 de Koste JR, Lagerwaard FJ, de Boer HC, et al: Are multiple CT scans required for planning curative radiotherapy in lung tumors of the lower lobe? Int J Radiat Oncol Biol Phys 2003;55:1394-1399 Wurstbauer K, Deutschmann H, Kopp P, et al: Radiotherapy planning for lung cancer: Slow CTs allow the drawing of tighter margins. Radiother Oncol 2005;75:165-170 Nakamura M, Narita Y, Matsuo Y, et al: Geometrical differences in target volumes between slow CT and 4D CT imaging in stereotactic body radiotherapy for lung tumors in the upper and middle lobe. Med Phys 2008;35:4142-4148 Dawood M, Büther F, Lang N, et al: Respiratory gating in positron emission tomography: A quantitative comparison of different gating schemes. Med Phys 2007;34:3067-3076 Wink N, Panknin C, Solberg TD: Phase versus amplitude sorting of 4D-CT data. J Appl Clin Med Phys 2006;7:77-85

V. Bettinardi et al

306 66. Abdelnour AF, Nehmeh SA, Pan T, et al: Phase and amplitude binning for 4D-CT imaging. Phys Med Biol 2007;52:3515-3529 67. Dawood M, Büther F, Stegger L, et al: Optimal number of respiratory gates in positron emission tomography: A cardiac patient study. Med Phys 2009;36:1775-1784 68. Bettinardi V, Rapisarda E, Gilardi MC: Number of partitions (gates) needed to obtain motion-free images in a respiratory gated 4DPET/CT study as a function of the lesion size and motion displacement. Med Phys 2009;36:5547-5558 69. van Elmpt W, Hamill J, Jones J, et al: Optimal gating compared to 3D and 4D PET reconstruction for characterization of lung tumours. Eur J Nucl Med Mol Imaging 2011;38:843-855 70. Boucher L, Rodrigue S, Lecomte R, et al: Respiratory gating for 3-dimensional PET of the thorax: Feasibility and initial results. J Nucl Med 2004;45:214-219 71. Pevsner A, Nehmeh SA, Humm JL, et al: Effect of motion on tracer activity determination in CT attenuation corrected PET images: A lung phantom study. Med Phys 2005;32:2358-2362 72. Park SJ, Ionascu D, Killoran J, et al: Evaluation of the combined effects of target size, respiratory motion and background activity on 3D and 4D PET/CT images. Phys Med Biol 2008;53:3661-3679 73. Pönisch F, Richter C, Just U, et al: Attenuation correction of four dimensional (4D) PET using phase-correlated 4D-computed tomography. Phys Med Biol 2008;53 74. Mitsumoto K, Abe K, Sakaguchi Y, et al: Determination of the optimal acquisition protocol of breath-hold PET/CT for the diagnosis of thoracic lesions. Nucl Med Commun 2011;32:1148-1154 75. Mageras GS, Yorke E: Deep inspiration breath hold and respiratory gating strategies for reducing organ motion in radiation treatment. Semin Radiat Oncol 2004;14:65-75 76. Berson AM, Emery R, Rodriguez L, et al: Clinical experience using respiratory gated radiation therapy: Comparison of free-breathing and breath-hold techniques. Int J Radiat Oncol Biol Phys 2004;60:419426 77. Giraud P, Morvan E, Claude L, et al: Respiratory gating techniques for optimization of lung cancer radiotherapy. J Thorac Oncol 2011;6: 2058-2068 78. Sixel KE, Aznar MC, Ung YC: Deep inspiration breath hold to reduce irradiated heart volume in breast cancer patients. Int J Radiat Oncol Biol Phys 2001;49:199-204 79. Korreman SS, Pedersen AN, Aarup LR, et al: Reduction of cardiac and pulmonary complication probabilities after breathing adapted radiotherapy for breast cancer. Int J Radiat Oncol Biol Phys 2006;65:13751380 80. Korreman SS, Pedersen AN, Josipovic´ M, et al: Cardiac and pulmonary complication probabilities for breast cancer patients after routine end-inspiration gated radiotherapy. Radiother Oncol 2006;80:257262 81. Hanley J, Debois MM, Mah D, et al: Deep inspiration breath-hold technique for lung tumors: The potential value of target immobilization and reduced lung density in dose escalation. Int J Radiat Oncol Biol Phys 1991;45:603-611 82. Rosenzweig KE, Hanley J, Mah D, et al: The deep inspiration breathhold technique in the treatment of inoperable non-small-cell lung cancer. Int J Radiat Oncol Biol Phys 2000;48:81-87 83. Mah D, Hanley J, Rosenzweig KE, et al: Technical aspects of the deep inspiration breath-hold technique in the treatment of thoracic cancer. Int J Radiat Oncol Biol Phys 2000;48:1175-1185 84. Barnes EA, Murray BR, Robinson DM, et al: Dosimetric evaluation of lung tumor immobilization using breath hold at deep inspiration. Int J Radiat Oncol Biol Phys 2001;50:1091-1098 85. Biancia CD, Yorke E, Chui CS, et al: Comparison of end normal inspiration and expiration for gated intensity modulated radiation therapy (IMRT) of lung cancer. Radiother Oncol 2005;75:149-156 86. Wu WC, Chan CL, Wong YW, et al: A study on the influence of breathing phases in intensity-modulated radiotherapy of lung tumours using four-dimensional CT. Br J Radiol 2010;83:252-256 87. George R, Chung TD, Vedam SS, et al: Audio-visual biofeedback for respiratory-gated radiotherapy: Impact of audio instruction and au-

88.

