Daily prostate positioning Frank Van den Heuvel … · Daily prostate positioning Frank Van den...

Daily prostate positioning

Frank Van den Heuvel Ph.D.

Lei Dong Ph.D.

David Jaffray Ph.D.

27th July 2004

• Measure with a micrometer.


• Mark with chalk.



• Cut with an axe.



• Cut with an scalpel.

Now that we have IMRT.



• Cut with an scalpel.

Now that we have IMRT.

But, we are very precise in determining the thickness of our

chalk!

The Goal of Image Guided Radiation Treatment


Reduction of the PTV margin!


Reduction of the PTV margin!

The PTV margin depends on:

• Organ

• Patient

• Modality of Treatment

van Herk et al.[1] proposes a margin recipe, based on:


• Obtaining a 98% equivalent uniform dose (EUD)



• For 90% of the patients




• Calculate this using a simulation procedure, using MC

calculations to simulate population spread.

Recipe:

M = 2.5Σ + 0.7σ − 3mm






Recipe:

M = 2.5Σ + 0.7σ − 3mm

• Σ: Spread of the systematic errors SD(Σi)






Recipe:

M = 2.5Σ + 0.7σ − 3mm

• Σ: Spread of the systematic errors SD(Σi)

• σ: Average of the random errors < σi >

Reducing the Margin

Reducing the Margin

We can reduce Σ and/or σ

Reducing the Margin


Reduction of Σ is most efficient and easiest to do

Reducing the Margin


Reduction of Σ is most efficient and easiest to do

Off Line Is the most popular correction system, to

date.

1. Gather data to sample positional distribution (up to

six fractions).

2. Apply a correction to minimize the systematic error.

3. Adapt margins to reflect the variations.

On–line adjustment: reduces both Σ and σ at

the same time.

1. No “bad” treatments

2. Conceptually simple, no assumptions on type of

probability distributions

How[2]

Essentially all on–line adjustments are identical, only the

modalities differ.

1. Patient is setup in treatment position.

2. The target organ (prostate) is detected and its position

(or a representation thereof) is measured.

3. When a threshold offset is detected the patient is

repositioned using a variety of methods.

4. A reassessment of the position is usually performed

before start of treatment.

On-line adjustment modalities

• Ultrasound detection

• Implanted Markers

– Active

– Passive

∗ US

∗ EPID

Ultrasound adjustment

Verification of Ultrasound based adjustment[3]

• A total of 19 patients have been enrolled.

• Compiled data of 17 patients will be presented.

• 275 treatment setups with markers have been analyzed.

• 156 image pairs using Ultrasound adjustment.

• 119 image pairs using traditional treatment.

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Figure 1: Coronal Plane

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Figure 2: Sagittal Plane

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Figure 3: Transverse plane

Why doesn’t Ultrasound aided repositioning perform better?


• User subjectivity[4].



• Discrepancy between contoured anatomy and actual

anatomy[5].

Figure 4: Inter–observer variation of contouring bladder




anatomy[5].

• Intra–fractional movement between the Ultrasound

procedure and the treatment[6].




anatomy[5].

• Intra–fractional movement between the Ultrasound

procedure and the treatment[6].

• Heisenberg ∆x∆p > h̄2

Improvements to reduce User subjectivity


1. BAT (Nomos Inc)

• Live CT–contour projection during acquisition.

• Seed localizers (Visicoil, Radiomed)


1. BAT (Nomos Inc)



2. Zmed (Varian Inc)

• Pseudo 3D acquisition.

• Live adjustment.


1. BAT (Nomos Inc)



2. Zmed (Varian Inc)

• Pseudo 3D acquisition.

• Live adjustment.

3. IBeam (CMS Inc)

• Pseudo 3D acquisition and reconstruction.

• Ultrasound contouring and export to planning

system.

Marker based protocols

Marker based protocols

Ultrasound Do not look for prostate, but look for long

seeds (need 3D acquisition)

EPID Take images and visualize the seeds

Calypso Seeds reflect RF radiation use detector to see

where they are.

Assessment of marker daily repositioning

The protocol used is as follows:

1. Obtain 2 images (45◦ and 315◦) using low exposure.




2. Determine 3D position of the markers or any measure

allowing to determine the position of the target w/

respect to the iso–center.




2. Determine 3D position of the markers or any measure

allowing to determine the position of the target w/

respect to the iso–center.

3. Calculate and perform shifts necessary to correct the

patient’s position.

