Control, Correction, and Modeling of Setup Errors and Organ Motion GeraldJ. Kutcher, Gikas S. Mageras, and Steven A. Leibel

As advances in radiotherapy technology enable higher precision treatments, it becomes increasingly important to understand the factors that contribute to treatment uncertainty. The recent developments in imaging modali- ties and computer algorithms have made possible quan- titative measurements of treatment uncertainties on statistically significant numbers of patients, which has led to new strategies for reducing as well as incorporat- ing them into the treatment planning process. This artii:le reviews the current literature on two sources of uncertainties deemed important in photon therapy, namely, patient localization (setup) errors and organ motion. In the area of patient localization there has been increasing work on protocols using electronic portal

imaging devices to correct setup errors. These protocols are derived from probability analyses based on knowl- edge of setup errors for a population of patients in combination with defined clinical endpoints. Measure- ments of organ motion and methods to correct or control it have been more limited, due partly to the larger difficulties in imaging and motion characteriza- tion. We also review two paradigms for accounting for uncertainties in treatment plans: the conventional ap- proach, which adds a margin around the tumor volume, and an alternative one, which includes uncertainties directly in the dose distributions of the tumor volume and nearby normal organs. Copyright �9 1995by W.B. Saunders Company

I nterest in t rea tment uncertainties has grown over the last decades, driven by medical needs and

technological advances. Conformal therapy, which seeks to manipulate the dose distribution to improve the therapeutic ratio, has brought into sharper focus the competi t ion between tumor control and tissue toxicity. However, as dose distributions become more conformal they may become more sensitive to treat- ment uncertainties, such as setup errors and organ motion. Fur thermore , if target doses are to be increased, it may prove efficacious to fur ther confine the high-dose volume leading to fur ther sensitivity of the plan to t rea tment uncertainties. At the same time technological advances (for example, three- dimensional [3-D] t rea tment planning systems, multi- leaf collimation) have not only made it possible to pursue conformal therapy, 1 but have also led to new tools like electronic portal imaging devices (EPIDs), which are likely to prove useful in reducing treat- ment uncertainties.

There are essentially two strategies for confront- ing t rea tment uncertainties: one is to a t t empt to reduce them, the second is to account for them in the t rea tment plan. These two approaches are comple- mentary ra ther than contradictory- because it is unrealistic to expect to el iminate all t r ea tment

From the Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY.

Supported in part by Grant No. CA 59017from the National Cancer Institute, Department of Health and Human Services, Bethesda, MD.

Address reprint requests to Gerald J. Kutcher, PhD, Department of Medical Physic6 Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY, 10021.

Copyright �9 1995 by W..B. Saunders Company 1053-4296/95/0502-0006505.00/0

uncertainties. To take one example, EPIDs have finite spatial resolution and, when used to measure (and correct) setup errors, contain an inherent uncer- tainty. In addition, they may introduce errors in their own right because of limitations in the algorithms used to measure the setup error; thus, they may lead to an under or overcorrection of the patient 's posi- tion. ~ Fur thermore , in clinical practice the pat ient 's position is generally modified only if the measured setup error exceeds an action level. The criteria used to choose an action level will necessarily reflect a t radeoff between the effort required to correct the patient 's position and the desired precision and quality of the t rea tment : as the action levels are tightened, the number of corrections are increased, as is the cost of the t reatment . Even if the resolution of the measurement devices were substantially re- duced, finite action levels would still be used in practice. Thus, there will be always be uncorrected and uncontrolled setup errors in patient t reatments . A similar analysis would apply, even more so, to organ motion. Therefore, the nature of uncorrected uncertainties should be understood and their effect accounted for in t rea tment plans. Two generic strat- egies are reviewed here. One is to account for uncertainties with margins around the tumor, s the other is to eschew such margins and include uncer-

45 tainties directly in the dose distr ibutions. , In this article we consider only two sources of t rea tment uncertainty; namely, setup errors and organ motion. Our focus derives not only from our own work and interest in setup errors and organ motion, but also from the conviction that these are two of the most important uncertainties in photon therapy. The main body of the article is in three sections. We first review

1 3 4 Seminars in Radiation Oncology, Vol 5, No 2 (April), 1995.'pp 134-145

Control, Correction, and Modeling 135

the nature of the problem, that is the current l i terature on setup errors and organ motion. We next discuss strategies that have been reported for reducing setup errors and organ motion, and their merit. Finally, we discuss how uncorrected and uncon- trolled t rea tment uncertainties may" be incorporated into the planning process. These sections are pre- ceded by a discussion of some basic concepts and terminology used throughout the body of the text, and followed with some reflections on the direction of developments in the next few years.