89. 90.

91.

92. 93.

94.

95.

96.

97.

98.

99. 100.

101.

102.

103.

104.

105.

106.

107.

108.

dio-visual biofeedback on respiratory-gated radiotherapy. Int J Radiat Oncol Biol Phys 2006;65:924-933 Neicu T, Berbeco R, Wolfgang J, et al: Synchronized moving aperture radiation therapy (SMART): Improvement of breathing pattern reproducibility using respiratory coaching. Phys Med Biol 2006;51:617636 Purdy JA: Current ICRU definitions of volumes: Limitations and future directions. Semin Radiat Oncol 2004;14:27-40 Berthelsen AK, Dobbs J, Kjellén E, et al: What’s new in target volume definition for radiologists in ICRU Report 71? How can the ICRU volume definitions be integrated in clinical practice? Cancer Imaging 2007;7:104-116 Nestle U, Kremp S, Schaefer-Schuler A, et al: Comparison of different methods for delineation of 18F-FDG PET-positive tissue for target volume definition in radiotherapy of patients with non-small cell lung cancer. J Nucl Med 2005;46:1342-1348 Yaremko B, Riauka T, Robinson D, et al: Thresholding in PET images of static and moving targets. Phys Med Biol 2005;50:5969-5982 Hong R, Halama J, Bova D, et al: Correlation of PET standard uptake value and CT window-level thresholds for target delineation in CTbased radiation treatment planning. Int J Radiat Oncol Biol Phys 2007;67:720-726 Zaidi H, El Naqa I: PET-guided delineation of radiation therapy treatment volumes: A survey of image segmentation techniques. Eur J Nucl Med Mol Imaging 2010;37:2165-2187 Gubbi J, Kanakatte A, Tomas K, et al: Automatic tumour volume delineation in respiratory-gated PET images. J Med Imaging Radiat Oncol 2011;55:65-76 Dewalle-Vignion AS, Yeni N, Petyt G, et al: Evaluation of PET volume segmentation methods: Comparisons with expert manual delineations. Nucl Med Commun 2012;33:34-42 Bradley J, Thorstad WL, Mutic S, et al: Impact of FDG-PET on radiation therapy volume delineation in non-small-cell lung cancer. Int J Radiat Oncol Biol Phys 2004;59:78-86 Steenbakkers RJ, Duppen JC, Fitton I, et al: Reduction of observer variation using matched CT-PET for lung cancer delineation: A threedimensional analysis. Int J Radiat Oncol Biol Phys 2006;64:435-448 Chavaudra J, Bridier A: Definition of volumes in external radiotherapy: ICRU reports 50 and 62. Cancer Radiother 2001;5:472-478 Grosu AL, Sprague LD, Molls M: Definition of Target Volume and Organs at Risk. Biological Target Volume. (New Technologies in Radiation Oncology/Medical Radiology). Netherlands, Springer, 2006, pp 167-177 Aruga T, Itami J, Aruga M, et al: Target volume definition for upper abdominal irradiation using CT scans obtained during inhale and exhale phases. Int J Radiat Oncol Biol 2000;48:465-469 Underberg RW, Lagerwaard FJ, Slotman BJ, et al: Use of maximum intensity projections (MIP) for target volume generation in 4DCT scans for lung cancer. Int J Radiat Oncol Biol Phys 2005;63:253-260 Muirhead R, McNee SG, Featherstone C, et al: Use of maximum intensity projections (MIPs) for target outlining in 4DCT radiotherapy planning. J Thorac Oncol 2008;3:1433-1438 Park K, Huang L, Gagne H, et al: Do maximum intensity projection images truly capture tumor motion? Int J Radiat Oncol Biol Phys 2009;73:618-625 Zamora DA, Riegel AC, Sun X, et al: Thoracic target volume delineation using various maximum-intensity projection computed tomography image sets for radiotherapy treatment planning. Med Phys 2010;37:5811-5820 Bradley JD, Nofal AN, El Naqa IM, et al: Comparison of helical, maximum intensity projection (MIP), and averaged intensity (AI) 4D CT imaging for stereotactic body radiation therapy (SBRT) planning in lung cancer. Radiother Oncol 2006;81:264-268 Chi PC, Mawlawi O, Luo D, et al: Effects of respiration-averaged computed tomography on positron emission tomography/computed tomography quantification and its potential impact on gross tumor volume delineation. Int J Radiat Oncol Biol Phys 2008;71:890-899 Huang L, Park K, Boike T, et al: A study on the dosimetric accuracy of treatment planning for stereotactic body radiation therapy of lung

Motion management in PET/CT

109.

