DBP2:Queens
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Segmentation and Registration Tools for Robotic Prostate Interventions
Contents
Team and Institute
- PI: Gabor Fichtinger, PhD: gabor at cs.jhu.edu
- Queen's Engineering Contact: David Gobbi
- Hopkins Engineering Contact: Csaba Csoma, Johns Hopkins University, csoma at jhu.edu
- NA-MIC Engineering Contact: Katie Hayes, Brigham and Women's Hospital, hayes at bwh.harvard.edu
- NA-MIC Algorithms Contact: Allen Tannenbaum, GeorgiaTech
- Affiliation/Institution: Queen's University & Johns Hopkins University
Research Goals
The Queen’s/Hopkins team is developing novel devices and procedures for cancer interventions, including biopsy and therapies.
Prostate cancer is the most common subcutaneous cancer in American men. In 2007 will be an estimated 220,000 new cases of prostate cancer and 28,000 deaths caused by prostate cancer in the United States alone. [1]
The current standard of care for verifying the existence of prostate cancer is transrectal ultrasound (TRUS) guided biopsy. TRUS provides limited diagnostic accuracy and image resolution. In a study [2] the authors conclude that TRUS is not accurate for tumor localization and therefore the precise identification and sampling of individual cancerous tumor sites is limited. As a result, the sensitivity of TRUS biopsy is only between 60% and 85%. [3, 4]
Targeted biopsies of suspicious areas identified by MRI could potentially increase the sensitivity of prostate biopsies. To address this problem the investigators have several active research projects in prostate biopsy and therapies under direct MRI guidance inside the bore. We have developed and clinically tried a semi-robotic device and system for planning and execution of prostate biopsy under MRI guidance [5]. We have conducted several clinical trials [5] and more are to follow. The generic workflow is as follows:
- Pre-Op: segment the prostate, identify suspicious areas, plan targets;
- Intra-Op: import plan, update plan, execute the biopsy/therapy
- Post-Op: compare post-op data with plan, evaluate technical variables
Currently, these functions are achieved by fragmented in-house code, some based on VTK/ ITK.
The objective of this DBP will be professional-grade clinical software engineering of existing and upcoming functions Slicer. This will allow the team to focus on project specific tasks, and benefit from the advances IGT capabilities of Slicer.
Experimental Data
The system for MRI guided transrectal prostate interventions was tested in patients [5] and a new embodiment has been tested recently in phantom experiments at NIH (Bethesda, MD) on a 3T Philips Intera MRI scanner (Philips Medical Systems, Best, NL) using standard MR compatible biopsy needles and non artifact producing glass needles [7].
Patient Data:
Typically, 3D axial MRI prostate datasets (patient positions mixed between prone and supine) acquired using different endorectal coils (coil diameter = 13 mm for two datasets, coil diameter = 26 mm for third) were used for algorithm evaluation. The scans were performed on Philips Intera 3T MRI system; T2-weighted images acquired using Spin Echo (SE) sequence with following parameters: SENSE protocol with acceleration factor of 1; TE/TR = 180 / 7155 ms for some datasets, TE/TR = 120 / 7155 ms for some others; matrix 256 x 256; field of view 140 x 140 mm; voxel size 0.55 x 0.55 mm; slice thickness 3 mm.
Phantom Data:
Biopsy Needle Accuracies: The manipulator was placed in a prostate phantom and its initial position was registered. Twelve targets were selected within all areas of the prostate on T2 weighted axial TSE images. Targets one through four were selected in the base of the prostate, targets five through eight in the mid gland, and targets nine through twelve in the apex of the prostate. For each target, the targeting program calculated the necessary targeting parameters for the needle placement.
The phantom was pulled out of the MRI scanner on the scanner table, the physician rotated the manipulator, adjusted the needle angle and inserted the biopsy needle according to the displayed parameters.
The phantom was rolled back into the scanner to confirm the location of the needle on axial TSE proton density images which show the void created by the biopsy needle tip close to the target point. The in-plane error for each of the twelve biopsies, defined as the distance of the target to the biopsy needle line was subsequently calculated to assess the accuracy of the system.
The needle line was defined by finding the first and the last slice of the acquired confirmation volume, where the needle void is clearly visible. The center of the needle void on the first slice and the center of the void on the last slice define the needle line. The out of plane error is not critical in biopsy procedures due to the length of the biopsy core and was not calculated. Hence, from the purpose of accuracy, there is no need for a more precise motorized needle insertion. The average in-plane error for the biopsy needles was 2.1 mm with a maximum error of 2.9 mm.
Glass Needle Accuracies: The void created by the biopsy needle is mostly due to susceptibility artifact caused by the metallic needle. The void is not concentric around the biopsy needle and depends on the orientation of the needle to the direction of the main magnetic field in the scanner (B0), and the direction of the spatially encoding magnetic field gradients [6]. Consequently, center of needle voids do not necessarily correspond to actual needle centers.
