1. A 2D-3D Registration Framework for Freehand TRUS-Guided Prostate Biopsy
Siavash Khallaghi, C. Antonio Sánchez,
Saman Nouranian, Samira Sojoudi, Silvia Chang, Hamidreza Abdi, Lindsay Machan, Alison Harris, Peter Black, Martin Gleave, Larry Goldenberg,
S. Sidney Fels, and Purang Abolmaesumi
Robotics and Control Laboratory,
University of British Columbia, Vancouver, Canada

2. Prostate This is the prostate Roger S Kirby and Manish I Patel.
Fast facts: Prostate cancer. Health Press, 2012
Roger S Kirby and Manish I Patel.
Fast facts: Prostate cancer. Health Press, 2012

3. Roger S Kirby and Manish I Patel.
Fast facts: Prostate cancer. Health Press, 2012
Roger S Kirby and Manish I Patel.
Fast facts: Prostate cancer. Health Press, 2012

4. Prostate Cancer
Most common cancer in men (excluding non-melanoma skin cancer)
Affects 1 in 8 during lifetime
Detection:
Digital rectal exam
High PSA
Core needle biopsy
Prostate Cancer (PCa) is the most common non-cutaneous cancer in North America
Affecting about 1 in 8 men in their lifetime.
( Canadian Cancer Statistics 2014)
There are several ways to detect prostate cancer, but the gold standard is the core needle biopsy
Roger S Kirby and Manish I Patel.
Fast facts: Prostate cancer. Health Press, 2012
Roger S Kirby and Manish I Patel.
Fast facts: Prostate cancer. Health Press, 2012

5. Endocavity Ultrasound Probe
Biopsy Gun
Needle Guide
Needle
The biopsy is most often guided using a 2D transrectal ultrasound probe, with attached biopsy gun
* Maybe remove this
Endocavity Ultrasound Probe

6. Prostate Biopsy Tissue samples tested in lab 30% false negatives
Frequent need to re-biopsy
The probe is inserted in through the rectum, and a needle is fired to collect a tissue sample to be tested in the lab
Even though this is the most reliable method of detection, it has a high false negative rate
Patients are frequently asked to repeat the procedure
Roger S Kirby and Manish I Patel.
Fast facts: Prostate cancer. Health Press, 2012

7. 3D Guidance Tracked TRUS probe Pre-procedure 3D image Plan:
To improve this, 3D biopsy guidance is needed.
A pre-procedure volume is acquired to help plan a set of targets,
The biopsy probe is tracked, acquiring 2D images to help with targetting
Roger S Kirby and Manish I Patel.
Fast facts: Prostate cancer. Health Press, 2012

8. Challenge: Prostate moves and deforms Probe tracking not sufficient
2D – 3D registration required
Unfortunately, the prostate moves and deforms during the procedure,
So slice-to-volume registration is needed to maintain alignment between the current 2D image, and the biopsy plan
Roger S Kirby and Manish I Patel.
Fast facts: Prostate cancer. Health Press, 2012

9. 3D Guidance Framework Reference Volume Slice-to-Volume Registration
Pre-procedure axial sweep
Volume reconstruction
Target planning
Rigid registration for bulk motion
Non-rigid registration for residual motion, deformations
We present a framework for registration in freehand prostate biopsies.
First, a 3D ultrasound is generated using a tracked axial sweep. This is reference volume used for planning
Next, we perform the slice-to-volume registration, consisting of 2 steps
A rigid registration to account for the bulk of the motion;
A non-rigid registration to account for residual motion and deformations.
Currently, achieve a mean target registration error of 3.15 mm for the combined method
Target registration error: 3.15 ± 0.81 mm

10. Rigid Registration Image-based metric Trajectory-based constraint:
Sum-of-squared distances (SSD)
Lots of local minima:
Limited spatial information
Low SNR of TRUS
Motion of prostate
Trajectory-based constraint:
For rigid registration, we minimizing the sum-of-squared distances of image intensities
This method alone is highly susceptible to fall into local minima due to
the limited spatial information
The low signal-to-noise ratio of ultrasound
And the large motion of the prostate
So, we introduce a constraint:
We know that the pre-procedure axial sweep traces along the rectal wall
The live 2D slice should also fall somewhere on the rectal wall, though that wall may have moved
Therefore, we constrain the probe tip to the initial trajectory, making sure the walls coincide
Pre-procedure axial sweep traces rectal wall
Live 2D slice should also fall on rectal wall
Constrain probe tip to trajectory

11. Rigid Registration
Video of rigid

12. Non-Rigid Registration
Finite element-based method:
Incorporates physical properties of the tissue
Simultaneously minimize strain and image SSD
Now, we need to account for residual motion and deformations.
This is done using a FEM-based registration method,
which allows us to incorporate physical properties of the tissue, letting it deform realistically
The FEM is driven by image forces, simultaneously minimizing the total strain and the sum-of-squared distances intensity metric.
<big picture of FEM>

13. Non-Rigid Registration
Video

14. Example Registration 2D Target Slice Initialization
Here is the target slice
Note the calcification in the middle.
Based on solely tracking information, the registration is initialized here [show initial position].
Note that the boundary of the prostate is not aligned in the initial image.
Rigid registration corrects much of this [show rigid result image].
However, the calcification is still missing from the image.
The FEM-based registration corrects for this [show FEM-based result].
2D Target Slice
Initialization

15. Example Registration 2D Target Slice Rigid Registration
Here is the target slice
Note the calcification in the middle.
Based on solely tracking information, the registration is initialized here [show initial position].
Note that the boundary of the prostate is not aligned in the initial image.
Rigid registration corrects much of this [show rigid result image].
However, the calcification is still missing from the image.
The FEM-based registration corrects for this [show FEM-based result].
2D Target Slice
Rigid Registration

16. Registration Results Target Initial Rigid FEM-Based
Our method is shown to consistently converge
Each of the two registration steps play a significant role
The trajectory-constrained rigid registration helps us avoid local minima, bringing us to a good starting point for the FEM-based method to take over, adjusting for the smaller details
[show two more rows of images].
Target
Initial
Rigid
FEM-Based

17. Siavash Khallaghi C. Antonio Sánchez Dept of Elec & Comp Eng
University of British Columbia
Vancouver, BC, Canada
C. Antonio Sánchez
Dept of Elec & Comp Eng
University of British Columbia
Vancouver, BC, Canada
If you’d like to find out more about our work, please come and find us. We would be delighted to answer of your questions, and we invite you to come see our poster.