Definit ions

Target Volumes and Tissues at Risk

We follow the definitions in The Internat ional Com- mission on Radiat ion Units Report 50 throughout? Although ICRU defines a number of volumes, we will concentrate on those of importance for defining and analyzing setup errors and organ motion. ICRU first defines a gross tumor volume (GTV) as the "gross palpable or vis ible/demonstrable extent and location of malignant growth" in short, the gross tumor. The clinical target volume (CTV) is the G T V " a n d / o r subclinical microscopic mal ignant disease which have to be el iminated." The CTV is that volume of tissue that must be eradicated to achieve the aims of therapy. Although both of the above definitions refer to mal ignant (or potentially malignant) tissue, a third and purely geometrical concept is introduced, namely, the planning target volume (PTV). It is defined to "select appropriate beam sizes and beam

a r r angemen t s , taking into consideration the net effect of all possible geometrical variations in order to ensure that the prescribed dose is actually ab- sorbed in the CTV. ''3 The PTV differs from the CTV because of one and only one generic issue: t rea tment uncertainties. For example, consider setup errors and organ motion. Because the PTV is a fixed volume in space in which the CTV moves due to setup errors and organ motion, the tumor-bearing regions (CTV) would receive no less than the pre- scribed dose as long as those motions were contained within the PTV, and the prescribed isodose surface did not encroach into the PTV. The aim of a t rea tment plan is, therefore, to assure that the prescribed dose distribution for the PTV is achieved; once the PTVis defined, no further reference to CTV is needed. In regard to normal organs, ICRU defines "organs at risk" as those normal tissues whose radiation sensitivity may affect the t rea tment plan, but makes no reference to the role of uncertainties.

Patient 2

..::':': Left Lateral

Superior

SOO@

Inferior

Patient I

Right Lateral

Figure 1. Random and systematic errors for two pa- tients. Each dot represents one measurement of the patient's position relative to the planned or prescribed position. For simplicity, the measurements are presented in a plane. The arrow from the origin to the average position (center of gravity) of the dots represents the systematic setup error for the patient; the difference between the position of each of the dots and the average represents the random error distribution for the patient.

We will re turn to this issue later. The ICRU nomen- clature is similar to an earlier National Cancer Insti tute Report on 3-D t rea tment planning. 6 In that study, the terms corresponding to GTV, CTV, and PTV were the tumor volume, the target volume, and the mobile target volume, respectively.

Systematic and Random Errors

In the discussions below we distinguish between random and systematic errors. To understand these concepts, we present an example for setup errors. Figure 1 represents setup errors in which the patient can be translated in the lateral and superior/ inferior directions. Each dot in the figure represents a daily measurement of the pat ient 's setup error, that is, the difference between the measured position (defined by a portal films or EPID image) and the prescribed position* (defined by a simulation film or digitally reconstructed radiograph). I f there were no setup error, then a dot would be placed at the origin. For each patient, the average position (or center-of- gravity) of the daily setup errors is the patient 's systematic setup error, represented by an arrow from the origin. The ensemble of differences between the setup errors and their mean comprises the distribu- tion of random setup errors for the patient. There-

*As used here, the prescribed position of the patient is defined by the relationship (registration) of the radiation field relative to the patient's anatomy. This registration is usually displayed on simulator films or digitally reconstructed radiographs.

136 Kutche~ Mageras, and Leibel

fore, each patient has a systematic setup error and a distribution of random setup errors. The same argu- ments could be made for pat ient number 2 and so on. Thus, for a population of patients, we could derive a distribution of systematic setup errors. Fur thermore , if the random setup error distribution is the same for all patients in the popula t ion] and if we pool the random errors for all the patients, we would obtain a pat ient-populat ion distribution of random setup er- rors. These two distributions could be used to gener- ate a distribution of total setup errors, and if the former are Gaussian (which will be true for large populations), then we could specify the total, system- atic and random distributions by their means and their s tandard deviations, ~t, (T~, and ~j., respectively By repeat ing this procedure for different t rea tments (and immobil izat ion methods) we would have a concise representa t ion of the systematic and random setup error distributions by site and technique. In principle, a similar analysis could be applied to organ motion, al though a division of errors into systematic and random components might prove cumbersome if there are significant spatial distortions.

It is impor tant to keep in mind that each pat ient has a single systematic error and a distribution of random errors (unless there is only one t rea tment fraction). The notion of a distribution of systematic

errors implies a population of patients, whereas the notion of a distribution of random errors does not.

Sta tements about systematic errors may refer either to a single patient, with his or her known and

measured systematic error, or may refer to a popula-

tion of patients from which statistical s ta tements about that population could be derived. I t is near a

truism to state that systematic errors are reduced by correcting the patient 's position based on judicious

review of portal films (see below for more details), whereas random errors are reduced by improved fixation and careful daily positioning with lasers.

The N a t u r e o f t h e P r o b l e m

Setup Errors

Setup errors have been of continuing interest in radiation oncology over the past decades. We will focus on setup errors of the pelvis 7-I6 (Table 1) because Verhey 17 has reviewed the l i terature in

detail by site and immobilization technique. The pelvis has been the site of a number of recent studies due in part to interest in using conformal techniques

for t reat ing prostate cancer. The table reveals some evolution in methodologies and results.

