Clinical Research Employs 3D Slicer Extension

Christian Herz, Kemal Tuncali, and Andrey Fedorov successfully used the SliceTracker extension of 3D Slicer (Fedorov et al., 2012a) to support an in-bore transperineal magnetic resonance imaging (MRI) guided biopsy procedure. The clinical research procedure was performed under institutional review board (IRB) approval in the Advanced Multimodal Image-Guided Operating (AMIGO) suite of Brigham and Women’s Hospital in Boston, MA.

SliceTracker

The SliceTracker extension has been in the works for more than a year now to replace the ProstateNav module of 3D Slicer version 3. The original ProstateNav module was released over five years ago. It has been used, with relatively minor changes, to support more than 400 cases in a research study that started in late 2009. The setup and results of this study have been described in several publications (Fedorov et al., 2012b; Tokuda et al., 2012; Penzkofer et al., 2015; and Behringer et al., 2015). Since ProstateNav relies on the now obsolete and non-maintained 3D Slicer version 3, it has been a long-standing task to develop the next generation of the functionality in the current version 4 of the 3D Slicer software. These improvements became critical as the use of the module increased in the operating room.

Andrey Fedorov supervised the development of SliceTracker. Peter Behringer completed initial prototyping as part of his Master’s thesis project at the University of Luebeck. Peter was a visiting scholar at the Surgical Planning Lab (SPL) for about five months . Christian Herz joined the team in the Summer of 2015, as a visiting engineer from Fraunhofer MEVIS. He became the lead developer of SliceTracker. Christian reimplemented the initial prototype, adding features and conducting tests with earlier versions of SliceTracker in “shadow” mode (running in parallel with ProstateNav).

After several months of testing in shadow mode, fixing bugs, conducting prospective user interviews, and identifying and correcting issues, SliceTracker was officially added as an extension to the 3D Slicer ExtensionManager. This addition occurred on Wednesday, July 13, 2016. On the following day, the nightly version of Slicer and the packaged SliceTracker extension were used on a Mac computer to support AMIGO prostate biopsy case number 419, for the first time without running it as a shadow of ProstateNav. As Andrey Fedorov noted on GitHub, “What was really amazing was that the extension built without errors on the mac dashboard right away, and the next day we were able to use the packaged version of the extension during a biopsy procedure in AMIGO! I could not believe that this was happening!”

Based on early experience and evaluation to date, SliceTracker promises to reduce the interaction time for the operator, improve usability of the interface, and introduce much needed features, such as hanging protocols for individual steps of the workflow, simplified segmentation, and continuous, mostly automatic, tracking of prostate motion during the procedure. SliceTracker is based on the officially maintained version of 3D Slicer and latest the releases of the Visualization Toolkit (VTK), the Insight Segmentation and Registration Toolkit (ITK)/SimpleITK, and the Digital Imaging and Communications in Medicine (DICOM) Toolkit (DCMTK). The module is easily available to the 3D Slicer community as a free open-source extension.

In our view, SliceTracker is an excellent example of a true collaboration between open-source developers and clinical researchers that is serving clinical research today. The registration technology underlying SliceTracker originated in ITK and the BRAINSFit registration module developed by Hans Johnson and colleagues at the University of Iowa. Andras Lasso from Perklab at Queen’s University contributed the VolumeClip module that provides the automated segmentation functionality. Calibration routines were migrated from ProstateNav, and were originally developed by Simon DiMaio, perhaps a decade ago. Steve Piper is the lead developer of the Editor module, which is also integrated into the workflow. Junichi Tokuda provided the advanced calibration routines that were developed more recently. Jean-Christophe Fillion-Robin at Kitware, along with many other members of the National Alliance for Medical Image Computing (NA-MIC) community, contributed key 3D Slicer infrastructure features, such as support for multiple extension dependencies.

The team could not have achieved this milestone without the daily enthusiastic support of the clinical staff at AMIGO. Kemal Tuncali is the lead interventional radiologist for MR-guided biopsy (and cryotherapy) at Brigham and Women’s Hospital as well as in AMIGO. He is a champion of image-guided therapy research that enables better patient care. His thoughtful suggestions, patience, and humor motivate and support the team. Soichiro Tani, a visiting scholar from Shiga University of Medical Science, has been a relentless supporter of the program and the operator of ProstateNav. He has provided feedback and encouragement for the improved software. Janice Fairhurst, the MR technologist at AMIGO, provided feedback in the early stages of development. The development team looks forward to our continued work with the AMIGO clinical team, and the 3D Slicer community to further refine and deploy SliceTracker in clinical research studies.

Acknowledgment

The Advanced Multimodal Image-Guided Operating (AMIGO) suite is a clinical translational test-bed for research of the National Center for Image-Guided Therapy (NCIGT) at Brigham and Women’s Hospital (BWH) and Harvard Medical School. Development of SliceTracker was supported in part by NIH grants R01 CA111288, P41 EB015898 (NCIGT) and U24 CA180918 (Quantitative Image Informatics for Cancer Research, QIICR).

References

  1. Behringer P., Herz C., Penzkofer T., Tuncali K., Tempany C., Fedorov A. 2015. Open-­source Platform for Prostate Motion Tracking during in­-bore Targeted MRI­-guided Biopsy. In: MICCAI Workshop on Clinical Image-based Procedures: Translational Research in Medical Imaging. DOI: 10.1007/978-3-319-31808-0_15.
  2. Fedorov A., Beichel R., Kalpathy-Cramer J., Finet J., Fillion-Robin J-C., Pujol S., Bauer C., Jennings D., Fennessy F., Sonka M., Buatti J., Aylward S., Miller J V., Pieper S., Kikinis R. 2012. 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magnetic resonance imaging 30:1323–1341. DOI: 10.1016/j.mri.2012.05.001.
  3. Fedorov A., Tuncali K., Fennessy FM., Tokuda J., Hata N., Wells WM., Kikinis R., Tempany CM. 2012. Image registration for targeted MRI-guided transperineal prostate biopsy. Journal of magnetic resonance imaging: JMRI 36:987–992. DOI: 10.1002/jmri.23688.
  4. Penzkofer T., Tuncali K., Fedorov A., Song S-E., Tokuda J., Fennessy FM., Vangel MG., Kibel AS., Mulkern RV., Wells WM., Hata N., Tempany CMC. 2015. Transperineal in-bore 3-T MR imaging-guided prostate biopsy: a prospective clinical observational study. Radiology 274:170–180. DOI: 10.1148/radiol.14140221.
  5. Tokuda J., Tuncali K., Iordachita I., Song S-EE., Fedorov A., Oguro S., Lasso A., Fennessy FM., Tempany CM., Hata N. 2012. In-bore setup and software for 3T MRI-guided transperineal prostate biopsy. Physics in medicine and biology 57:5823–5840. DOI: 10.1088/0031-9155/57/18/5823.

Questions or comments are always welcome!