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Automatic path proposal computation for CT-guided percutaneous liver biopsy.

Authors :
Helck, A.
Schumann, C.
Aumann, J.
Thierfelder, K.
Strobl, F.
Braunagel, M.
Niethammer, M.
Clevert, D.
Hoffmann, R.
Reiser, M.
Sandner, T.
Trumm, C.
Source :
International Journal of Computer Assisted Radiology & Surgery; Dec2016, Vol. 11 Issue 12, p2199-2205, 7p
Publication Year :
2016

Abstract

Purpose : To evaluate feasibility of automatic software-based path proposals for CT-guided percutaneous biopsies. Methods : Thirty-three patients (60 $$\pm $$ 12 years) referred for CT-guided biopsy of focal liver lesions were consecutively included. Pre-interventional CT and dedicated software (FraunhoferMeVis Pathfinder) were used for (semi)automatic segmentation of relevant structures. The software subsequently generated three path proposals in downward quality for CT-guided biopsy. Proposed needle paths were compared with consensus proposal of two experts (comparable, less suitable, not feasible). In case of comparable results, equivalent approach to software-based path proposal was used. Quality of segmentation process was evaluated (Likert scale, 1 $$=$$ best, 6 $$=$$ worst), and time for processing was registered. Results : All biopsies were performed successfully without complications. In 91 % one of the three automatic path proposals was rated comparable to experts' proposal. None of the first proposals was rated not feasible, and 76 % were rated comparable to the experts' proposal. 7 % automatic path proposals were rated not feasible, all being second choice ( $$n=1$$ ) or third choice ( $$n=6$$ ). In 79 %, segmentation at least was good. Average total time for establishing automatic path proposal was 42 $$\pm $$ 9 s. Conclusion : Automatic software-based path proposal for CT-guided liver biopsies in the majority provides path proposals that are easy to establish and comparable to experts' insertion trajectories. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18616410
Volume :
11
Issue :
12
Database :
Complementary Index
Journal :
International Journal of Computer Assisted Radiology & Surgery
Publication Type :
Academic Journal
Accession number :
119478664
Full Text :
https://doi.org/10.1007/s11548-015-1349-0