Flexible Needle and Patient Tracking Using Fractional Scanning in Interventional CT Procedures

Overview

Journal Int J Comput Assist Radiol Surg

Publisher Springer

Specialties General Surgery
Radiology

Date 2019 Apr 10

PMID 30963457

Citations 3

Authors

Guy Medan

Leo Joskowicz

Affiliations

Soon will be listed here.

Abstract

Purpose: We present a new method for flexible needle and patient localization in interventional CT procedures based on fractional CT scanning. Our method accurately localizes the trajectory of a flexible needle to which a spherical marker is attached at a known distance from the tip with respect to a baseline scan of patient in the CT scanner coordinate frame.

Methods: The localization is achieved with a significantly lower dose compared to a full scan using sparse view angle sampling and without reconstructing the CT image of the repeat scan. Our method starts by performing rigid registration between the patient and the baseline scan in 3D Radon space computed from the sparse projection data. It then computes 2D projection difference images in which the flexible needle and the spherical marker appear as prominent features. Their 3D spatial locations are then automatically extracted from the projection images to accurately trace the flexible needle trajectory. To validate our method, we conducted registration and needle trajectory localization experiments in seven abdomen phantom scans using a short and a long flexible needle.

Results: Our experimental results yield a mean needle trajectory localization error of 0.7 ± 0.2 mm and a mean tip localization error of 2.4 ± 0.9 mm with a [Formula: see text]7.5 radiation dose reduction with respect to a full CT scan.

Conclusions: The significant radiation dose reduction enables more frequent needle trajectory localization during the needle insertion for a similar total dose, or a reduced total dose for the same localization frequency.

Citing Articles

Hybrid Deep Learning and Model-Based Needle Shape Prediction.

Lezcano D, Zhetpissov Y, Bernardes M, Moreira P, Tokuda J, Kim J IEEE Sens J. 2024; 24(11):18359-18371.

PMID: 39301509 PMC: 11410364. DOI: 10.1109/jsen.2024.3386120.

Optical Fiber-Based Needle Shape Sensing in Real Tissue: Single Core vs. Multicore Approaches.

Lezcano D, Zhetpissov Y, Cheng A, Kim J, Iordachita I J Med Robot Res. 2024; 9(1-2).

PMID: 38948444 PMC: 11212684. DOI: 10.1142/s2424905x23500046.

Optical Fiber-Based Needle Shape Sensing in Real Tissue: Single Core vs. Multicore Approaches.

Lezcano D, Zhetpissov Y, Cheng A, Kim J, Iordachita I ArXiv. 2023; .

PMID: 37731661 PMC: 10508835.

References

Sheafor D, Paulson E, Kliewer M, Delong D, Nelson R . Comparison of sonographic and CT guidance techniques: does CT fluoroscopy decrease procedure time?. AJR Am J Roentgenol. 2000; 174(4):939-42. DOI: 10.2214/ajr.174.4.1740939. View

Mettler Jr F, Wiest P, Locken J, Kelsey C . CT scanning: patterns of use and dose. J Radiol Prot. 2001; 20(4):353-9. DOI: 10.1088/0952-4746/20/4/301. View

Stoeckelhuber B, Leibecke T, Schulz E, Melchert U, Bergmann-Koester C, Helmberger T . Radiation dose to the radiologist's hand during continuous CT fluoroscopy-guided interventions. Cardiovasc Intervent Radiol. 2005; 28(5):589-94. DOI: 10.1007/s00270-005-0104-2. View

Chodick G, Ronckers C, Shalev V, Ron E . Excess lifetime cancer mortality risk attributable to radiation exposure from computed tomography examinations in children. Isr Med Assoc J. 2007; 9(8):584-7. View

Orth R, Wallace M, Kuo M . C-arm cone-beam CT: general principles and technical considerations for use in interventional radiology. J Vasc Interv Radiol. 2008; 19(6):814-20. DOI: 10.1016/j.jvir.2008.02.002. View

Yaniv Z, Cheng P, Wilson E, Popa T, Lindisch D, Campos-Nanez E . Needle-based interventions with the image-guided surgery toolkit (IGSTK): from phantoms to clinical trials. IEEE Trans Biomed Eng. 2009; 57(4):922-33. DOI: 10.1109/TBME.2009.2035688. View