Results

An IRB approved study with 15 patients total accrual

(currently 14 accrued) was initiated, using the

abovementioned protocol.

Results




Results shown here are for 10 patients. A total of 270

treatments were analyzed (27 fractions average per

patient).

Results




Results shown here are for 10 patients. A total of 270

treatments were analyzed (27 fractions average per

patient).

Every fraction had before and after measurements.

Resulting in 540 total position measurements (270 before

and after pairs).

mean (mm) SD (mm)

before

AP 7.45 5.99

LAT 1.29 5.34

CC 5.12 4.44

after

AP 0.65(P < 0.00001) 2.82(P < 0.00001)

LAT 0.11(P < 0.00001) 2.64(P < 0.00001)

CC 0.46(P < 0.00001) 2.22(P < 0.00001)

Table 1: Pooled results, significance of reduction using t–

test(mean) and F–test(Variances)

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AP

(m

m)

CC (mm)

AfterBefore

Figure 5: Scatterplot showing before and after positions for a total of 540 mea-surements. All sizes are in millimeter. The ellipses cover 95% of all datapoints.

Margin Calculations

Σ (mm) σ (mm) Margin (mm)

before

AP 3.6 5.08 9.6

LAT 3.41 4.29 8.5

CC 3.88 2.36 8.4

after

AP 0.56 2.64

LAT 0.39 2.37

CC 0.40 1.95

Table 2: Population statistics and margins calculated using

2.5Σ + 0.7σ − 3mm.

Margin Calculations


before

AP 3.6 5.08 9.6

LAT 3.41 4.29 8.5

CC 3.88 2.36 8.4

after

AP 0.56 2.64 0.25

LAT 0.39 2.37

CC 0.40 1.95


2.5Σ + 0.7σ − 3mm.

Margin Calculations


before

AP 3.6 5.08 9.6

LAT 3.41 4.29 8.5

CC 3.88 2.36 8.4

after

AP 0.56 2.64 0.25

LAT 0.39 2.37 -0.63

CC 0.40 1.95


2.5Σ + 0.7σ − 3mm.

Margin Calculations


before

AP 3.6 5.08 9.6

LAT 3.41 4.29 8.5

CC 3.88 2.36 8.4

after

AP 0.56 2.64 0.25

LAT 0.39 2.37 -0.63

CC 0.40 1.95 -0.64


2.5Σ + 0.7σ − 3mm.

Figure 6: The model proposed by van Herk et al. is not valid at the valueswe are measuring.

Important!

Important!

The residual errors observed were after the adjustment, but

before the treatment. In order to gauge the efficacy of any

repositioning scheme we need data during the treatment.

Important!

The residual errors observed were after the adjustment, but

before the treatment. In order to gauge the efficacy of any

repositioning scheme we need data during the treatment.

We need to address the following problems:

• Patient position at time of treatment (not before or

after).

• Treatment delivery.

Important!

Important!

There are only two modalities that allow in–treatment

patient monitoring.

• EPID

• Calypso

They need to address the following problems:

• Patient position at time of treatment (not before or

after).

• Treatment delivery.

Calypso has the (not proven) capability to perform

in–treatment monitoring of the position if the detector

is built in the couch. Dose verification could be

possible if combined with Radiation Dosimetry (Sicel

Technologies Inc.)

EPID can perform in–treatment position verification

(even for IMRT) and intensity map verification, or even

absolute measurement (A Radiation Dosimeter can

replace one of the seeds).

Figure 7: Portal Image of an IMRT treatment

The previous image was taken using an electronic portal

imager in cumulative mode (e.g. All frames taken are

averaged).

The previous image was taken using an electronic portal

imager in cumulative mode (e.g. All frames taken are

averaged).

Intensity Modulation This information shows up

as fairly large variations in contrast (steps are at least

5%).

Patient Anatomy Small signals indicating bony

edges or implanted markers.

Other stuff Scattered radiation, source variations, (in

short things we don’t want to see).

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Pix

elV

alue

(ar

bitr

ary

units

)

Pixel Number

Patient ImageOpenImage

Figure 8: Cross–section of two images. One obtained during an IMRT–treatment(bottom) with the patient in place, the second without the patient (top).The major difference between the two signals is due to increased scat-tered radiation reaching the imager and decreased direct signal throughpatient attenuation of the primary dose.

