A method to analyze 2-dimensional daily radiotherapy portal images from an on-line fiber-optic...

Inr J Radrarwn @,W/0R? BKI/ Phys Vol. 20. pp. 6 13-b I9 Printed in the U.S.A. All rights reserved.

0360-3016/91 $3.00 t .oO copyright 0 1991 Pergamon Press plc

0 Technical Innovations and Notes

A METHOD TO ANALYZE 2-DIMENSIONAL DAILY RADIOTHERAPY PORTAL IMAGES FROM AN ON-LINE FIBER-OPTIC IMAGING SYSTEM

MARY LEE GRAHAM, M.D.,’ ABEL Y. CHENG, M.SC.,~ LEWIS Y. GEER, B.SC.,~ W. ROBERT BINNS, PH.D.,~ MICHAEL W. VANNIER, M.D.’

AND JOHN W. WONG, PH.D.’

‘Mallinckrodt Institute of Radiology, Division of Radiation Oncology, Washington University School of Medicine, St. Louis, MO 63 110: ‘Fiber Imaging, Inc., St. Louis. MO 63 130; and 3Department of Physics, Washington University, St. Louis, MO 63 130

On-line radiotherapy imaging systems allow convenient treatment verification and generate a wealth of data. Quan- titative analysis of data will provide important information about the nature of treatment variations. Using an in- house fiber-optic imaging system to acquire daily portal images for five patients, we have developed a method to analyze the cumulative positional variation of blocks in the 2-dimensional images. For each beam arrangement used to treat a particular patient, a reference portal image was established. All other images for that patient were registered with respect to the anatomical landmarks visible on the reference image. Two-dimensional frequency distributions describing the overlap of the blocks during the course of treatment were then calculated and superimposed on the reference image. Results of the analysis show positional and quantitative information about the daily variation in block placement, and appeared to be site-dependent. Long term verification studies using on-line imaging systems will be important in the understanding of treatment uncertainties.

Daily treatment verification, On-line radiotherapy imaging, Treatment uncertainties.

INTRODUCTION

The recent advent of on-line radiotherapy imaging is a major technical development in radiotherapy. Not only will it play an important role in verifying the correct implementation of future innovative treatment methods, such as conformal radiotherapy designed with 3D radiotherapy treatment planning systems, it will also improve on current practice by allowing routine verification of the daily treatment.

Equally important, on-line imaging devices allow the in-depth study of the magnitude and nature of treatment uncertainties. Many sources contribute to treatment uncertainties. They stem from the uncertainty in the dosi- metric and patient data used in treatment planning, in the implementation of a treatment plan, in patient mo- tion, and in the reproducibility of the daily setup. The extent of such a study addressing all these issues would be enormous. The information would help refine our concept of treatment uncertainties and could be important for developing future knowledge-based computer assisted treatment verification methods.

We have recently installed an in-house fiber-optic on- line imaging system for clinical evaluation (7). In view of the wealth of verification information, the intent of this work is to investigate a method to analyze the data quan- titatively. At present, we have limited our consideration to the variation of daily treatment setup. Previous studies using films have dealt mainly with measuring linear geometric variations, such as the displacement of anatomical landmarks from the edges of blocks ( 1,6), or with defining localization errors based on clinical criteria (3, 4, 5). In our approach, we attempt to relate the daily treatment variation with the irradiated volume, or more precisely, the irradiated area in terms of the Z-dimensional projection as recorded on the portal images. Five patients were studied to demonstrate the approach.

METHODS AND MATERIALS

The on-line fiber-optic imaging device was used to acquire portal images on five patients treated with 6 MV x- ray beams. Operation of the device has been described in

Presented at the 3 1 st Annual Meeting of the American Society for Therapeutic Radiology and Oncology, San Francisco, CA, 1989.

Reprint requests to: John W. Wong, Ph.D., Mallinckrodt In- stitute of Radiology, Physics Section, 5 10 South Kingshighway Blvd., St. Louis, MO 63 110.

Acknowledgements-The authors wish to thank R. Knapp and C. Offitt for providing assistance in image processing. This work is supported in part by a grant from Fiber Imaging, Inc., St. Louis.

Accepted for publication 11 October 1990.