110.

111.

112. 113.

114.

115.

116.

117.

118.

119.

cancer using average and maximum intensity projection images. Radiother Oncol 2010;96:48-54 Lamb JM, Robinson C, Bradley J, et al: Generating lung tumor internal target volumes from 4D-PET maximum intensity projections. Med Phys 2011;38:5732-5737 Underberg RW, Lagerwaard FJ, Slotman BJ, et al: Benefit of respiration-gated stereotactic radiotherapy for stage I lung cancer: An analysis of 4DCT datasets. Int J Radiat Oncol Biol Phys 2005;62:554-560 Rietzel E, Chen GT, Choi NC, et al: Four-dimensional image-based treatment planning: Target volume segmentation and dose calculation in the presence of respiratory motion. Int J Radiat Oncol Biol Phys 2005;61:1535-1550 Rietzel E, Liu AK, Doppke KP, et al: Design of 4D treatment planning target volumes. Int J Radiat Oncol Biol 2006;66:287-295 Aristophanous M, Berbeco RI, Killoran JH, et al: Clinical utility of 4D FDG-PET/CT scans in radiation treatment planning. Int J Radiat Oncol Biol Phys 2012;82:e99-e105 Hof H, Rhein B, Haering P, et al: 4D-CT-based target volume definition in stereotactic radiotherapy of lung tumours: Comparison with a conventional technique using individual margins. Radiother Oncol 2009;93:419-423 Vedam S, Archambault L, Starkschall G, et al: Determination of prospective displacement-based gate threshold for respiratory-gated radiation delivery from retrospective phase-based gate threshold selected at 4D CT simulation. Med Phys 2007;34:4247-4255 Saw CB, Brandner E, Selvaraj R, et al: Brandner E, Selvaraj R, et al: A review on the clinical implementation of respiratory-gated radiation therapy. Biomed Imaging Interv J 2007;3:e40 Wink NM, Chao M, Antony J, et al: Individualized gating windows based on four-dimensional CT information for respiration-gated radiotherapy. Phys Med Biol 2008;53:165-175 Schwarz JK, Lin LL, Siegel BA, et al: 18-F-fluorodeoxyglucose-positron emission tomography evaluation of early metabolic response during radiation therapy for cervical cancer. Int J Radiat Oncol Biol Phys 2008;72:1502-1507 Shreve P, Swanston NM, Faasse T: Positron emission tomographycomputed tomography protocols for radiation therapy planning and therapy response assessment. Semin Ultrasound CT MR 2010;31: 468-479

307 120. Faasse T, Shreve P: Patient and image data management in positron emission tomography-computed tomography for radiation therapy and therapy response assessment. Semin Ultrasound CT MR 2010;31: 480-489 121. Segall GM: Therapy response evaluation with positron emission tomography-computed tomography. Semin Ultrasound CT MR 2010; 31:490-495 122. Blodgett T: Best practices: Consensus on performing positron emission tomography-computed tomography for radiation therapy planning and for therapy response assessment. Semin Ultrasound CT MR 2010;31:506-515 123. Rohren EM: Positron emission tomography-computed tomography reporting in radiation therapy planning and response assessment. Semin Ultrasound CT MR 2010;31:516-529 124. Mac Manus MP, Hicks RJ, Matthews JP, et al: Positron emission tomography is superior to computed tomography scanning for response-assessment after radical radiotherapy or chemoradiotherapy in patients with non-small-cell lung cancer. J Clin Oncol 2003;21: 1285-1292 125. Mac Manus MP, Hicks RJ, Matthews JP, et al: Metabolic (FDG-PET) response after radical radiotherapy/chemoradiotherapy for non-small cell lung cancer correlates with patterns of failure. Lung Cancer 2005; 49:95-108 126. Aristophanous M, Yong Y, Yap JT, et al: Evaluating FDG uptake changes between pre and post therapy respiratory gated PET scans. Radiother Oncol 2012;102:377-382 127. Li T, Xing L: Optimizing 4D cone-beam CT acquisition protocol for external beam radiotherapy. Int J Radiat Oncol Biol Phys 2007;67: 1211-1219 128. Boda-Heggemann J, Lohr F, Wenz F, et al: kV cone-beam CT-based IGRT: A clinical review. Strahlenther Onkol 2011;187:284-291 129. Bujold A, Craig T, Jaffray D, et al: Image-guided radiotherapy: Has it influenced patient outcomes? Semin Radiat Oncol 2012;22:50-61 130. Smeenk C, Gaede S, Battista JJ: Delineation of moving targets with slow MVCT scans: Implications for adaptive non-gated lung tomotherapy. Phys Med Biol 2007;52:1119-1134 131. Maurer J, Pan T, Yin FF: Slow gantry rotation acquisition technique for on-board four-dimensional digital tomosynthesis. Med Phys 2010; 37:921-933