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Open-­Source Platform for Prostate Motion Tracking during In­-bore Targeted MRI­-guided Biopsy

1Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
2Institute of Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany.
Publication Date:
Volume Number:
Clin Image Based Proced. 2016 May; 9401:122-9.
PubMed ID:
prostate cancer, image-guided interventions, magnetic resonance imaging, image registration, software evaluation, 3D Slicer
Appears in Collections:
Prostate Group, NCIGT, SLICER, SPL
P01 CA067165/CA/NCI NIH HHS/United States
P41 EB015898/EB/NIBIB NIH HHS/United States
U24 CA180918/CA/NCI NIH HHS/United States
Generated Citation:
Behringer P.A., Herz C., Penzkofer T., Tuncali K., Tempany C.M., Fedorov A. Open-­Source Platform for Prostate Motion Tracking during In­-bore Targeted MRI­-guided Biopsy. Clin Image Based Proced. 2016 May; 9401:122-9. PMID: 27135064. PMCID: PMC4844802.
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Accurate sampling of cancer suspicious locations is critical in targeted prostate biopsy, but can be complicated by the motion of the prostate. We present an open ­source software for intra­procedural tracking of the prostate and biopsy targets using deformable image registration. The software is implemented in 3D Slicer and is intended for clinical users. We evaluated accuracy, computation time and sensitivity to initialization, and compared implementations that use different versions of the Insight Segmentation Toolkit (ITK). Our retrospective evaluation used data from 25 in­-bore MRI-­guided prostate biopsy cases (343 registrations total). Prostate Dice similarity coefficient improved on average by 0.17 (p<0.0001, range 0.02­0.48). Registration was not sensitive to operator variability. Computation time decreased significantly for the implementation using the latest version of ITK. In conclusion, we presented a fully functional open ­source tool that is ready for prospective evaluation during clinical MRI-­guided prostate biopsy interventions.

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