613

614 I. J. Radiation Oncology 0 Biology 0 Physics March 1991. Volume 20. Number 3

an earlier paper (7). One image was measured for each daily treatment field for each of five patients. For various reasons, such as conflict of patient schedules, only a subset of daily images were acquired. Patient 1 was treated via left and right lateral portals to the whole brain. Images were collected for 1 1 treatments. Patients 2 and 3 were treated with mantle portals for Hodgkin’s disease. For Patient 2, images were acquired for 11 anterior-to-posterior (AP) and 8 posterior-to-anterior (PA) treatments. For Patient 3, only 9 AP images were collected. Patients 4 and 5 were treated with left and right lateral portals for head and neck cancers. Twenty-three left portal images were acquired for Patient 4 and 28 for Patient 5. At the onset of this study we decided not to use the on-line portal images as basis for making treatment decisions. The images were not reviewed until the patient had completed therapy. Thus the causes of treatment variations and “errors” were not specifically analyzed.

performed in this study. For simplicity and in accordance with the ICRU Report 29, we have defined the unshielded patient image area in a “reference” portal image as the prescribed irradiated area.

Essential to our method was the definition of an irradiated area so that the frequency with which it had been treated could be quantified. There were two steps involved in the data analysis.

1. Image registration

Anal_vsis qf ver$cation data It is important to relate treatment variations with the

target volume that the physician wished to treat. Ideally, target volumes could be defined using 3D CT data. With the use of Beam’s Eye View 2D projection, a radiation field could be designed that delineates the 2D areas (or target areas) to be treated and areas to be shielded. The target area, as interpreted from the concept of target volume described in the ICRU Report 29 (2), would include consideration of treatment variation. However, the link to treatment planning and 3D patient CT data was not

All portal images of the patient were aligned according to the anatomical landmarks that could be visualized. To do this, images were downloaded from the computer of the fiber-optic imaging system to an image processing workstation*. Each image was enhanced using a combi- nation of low-pass filtering and the contrast enhancement utilities available on the workstation. One image, acquired on the same day that the first port film of the patient was approved by the physician. was established as the “reference” image. Each subsequent image was then registered, or aligned, with respect to the “reference” image.

For image registration, we used the interactive split image display utility function of the image processing workstation where one image could be scrolled over another. During registration, the positions of the blocks were not considered. All anatomies that could be visualized in the split display were inspected visually for continuity from one image to another. Figure la shows the split image for Patient 2. Translational and rotational operations, about any origin on the 2D portal image. were performed on

A

Fig. l.(a) The split screen display showing 2 PA portal images for Patient 2 that had not been aligned. Note the apex of left lung and left clavicle. (b) The same display showing the 2 PA portal images for Patient 2 that were aligned for patient anatomy. Note continuity of the apices and clavicles. However, the lung blocks are not aligned.

* Model 75, International Imaging System, Inc., Milpitas, CA.

On-line 2 0 M. L. GRAHAM et al. 615

the non-reference image until the two images were aligned to visual satisfaction of the operator (see Fig. lb). Note that these imaging studies were made at the very early stage of the development of the imaging device so that image quality was inferior to those presented more recently (8). The images here lacked fiber-to-pixels geometric correction, but relied on an coarser bundle alignment correction method (7).

Image registration analysis. Portal image registration was performed by only one of the authors (MLG). Ana- tomical variations affected her ability to align the images. Changes in the projected 2D portal images due to changes in the non-rigid patient body were particularly difficult to separate from other 2D translational and rotational variations that might be due to block placement errors. The base-line ability of the one assigned observer in aligning the images was tested by her registering various pairs of images repeatedly on multiple occasions and on separate days. The translational operations performed for the same pair of images were less than three pixels or 2 mm. Inter-observer variability was not examined in this study.

Because of the subjective nature in aligning the daily portal images, a method was developed to provide a quantitative estimation of the uncertainty of the procedure. After all the images were considered registered, each individual image was re-examined. An outline of the primary anatomical landmark used in image registration was drawn onto each individual image. For Patient 1, the primary landmark was the base of skull; Patients 2 and 3, the apices of the two lungs and the carina of the trachea: Patient 4. the lower edge of the C2 vertebral body; and Patient 5, the base of skull and the angle of the mandible. For each field setup, the positions of all the lines from all the daily images were then superimposed on a composite bit-map. Figure 2 shows the AP results for Patient 2.

