©2005 surgical planning laboratory, arr slide 1 prostate image processing steven haker, phd

©2005 Surgical Planning Laboratory, ARR Slide 1

Prostate Image Processing

Steven Haker, PhD


The Basic Problem

• New MR imaging parameters and high field strengths hold promise for increased sensitivity and specificity in cancer detection.


The Basic Problem


• Constraints of low-field strength intra-operative scanners and limited time in the operating room limit imaging.


The Basic Problem


• Constraints of low-field strength intra-operative scanners and limited time in the operating room limit imaging.

• Solution: Image registration, which allows all pre-operative imaging to be used for targeted therapy.


Challenge: MR-Guided Prostate Therapy

High quality 1.5 Tesla imaging is not available in the our 0.5T intra-operative MRT


Promise: New MR Acquisitions

Promising new imaging techniques are not readily available in the operating room.

Haker, ISMRM 2005

Diffusion ImagingT2-Weighted Imaging


Promise: New MR Acquisitions

MR-Spectroscopy

T2-Weighted Imaging

MR Spectroscopy yields information on local metabolism


Image Fusion for Increased Specificity

Summary Statistical Mappingshowing most suspicious focus

in red.

Using image fusion and machine learning techniques, we maximize information from multiple MR imaging techniques into one summary image.

Chan, et al., 2003


The Need for Registration

• How can these imaging techniques be used in the operating room to guide therapy?

– Limited time

– Low field-strength


The Need for Registration

• How can these imaging techniques be used in the operating room to guide therapy?

– Limited time

– Low field-strength

• Image registration allows us to align pre-operative imaging with intra-operative imaging.– Targets may be chosen in pre-operative

imaging and used to guide therapy.

– Pre-operative imaging can be visualized overlaid with intra-operative imaging.


Intra-operative 0.5T

Pre-operative 1.5T T2

Deformed pre-op T2 FSE

Registration – Our Method

Registration


Surface Matcher – Elastic Model

Pre-Op Intra-Op


Registration

Pre-operative data (left), needs to be registered to intra-operative images (right). We use a bio-mechanical model to warp the central

gland (red) and peripheral zone (green).


Non-Rigid Registration - Prostate

Registration of T2 imaging yields image with greater conspicuity


Registration – Pre-Operative Targeting

On the left, targets for biopsy chosen using pre-operative 1.5 Tesla MR imaging. On the right, registered positions in intra-operative 0.5 T imaging taken in the operating room.

Davatzikos External Collaboration (UPenn)


Clinical Application – Prostate Therapy

• Registration for targeted MR biopsy– Done regularly as part of our MR-guided prostate

biopsy program.

– Targets from imaging (Spectroscopy, T2-W imaging)

– Targets from our collaboration with U Penn (statistical model of likely cancer sites)


Clinical Application – Prostate Therapy

• Registration for targeted MR biopsy– Done regularly as part of our MR-guided prostate

biopsy program.

– Targets from imaging (Spectroscopy, T2-W imaging)

– Targets from our collaboration with U Penn (statistical model of likely cancer sites)

• Visualization for needle guidance– Image overlay of preop and intraoperative imaging

– Visual feedback of needle placement

– Visualization of targets


3D Slicer

The 3D Slicer is the SPL’s workhorse for visualization and image processing.


Real-Time MR for Biopsy Guidance

Real-time FGR image (left) taken during biopsy with needle artifact (arrow). T2 image (right) taken before needle placement, and sampled to display the same

spatial locations. Note that in the T2 image on the right the peripheral zone (bright area) is clearly visible (arrow).


Real-Time Display

Imaging taken before needle insertion (T2-W, left) and during needle placement (middle) can be fused to allow for visualization of prostate peripheral zone and needle simultaneously (right).


Image Fusion and Visualization

Real time intra-operative images and registered pre-operative image can be fused to aid in needle guidance. Images not otherwise available in the operating room can be utilized.

M. So (R25 Fellow) RSNA 2004


Program Interaction

Capturing Intraoperative Deformations: Research Experience At The Surgical Planning Laboratory Simon K. Warfield, Steven J. Haker, Ion-Florin Talos, Corey A. Kemper, Neil Weisenfeld, Andrea U. J. Mewes, Daniel Goldberg-Zimring, Kelly H. Zou, Carl-Fredrik Westin, William M. Wells, Clare M. C. Tempany, Alexandra Golby, Peter M. Black, Ferenc A. Jolesz and Ron Kikinis. Medical Image Analysis 9 (2005) pp 145-162. This paper reviews the experience at the Surgical Planning Laboratory of developing and applying novel registration and image processing algorithms for capturing intraoperative deformations in support of image guided therapy. Applications to brain and prostate therapy and treatment are presented, showing the diverse range of procedures which can benefit from basic research. New methods which incorporate diffusion tensor imaging and bias field correction into the registration process, as well as novel methods for validation of segmentation, are described.


Program Interaction

• Radiation Oncology– Seed counting post brachytherapy– Bladder registration for dosimetry– Pre to Post therapy CT and MR

registration (e.g. NVB dosimetry, A. Szot R25 Fellow)

– MR to CT registration for radiation therapy planning.


Conclusion

• Registration allows the best of two worlds– Use of high-quality, innovative imaging for

targeting and guidance

– Use of real-time imaging to guide needle placement


Conclusion

• Registration allows the best of two worlds– Use of high-quality, innovative imaging for

targeting and guidance

– Use of real-time imaging to guide needle placement

• Registration is practical for operating room use– Regular part of our MR-guided biopsy

procedures

– In-bore display system can provide integrated visual feedback to the doctor.


Future Work

• Migration to higher-field strength, closed bore intraoperative systems (U41).

• Patient motion and needle placement accuracy (integrate with robotics).

• Continued research into new imaging modalities (Tensor imaging, gadolinium studies, spectroscopy, SSMs, etc.)

• Extend collaborations with physicists (XRT) and other researchers.

• External collaborations (Davatzikos, UPenn)

• Other prostate therapies (Focused Ultrasound).

©2005 surgical planning laboratory, arr slide 1 prostate image processing steven haker, phd

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