Table 1. Setup Error Measurements for the Pelvis

Investigator Immobilization Setup Errors Technique Comments

Soften a Yes 3.3 mm* Port/sim films 5 consecutive days; visual comparison; No 8.0 mm* Port/sim films average magnitude of total error

Rabinowitz 9 No 5.6 mm* Port/sire films Visual comparison Rosenthal t~ Yes 4.0 mm* Port/sire films Isocenter deviation using AP films; 22

No 6.0 mm* Port/sim films patients Richards II No 57% patients < 10 mm Port/sim films Visual comparison of AP/PA films Bijhold 7 No Lat (1.2 -- 1.7) mint EPID/sim films Template matching

SI (2.0 • 1.8) mmt AP (1.8 • 2.3) mint

el-Gayed 12 No Lat (-0.4 - 2.8) mint EPID/sim films Template matching; 10 patients SI ( - 1.1 • 1.6) mm~ AP (0.7 • 2.4) mmi"

Hanley 13 Yes Lat (0.2 • 2.4) mmt Digitized port/sim films Template matching; 15 patients SI (0.3 • 1.8) mm~ AP (-0.2 • 1.8) mmt

Michalski t4 No One edge shift 2.0 ram* EPID/sim films Block overlap isofrequency distribu- tion; 4 patients

Cionini j5 No Lat ( - 1.3 • 3.8) mm# EPID/sim films Template matching; 9 patients, 2 insti- SI (-0.7 • 2.8) mmi tutions AP (0.1 • 5.5) mm~

Herman ~6 ) 70% < 5 mm EPID/sim films Visual comparison 18% < 10 mm 12% > 10 mm

*Total setup error: average of the magnitudes of the displacements. tTotal setup error: average (-+(rt) of the displacements.

Control, Correction, and Modeling 137

For the most part, earlier studies used simulator and portal films and visual comparison to extract the setup errors. More recently, EPIDs and digitized port films have been introduced along with image match- ing algorithms. Another point to note is that more recent studies generally report the total error along with the random and systematic components. How- ever, to be concise, the mean and standard deviation for the total error alone is recorded in entries in the table for Bij hold] el-Gayed, l~ Hanley,13 and Cionni.I5 For example, for el-Gayed's population] 2 the total lateral displacement is 0.4 mm -- 2.8 mm. This implies the mean lateral systematic error for the population of 10 patients is less than 1 mm; if it were otherwise, there would be cause for concern, gt, is 2.8 mm; while the random and systematic components will be smaller. In contrast, somewhat earlier stud- ies 8-1~ tend to report other quantities, for example, the average of the magnitudes of the displacements of the isocenter.

The total setup error for the pelvis can be as small as 2 mm as reported by Bijhold, 7 el-Gayed, ~2 and Hanley, t3 although larger setup errors are possible. These magnitudes should be contrasted to the range of organ motions discussed below. Finally, it should be noted that the number of patients in the popula- tions are quite small, although, in an update, Hanley et a118 report on 50 patients. Because target margins will generally be set at 1.5 to 2 standard deviations, small data sets will lead to large uncertainties in the target margins. Moreover, it is virtually impossible to derive a reliable estimate of the systematic compo- nent for small populations because each patient provides but one data point. Clearly more work is needed.

Organ Motion Organ motion refers to the variation of organ posi- tion and shape relative to the skeletal anatomy. During a single treatment, organ motion can be caused by breathing, heartbeat, swallowing, and peristaltic motion; between treatments, it may be caused by variable filling of the bladder or gastrointes- tinal tract, weight gain or loss, and other factors. Organ motion can be significant for certain treat- ment sites and, although it can be taken into account for the tumor with appropriate margins (following ICRU Report 50), nontarget tissues may have larger irradiated volumes than is apparent from the treat- ment plan.

Several published studies have focused on pros- tate motion for the reasons mentioned before. Ten

Haken et al ju have examined whether partial filling of the bladder and rectum with contrast material has an effect on prostate position. A comparison in 50 patients of computed tomography (CT)-based treat- ment plans without contrast to simulator films taken with the rectum and bladder opacified showed indi- rect evidence of prostate movement, with a range from 0 to 2 cm and an average of 0.5 cm, mostly in the anterior and/or superior direction. In 6 addi- tional patients, CT scans with and without 50 to 60 mL of contrast in the bladder and/or rectum were compared. 19 An average change of 0.35 -- 0.25 cm in the center-of-mass of the prostate was observed, primarily in the superior part of the prostate and the seminal vesicles.

More recent studies have concentrated on long- term variation in prostate position by employing multiple CT scans. Melian et al 2~ performed four serial CT scans over a 5- to 6-week period on each of 12 patients in a prone position. The borders of the PTV were observed to shift from 0 to 3.0 cm in the anterior-posterior (AP) direction and were corre- lated primarily with bladder filling. The superior aspects of the target volume were particularly af- fected. Lateral displacement of up to 1.6 cm was also observed, but was uncorrelated with bladder or rectal filling. Beard et a121 examined movement of the prostate and seminal vesicles, for 12 patients who underwent two CT scans 4 weeks apart in the supine position. The greatest movement was observed in the AP direction, up to 1.6 cm with a median value of 0.45 cm, and appeared to correlate with bladder and rectal filling. Forman et a122 examined patients who received CT scans on a weekly basis over the treat- ment course. An initial study of five patients showed an average prostate and seminal vesicle movement of 1.7 cm (range 0 to 3.5 cm), primarily in the AP direction. In an alternative approach, Balter et a123 measured prostate motion by means of implanted radio-opaque markers that were visible in portal films. A study of 15 patients over the treatment course yielded standard deviations in prostate posi- tion of 0.22, 0.08, and 0.18 cm in the AP, lateral, and cranial-caudal directions, respectively.