Each composite image was analyzed according to the variation of the values of the x and y coordinates of the points on the lines. At every pixel increment along the y axis of the composite image, representing about 0.6 mm

Fig. 2. A composite bit-map of the lines outlining the primary anatomical landmarks used in image registration for all the AP treatment portal images for Patient 2.

increment at the mid-depth of the patient, the corre- sponding x coordinates of all the lines at that y position were recorded. The root mean square deviation of the values in the x coordinate was then calculated. Special attention was made to exclude those individual line seg- ments where a single y coordinate value had multiple x coordinate values, such as with a horizontal line. The same procedure was repeated for each x axis increment to cal- culate the root mean square variation of the y coordinate values. The resultant variations of the x and y coordinates of the loci of the points that defined the anatomical landmarks gave a conservative estimate of the uncertainty in our image registration which included the anatomical variability of the non-rigid patient body. Larger variations in the daily positions of the beam edges after image registration would then represent additional variations in patient setup.

2. Treatment variation analysis After all images were aligned, the areas of the blocks

were extracted and superimposed on the “reference” image. The frequency distribution of the overlap of the blocked regions were calculated for the Hodgkin’s patients. The frequency distribution of the overlap of the irradiated regions was calculated for the brain, and the head and neck patients. The information, presented in a 2D display, provided then a measure of the frequency and extent of the irradiated areas that were shielded. Conversely, com- paring the regions of block overlap with respect to the blocked regions of the “reference” image showed then the frequency and extent of the shielded regions, presumably normal tissues or critical structures, that were irradiated.

RESULTS

The variations of loci of points for the superimposed lines after image registration were not significantly different when the images were examined in the x and y direc- tions. The results were combined and shown in Figures 3a, b, c, and d as bar graphs for Patients 1, 2, 3 and 5. Results for the head and neck Patients 4 and 5 were similar. The root mean square variations were given in pixel separations, each representing 0.6 mm along both x and y axes at mid-plane of the patient. Similar to other studies (6) the uncertainty in image registration included the un- avoidable variations in patient positioning in the third dimension, such as a roll in the patient position, or variations related to the non-rigidity of the human body. These effects are reflected in Figures 3a through d. Data for Hodgkin’s lymphoma Patients 2 and 3 show that image alignment for the latter was significantly more varied, pri- marily because of the difficulty in repositioning the youn- ger patient throughout the course of treatment. Variations were least for Patients 4 and 5, who were immobilized with a bite-block device and whose treatment fields were smaller. Patient 1 was immobilized with a head mask. However, the variation was larger for the right lateral field

616 I. J. Radiation Oncology ??Biology 0 Physics

PATIENT 1

n = 260

A Hoot mean square deviation tin pixels)

PATIENT 3

C Root mean square deviation (in pixels)

March 1991. Volume 20, Number 3

PATIENT 2

60 1 Es3 PA El B AP

I,- 1 i2 21 34 4-s 56 67 7k XY Y.,,,

Huot mean square deviation (in pixels)

PATIENT 5

II I 1~2 2~3 3.4 J-5 S-6 h-7 7-x R-Y 9 10

hot mean square deviation (in pixels)

Fig. 3. Analysis of the uncertainty in image registration: Summary bar graphs of the root mean square variations of the x and y coordinates of the anatomical lines for (a) Patient I. (b) Patient 2, (c) Patient 3, and (d) Patient 5. The root mean square variations are expressed as pixel separations with 1 pixel being approximately 0.6 mm at the mid-plane of the patient. n denotes the number x and y coordinates used in the analysis.

than the left. The differences could be related to the fact that the setup always began with left lateral treatment. Although the right lateral setup was also inspected before treatment, it might have been difficult for the young patient to remain motionless for the duration of treatment despite immobilization.

As noted earlier, the results of our image registration analysis represented a conservative estimation of our ability to align the anatomies on the portal images. For those patients who could be more readily re-positioned between treatments, the images could be aligned to within 4 pixel separation, or about 2.5 mm. For the more restless

patients, the images could be aligned conservatively to within 9 pixel separation, or about 5.5 mm.

Figure 4 shows the treatment variation results for the PA treatments of Patient 2 where the positions of the blocks are superimposed on the gray scale “reference” image. The cumulative block positions show substantial amount of travel. In Figure 5, the irradiated area of the reference image of Figure 4, that is, the region on the image that was not shielded, was outlined for clarity. The frequency distribution of the cumulated blocked regions is represented as color shaded regions denoting overlap of the blocked regions that occurred less than 20%, 20%

On-line 2 0 M. L. GRAHAM ef al. 617

Fig. 4. Gray scale reference PA portal image for Patient 2 with the blocks from all the acquired images superimposed upon the reference image.

to 50%, 5 1% to 70%, 7 1% to 90%. and 9 1% to 100% of the time. Results for the AP treatments show less variation with the 50% block overlap contour approximately track- ing the “reference” block position. It might have been easier to reproduce the patient setup in the AP position.

