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

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

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

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. (http://www.crs-src.ca/page.aspx?pid=1325&gclid=CNv34dvhwcUCFRSUfgod-ZQAkg, 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

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

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

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

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

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

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

Rigid Registration Video of rigid

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>

Non-Rigid Registration Video

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

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

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

Siavash Khallaghi C. Antonio Sánchez Dept of Elec & Comp Eng University of British Columbia Vancouver, BC, Canada siavashk@ece.ubc.ca C. Antonio Sánchez Dept of Elec & Comp Eng University of British Columbia Vancouver, BC, Canada antonios@ece.ubc.ca 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.