These results point to some conclusions. (1) There are large discrepancies in the reported magnitude of prostate movement, resulting from a variety of factors: different treatment and measurement proto- cols, the measured quantities differ, and the seminal vesicles may or may not be included in the analysis. (2) Although some of the reported results are prelimi- nary, there appears to be agreement that AP move-

138 Kutcher, Mageras, and Leibel

ment is largest, that movement occurs primarily in the superior part of the prostate and seminal vesicles, and that movement correlates with bladder and rectal filling. Moreover, there are indications that bladder filling is more significant for prone patients and rectal filling for supine patients. 3 The dosimetric consequences of organ motion for conformal treat- ments can be a significant.Ig,20,22

Turner et a124 studied bladder and rectal move- ment for 30 patients with bladder cancer. Three CT scans subsequent to the initial planning scan were performed at weekly intervals over the treatment period. Bladder area as measured on the mid- bladder CT slice was found to have a range from 16.2 to 80.9 cm 2, while the change in bladder area for an individual patient was found to vary from 3.3 to 29.1 cm 2. Displacements of the bladder wall of at least 1.5 cm toward the 95% isodose line were observed in 10 patients (33%) in one or more of the subsequent CT scans. The maximum change in rectal diameter for individual patients over the treatment period ranged from 0.3 to 4.6 cm, with a median change of 1.3 cm. In an investigation of the factors influencing bladder movement, patients whose posterior bladder wall changed by more than 1.5 cm were more likely to have correspondingly large ( > 2 cm) change in rectal diameter. On the basis of these results, the authors recommended using no less than 2.0 to 2.5 cm margins.

Organ motion studies in the thorax have concen- trated on short-term tumor movement during car- diac and respiratory cycles. Ross et a125 examined 20 patients who were planned with conventional simula- tion techniques, then evaluated with ultrafast (cine) CT. They found that in 3 patients (15%) the neo- plasm was not fully contained within the geometric field edge for part of the observation period (7 seconds, or approximately 10 cardiac cycles and 2 to 3 respiratory cycles), although the treatment portals were designed with a 1.5 cm margin. The minimum tumor dose for the 3 patients was calculated to be below 50% of the prescribed dose. The study con- cluded that larger margins are required for tumors in the lower lobes (average movement 10 mm) and near the heart or aorta (10 to 15 m m movement), whereas smaller margins are acceptable for tumors in the upper lobes or attached to the chest wall (average movement l mm). Ross et a125 also strike a note of caution: conventional CT images may overes- timate size of a moving lesion because of motion of the lesion during the scanning interval. If a margin for motion is added, this may result in too large a

trFV. An alternative method of PTV definition sug- gested by Onogi et a126 is to perform several ultrafast CT scans during one respiration or cardiac cycle. The

is then defined by the outer envelope containing the tumor in all the scans.

Short-term organ movement has also been mea- sured using recorded flouroscopic movies. 27,28 One such study, which used implanted markers in the lung and liver, found that the ventilory motion differed by more than 5 mm from a physician's estimate inferred from observing similar movies in the absence of markers. 27

In light of the poor statistics in the published data, there is clearly a need for additional studies with larger patient populations to better characterize organ motion and the influence of factors such as age, weight, organ size, and treatment technique. Consensus should be established on what should be measured. Results should preferably be represented in the form of movement frequency distributions as a function of position within the organ, for example, upper versus lower lobes of the lung. Reliable fre- quency distributions are important because the ex- tremes in motion, if used to define target margins, could lead to inordinately large treatment volumes. In addition, it would be useful to have a library of CT organ motion studies available over wide-area com- puter networks so that research institutions could pool their data samples.

Correct ing Setup Errors and Organ Mot ion

Rational protocols that balance cost and efficacy should be developed to reduce and control setup errors and organ motion. The first step is to assess the current treatment methodology- by measuring treatment uncertainties in a patient population and analyzing the dosimetric consequences. This will assess the adequacy of currently used margins, which generally have been estimated from anecdotal infor- mation, and may indicate ways of modifying them. Roach et a129 performed such an analysis to define "ideal margins" for 6-field conformal treatments of the prostate. Minimum margins required to encom- pass the GTV within the 95% prescribed isodose surface were determined, then additional margins were included to take into account published data on extracapsular penetration, setup error, and prostate movement. An interesting outcome was the need for nonuniform margins, which varied from 0.75 to 2.25 cm about the GTV. The authors propose that this

Control, Correction, and Modeling 139

strategy may maximize the probability for tumor control while minimizing the risk of morbidity. Bai- ter et aP ~ have analyzed the relationship of margin size to target coverage and normal tissue sparing in the presence of setup errors. For a 4-field box treatment of the prostate, they conclude that a margin of 1.2 cm margin is required to achieve 95% CTV coverage with conventional correction proce- dures, whereas a 6-ram reduction in the margins would be possible with daily, corrections (before treatment) of setup errors exceeding 1 cm.