Results for Patients 1, 3, and 5 are shown in Figures 6, 7, and 8, respectively. The extent of the maximum deviation of the block positions or the beam boundaries, that is, the region between greater than 9 1% overlap and less than 20% overlap, is larger than the conservative estimation of the uncertainty in the image registration. Fig- ure 6 shows the right lateral treatments of the crania1 region of Patient 1. Here, the colored &frequency contours describe the overlap of the irradiated areas. The inferior border of the field was to be abutted to a later session of PA treatments of the spinal column. The overlap of the blocks caused by the “moving junction” treatments at orderly discrete intervals, or gaps, can be observed. The gap intervals were more variable for the right lateral treatments.

Figure 7 shows the AP treatment results for Patient 3. The variation of the iso-frequency contours of block overlap was significant, and larger than the 5 mm uncertainty in image registration. Correct block placement was more difficult with the restless young patient, despite the use of an repositioning device.+

Figure 8 shows the iso-frequency contours of the irradiated areas for the left lateral neck treatments for Patient 5. The off-cord portion of the treatment session resulted in a reduction of dose to the spinal cord region. The

slightly wider separation of the iso-frequency contours in the anterior position was due to the erroneous placement of the block for four consecutive daily treatments in the on-cord portion of the treatment session. Portal films were not taken during those 4 days and the errors were not detected. The errors did not reappear for the remainder of the treatment. As previously stated, daily images were not evaluated until after the course of treatment and were not used as basis for making clinical corrections. For patient 4, the blocks were trimmed after the first four treatments and the effects were clearly observed in the iso- frequency contours.

Table 1 summarizes the results for each patient in terms of fraction of the “reference” irradiated area shielded and area of the “reference” blocked regions treated that should have been shielded. Values in parenthesis show the reduction in treatment variation if the block had been designed correctly from the beginning for Patient 4, and if the four erroneous treatments had been corrected for Pa- tient 5.

DISCUSSION

In this work, our primary goal was to investigate an approach to quantify daily treatment uncertainties using verification information acquired from an on-line radiotherapy imaging devices. Different from earlier efforts using port films where the treatment variations were measured in linear dimensions, we have considered it important to relate the information to the intended irradiated area. The approach provides quantitative information about the frequency with which an irradiated area is treated, and the effectiveness of block design in shielding critical structures. Positional information about treatment variation is also readily available. For these studies, we have chosen to define an irradiated area from a reference portal image. Ideally, one would derive a target area from projected 3D CT patient data, thereby providing a link between treatment planning and verification. That re- search effort is currently being pursued at our institution.

Results from our limited studies demonstrate the wealth of important information that can be derived from on- line imaging devices. The frequency distributions of block overlap can be measured for different disease sites to give an estimate of the variability of the setups and would be important in defining treatment margins, a task that, at present, is based almost entirely on clinical experience and can vary from physician to physician. Even during the course of treatment, the cumulative verification data can be used for mid-course adjustment if the blocking arrangement proves to be sub-optimal. The same approach would be particularly useful in the abutment regions of multiple beams.

+ Alpha Cradle, Smithers Medical Products, Inc., Hudson, OH.

618 1. J. Radiation Oncology 0 Biology 0 Physics March 1991. Volume 20, Number 3

Fig. 5. Colored summary image displaying the iso-frequency of the blocking variations for the PA treatments of Patient 2 as shown in Fig. 4. Blue represents the area blocked less than 20% of all the treatments, green, 2 I%-50%. yellow, 5 I%-70%. orange, 7 I%-90% and red, 9 1 %- 100%. The white contour line represents the irradiated area as defined by the reference image. The horizontal line in the image represents 20 pixels length, or about 1.2 cm at the mid-plane of the patient.

Fig. 6. Colored summary image for the left lateral whole brain treatments for Patient 1. Here the color contours denote the frequency distribution of the overlap of the irradiated area. The contours have the same intervals as in Fig. 5.

Fig. 7. Colored summary image of the frequency of block overlap for the AP mantle treatments of Patient 3. The color intervals are the same as in Fig. 5. The horizontal line represents 1.2 cm at the mid-plane of the patient.

Fig. 8. Colored summary image of the frequency of overlap of the irradiated area for the left lateral neck treatments of Patient 5. The contour intervals are the same as in Fig. 5. The horizontal line in the image is of I7 pixels length, representing about 1 cm at the mid-plane of the patient.

