Surgical Planning Laboratory - Brigham & Women's Hospital - Boston, Massachusetts USA - a teaching affiliate of Harvard Medical School

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Motion Compensation for MRI-compatible Patient-mounted Needle Guide Device: Estimation of Targeting Accuracy in MRI-guided Kidney Cryoablations

Institution:
Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Publisher:
IOP Publishing Ltd.
Publication Date:
Apr-2018
Journal:
Phys Med Biol
Volume Number:
63
Issue Number:
8
Pages:
085010
Citation:
Phys Med Biol. 2018 Apr 13;63(8):085010.
PubMed ID:
29546845
PMCID:
PMC5899055
Keywords:
MRI-compatible robot, MRI-guided interventions, renal cryoablation
Appears in Collections:
NCIGT, SPL
Sponsors:
R01 CA138586/CA/NCI NIH HHS/United States
P41 EB015898/EB/NIBIB NIH HHS/United States
R01 EB020667/EB/NIBIB NIH HHS/United States
Generated Citation:
Tokuda J., Chauvin L., Ninni B., Kato T., King F., Tuncali K., Hata N. Motion Compensation for MRI-compatible Patient-mounted Needle Guide Device: Estimation of Targeting Accuracy in MRI-guided Kidney Cryoablations. Phys Med Biol. 2018 Apr 13;63(8):085010. PMID: 29546845. PMCID: PMC5899055.
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Patient-mounted needle guide devices for percutaneous ablations are vulnerable to patient motion. The objective of this study is to develop and evaluate a software system for MRI-compatible patient-mounted needle guide device that can adaptively compensate for the displacement of the device due to the patient motion using a novel image-based automatic device-to-image registration. Materials and Methods. We developed a software system for an MRI-compatible patient-mounted needle guide device for percutaneous ablations. It features fully-automated image-based device-to-image registration to track the device position and a device controller to adjust the needle trajectory to compensate for the displacement of the device. We performed: a) a phantom study using a clinical MR scanner to evaluate the performance of registration, b) simulations using intraoperative time- series MR data acquired in 20 clinical cases of MRI-guided renal cryoablations to assess its impact on motion compensation, and c) pilot clinical study in three patients to test its feasibility during the clinical procedure. Results. FRE, TRE, and success rate of device-to-image registration were 2.71 ± 2.29 mm, 1.74 ± 1.13 mm, and 98.3% for the phantom images. The simulation study showed that the motion compensation reduced the targeting error for needle placement from 8.2 mm to 5.4 mm (p < 0.0005) in patients under general anesthesia (GA), and from 14.4 mm to 10.0 mm (p < 1.0 × 10-5) in patients under monitored anesthesia care (MAC). The pilot study showed that the software registered the device successfully during clinical cases. Discussion and Conclusion. Our simulation study demonstrated that the software system could significantly improve the targeting accuracy both in patients treated under MAC and GA. Intra-procedural image-based device-to-image registration was feasible.