Protocols for Reducing Setup Errors

The importance of portal films in detecting patient positioning and field placement errors has been widely recognized; however, the frequencywith which the films are taken varies considerably. A survey of radiotherapy centers has found that although 90% of the institutions take port films on the first day of treatment, only 40% repeat them on a weekly basis.31 Mitine et a132 have emphasized the importance of taking port films on the first or second day of treatment, as a means of detecting systematic errors resulting from the treatment preparation chain. In a study of head and neck patients, they found that the majority of the systematic localization errors were detected in the first portal films, and that most errors detected subsequently were considered small (less than 5 mm). Recently, the American Association of Physicists in Medicine has recommended film review of all t reatment fields at least once per week, based on studies that have shown that (1) localization errors of the order of 1 cm occur relatively fre- quently, 10% to 36% of the time depending on treatment site; and (2) the relative frequency of localization errors decreases as film checks become more frequent. 33 In addition, there may be gradual changes in the patient displacement over time; thus, E1-Gayed et a112 recommend that for treatments requiring a high precision, localization checks should be performed throughout the treatment course.

With the advent of EPIDs, which can rapidly capture portal images, pilot studies have been per- formed to evaluate the feasibility of daily measure- ment and correction of the patient's position before treatment. 34'35 However, it has been recognized that this approach adds considerably to the overall treat- ment time, due in part to limitations in the available software toolsg,~6,34 In addition, for conformal therapy, the small apertures make accurate measurements difficult with verification images of the treatment field and, although double-exposure portal images

(taken before treatment) can overcome this prob- lem, their use on a daily basis would result in a large dose outside the target volume. Because of these issues, attention has also focused on protocols in which a decision, based on setup measurements, is made after the treatment, and a correction, if needed, is applied to the next patient setup. 7,32,36-38 Rather than correct both systematic and random errors, the aim is to maintain the systematic error below some acceptable level. Because a given measurement con- tains both systematic and random components, the decision rules are based on probabilities and require knowledge of the probability distribution of each error. For example, if a setup error measurement exceeds 3cry, then there is a high likelihood that the setup error contains a systematic component.

Bel et a136 have designed a protocol that mini- mizes the number of measurements and corrections. Patient setup is measured for a limited number of fractions following the start of treatment. A correc- tion is applied to the patient's position only when the setup error, averaged over these measurements, exceeds an action level (see Fig 2). The size of the

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Correction Applied

\, I

/ e - . .@ s t \ ,"

Corrflll~c tio n Applied

f I I I |

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Figure 2. An example application of the correction protocol. (-Q-) Displacement, (m) average displacement, (--) action level. In fraction 1, the average displacement davg exceeds the action level; therefore, a correction is applied to fraction 2, and the action level and calculation of davg are reinitialized. Following the correction, a measure- ment is made for fraction 2, davg is less than the action level, so a reduced action level is applied to fraction 3. In fraction 3, da,.g (the average of fractions 2 and 3) exceeds the action level, resulting in a correction to fraction 4 and reinitializa- tion of the action level and d~vg. In fractions 4 and 5, there have been two consecutive measurements that did not require a correction, and so subsequent measurements are not required. Adapted and reprinted with permission, a6

140 Kutcher, Mageras, and Leibel

action level decreases as the number of fractions used to determine the mean increases. The shrinking action level is predicated on the following assump- tion: the precision in determining the mean setup error, and hence the systematic error, improves with the number of measurements . For one scenario in which the systematic errors are twice as large as the random errors, the protocol results in less than 5% of the setups having a large error (greater than 3 ~rr), while requiring 3.2 measurements and 0.9 correc- tions per pat ient on average.

Shalev and Gluhchev 37 have proposed a scheme in which the setup error is evaluated after each frac- tion, and if it exceeds some action level, a correction is applied to the next fraction. Determinat ion of the action level requires a clinical determinat ion of an acceptable systematic error (based on the dosimetric consequences) and knowledge of the inherent accu- racy of the measurement and correction procedures.

Yan et aP 8 have described a theoretical frame- work for deriving "accept or reject" decisions. From measurements of previous t rea tment positions, a confidence region for a subsequent t rea tment posi- tion is est imated. The confidence region is compared with an acceptable region, which represents the allowable margin of position variation. The differ- ence between the two regions is then evaluated to arrive at a decision for accepting or correcting the pat ient 's position. The model has the ability to include the effects of a possible long-term drift in pat ient 's position into the confidence region esti-

mate.

Strategies to Correct or Control Organ Motion

Organ motion is inherently more difficult to correct than setup error. First, it is difficult or impossible to discern the location of most organs from a megavolt- age portal image. Second, correcting for motion during t rea tment requires control systems on the t rea tment machine that are synchronized to the source of motion in the patient. An example is to gate the delivery of dose with the respiratory cycle for tumors in the thorax. Given the technological com- plexity and the stringent safety features that are required, it is unlikely that such control systems would be commercially available in the near future.

