4D dose calculations at PSI - current status and ongoing work - GSI

4D dose calculations at PSI - 

current status and ongoing work 

Dirk Boye, Ye Zhang, Andreas Schaetti, Antje Knopf, Tony Lomax 

4D workshop Dirk Boye, December 10 th

Content 

1. 4D dose calculation on a deforming dose grid 

2. Deforming dose grid & rescanning 

3. Proton range variations & target contour adaptation 

4. 4DMRI / simulated 4DCT 

5. Other projects from Ye Zhang and Andreas Schaetti 








Static 3D dose calculation at PSI 

Contribution of pencil beam to total dose at 

grid point (s, t, u) 



For each pencil beam the dose contributions to all relevant dose grid 

points are calculated 

Total dose is the sum over all pencil beam at all grid points 

Dose between grid points is interpolated 






Issues of 3D dose calculation 

Always dose to water 

Steep density gradients 

It does not take into account where a high density area is 

(more upstream/downstream) -> different scattering effects 


Why 4D dose calculation ? 

Direction of protons perpendicular to target motion 

This will lead to huge interplay effects and subsequently to 

hot and cold spots in dose distribution (worst case: 

scanning of protons is in phase with organ motion) 

Different approaches to compensate for interplay effects 

(tracking, gating, rescanning or combinations) 

Use which approach? In which case? 


4D approach 

Start with a static 3D treatment plan 

Exact timeline and positions of all individual pencil beams is known 

Idea: Change positions and water equivalent range of dose grid points 

during dose calculation reflecting organ motion at specific timestamp 

(TS) of pencil beam that is currently calculated 


Deforming dose grid 


Stages of development 

1. Rigid motion of all dose grid points 

2. Non-rigid motion of individual dose grid points 

3. Non-rigid motion and changes of water equivalent range 


Deforming dose grid – inputs 

Source of displacement maps: 

Image registration (4DCT, 4DMRI) or motion models 

Source of density-variation maps: 

4DCT or simulated 4DCT (displacement maps+3DCT) 


Deforming dose grid – inputs 

Input data is sampled into timesteps, sampling rate dependent on 

source 

Motion in between timesteps can be easily interpolated 

Open question: What about the density in between timesteps? 


4D dose calculations in homogenouos CT phantom 

Box of water 

Target: sphere 

V=112ccm, depth 10cm 

Proton beams from top 

Linear motion (period: 5s) 

perpendicular to the beam 

(motion field is discontinuous) 






4D dose calculations in simple CT phantoms 








Rescanning for motion mitigation 

1 st step: Scaled rescanning 

Apply all pencil beams multiple times 

with a fraction(1/number of rescans) of 

dose 

(easy to implement) 

“Wash-out” of interplay effects 

(if scanning is not exactly in phase with 

motion) 


Scaled rescanning & deforming dose grid results 

4x rescanning 8x rescanning 


Motion adapted target contour 


Rescanning results 

4x rescanning 6x rescanning 


4D dose calculations in heterogeneous CT phantom 





Upstream obstacle with high 

density area 

Motion scenario 1: 

moving target, static obstacle 


no rescanning 

Results 

6x rescanning to adapted contour 








density area 


static target, moving obstacle 


no rescanning 

Results 

8x rescanning 








Proton range variations & target contour adaptation 

Even though target is not moving, rescanning alone is not enough to 

achieve a homogeneous dose distribution 

Contour adaption accounting for proton range variations needed 










Results 









density area 


moving target & obstacle 


Motion & density variation target adaptation 


Results 



Rescanning – next steps 

- Real patient geometries 

- Implement iso-layered rescanning (Zenklusen et al.) in treatment 

planning 

(huge effect on scanning pattern resulting in de-phasing of beam 

scanning and target motion, dead-time / beam-on time ratio better) 

- 4D plan optimization (beam weights, not relying on 3D plan) 








4DMRI - 

source of deformation maps 


4DMRI 

[Siebenthal et. al 2007] – 4D MR imaging of respiratory organ motion and 

its variability 

- free breathing 

- long acquisition times ( ~ 1h) 

- no external signal 

- reconstruction by internal navigator slice registration 


4DMRI – principal 

navigator slices and image slices are acquired alternately 


4DMRI – principal 

idea: if navigator before and after one image slice match those surrounding 

another image slice those image slices belong to one 3D stack 


4DMRI – liver 


4DMRI – lung 


4DMRI – possible advantages for dose calculations 

- long acquisition times & free breathing 

many different breathing cycles 

organ drift is acquired 


Simulated 4DCT - 

source of density variation maps 


Simulated 4DCT 

Steps for simulation: 

1. Statistical organ motion model of liver from 4DMRI of test subjects 

2. Find correspondent points in static CT dataset suitable for model 

3. Create continuous deformation fields from model 

4. Warp fields to CT set to create 4DCT 

Or: 1. Acquire 4DMRI of patient and work without model 

Result will show motion only in a region of interest (1 st step: only liver) 


Simulated 4DCT 

Possible advantages over 4DCT: 

- no additional dose 

- not restricted to one average breathing cycle 

- no artifacts due to acquisition 


Simulated 4DCT – Coronal view 


Simulated 4DCT – Axial view 


Work in progress: sliding boundaries 


Simulated 4DCT – next steps 

- Sliding boundaries (1 st : ribs static + collision detection) 

- QA of simulations? 

(example: treatment plan comparison 4DCT – simulated 4DCT) 

- Create motion library for liver (test plans for robustness to motion 

variations) 








Andreas Schaetti 


4D measurements 

Verify 4D dose calculations with measurements (CCD+gafchromic film) 

1 st step: simple Quasar 2D motion phantom 

later: free table motion or advanced phantom 

Investigate Advanced scanning modes (combination gating, rescanning 

line scanning) 


Ye Zhang 


4DCT image registration 

Question: Which registration (+settings) should one use to extract needed 

data (Affine, B-Spline, Demons, .... ) ? 

Preliminary results: 

- Best method so far: Combination of Affine and Demons 

- Difference in dose distributions when using different registration methods 

in dose calculation up to 10 % (for rescanning) 


Beam‘s Eye View (BEV) 



- Patient positioning 

- Verifying tumor position online 

- Motion prediction 

- Gated rescanning 

- Pulsed radiograph mode (10 Hz) for tracking 



1 st step: automatic landmark recognition 

- use simulated BEV images (DRRs) to create algorithms 

2 nd step: motion prediction 

as soon as BEV system is up and running: 

measurements with 4D phantoms 




Thank you for your attention

4D dose calculations at PSI - current status and ongoing work - GSI

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