And since the same imaging sequence and similar orientation of the needle is used for all targets in a procedure, a systematic shift between needle void and actual needle might occur, which introduces a bias in the accuracy calculations. To explore this theory, every biopsy needle placement in the prostate phantom was followed by a placement of a glass needle to the same depth. The void created by the glass needle is purely caused by a lack of protons in the glass compared to the surrounding tissue, and is thus artifact free and concentric to the needle. The location of the glass needle was again confirmed by acquiring axial TSE proton density images. The average in-plane error for the glass needles was 1.3 mm with a maximum error of 1.7 mm.
The procedure time for six needle biopsies not including the glass needle insertion was measured at 45 minutes.
Current Image Software
The targeting program runs on a laptop computer located in the control room. The only data transfer between laptop and scanner computer are DICOM image transfers. The fiber optic encoders from the robot interface via a USB counter (USDigital, Vancouver, Washington) to the laptop computer.
The targeting software displays the acquired MR images, provides the automatic segmentation for the initial registration of the manipulator, allows the physician to select targets for needle placements, it provides targeting parameters for the placement of the needle, and tracks rotation and needle angle change provided by the encoders, while the manipulator is moved on target.
After targeting the software overlays the target and projected needle path with the confirmation volume scan. This allows the physician to quickly asses the success of the intervention.
Image Processing Needs
Although the current software covers the intervention needs for the first project, additional functions are necessary to allow easy and quick access to the data before, during and after procedure, and to accommodate the needs of the other two projects.
Segmentation and deformable registration functions, 3D visualization instead of the current 2D view, and the extensive data analysis technology of Slicer are all on the projects software specification list.
A basic requirement is the good memory management and stable software. Since the program is running on a laptop, there are only very limited resources available (CPU and memory).
The automatic segmentation algorithms are not always accurate, so it should provide interactive correction capabilities, like moving the slider to change the threshold followed by re-segmentation. Other interactive part is modification of the proposed needle path within the robot constraints.
LPS coordinate system: During the procedure targets are selected using the 2D projection image obtained from the scanner and the target coordinates are in the DICOM image coordinate system. This is also used to display parameters for the manual prescription and for the real time tracking.
As each landmarking defines an independent coordinate system, and this Frame of Reference (FoR) correspondence between volumes is essential for the patient safety. The operating personnel should not be able to use registration data from one volume and target other volume if there’s no transformation between the two coordinate systems.
With OpenTracker capable MRI scanners we would like to use real time needle tracking.
Summary
Manifold benefits exist for both NA-MIC and the Brigham-Hopkins joint program in MRI-guided prostate interventions, owing to existing loops of collaborations, cross-compatibility of research (MR guided prostate interventions), and shared Slicer/VTK/ITK based software platforms.
The project's clinical partners are based in the intramural research program of the National Cancer Institute. Thus the proposed NA-MIC DBP will tie a significant segment of extramural cancer research into a prominent intramural effort, thereby leading to a better understanding, coherency, and active collaboration between these otherwise disjoint efforts. For NA-MIC the benefits are also tangible: the functions will be developed in a controlled and professional environment in the CISST ERC that has been in close collaboration with NA-MIC/Brigham. The development environment used in both groups are similar, in that we both base our image processing tools on VTK, ITK and Slicer and uses many of the same development tools, including CVS, CMake, Doxygen and Dart. In short, the proposed work will be conducted on a shared platform (VTK, ITK, and Slicer) with a compatible development process, and thus the results will be directly absorbable by NA-MIC.
Projects
References
- Jemal, A., Siegel, R., Ward, E., Murray, T., Xu, J., Thun, M.J.:
Cancer statistics, 2007
CA Cancer J Clin 57(1) (2007) 43–66 - Yu, K.K., Hricak, H.:
Imaging prostate cancer
Radiol Clin North Am 38(1) (2000) 59–85, viii - Norberg, M., Egevad, L., Holmberg, L., Sparn, P., Norln, B.J., Busch, C.:
The sextant protocol for ultrasound-guided core biopsies of the prostate underestimates the presence of cancer
Urology 50(4) (1997) 562–566 - Terris, M.K.:
Sensitivity and specificity of sextant biopsies in the detection of prostate cancer: preliminary report
Urology 54(3) (1999) 486–489 - Krieger A, Csoma C, Guion P, Iordachita I, Metzger G, Qian D, Singh A, Whitcomb L, Fichtinger G:
Design and Preliminary Accuracy Studies of an MRI-Guided Transrectal Prostate Intervention System
MICCAI 2007 - DiMaio, S.P., Kacher, D.F., Ellis, R.E., Fichtinger, G., Hata, N., Zientara, G.P., Panych, L.P., Kikinis, R., Jolesz, F.A.:
Needle artifact localization in 3T MR images
Stud Health Technol Inform 119 (2006) 120–125 - Krieger A, Csoma C, Iordachita I, Guion P, Fichtinger G, Whitcomb LL,
Design and Preliminary Accuracy Studies of an MRI-Guided Transrectal Prostate Intervention System
MICCAI 2007 (submitted)