There have been two approaches to determining target position from one t rea tment to the next that include setup errors and organ motion. Nakagawa et aP 9 have developed a system which has a CT scanner in the same room as the t rea tment unit and shares

the same t rea tment couch. The patient is scanned in the t rea tment position and the target is de termined on each CT slice; this information is then used to adjust a mult i leafcoll imator . A second approach is to detect the target organ by means of implanted radio-opaque markers. For example, marker posi- tions can be accurately measured with computerized recognition software, 4~ and automatically tracked via megavoltage portal images. 42 A correction would presumably involve repositioning the patient and /o r adjusting the mult i leafcoll imator.

An alternative to correction is control. Examples include insertion of a rectal stent to establish repro- ducible dilation of the rectum; 43 the use of a Foley catheter to inflate the bladder to a known amount at each treatment;19 or, more simply, requiring patients to fill or empty their bladders before t reatment . I An alternative strategy in bladder t rea tments is to fill the bladder sufficently to simulate its position and empty it before t rea tment in an a t tempt to assure that the bladder is fully within the t rea tment por- tal. 44 These and similar a t tempts to control organ motion have their limitations. Whereas interven- tional procedures may lead to increased control, they may be difficult to implement on a wide basis. To cite one example, in conformal therapy of the prostate, doses in the range of 80 Gy would require as many as 45 applications of a rectal stent and 45 catheteriza- tions to control the rectum and bladder.

Removing large systematic organ motion errors between planning and t rea tment is an important aim; for example, large systematic errors would occur in t rea tment of the prostate if the patient were scanned with a full bladder, but t reated with an empty one. However, it is not so clear whether random organ motion of nontarget tissues (either during or between t reatments) is necessarily bad. For example, small random motion of a nontarget organ into and out of a high-dose region may lead to a lower total dose spread out over a larger volume of the organ; tissues with a small volume effect would presumably have reduced toxicity. 45

Incorporation of Uncorrected and Uncontrol led Setup Errors and Organ Motion in Treatment Plans

As the discussion above shows, setup errors and organ motion occur throughout t rea tment , even after the most assiduous a t tempts to remove them. Moreover, because of cost and variations in the quality of t r ea tment delivery, the level of uncor-

Control, Correction, and Modeling 1 4 1

rected errors will usually be larger than the theoreti- cal limit. The issue is not whether errors are present or absent, but rather their magnitude, the effort required to reduce them, and their implications for planning treatments. This section deals with the latter issue, namely, how treatment plans can reflect uncorrected and uncontrolled setup errors and organ motion. Two paradigms will be discussed: one uses margins around the CTV and calculates nominal dose distributions (ie, without uncertainties) that are evaluated for the PTV; the other incorporates the uncertainties in the dose distributions that are evalu- ated for the CTV. In the former paradigm, setup error and organ motion distributions are used to derive margins around the CTV, in the latter they are used to derive altered dose distributions. The former approach is standard and ubiquitous, the latter is a relatively recent and evolving development. For a further discussion of these paradigms with examples see Kutcher et al. 5

Target Margins around CTV The standard approach, as described earlier, adds a margin around the CTV to account for the types of treatment uncertainties outlined in this article. How large are the margins, and how are they to be applied? ICRU Report 503 argues that to obtain the standard deviation for the total uncertainty, ~ , combine the random and systematic components, crr and cry, in quadrature. The number of standard deviations in the total error used to define the margin is a clinical issue. The tighter the margin, the more likely that underdoses will occur, whereas the larger the margin, the more normal tissue irradi- ated. Although the latter implies a higher likelihood of delivering the prescribed dose to CTV, it may, ironically, lead to a lowering of the prescription dose because of the higher volume of irradiated normal organs. 46 With respect to such issues, Goitein 47 has suggested the use of 1.5 standard deviations (which encompasses about 85% of the population) for clini- cal situations. However, the full implication of setup errors and organ motion is, we believe, best appreci- ated, not within the paradigm of target margins, but rather within one that incorporates uncertainties in the dose distributions. This approach is described below first for setup errors and then for organ motion.

Modeling Setup Errors The underlying notion in modeling setup errors is the assumption that the position of the radiation

isocenter relative to the skeletal anatomy of the patient differs from the planned treatment. For example, Hunt et al, 48 for nasopharynx patients treated with 3-D treatment plans, measured the setup error at each daily fraction and calculated the associated dose distribution. For the course of therapy they generated, for each patient and each organ, a family of daily dose-volume histograms (DVHs). Shown in Fig 3 are the nominal DVH and the envelope of the daily DVHs for one of the patients. As can be noted in the figure, the nominal DVH for the brainstem represents the most optimistic esti- mate of the volume irradiated to high dose. This is a consequence of the planning technique which, in order to respect the tolerance of the brainstem, produced a horseshoe shaped dose distribution sur- rounding the brainstem on three sides. With such a distribution, the high dose-volume of the brainstem is increased by almost any displacement of the patient relative to the planned position. For our purposes, there are two salient points that follows from this study. (1) There is a distribution of dose at each point in the patient, rather than a single nominal dose distribution. (2) Representation of treatment uncertainties within the dose distribution shows their dosimetric effects for nontarget (as in Fig 3) as well as for target tissues; this should be contrasted with the conventional paradigm that

, 00

.................... Average 80 - Nominal

Envelope A o~ 60 - ~ Envelope

�9 "~ 40 - >

20 " " ~%%o%

0 t E �9 1 . 1 , ~ -

o ~o 40 60 80 1oo 1 2 o

Dose ( % )

Figure 3. The nominal (or planned) DVH for the brainstem and the envelope of daily DVHs for a patient treated for nasopharynx cancer with a 3-D conformal technique. At each fraction, the patient's position was measured and used to generate a DVH whose envelope is represented in the figure. (Reprinted from Int J Radiat Oncol Biol Phys 48 with kind permission from Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington 0X5 1GB, UK.)