On-line 2 0 M. L. GRAHAM et al. 619

Table 1. Summary of treatment variations relative to the reference image

Patient Port

Percentage of irradiated area

shielded Area of blocked area

treated in sq. cm

1 Left Right

2 AP PA

3 AP 4 Left l*

Left 2 5 Left I*

Left 2

Not calculated Not calculated

0.9% f 0.6% 2.1% f 0.8% 3.6% + 1.3% 5.3% f 5.2%

(3.3% + 1.9%)’ 5.6% f 2.9% 3.1% f 1.7%

(2.3% + l.O%)+ 4.7% f 1.8%

5.6 t 2.5 24.6 + 4.7 36.5 + 10.4

5.9 f 2.6

2.6 + 1.7 6.3 a 3.8

(4.6 ? 2.1)+ 3.4 + 2.2

* Left 1 denotes treatments with the spinal cord unshielded; Left 2 denotes treatments with the spinal cord shielded.

’ Values after correcting the block design used in the first four treatments.

+ Values by omitting four mid-course treatment sessions which deviated substantially from the reference image.

Our studies addressed the problem of daily treatment variation with respect to the irradiated area by aligning anatomies on daily portal images. However, anatomical registration became difficult when the 2D images varied significantly due to the non-rigidity of the patient body. That component of variation could not be easily separated from other sources of setup variations, such as field placement. Correct repositioning will always be difficult for

I.

2.

3.

4.

5.

some patients. Not surprising, problematic patient repositioning would inherently make it more difficult to place the block correctly, thereby increasing the overall treatment uncertainty. Results for Patient 3 show such an ex- ample. On-line imaging allows convenient identification of these problems in a prompt manner so that other ac- tions, such as the use of more restrictive immobilization devices or sedation, could be applied. Conversely, on-line imaging provides an excellent tool to evaluate the effectiveness of immobilization devices.

CONCLUSIONS

On-line radiotherapy imaging systems will play a key role in improving the accuracy of radiotherapy. Treatment verification data could be made available much more conveniently than with the customary portal film expo- sure. More important, the information allows the in-depth analysis of treatment uncertainties. In this work, we have introduced a method to analyze the data which relate the daily treatment variations to the intended irradiated area as projected on the 2-dimensional image. The results presented are preliminary. However, we believe the method provides useful quantitative information about treatment uncertainty. A more detailed analysis should incorporate 3D CT treatment planning information. In the future, a systematic analysis of long term clinical studies with on- line radiotherapy verification information would help refine radiotherapy, correlate accuracy of treatment with clinical outcome, and assist in the development of knowledge-based systems for treatment verification.

REFERENCES

Huizenga, H.; Levendag, P. C.; De Porre, P. M. Z. R.; Visser, A. G. Accuracy in radiation field alignment in head and neck cancer: a prospective study. Radiother. Oncol. 11: I8 l- 187; 1988. International Commission on Radiation Units and Mea- surements. Report #29: dose specification for reporting ex- ternal beam therapy with photons and electrons. Washing- ton, D.C.; 1978. Kinzie, J. J.; Hanks, G. E.; Maclean, C. J.; Kramer, S. Pat- terns of care study: Hodgkin’s disease relapse rates and ad- equacy of ports. Cancer 52:2223-2226; 1983. Marks. J. E.; Haus, A. G.; Sutton, H. G.; Greim, M. L. Localization error in the radiotherapy of Hodgkin’s disease and malignant lymphoma with extended mantle fields. Cancer 34:83-90; 1974. Marks, J. E.; Haus, A. G.; Sutton, H. G.; Greim, M. L. The

value of frequent verification films in reducing localization error in the irradiation of complex fields. Cancer 37:2755- 2761; 1976. Rabinowitz, I.; Broomberg. J.; Goitein, M.; McCarthy, K.; Leong, J. Accuracy of radiation field alignment in clinical practice. Int. J. Radiat. Oncol. Biol. Phys. 11:1857-1867; 1985. Wong, J. W.; Binns, W. R.: Cheng, A. Y.; Geer, L. Y.; Eg stein, J. W.; Klarmann, J.; Purdy, J. A. On-line radiotherapy imaging with an array of fiber-optic image reducers. Int. J. Radiat. Oncol. Biol. Phys. 18: 1477-1484; 1990. Wong, J. W.; Binns, W. R.; Cheng, A. Y.; Geer, L. Y.; Ep- stein, J. W.; KIarmann, J. On-line radiotherapy imaging. I: refinement of a fiber-optic imaging system for clinical ap- plications (Abstr.). Int. J. Radiat. Oncol. Biol. Phys. 17(Suppl. 1):158; 1989.

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