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its)

Pixel number

Imageadjusted open field

Figure 9: The same cross–section of two images as shown in Figure 8. The open

field is scaled linearly to minimize the χ2–goodness of fit. The fit isperformed on the pixels inside of the field only. The good agreementoutside of the field is likely due to chance and the fact that a smallphantom will not change the out–of–field scatter significantly.

(a) Treatment

Field

(b) Open Field (c) Subtracted

Figure 10: Two–parameter adaptive subtraction, using identical image geometry.An open image was obtained using the intensity map, the phantomplaced on the table was positioned in the beam and a new images wasacquired.

Practical application

1. Detect the field outline.

2. Adjust magnification and position of open field to

match the original portal image.

3. Mathematical morphological erosion (to stay within the

boundaries).

4. Minimize χ2-function for all pixels within detected field.

5. Determine a and b.

6. Subtract adjusted open field from original portal image.

7. Renormalize values for display.

Figure 11: Adjusted

But wait! There’s more


The final χ2–value is sensitive to the intensity modulation

function. If the incorrect value is used the value will be

higher than normal.


The final χ2–value is sensitive to the intensity modulation

function. If the incorrect value is used the value will be

higher than normal.

This allows to verify intensity modulated fields, if we know

how they would interact with an electronic portal imaging

device.

Pixel i

Pixel j

Figure 12: The χ2 value is calculated along each line shown in this graphical repre-sentation. This is repeated for all pixels in the image. The “error”–mapis generated by multiplying the four values, after which thresholding isperformed. Pixels that remain highlighted indicate errors in the inten-sity map.

Figure 13: Intensity map , With 6mm error introduced during

10% of the treatment

Figure 14: 6mm leaf error introduced in 1 segment (10.11%

of the treatment

Figure 15: Fit map , thresholded to point out error in treat-

ment

Things to do

• Determine adequate threshold values (ROC analysis).

• Generate EPID-open fields.

• Can we “pre–port”?

Things to do




Delivering a small amount of dose to the patient,

mimicking the treatment at a smaller dose rate.

Things to do




Delivering a small amount of dose to the patient,

mimicking the treatment at a smaller dose rate.

what is an adequate pre-port amount 5MU?

Acknowledgments

• Therapists

• Jesse Larrew

• Pat McDermott

• Part of this research was sponsored by the Uniformed

Services University of the Health Sciences through

Contract No. MDA905-92-C-0009 awarded to the

Henry M. Jackson Foundation for the Advancement of

Military Medicine. The content of the information does

not necessarily reflect the position or the policy of the

government, and no official endorsement should be

inferred.

References

[1] M. van Herk, P. Remeijer, and J. V. Lebesque. Inclusion

of geometric uncertainties in treatment plan evaluation.

Int J Radiat Oncol Biol Phys, 52(5):1407–22., Apr 1

2002.

[2] F. Van den Heuvel, W. De Neve, D. Verellen, M. Coghe,

V. Coen, and G. Storme. Clinical implementation of an

objective computer-aided protocol for intervention in

intra-treatment correction using electronic portal

imaging. Radiother. Oncol., 35:232–239, 1995.

[3] Frank Van den Heuvel, Tanya Powell, Edward Seppi,

Peter Littrupp, Mubashra Khan, Yue Wang, and

Jeffrey D. Forman. Independent verification of

ultrasound based image-guided radiation tre atment,

using electronic portal imaging and implanted gold

markers. Medical Physics, 30(11):2878–2887, 2003.

[4] K. Langen, J. Pouliot, C. Azinos, M. Aubin, A.R.

Gottschalk, I. Hsu, D. Lowther, K. Shinora,

V. Weinberg, L.J. Verhey, and M. Roach. Evaluation of

the use of the bat ultrasound system for prostate

localization and repositioning: An inter–user study. Int

J Radiat Oncol Biol Phys, 54(2 Suppl):316, October

2002.

[5] G.J. Meijer, C. Rasch, P. Remeijer, and J.V. Lebesque.

Three dimensional analysis of delineation errors, setup

errors, and organ motion during radiotherapy of bladder

cancer. Int J Radiat Oncol Biol Phys, 55:1277–1287,

2003.

[6] J. Lattanzi, S. McNeeley, W. Pinover, E. Horwitz,

I. Das, T. E. Schultheiss, and G. E. Hanks. comparison

of daily localization to a daily ultrasound-based system

in prostate cancer. Int J Radiat Oncol Biol Phys,

43(4):719–25., Mar 1 1999.

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