142 Kutcher, Mageras, and Leibel

assigns spatial margins solely to the target , and does not consider uncertainties for nontarget tissues.

However, the above approach requires daily mea- surements of the pat ient ' s position. More to the point, the calculations are retrospective ra ther than prospective. They represent what actually happens to an individual patient , not what might happen. Be- cause they are retrospective, they cannot be used per se in the planning process. Alternative approaches to modeling errors in dose distributions a t tempt to be prospective and predict (in a statistical sense) the likelihood that a DVH or dose distribution would occur for the patient by considering that pat ient as one member of a population. Thus, dose distribu- tions and DVHs may be assigned confidence limits (CL-DVHs); the part icular confidence level chosen for a CL-DVH is dictated by clinical considerations, similar to the number of s tandard deviations in setup error used to define the target margin. We describe briefly below two approaches to this type of predictive and statistical dose calculation.

Goitein 4 has described a method that would in- clude random and systematic errors in the dose distributions. He argues that, for example, pat ient translations may be represented by an equal and opposite movement of the t rea tment field aperture. Because patients will move in different directions with different likelihoods, a family of t rea tment

apertures could be generated. To represent this situation, three aper tures are calculated (as shown in Fig 4): a nominal; a second made larger than the nominal by an amount equal to the range in pat ient motion (maximal); and a third made smaller by the same amount (minimal). This leads to three dose distributions: nominal, maximal, and minimal. He further argues that the confidence limits for the maximal and minimal dose distributions reflect the individual confidence limits used to define the dis- placements of the apertures. This approach is ex- tended further to include other sources of uncer- ta inty including calibration uncertaint ies , beam modifier positioning errors, and so on. Organ motion is not explicitly considered, but could presumably be included.

Kutcher et al 5 first consider setup errors (organ motion is t reated separately, see Mageras et a149 and below). Random and systematic spatial setup distri- butions are considered independently. The model assumes that the random error distributions are known and are the same for all patients; 7 however, the systematic error for a pat ient is not known a priori, but its effect is predicted in a statistical sense.

a x i m a l

Nominal

F i g u r e 4. The nominal, minimal, and maximal field apertures. Because of daily setup errors, the position of the aperture relative to the patient varies. This implies that there is a region that is always irradiated (or in a statistical sense is always irradiated with a certain likelihood) and that region is contained within the minimal aperture. Similarly, there is a region that is unlikely to be irradiated and that region lies outside of the maximal aperture. The nominal aperture is used to generate the planned or intended dose distribution whereas the minimal and maxi- mal apertures are used to generate dose distributions that account for patient uncertainties. (Adapted and reprinted with permission. 4)

First, the mean DVH due to random setup errors is calculated using a convolution method of Chui et al. 5~ Then the systematic error is included by sam- pling the distribution of systematic setup errors for a population of patients. Each sample yields a setup error, which may be modeled by an equal and opposite motion of the radiation pa t te rn relative to the skeletal anatomy. An ensemble of such calcula- tions will yield an ensemble of doses that may be ranked. The dose distribution corresponding to the X th percentile in the ranked doses corresponds to the X% confidence limit dose distribution and X% CL-DVHs. Shown in Fig 5 are the nominal DVH and the 15% and 85% CL-DVHs for the rectum (for a 6-field prostate t rea tment plan). For example, the 15% CL-DVH should be interpreted to mean that there is a 15% chance that the DVH for the patient 's t rea tment course would be worse.

Modeling Organ Motion Because of the lack of da ta on organ motion until recent years, there have been few developments for modeling organ motion. For example, in the mul- tiple CT scan studies of organ motion, the dosimetric consequences have been examined by applying the t rea tment plan from the simulation CT scan, or

Control, Correction, and Modeling 143

lO0 -

80.

60'

E

40. ~>

2 0

Nominal 15% CL 85% CL

J �9 i ,

20 40 120

�9 j �9 , j ,

60 80 100

Dose (%)

Figure 5. Nominal and CL-DVHs of the rectal wall for a six-field treatment plan of the prostate. It was assumed that the spatial systematic setup error distribution for a population of patients was Gaussian with a standard deviation of 5 mm for the three possible directions of translation: there were no rotations of the patient and no random setup errors. The CL-DVHs in this figure are a statistical measure of the effects of these setup errors on the dose distribution of the patient. However, the CL- DVHs in the figure do not account for correlated motion, as they would if a dose-based endpoint algorithm, as described in the text, were used. In this respect, these CL-DVHs are analogous to the maximal and minimal distributions of Goitein. 4 For an elaboration of this point and further discussion of the methodology from which this figure was drawn see Kutcher et al. 51 (Reprinted from IntJ Radiat Oncol Biol Phys 51 with kind permission from Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington 0X5 1GB, UK.)

s imula t ion radiographs , to the subsequent scans. I9,2~ However, application of this technique

would require multiple CT scans of all patients undergoing t rea tment , obviously a costly and imprac- tical solution.