Manduca A, Yu L, Trzasko J, Khaylova N, Kofler J, McCollough C . Projection space denoising with bilateral filtering and CT noise modeling for dose reduction in CT. Med Phys. 2009; 36(11):4911-9. PMC: 4108640. DOI: 10.1118/1.3232004. View

Miller D, Vano E, Bartal G, Balter S, Dixon R, Padovani R . Occupational radiation protection in interventional radiology: a joint guideline of the Cardiovascular and Interventional Radiology Society of Europe and the Society of Interventional Radiology. Cardiovasc Intervent Radiol. 2009; 33(2):230-9. PMC: 2841268. DOI: 10.1007/s00270-009-9756-7. View

Engh J, Minhas D, Kondziolka D, Riviere C . Percutaneous intracerebral navigation by duty-cycled spinning of flexible bevel-tipped needles. Neurosurgery. 2010; 67(4):1117-22. DOI: 10.1227/NEU.0b013e3181ec1551. View

10.

Sarti M, Brehmer W, Gay S . Low-dose techniques in CT-guided interventions. Radiographics. 2012; 32(4):1109-19. DOI: 10.1148/rg.324115072. View

11.

Liu Y, Liang Z, Ma J, Lu H, Wang K, Zhang H . Total variation-stokes strategy for sparse-view X-ray CT image reconstruction. IEEE Trans Med Imaging. 2014; 33(3):749-63. PMC: 3950963. DOI: 10.1109/TMI.2013.2295738. View

12.

Wu G, Li X, Lehocky C, Riviere C . Automatic Steering of Manually Inserted Needles. Conf Proc IEEE Int Conf Syst Man Cybern. 2014; :1488-1493. PMC: 3989365. DOI: 10.1109/SMC.2013.257. View

13.

Niu S, Gao Y, Bian Z, Huang J, Chen W, Yu G . Sparse-view x-ray CT reconstruction via total generalized variation regularization. Phys Med Biol. 2014; 59(12):2997-3017. PMC: 4219274. DOI: 10.1088/0031-9155/59/12/2997. View

14.

Kim K, Ye J, Worstell W, Ouyang J, Rakvongthai Y, El Fakhri G . Sparse-view spectral CT reconstruction using spectral patch-based low-rank penalty. IEEE Trans Med Imaging. 2014; 34(3):748-60. DOI: 10.1109/TMI.2014.2380993. View

15.

Cong W, Yang J, Ai D, Chen Y, Liu Y, Wang Y . Quantitative Analysis of Deformable Model-Based 3-D Reconstruction of Coronary Artery From Multiple Angiograms. IEEE Trans Biomed Eng. 2015; 62(8):2079-90. DOI: 10.1109/TBME.2015.2408633. View

16.

Zhang Y, Wang Y, Zhang W, Lin F, Pu Y, Zhou J . Statistical iterative reconstruction using adaptive fractional order regularization. Biomed Opt Express. 2016; 7(3):1015-29. PMC: 4866445. DOI: 10.1364/BOE.7.001015. View

17.

Medan G, Shamul N, Joskowicz L . Sparse 3D Radon Space Rigid Registration of CT Scans: Method and Validation Study. IEEE Trans Med Imaging. 2016; 36(2):497-506. DOI: 10.1109/TMI.2016.2615653. View

18.

Marinetto E, Uneri A, De Silva T, Reaungamornrat S, Zbijewski W, Sisniega A . Integration of free-hand 3D ultrasound and mobile C-arm cone-beam CT: Feasibility and characterization for real-time guidance of needle insertion. Comput Med Imaging Graph. 2017; 58:13-22. PMC: 9097947. DOI: 10.1016/j.compmedimag.2017.03.003. View

19.

Medan G, Joskowicz L . Reduced-Dose Imageless Needle and Patient Tracking in Interventional CT Procedures. IEEE Trans Med Imaging. 2017; 36(12):2449-2456. DOI: 10.1109/TMI.2017.2742898. View

20.

Ben-David E, Shochat M, Roth I, Nissenbaum I, Sosna J, Goldberg S . Evaluation of a CT-Guided Robotic System for Precise Percutaneous Needle Insertion. J Vasc Interv Radiol. 2018; 29(10):1440-1446. DOI: 10.1016/j.jvir.2018.01.002. View