An alternative approach, already discussed for modeling setup errors, is to derive predictions for a pat ient 's dose distribution based on da ta from a similar group of patients. Mageras et a149 have developed a method of incorporating organ motion uncertainties into 3-D prostate plans, which makes use of da ta from a multiple CT scan study of a cohort of "reference" patients 2~ to calculate confidence lim- its on the dose for any "study" patient whose treat- ment plan is available. The model assumes that the reference patients are representative of organ mo- tion for the patient population. The input da ta consist of contours of the target volume and organs at risk. A computer program records the differences in contour position and shape between the reference

pat ient 's simulation CT scan and one of the subse- quent scans, which have been previously matched with the simulation CT scan by aligning the peMc anatomy. This set of contour differences is used to adjust the contours on a study patient 's planning CT scan, thus simulating organ motion. The dose distri- bution is then calculated, and DVHs accumulated, by using the study patient 's originally planned set of t rea tment fields with the adjusted set of organ contours. The process is repeated over the set of reference patients and scans, resulting in a set of t rea tment plans. The ensemble of plans is ranked to yield CL-DVHs.

Summary and Future Direct ions

Setup errors and organ motion both have an impor- tant influence on the accurate and precise delivery of radiation t reatments . Recent developments of imag- ing modalities and image correlation algorithms make it possible to measure these errors on large enough patient populations to establish statistical confidence in the results. Indeed, we expect that there will be increased efforts to measure setup errors and organ motion over the near future.

If we consider setup errors first, we find that, as da ta continue to appear, there is evolving agreement on how to specify them (ie, with distributions for the random and systematic displacements of the iso- center from the planned position). This is in part due to the availability of EPIDs as well as the current state-of-the-art software tools for measuring position- ing errors. At the same time, there has been increas'- ing work on protocols to correct setup errors that rely on measured setup error da ta in combination with defined clinical endpoints and analytic algorithms to decide when and by how much to adjust the patient 's position. This will be an area of intense effort as protocols are developed and tested in clinical set- tings. Indeed, it is feasible that a multi-insti tutional study to determine the costs and benefits of these new developments over conventional film-based pro- cedures may" be warranted. Such a study could make recommendations on the design of commercial EPID systems as well as on protocols for pat ient localiza- tion.

Knowledge of organ motion and methods to control it is in a much more primitive state. As has been remarked earlier, there is too little da ta and much of it appears to be contradictory. Part of this stems from the fact that different endpoints are measured for different clinical situations. Moreover,

144 Kutcher, Mageras, and Leibel

o r g a n m o t i o n i t se l f is a m o r e com pl ex p r o b l e m t h a n

se tup er rors : some o rgans a re difficult to i m a g e w i th

conven t iona l r a d i o g r a p h y a n d o r g a n d i s to r t ion con-

founds m e a s u r e m e n t a n d analysis. Never the les s , be-

cause of its p o t e n t i a l i m p a c t on t he accuracy of

t r e a t m e n t delivery, s tudies o f o r g a n m o t i o n will be

in tens ive over t he fol lowing years .

W e expec t t h a t one cons equence of local izat ion

a n d o r g a n m o t i o n s tudies will be m o r e r a t i ona l

r e c o m m e n d a t i o n s on the m a r g i n s to be used for

widely p rac t i ced t r e a t m e n t s . O n the o t h e r h a n d , the

i nco rpo ra t i on o f u n c e r t a i n t i e s in dose d i s t r ibu t ions

m @ provide a n a l t e r na t i ve a v e n u e for c h a r a c t e r i z i n g

the i m p a c t of unce r t a in t i e s . T h e r e is a c e r t a i n logic in

the l a t t e r approach : t he biology is used to es tab l i sh a

CTV, while the physical u n c e r t a i n t i e s (as the res t of

the physics) a re i n c o r p o r a t e d in to the dose d is t r ibu-

t ions. I t is likely t h a t t he P T V type p a r a d i g m will

con t inue to d o m i n a t e t r e a t m e n t p l a n n i n g in the

n e a r fu tu re . However , th is a p p r o a c h will have to

a d a p t i t se l f to accoun t for the effects of s e tup e r ro rs

a n d o r g a n m o t i o n on n o n t a r g e t t issues as well as the

ca lcu la t ion of biological indices in the p r e sence of

unce r t a in t i e s . As occu r red w i th the P to lomeic sys-

t em , these c h a n g e s m a y lead to a level of complex i ty

t h a t m a y lead to a new p a r a d i g m .

Acknowledgment We thank Dr Joseph Hanley for working up Table 1.

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